Owner Prof. Dr. Naci GUNDOGAN (Anadolu University Rector)
Editor-in-Chief Dr. T. Volkan YUZER (Anadolu University)
Associated Editor Dr. Gulsun EBY (Anadolu University)
International Affairs Dr. Ugur DEMIRAY (Anadolu University)
Editorial Board in English Language Dr. Zulal BALPINAR (Anadolu University) Dr. Ilknur KECIK (Anadolu University)
Proof Reading Team Dr. Ali MERC (Anadolu University) Dr. Ozgur YILDIRIM (Anadolu University) Dr. Ipek KURU GONEN (Anadolu University) Dr. Gonca SUBASI (Anadolu University)
Web Support Team Dr. Nilgun OZDAMAR KESKIN (Anadolu University) Abdulkadir KARADENIZ (Anadolu University) Altan DEVRIM (Anadolu University)
Editorial Board Members Dr. Abdul Waheed KHAN (Canada) Dr. Anna RYBAK (Poland)
Dr. António TEIXEIRA (Portugal) Dr. Antonis LIONARAKIS (Greece) Dr. Asha KANWAR (Canada) Dr. Bobby HARREVELD (Australia) Dr. Carmencital CASTOLO (Philippines) Dr. Cleborne D. MADDUX (Canada) Dr. David METCALF (USA) Dr. Dursun GOKDAG (Turkey) Dr. Ene KOITLA (Estonia) Dr. Ezendu ARIWA (United Kingdom) Dr. Fahriye ALTINAY AKSAL (Turkey) Dr. Farhad SABA (USA) Dr. Ferhan ODABASI (Turkey) Dr. Feyzi ULUG (Turkey) Dr. Fons NOUWENS (Australia) Dr. Francis GLASGOW (South America) Dr. Gilly SALMON (United Kingdom) Dr. Gonca Telli YAMAMOTO (Turkey) Dr. Hakan TUZUN (Turkey) Dr. Hanafi ATAN (Malaysia) Dr. Jack KOUMİ (United Kingdom) Dr. Jim FLOOD (United Kingdom) Dr. John TRAXLER (United Kingdom) Dr. Katherine M. SINITSA (Ukraine) Dr. Kinshuk (New Zealand) Dr. Kay Mac KEOGH (Ireland) Dr. Loreta ULVYDIENE (Lithuania) Dr. Marina McISAAC (USA) Dr. Mark BULLEN (Canada) Dr. Meena HWANG (South Korea) Dr. Michael R. SIMONSON (USA) Dr. Michail KALOGIANNAKIS(France) Dr. Mihai JALOBEANU (Romania) Dr. Nabi Bux JUMANI (Pakistan) Dr. Natalija LEPKOVA (Lithuania) Dr. Patrick DANAHER (Australia) Dr. Paul KAWACHI (China) Dr. Piet KOMMERS (Netherlands) Dr. Ramesh C. SHARMA (India) Dr. Roza DUMBRAVEANU (Moldova) Dr. Rozhan B. M. IDRUS (Malaysia) Dr. Santosh PANDA (India) Dr. Sarah GURI-ROSENBLIT (Israel) Dr. Shivakumar DEENE (India) Dr. Simon STOBART (United Kingdom) Dr. Som NAIDU (Australia)
Dr. Stephen DOWNES (Canada) Dr. Steve WHEELER (United Kingdom) Dr. Tamar LOMINADZE (Georgia) Dr. Ugur DEMIRAY (Turkey) Dr. William John FRASER (South Africa) Dr. Yavuz AKBULUT (Turkey) Dr. Zehra ALTINAY GAZİ (Turkey) Dr. Zeki KAYA (Turkey) Dr. Zdena LUSTIGOVA (Czech Republic) Dr. Zhang WEI-YUAN (Hong Kong)
Honorary Editorial Board of TOJDE (Ordered alphabetically) Prof. Dr. Cevat ALKAN - The pioneer of educational technology in DE in Turkey (Turkey) Prof. Dr. Engin ATAC - Former Rector of Anadolu University for 1999-2006 period (Turkey) Prof. Dr. John BAATH - The well-known Swedish distance educator (Sweden) Prof. Dr. Tony BATES - Father of DE in Canada (Canada) Prof. Dr. Yılmaz BUYUKERSEN - The founder of DE in Turkey (Turkey) Prof. Dr. Chris CURRAN - The founder director of National DE Centre in Ireland (Ireland) Prof. Dr. Chere Campbell GIBSON - She studied for DE all her life. Emeritus Professor (USA) Prof. Dr. Börje HOLMBERG - He studied for DE. Emeritus Professor (Sweden) Prof. Dr. James MARAJ - The pioneer of the open university movement (Australia) Prof. Dr. Charles A. WEDEMEYER - The pioneer of DE in the world (USA)
TOJDE is abstracted, indexed and cited by the following databases around the world:
ASOS The Education Resources Information Center – ERIC The Directory of Open Access Journals – DOAJ EBSCOhost Research Databases Genamics JournalSeek Google Scholar InfoBase Index International Institute of Organized Research - I2OR Scientific Indexing Service SCOPUS UlrichsWeb - Global Serials Directory
Table of Contents
From The Editor Welcome to the Volume 17, Number 2 of TOJDE Marcela Gerogina GOMEZ-ZERMENO & Lorena ALEMAN DE LA GARZA Research Analysis on Mooc Course Dropout and Retention Rates
Hasan UCAR & Mujgan YAZICI BOZKAYA Pre-Service EFL Teachers’ Self-Efficacy Beliefs, Goal Orientations, and Participations in an Online Learning Environment
Djoko RAHARDJO, SUMARDJO, Djuara P. LUBIS & Sri HARIJATI Internet Access and Usage in Improving Students’ Self-Directed Learning in Indonesia Open University
Gurhan DURAK, E. Emre OZKESKIN & Murat ATAIZI QR Codes in Education and Communication
Jose CAPACHO Teaching and Learning Methodologies Supported by ICT Applied in Computer Science
Muhammad Razuan ABDUL RAZAK & Ahmad Zamzuri MOHAMAD ALI Instructional Screencast: A Research Conceptual Framework
Moanes H. TIBI Essential Components in Structuring Asynchronous Discussion Forums
Harun CIGDEM & Mustafa OZTURK Critical Components of Online Learning Readiness and Their Relationships with Learner Achievement
Indrajeet DUTTA Open Educational Resources (OER): Opportunities and Challenges for Indian Higher Education
Reviewed By Hakan ALTINPULLUK REVEW: E-Learning Paradigms and Applications Agent-Based Approach Edited By Mirjana Ivanovic And Lakhmi C. Jain
Reviewed By Aylin OZTURK REVIEW: Educational Data Mining: Applications and Trends Edited by Alejandro Pena-Ayala
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2
Dear TOJDE Readers, Welcome to the Volume 17, Number 2 of TOJDE, In April 2016 issue, there are 9 articles and 2 book reviews. 18 authors from 7 different countries write the articles. All these articles are from Colombia, India, Indonesia, Israel, Malaysia, Mexico, and Turkey. The 1st article is written by Dr. Marcela Gerogina GOMEZ-ZERMENO and Lorena ALEMAN DE LA GARZA. The title of this article is RESEARCH ANALYSIS ON MOOC COURSE DROPOUT AND RETENTION RATES. This article researches terminal efficiency of the Massive Online Open Course “Educational Innovation with Open Resources” offered by a Mexican private university. A quantitative methodology is used in this research. The reasons of dropout and retention rates is explained by the writers in the article. PRE-SERVICE EFL TEACHERS’ SELF-EFFICACY BELIEFS, GOAL ORIENTATIONS, AND PARTICIPATIONS IN AN ONLINE LEARNING ENVIRONMENT is the title of the 2nd article. Hasan UCAR and Prof. Dr. Mujgan YAZICI BOZKAYA are the writers. Embedded mixed design was used in the study. In the quantitative part of the study, the participants were 186 senior pre-service EFL teachers and data were collected on two scales and a questionnaire. Qualitative data were collected in form of one-on-one interviews from 2 preservice EFL teachers. Results shows several positive associations between teachers’ goal orientations and self-efficacy beliefs. The writers also presents future research suggestions in the end of article. The 3rd article’s title is INTERNET ACCESS AND USAGE IN IMPROVING STUDENTS’ SELFDIRECTED LEARNING IN INDONESIA OPEN UNIVERSITY. Djoko RAHARDJO, Prof. Dr. SUMARDJO, Dr. Djuara P. LUBIS, and Dr. Sri HARIJATI are the writers of the article. This study aims to analyze the relationship between internet access and usage in improving students' self-directed learning which is using structural equation model method. The result shows that the internet usage is still low in Indonesia due to limited internet facilities that affect the knowledge and willingness of students to access the internet. In the end, the writers has a suggestion. The strategy in improving student internet usage is applying social media as guidance that can be accessed through cellular phones. Dr. Gurhan DURAK, E. Emre OZKESKIN, and Dr. Murat ATAIZI are the writers of the 4th article. QR CODES IN EDUCATION AND COMMUNICATION is the tile of this article. Descriptive data analysis is used in the study. The findings are interpreted on the basis of Theory of Diffusion of Innovations and Theory of Uses and Gratifications. The writers highlight that the students mentioned that they did not have any difficulty using QR Codes. According to students, the content should include both superficial and in-depth information. The 5th article, titled TEACHING AND LEARNING METHODOLOGIES SUPPORTED BY ICT APPLIED IN COMPUTER SCIENCE, is written by Dr. Jose CAPACHO. The main objective of this paper is to show a set of new methodologies applied in the teaching of Computer Science using ICT. Behavioral Theory, Gestalt Theory. Genetic-Cognitive Psychology Theory, and Dialectics Psychology support the theoretical framework of the article. INSTRUCTIONAL SCREENCAST: A RESEARCH CONCEPTUAL FRAMEWORK is the tile of the 6th article. Muhammad Razuan ABDUL RAZAK and Ahmad Zamzuri MOHAMAD ALI are the writers of this article. According to writers, the cognitive style will ultimately affect how information is processed in the students’ memory structure. Students will also easily process the given information, if it is performed in accordance with their dominant learning
style. In the end of the article, the writers suggest experimental studies are important to determinate the ideal screencast design for specific learning style and cognitive style. The 7th article is titled ESSENTIAL COMPONENTS IN STRUCTURING ASYNCHRONOUS DISCUSSION FORUMS. Dr. Moanes H. TIBI is the writer of this article. This paper reviews the literature regarding the main elements and components that makes an asynchronous discussion forum more effective for knowledge acquisition and thereby increases the quality of online learning. Dr. Harun CIGDEM and Dr. Mustafa OZTURK are the writers of the 8th article. The title of this article is CRITICAL COMPONENTS OF ONLINE LEARNING READINESS AND THEIR RELATIONSHIPS WITH LEARNER ACHIEVEMENT. This study is aimed to examine the relationship between certain factors of online learning readiness and learners’ end-ofcourse achievements. The results show that the students’ self-direction towards online learning appeared to be the strongest predictor of their achievements within the course; whereas computer/Internet self-efficacy and motivation for learning did not predict the learner achievement significantly. The title of the 9th article is OPEN EDUCATIONAL RESOURCES (OER): OPPORTUNITIES AND CHALLENGES FOR INDIAN HIGHER EDUCATION and the writer is Dr. Indrajeet DUTTA. The writer highlights the easy and widespread availability of high quality educational material will change the paradigm of teaching and learning and thus improve the quality of education. Government of India has started several innovative programs and schemes like SHAKSHAT, NMEICT, NPTEL, OSCAR, E-grid etc. related to developing and disseminating educational resources. This article focuses on the opportunities and challenges with respect to OER in Indian higher education. There are two book reviews in this issue. E-LEARNING PARADIGMS AND APPLICATIONS: AGENT-BASED APPROACH is the title of 1st book. This book is an editorial book. The editors are Mirjana Ivanovic and Lakhmi C. Jain. The reviewer is Hakan ALTINPULLUK. Other book’s title is EDUCATIONAL DATA MINING: APPLICATIONS AND TRENDS. This is another editorial book and the editor is Alejandro Pena-Ayala. This book is reviewed by Aylin OZTURK. Hope to meet you July 2016 issue of TOJDE. Cordially, Dr. T. Volkan YUZER Editor-in-Chief
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 1
RESEARCH ANALYSIS ON MOOC COURSE DROPOUT AND RETENTION RATES Dr. Marcela Gerogina GOMEZ-ZERMENO Tecnológico de Monterrey, School of Education, Humanities and Social Sciences, Monterrey, MEXICO Lorena ALEMAN DE LA GARZA Tecnológico de Monterrey, School of Education, Humanities and Social Sciences, Monterrey, MEXICO ABSTRACT This research’s objective was to identify the terminal efficiency of the Massive Online Open Course “Educational Innovation with Open Resources” offered by a Mexican private university. A quantitative methodology was used, combining descriptive statistics and probabilistic models to analyze the levels of retention, completion, and desertion, as well as the characteristics of the students who completed the course. The results show a 14% of student retention and an 11.7% of student completion, relative to the total number of participants, who had some common characteristics: having a graduate (master or doctorate), being experienced in online education, committed to the course and self-taught. The participants who abandoned the course expressed the following reasons: problems with the course’s structure, limitations in the use of information and communication technologies or limited English proficiency, family reasons or low time disposition. It is recommended to take actions that will increase the knowledge in order to explain the MOOCs’ desertion rates and to strengthen their structures to improve the retention and completion rates. Keywords: Distance education, Open educational resources, MOOC, Terminal efficiency, School desertion INTRODUCTION The evolution of distance education and technological advances signify an important opportunity to increase education’s access and contribution to the compliance of international commitments regarding education. In this respect, the United Nations Educational, Scientific, and Cultural Organization (UNESCO, 2002, 2012) has established that free access to educational resources is a strategy to upgrade the quality of education, to facilitate the dialogue about policies, to interchange knowledge and to develop skills. Massive Online Open Courses (MOOC) are an emerging practice in open learning. It began in 2008, when George Siemens and Stephen Downes offered the course Connectivism and Connective Knowledge in the University of Manithoba in Canada; the course had a duration of 12 weeks and 2,300 students enrolled (Fini, 2009; Wiley & Hilton III, 2009). Among their characteristics, MOOCs allow the construction of bonds between hundreds or even thousands of students who self-organize their participation, learning goals, knowledge,
abilities and interests (McAuley, Stewart, Siemens & Cormier, 2010). Additionally, their free online access enables the enrollment of a large number of students (SCOPEO, 2013). Currently, Coursera, EdX, and Udacity are among the platforms that host MOOCs. For Latin American participants, MiriadaX and RedunX are available (Lushnikova, Chintakayala, Rodante, 2013; SCOPEO, 2013). Many Latin American universities have developed their own MOOCs in their institutional platforms or even through social networking sites such as Facebook. Nevertheless, only three Latin American universities are part of the Coursera community. In developing countries, the use of MOOCs is an alternative educational offering for professionals who look for complementary training and education. In addition, these courses allow the acquisition of new knowledge and skills in fields that could provide them the opportunity for a better income or to continue learning throughout life. Massive courses attract thousands of participants who are interested in the offered topic; however, it is important to note that approximately only 10% of the registered students complete the course (Lushnikova et al., 2013). Such case is reported by the University of Toronto (Harrison, 2013), where the percentage of terminal efficiency varied between 3% and 16%. On a similar note, SCOPEO (2013) reported an average of 13.5% of students who completed the course, out of 188,802 registered participants in 58 courses from 18 universities. The low terminal efficiency rates of MOOCs reveal a lack of self-regulation and self-motivation in students (Lushnikova et al., 2013). Likewise, Clow (2013) remarks that the student’s compromise level may diminish as the courses move forward. On this respect, Siemens and Tittenberg (2009) established that desertion rates could be minimized by providing more attention to the students regarding the components of effective learning, motivation, institutional support and free access to educational resources, in order to promote the development of interpersonal relationships among peers, faculty, and teaching staff. A dropout in online courses refers to the persons who inconspicuously discontinue their participation in the course; however, they are different from passive participants, students who do not unregister and continue the course without active collaboration in it (Rodríguez, 2012). Additionally, the author signals that the desertion rates and passive behavior of some MOOCs’ participants are among the educators’ concerns. In Latin America, experiences related to MOOCs are still developing; due to the growing research demand for these educational practices, it is necessary to identify and overcome the difficulties and obstacles in order to increase their dissemination and implementation, as well as the promotion of this type of initiatives, so they can be integrated in the public agenda of countries, institutions and inter-institutional projects in Latin America (Mortera, 2012). These circumstances have been confirmed by Liyanagunawardena, Adams and Williams (2013), who signal a lack of research and information about MOOCs that can explain why participants do not complete a course. According to Gómez-Zermeño (2012), it is important to create a context that supports innovative practices to evaluate the results of the undertaken efforts when new ways of teaching and learning are promoted. Given the research demands about the potentialities of MOOCs, it is important to inquire into the terminal efficiency of an MOOC offered in Spanish. This investigation generated information about the MOOC Educational Innovation through Open Resources, offered in Coursera on September of 2013. The study had the following research questions: What was the terminal efficiency of participants in the course Educational Innovation through Open Resources? What are the characteristics of the participants who successfully completed the course? With a quantitative methodology that combines
descriptive and econometric statistics, the research results show the retention and terminal efficiency rates of the course, the features of students who completed the course, as well as the causes of dropout and abandonment. A probabilistic model was used to identify the weight of each one of the dropout factors and thus evaluate the terminal efficiency of the MOOC “Educational Innovation through Open Resources”. RESEARCH METHOD Based on the research questions, the study opted for a quantitative methodology, combining the use of descriptive and econometric statistics, which allowed to identify the MOOCs’ participants profile and to calculate the dropout rates and terminal efficiency. Probabilistic models were used to identify the weight of each one of the dropout factors. The dependent variable is a binary variable (if the student abandoned the course, it was assigned the value of 1 and 0 on the contrary) and the independent or explanatory variables include factors such as gender, age, previous experience in virtual education and electronic media, educational level, English proficiency, and intrinsic characteristics such as being proactive, innovative and selftaught. The quantitative approach was used to analyze information through statistical methods; participants answered a diagnostic and final survey to inform about their opinions and perspective, this allowed understanding better the numerical data. Recognizing the participants’ experiences allowed the comprehension of the phenomenon (Alemán & GómezZermeño, 2012; Gómez-Zermeño, Rodríguez Arroyo & Márquez Guzmán, 2013). From an explanatory point of view (Creswell & Plano, 2011), the study sought to understand why the dropout phenomenon occurs and under what conditions, in order to identify the reasons why MOOC’s participants decide to dropout and not complete the course. We used a non-experimental, cross-section and ex-post-facto design, and the participants’ information was collected during August-September of 2013 (Valenzuela y Flores, 2012). MOOCS’s Description and Context The MOOC “Educational Innovation through Open Resources”, offered in Coursera, can be catalogued as continuous training; although it’s access was not restricted, it was designed mainly for basic education teachers in Mexico. Two Head Professors who have ample experience in the design of online courses, the use of Open Education Resources and Educational Technology designed it. The context of the MOOC’s creation is within a prominent Mexican University, leader in Educational Technology and the first Mexican University to impart courses via satellite in the mid 90’s. This University has offered online courses through their virtual campus for over 20 years. The course covers the subject of the selection, use and reuse of open educational resources, the possibilities the repositories that house these materials have, search strategies and integration into educational processes, as well as measuring and assessing their impact on learning of the participants. Thus, the participant would develop digital skills and instructional design skills to integrate open educational resources (OER) in their learning environments through open educational practices. In four modules, participants were able to watch videos or read about the course’s topics, and interacted with other participant in discussion boards by answering opinion questions. Digital portfolios and self and peer evaluations were used to assess the students’ understanding of how to integrate OER in institutional and learning processes in their own learning environment.
Research Population and Sample According to the statistics provided by the platform, 20,400 people registered for the course, which started in September of 2013. From the initial population, 4,407 participants completed the instrument called, “Pre-diagnosis survey” and 3,547 people answered the “Initial survey.” The data of each participant was given a unique identification code, which cannot be duplicated; by combining these two registers, we obtained 5,854 participants who were considered as the study sample. Table 1 shows the results of both surveys. Table: 1 Results from Pre-diagnostic and Initial Survey Instrument Participants Pre-diagnostic survey 2,307 Initial survey Both instruments Participants of the research population
1,447 24.7 2,100 35.9 5,854 100.0
Considering the information of 5,854 out of 20,400 people who registered, it was important to confirm if the number of existing cases permitted a statistical analysis in order to identify significant differences among the constructs. The formula to calculate the sample of finite populations was used; in Social Sciences research, the maximum sampling error is 5%, and although this data was not available, 5,854 of the participants who completed either the prediagnosis or the initial survey correspond to a sampling error of 1.2%, considered statistically significant. Instruments The data collection instruments were created by the head professors of the MOOC; there following 6 surveys were applied and used for collecting data: Ø
Ø Ø Ø Ø
Pre-diagnosis survey: is a structured questionnaire with 49 questions, combining closed questions, multiple options and weighted options using Likert rating scale. This instrument collects information about: general student data, MOOCs perceptions, skills and knowledge of information technologies, use of search engines, use of OER, Innovation and open education movement, Initial survey: collects general information on participants such as age, sex, marital status, country of residence, education, experience in online education, computer and internet connection type, social networks used, among others. Additionally, survey asked about the reasons for registering in the course, the level of commitment and hours per week to devote to the course. Topic 1 self-assessment: 15 multiple choice questions regarding the topic 1 Open educational movement. Topic 2 self-assessment: 15 multiple choice questions regarding the topic 2 Search of educational resources. Topic 3 self-assessment: 15 multiple choice questions regarding the topic 3 Use of open educational resources in learning processes. Topic 4 self-assessment: 15 multiple choice questions regarding the topic 4 Mobilization of open educational resources in learning environments.
These instruments do not have psychometric test results and do not correspond to an evaluation research design, but rather an exploratory design. They were completed online by participants using the platform Coursera.
Research Procedure During the first week of the course, the pre-diagnosis and initial electronic surveys were administrated; a link was provided thru the platform, and e-mail notification was sent to all the registered participants. The instruments were completed virtually and voluntarily; the results show that more than 70% of the enrolled students did not answer the surveys. The self-assessment instruments for topics 1 to 4 were provided at the end of each week thru a direct link. As the course moved forward, the number of participants who completed the instruments decreased. Table 2 shows that at the end of the first week, 30% of the participants delivered evidence of their work, which diminished to a 15.6% in the last week of the course. Table: 2 Level of participation throughout the course Instrument Participants % Research population 5854 100.0% Topic 1 Self-assessment 1779 30.4% Topic 2 Self-assessment 1165 19.9% Topic 3 Self-assessment 967 16.5% Topic 4 Self-assessment 911 15.6%
RESULTS ANALYSIS Using a quantitative method, in this research, descriptive and econometric statistics were used to calculate the retention and terminal efficiency rates of the course, to identify the features of students who completed the course, as well as the causes of dropout and abandonment. Finally, a probabilistic model was created to identify the weight of each one of the dropout factors and thus evaluate the terminal efficiency of the MOOC “Educational Innovation through Open Resources”. Retention and Terminal Efficiency Rates The databases were processed in SPSS (Statistical Package for the Social Sciences) and STATA, in order to calculate the MOOCs’ retention rate by dividing the number of participants who completed the last self-assessment (Topic 4) by the total number of students who fulfilled the first instruments (pre-diagnosis and initial survey). Table 3 shows the retention and terminal efficiency results of the MOOC, regarding the gender and total participants. 14.5% of retention was reported, meaning 818 participants who remained engaged until the last week of the course; while 11.7%, 683 participants, delivered all four topic’s self-assessments. Table: 3 Terminal efficiency according to gender
Desertion Retention Incomplete Completed
82.2% 17.8% 85.5% 14.5%
82.4% 17.6% 84.3% 15.7%
86.0% 14.0% 88.3% 11.7%
Total number 5,036 818 5,171 683
It is interesting, that when comparing the retention results (14%) and terminal efficiency (11.7%) of the course, the percentages are similar to those denoted by the University of Toronto which reported 8% average of terminal efficiency (Harrison, 2013), 10% reported by Miriadax (SCOPEO, 2013), and 10% reported by Lushnikova et al. (2013).
Features of Students who Completed the Course Researchers carried out a comparative analysis of the characteristics of the persons who abandoned the course against those who remained, and the features confrontation of those who completed the course and those who did not deliver the self-evaluation assessments. This analysis shows that the students who possess a master’s degree or higher are more likely to remain in the course, rather than those who only have a professional degree or lower educational level (Table 4). The persons who did not have previous experience with online education had lower rates of completion and terminal efficiency (Figure 1). Table: 4 MOOCs Terminal efficiency according to educational level Educational Level Student’s retention Terminal efficiency High school 11.4% 10.7% Technical career 9.0% 8.0% Undergraduate degree 14.4% 12.1% Master’s degree 19.0% 15.9% Doctorate Post-doctorate
20 15 10 5 0 Retention
Experienced in online education Unexperienced in online education
Figure: 1 Terminal efficiency in the MOOC according to experience with online courses. Additionally, results show that the participants who expressed more initial commitment presented higher completion and terminal efficiency rates; these participants planned to complete all the activities and evaluations to obtain a diploma and registered to the course as a way to complement their previous studies. On the contrary, the people who registered out of curiosity or who were not committed to the activities registered lower completion and terminal efficiency rates. These results confirm the statements by Cabrol & Székely (2012), regarding the importance of relevant education as a strategy to avoid academic failure and desertion. Likewise, Alemán, Sancho-Vinuesa y Gómez-Zermeño (2015) highlight the need for resource and strategy analysis under selection criteria. Individuals who expressed to have economic stability, either full-time or part-time workers, business owners, at home work or people who have a flexible schedule, reported higher completion and terminal efficiency rates, as opposed to those who study in high school or a undergraduate degree. It is important to mention that the participants who described themselves as self-learners obtained higher completion and terminal efficiency rates.
Regarding the features of the participants with higher completion rates, they displayed a proficient use of information technologies, of digital resources design, intermediate English level, knowledge organization skills, participation in research networks, and other characteristics. In relation to the people who described themselves as pro-active, there were no significant differences in the results of completion and terminal efficiency. On the contrary, the people without knowledge about copyrights, web information administration, use of OER in the classroom, and lack of experience in research networks presented higher abandonment of the course. It must be noted that the previously mentioned characteristics have significant statistic differences, which were validated by the Pearson’s chi-squared test, at 95% confidence interval. Causes of Dropout and Abandonment Coursera politics do not allow e-mail sharing in order to avoid spam. Therefore, it was not possible to administrate a sanctioned follow-up survey to explore the specific reasons some participants had when deciding to dropout or abandon the course. As an alternative, a reflection about various messages shared on the discussion forums was made. Among the stated reasons that may cause the discouragement of the participants and to abandon the course were: Ø Difficulties with the structure of the course, and lack of a tutorial to guide users. Ø The quality of the materials was also criticized. Ø Family reasons and no availability for the course. Ø Limitations on the use of information technology or in the English language. Ø Limitations of the Coursera platform. Probabilistic Model to Evaluate Terminal Efficiency of MOOC Given the results, the terminal efficiency of the MOOC was analyzed through the construction of a probabilistic model in order to quantify the weight of the main features of participants who do not complete the course. The main results of the models (table 5) are: The odds of desertion of the MOOC increases 5.7% when the participant has an undergraduate or lower degree, and the probability rises 5% when the student does not have knowledge about copyrights. On the contrary, the odds of desertion diminishes 7% if the participant is older than 55 years old, 17% when they show a strong commitment to the MOOC and 4.2% when they have a full-time or part-time job Ø The odds to complete the MOOC increases by 3.2 % when the participant is female and 3.8 % when it has no copyrights knowledge. By contrast, the odds of not completing decreases 8% when participants are over 55, 15 % when they have a strong commitment, and another 3.2 % when they are excited by applying course’s knowledge in their practice as teachers or daily life. Ø
Table: 5 Probabilistic model of the participants who do not complete an MOOC Traits of the participant
Older than 55 years old
Experienced in online education
Does not have a degree (high school or technician)
Full-time or part-time job
Plans to accomplish activities and tests to obtain certificate
Null (0 - 20%) - IT domain to create audio, video, images, etc.
Null (0 - 20%) – Knowledge about copyrights
Not important – Research filters
Null (0 - 20%) I do not know the English language
Lack of confidence – During information research
Self-taught (Constantly updating my knowledge)
Null (0 - 20%) - Knowledge of use of techniques and methods to organize knowledge in an accessible and considering scientific objectives, observable facts, and / or measurable Null (0 - 20%) - Domain to communicate in virtual environments Null (0 - 20%) - Domain to determine credibility of information To complement my classes (design and/or prepare courses) Uncertain, because they do not know what students will think of the use of open resources Does not participate in research network
Not willing to participate as facilitator or Teaching 0.0092 0.0166 Assistant Note: ** significant at 95 % confidence level * significant at 90 % confidence.
For probabilistic models, the dependent variable is constrained between zero and one, being derived from the cumulative distribution function (Gujarati, 1997). One way of evaluating the probabilistic models is derived from the goodness of fit (R2); however, when dealing with nonlinear models the goodness of fit is meaningless in terms of the defined coefficient of determination. The pseudo R2 of the model to neglect and no completion corresponds to 0.0249 and 0.0252, respectively. However, note that by supplementing with another statistic shows that the model correctly classifies drops to 75% of cases, whereas the model for not completed correctly classified 78% of instances. So the models can be considered quite acceptable for a multi factorial phenomenon as desertion and abandonment. CONCLUSIONS The main results of this research reveal low terminal efficiency rate of a MOOC, which was offered by a higher education institution. Although there was a positive response from the students, the percentage of participants who successfully completed the course indicates the opposite; therefore, it is important to study the reasons that led the participants to enroll and the causes of desertion.
The MOOC analyzed in this study had a rate of 11.7 % completion rate, which represents the number of students who delivered their respective assessments and answered throughout the course evaluations. In contrast, the high dropout rate of 86% agrees with the statements of Clow (2013), who mentions that the abandonment of online courses is higher than in classroom education. This result is parallel with the report of the University of Toronto, which showed a rate of approximately 8% of students who completed the course (Harrison, 2013). Similarly, Lushnikova et al. (2013) indicate that about 10 % of the students who enrolled in a MOOC managed to complete the course. In this connection, Siemens and Tittenberger (2009) note that desertion rates can be minimized by upgrading the course components that lead to an increase in the motivation levels and better student-faculty relationships. This study identified the main characteristics of the participants who managed to stay and complete the course, being favored those with graduate degrees, online educational previous experience, greater commitment to the course and economic stability. Other found features were the advanced or expert proficiency in the use of information technology, advanced proficiency in creating digital resources, intermediate English language skills, advanced proficiency in the use of techniques and methods to organize knowledge and active participation in research networks, among others. On the other hand, those who decided to leave the course indicated problems with the structure and guidance in the course, limitations on the use of information technology or in English, in addition to the limited availability of time due to family or work reasons. It is noteworthy that among the deserters were participants with a high school or bachelor education who do not participate in research networks, which is consistent with the statement made by Siemens (2005), who defines the research groups as a means to update the knowledge and maintain connections for continuous learning. The results of the probabilistic models constructed to measure the weight of the characteristics of participants who drop out or fail to complete a MOOC course, reflect that the participants’ likelihood to leave the MOOC course increases when the participant has a lower educational degree level and has no knowledge of copyrights. On the contrary, the probability of abandonment decreases when participants are over 55, have a strong commitment to the MOOC and when they have full or partial employment. In terms of completeness, the chances of not completing the MOOC increases when the participant is female and does not have any knowledge of copyrights. By contrast, the odds of not completing decreases when participants are over 55 when they have a strong commitment, and when they are excited by applying knowledge of the course in their practice as teachers or daily life. In light of the results obtained in this research, two possible courses of action arise as strategies to increase the level of awareness of the terminal performance of MOOCs’ participants: First, the application of surveys to students who decide to leave the course to obtain additional information about their reasons. Second, to increase the level of terminal efficiency of MOOCs, it is proposed to include in the course’s structure items such as a welcome tutorial to guide novice users in this type of courses, on their function and structure; organize discussion forums by language, country or thematic affinities, and improve the quality of the videos and captions. These recommendations are consistent with the approach of Aguaded (2013) who states the need to strengthen areas, such as interaction with the facilitators, collaborative and interactive work, respect cultural and linguistic diversity, for MOOC constituting an exceptional learning experience. Similarly, for the effectiveness of these courses you must create a scaffold to guide and help the participants to achieve their learning goals (Salmerón, Rodríguez, & Gutiérrez2010).
This research enables institutions that offer MOOC courses to consider the characteristics of the participants, in order to achieve greater efficiency and lower desertion rates. Thus, the educational practices in MOOC will benefit by improving their implementation and continue gathering information on new experiences in such resources.
BIODATA and CONTACT ADDRESSES of the AUTHORS Prof. Dr. Marcela Gerogina GOMEZ-ZERMENO holds a doctorate in Educational Innovation from Tecnológico de Monterrey, and a master’s degre in Information and Communication Technology Engineering Sciences. INT-CITCOM, France Télécoms Higher Education. She also holds a bachelor’s degree in Computer and Administration Systems from ITESM. She is a tenured lecturer at Tecnologico de Monterrey’s masters degree programs in Education and in Educational Technology, as well as on the doctoral program in Educational Innovation. She is a member of the the Mexican Education Research Council (COMIE). She is the technical manager on educational research projects of the Mexican National Council of Science and Technology (CONACYT) and on the ALFA program of the European Commission. She forms part of the National System of Researchers (SNI) Level 1.
Prof. Dr. Marcela Gerogina GOMEZ-ZERMENO Tecnológico de Monterrey, Campus Monterrey, Edificio CEDES, Ave. Eugenio Garza Sada, 2501 Sur, CP 64849 Monterrey, N.L., MÉXICO. Phone: +52 81 16461430. Email: [email protected]
Lorena ALEMAN DE LA GARZA is a doctoral candidate on the Education and ICT (e-learning) doctoral program at the Open University of Catalonia (UOC), Spain. She holds a master’s degree, with honors, in Educational Institution Administration from ITESM, and a bachelor’s degree, with honors, in Business Administration from TecMilenio University, Mexico. She has worked as a postgraduate lecturer at Tecnológico de Monterrey’s masters degree programs in Educational Institution Administration, in Education and in Educational Technology. She is the technical manager on educational research projects of the Mexican National Council of Science and Technology (CONACYT). She currently is the director of Continuing Education at Tecnológico de Monterrey. Lorena ALEMAN DE LA GARZA Tecnológico de Monterrey, Campus Monterrey, Edificio CEDES, Ave. Eugenio Garza Sada, 2501 Sur, CP 64849 Monterrey, N.L., MÉXICO. Phone: +52 81 16461435. Email: [email protected]
REFERENCES Aguaded, J.I. (2013). La revolución MOOCs, ¿una nueva educación desde el paradigma tecnológico? Comunicar, 41, 07-08. Alemán de la Garza, L.Y., Sancho-Vinuesa, T. & Gómez-Zermeño, M.G. (2015). Indicadores para evaluar la calidad de un curso en línea masivo y abierto para la actualización docente. Revista Universidad y Sociedad del Conocimiento, 12(1), 104-118. Alemán, L., & Gómez-Zermeño, M. G. (2012). Liderazgo Docente para la Enseñanza de la Innovación. Revista de Investigación Educativa, 4(2), 2-7. Cabrol, M. y Székely, M. (2012). Educación para la Transformación. Washington, DC: Banco Interamericano de Desarrollo.
Clow, D. (2013). MOOCs and the Funnel of Participation. The Open University. Retrieved from http://dougclow.org/mooc-funnel/ Creswell, J. W. y Plano Clark, V. L. (2011). Designing and conducting Mixed Method Research (2a ed.). Thousand Oaks CA, USA: Sage. Fini, A. (2009). The Technological Dimension of a Massive Open Online Course: The Case of the CCK08 Course Tools. The International Review Of Research In Open And Distance Learning, 10 (5). Gómez-Zermeño, M. G. (2012). Digital Libraries: Electronic Bibliographic Resources on Basic Education. Comunicar, 20(39), 119-126. Gómez-Zermeño, M. G., Rodríguez Arroyo, J. A. y Márquez Guzmán, S. (2013). Estudio Exploratorio-Descriptivo ʺCurso Híbrido: Contabilidad Vʺ. Revista de Investigación Educativa de la Escuela de Graduados en Educación, 4(7), 70-79. Gujarati, D. (1997). Econometría Básica. Colombia: McGraw Hill. Harrison, L. (2013). Open UToronto MOOC Initiative: Report on First Year on Activity. Toronto: University of Toronto. Liyanagunawardena, T., Adams, A., y Williams, S. (2013). MOOCs: A systematic study of the published literature 2008-2012. The International Review of Research in Open and Distance Learning, 14(3). Lushnikova, N., Chintakayala, P. & Rodante, A. (2013). Massive Open Online Courses from Ivy League universities: benefits and challenges for students and educators. XI International Conference “Providing continuity of content in the system of stepwise graduate and postgraduate education", Ukraine, November 15-16, 2012. McAuley, A., Stewart, S., Siemens, G. y Cormier, D. (2010). The MOOC Model for Digital Practice. Canadá: University of Prince Edward Island. Mortera, F. (2012). Internet, los Recursos Educativos Abiertos y el Movimiento Abierto. Red Latinoamericana Portales Educativos (RELPE). Retrieved from: http://www.relpe.org/destacados/internet-los-recursos-educativos-abiertos-y-elmovimiento-abierto/ Rodríguez, O. (2012). MOOCs and the AI-Stanford like Courses: Two Successful and Distinct Course Formats for Massive Open Online Courses. European Journal of Open, Distance and E-Learning. Retrieved from: http://files.eric.ed.gov/fulltext/EJ982976.pdf Salmerón, H., Rodríguez, S. y Gutiérrez, C. (2010). Metodologías que optimizan la comunicación en entornos de aprendizaje virtual. Comunicar, 34, 163-171. DOI: 10.3916/C34-2010-03-16. SCOPEO (2013). MOOC: Estado de la situación actual, posibilidades, retos y futuro. Scopeo Informe No. 2. Siemens, G. (2005). Connectivism: A learning theory for the digital age. International journal of instructional technology and distance learning, 2(1), 3-10. Siemens, G. y Tittenberger, P. (2009). Handbook of Emerging Technologies for Learning. Retrieved from: http://elearnspace.org/Articles/HETL.pdf UNESCO (2002). Forum on the impact of open courseware for higher education in developing countries: final report. Paris: UNESCO. UNESCO (2012). Declaración de París de 2012 sobre los REA. Congreso Mundial sobre los Recursos Educativos Abiertos (REA). Paris: UNESCO.
Valenzuela, J. R. y Flores, M. (2012). Fundamentos de investigación educativa, Volumen 2. Monterrey, México: Editorial Digital Tecnológico de Monterrey. Wiley, D., & Hilton III, J. (2009). Openness, Dynamic Specialization, and the Disaggregated Future of Higher Education. The International Review of Research in Open and Distance Learning, 10(5).
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 2
PRE-SERVICE EFL TEACHERS’ SELF-EFFICACY BELIEFS, GOAL ORIENTATIONS, AND PARTICIPATIONS IN AN ONLINE LEARNING ENVIRONMENT Hasan UCAR Bilecik Seyh Edebali University, Bilecik, Turkey Prof. Dr. Mujgan YAZICI BOZKAYA Open Education Faculty Anadolu University, Eskisehir, Turkey ABSTRACT This study examined the pre-service EFL teachers’ self-efficacy beliefs, goal orientations, and participations in an online learning environment. Embedded mixed design was used in the study. In the quantitative part of the study, the participants were 186 senior pre-service EFL teachers and data were collected on two scales and a questionnaire. Qualitative data were collected in form of one-on-one interviews from 2 pre-service EFL teachers, the most representative of the population, to understand the motivation and behaviour variables. The findings of this research revealed that pre-service EFL teachers’ self-efficacy believes are high but fragile. However, some of the participants had more than one goal orientation. The mastery and performance oriented pre-service teachers displayed different characteristics of motivation. Moreover, few of the pre-service EFL teachers participate in the online learning environment. Results also showed several positive associations between teachers’ goal orientations and self-efficacy beliefs. The results as well as their implications are discussed and suggestions for future research are presented. Keywords: Pre-service EFL teacher, self-efficacy, achievement goal orientation INTRODUCTION Teachers’ self-efficacy beliefs and goal orientations have significant implications in education settings. Teachers are one of the most important components in education systems. Their beliefs and attitudes during education process affect their behaviours in teaching (Bandura, 1997). Recent studies done in the field of education have showed that knowledge and skills are not adequate for active teaching. Teachers’ attitudes and beliefs have also been found to be contributing to their effectiveness as educators (Bandura, 1997; Tschannen-Moran, Woolfolk Hoy, & Hoy, 1998). Even though there are many studies on students’ motivation for learning, there has been little research on teachers’ motivation for teaching (Retelsdorf, Butler, Streblow, & Schiefele, 2010). One of main objective in education process is to reach a goal. To achieve this goal, many variables interact with each other. The main variables that affect the teachers, the learners, and the teaching and learning environment are self-efficacy and goal orientation constructs. The first construct, self-efficacy belief, has been mostly studied in education area in the last two decades. Self-efficacy belief refers to perception of one’s own ability in organizing and completing a task successfully (Bandura, 1997). It has been applied to understanding how teachers’ thoughts about their competence in classroom teaching, students’ achievement and management of the classroom. Chacon (2005) also reported that teachers’ sense of efficacy influences teachers’ actions and student outcomes. It is also accepted that one of the most important factors affecting students’ perception and 15
goal orientation is the teacher (Afsaneh & Safoura, 2015). Beghetto (2007) and Egel (2009) also stated that it is important for researchers to examine pre-service teachers’ efficacy beliefs about student motivation. Achievement goal orientation is the second construct, which has been pointed to affect the teaching and learning environment in numerous studies. This concept is about purposes and motives that individuals had in a task. This variable has been used to assess the students’ motivation for learning but later it has begun to be used to understand the teachers’ motivation, as well (Butler, 2007). Kucsera, Roberts, Walls, Walker, and Svinicki (2011) reported that achievement goal theory affects many motivation and behaviour variables in the student and work literatures, but it is still applied specifically to teachers and teaching. Nitsche, Dickhäuser, Fasching, and Dresel (2011) reported that teachers’ goal orientation is a significant factor for teachers’ individual development of competence. According to Retelsdorf et al., (2010) achievement goal construct may also be useful for defining motivation of pre-service teachers. Pre-service teachers, when compared with experienced in-service teachers, are in closer touch with updated teaching approaches and in fact, often bring information about new methodologies to the in-service teachers through teaching practicum (Tang, Lee & Chun, 2012) . However, pre-service teachers’ achievement goals and efficacy belief may change in terms of learning environments. To date, no study has researched online distance preservice EFL teachers’ psychological incentives, achievement goals, and efficacy belief. In the present study, we attempt to examine the mentioned variables and assess the relationships between pre-service teachers’ participation in an online learning environment and psychological incentives, achievement goals and efficacy belief. This may help those concerned both educators and administrators in making policy decisions about the learning environment in order to maintain or increase psychological incentives of the pre-service ELT teachers. LITERATURE REVIEW Historically, the first theory that influenced the first studies on teacher efficacy was grounded in Rotter’s social learning theory (Tschannen-Moran, Woolfolk Hoy & Hoy, 1998). This theory also known as Rotter’s locus of control. Locus of control defined teacher efficacy as the extent to which teachers believed that they could control events that affect them. There are two kinds of locus of control, internal locus of control and external locus of control. Teachers with internal locus of control believe that their own actions determine the outcomes they obtain, while teachers with external locus of control believe that their experiences are not determined by themselves but by sources outside themselves like chance, and fate. Bandura’s social cognitive theory (1997) is another theory, which has been shown to have a connection to the educational psychology for the last two decades. Bandura’s theory consists of three components: human agency, outcome expectancy, and efficacy belief. As Bandura (1997) defined self-efficacy belief is “the beliefs in one’s capabilities to organize and execute the course of action required to produce given attainments”. According to Bandura, self-efficacy belief affects individuals in many ways. If the people have high efficacy, in turn, they will have high effort to accomplish the work that they deal with (Pajares, 2002). Bandura defined teacher efficacy as a kind of efficacy. Tschannen-Moran and Woolfolk Hoy (2001) described teacher efficacy as teachers’ belief about their capabilities to get the desired outcomes of student engagement and learning. Henson (2001) stated that teachers’ self-efficacy beliefs have been repeatedly associated with positive teaching behaviours and student outcomes. In addition, self-efficacy is even a stronger positive predictor for self-regulation (Daal, Donche, & Maeyer, 2014). Bandura (1997) stated that teachers’ efficacy beliefs are generally open to change during the preservice time. Therefore, this construct should be examined deeply.
Achievement goal theory is the third theory that affects the pre-service teachers. It is very common in the achievement motivation literature. This construct is about the purposes and motives the individuals get in achievement task (Dweck & Leggett, 1988). It consists of four constructs. These are: mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance achievement goal orientations (Elliot & Murayama, 2008). Learners with approach goals try to master learning tasks and they do their best to completely acquire the subjects, while students with avoidance goals avoid negative results such as failure while mastering the tasks (Elliot & McGregor, 2001). In other words, in approach aspects (mastery-approach and performance-approach) learners believe in themselves to do well but in avoidance aspects (performance-avoidance and masteryavoidance) these learners doubt about their ability to perform well (Coutinho & Neuman, 2008). Kucsera et al., (2011) reported that achievement goal theory affect many motivation and behaviour variables in the student and work literatures, but it is still applied specifically to teachers and teaching. Nitsche et al. (2011) reported that teachers’ goal orientations are significant factors for teachers’ individual development of competence. Retelsdorf et al. (2010) cited that achievement goal construct may also be useful for defining motivation of pre-service teachers. The literature provides proofs that self-efficacy and achievement goal orientations are contributing factors of success of learners and pre-service teachers (Afsaneh & Safoura, 2015; Bandura, 1997; Coutinho & Neuman, 2008; Elliot & McGregor, 2001). However, there is a gap in the literature that identifies and links self-efficacy and achievement goal orientation to online pre-service EFL teachers. This study adds evidence and knowledge to the literature. Goal of the Study and Research Questions The study aimed to explore pre-service EFL teachers’ self-efficacy beliefs, goal orientations, and participation in the online learning environment and examine the relationships among these variables. The research questions that guide this research are as follows: What is the level of self-efficacy beliefs of the pre-service EFL teachers? What kind of achievement goal orientations do the pre-service EFL teachers have? Is there a relationship between the pre-service EFL teachers’ self-efficacy beliefs and achievement goal orientations? Do pre-service EFL teachers’ self-efficacy beliefs change according to status of participation in the online learning environment? Do pre-service EFL teachers’ achievement goal orientations change according to status of participation in the online learning environment? METHOD Research Design Embedded mixed design, which is one of the mixed method design, was used for this study. The purpose of the embedded design is to collect quantitative and qualitative data simultaneously or sequentially, but to have one form of data play a supportive role to the other form of data (Cresswell, 2012:544). In this study a sequential design was used with the embedded design. That is to say, quantitative data as a primary form was used to inform the qualitative phase. For the quantitative part of the study, pre-service EFL teachers who volunteer and who agree attended the study. The data were collected from 186 convenient participants. The representative sample is accepted at 95% confidence level, 5.95% margin of error, and 50% response distribution. Three instruments, namely English Teachers’ Sense of Efficacy Scale (ESTES), Achievement Goals Questionnaire-Revised (AGQ-R), and demographic and online learning environment questionnaire were used. The quantitative information represented a major source of information for this study. For the qualitative part, data were collected in the form of one-on-one interviews to understand the beliefs, goals and perceptions of the pre-service teachers at first hand. 17
Quantitative Data Collection and Analysis Interpretation
Qualitative Data Collection and Analysis
Figure: 1 The study design (Creswell, 2012) Participants of the Study The population consisted of pre-service EFL teachers enrolled at Distance English Language Teacher Education BA program at College of Open Education, Anadolu University in Turkey. This program has a blended model of instruction, supplies both face to face, and distance education. The first two years of the program are conducted mainly through traditional classroom instruction, and the third and fourth years of the program are conducted by means of distance education supported by online courses through the online learning environment, that is asynchronous Web-based course management tool. Online component of the program aims to provide guidance to students. Before the main quantitative study, 38 pre-service EFL teachers consented to participate voluntarily to the face-to-face pilot study. For the main study, 186 pre-service teachers participated. There were 144 females and 42 males students. The age range of the sample was 21 years to 30 years. Table 1 provides the demographic information for the population, and for the sample used in this study. As seen in Table 1, the proportions of the gender and age within the sample are generally representative of the population. Table: 1 The proportions of the gender and age within the sample and population Sample (n=186)
Qualitative part of the study was consisted of two one-on-one interviews. Participants of the interviews were two pre-service EFL teachers. The participants were purposefully selected from 186 pre-service EFL teachers who completed the English Teachers’ Sense of Efficacy Scale (ESTES) and Achievement Goals Questionnaire - Revised (AGQ-R), and the questionnaire. They were selected for the one-on-one interviews because their scores on the scales and the questionnaire identified them as the most representative of the population.
Table: 2 Features of the participants in the qualitative phase Use of the Online Learning Environment
Pre-service EFL Teachers
High mastery Low performance
Yes / Active
Low mastery High performance
Yes / Not Active
Data Collection Instruments The data were obtained, primarily, via two scales, namely English Teachers’ Sense of Efficacy Scale (ESTES) (Chacon, 2005) and Achievement Goals Questionnaire - Revised (AGQ-R) (Elliot & Murayama, 2008). The participants also responded to the demographic and online learning environment questionnaire. For the qualitative part, data were collected through two one-on-one interviews. English Teachers’ Sense of Efficacy Scale (ESTES) consists of five subscales. In this research, only adapted version of Teachers’ Sense of Efficacy Scale (TSES) (TschannenMoran & Woolfolk Hoy, 2001), with 12 items including four items for each of the three dimensions was used to assess pre-service EFL teachers’ self-efficacy beliefs. The measured three subscales are: Teachers’ efficacy for engaging students learning in EFL, teachers’ perceived efficacy for managing EFL classes, and teachers’ perceived efficacy for implementing instructional strategies to teach EFL. Achievement Goals Questionnaire - Revised (AGQ-R). The AGQ-R is a 12 item, 5-point Likert scale questionnaire used to measure achievement goal orientations namely masteryapproach, mastery-avoidance, performance-approach and performance-avoidance. The demographic information section, which was developed by the researchers, includes questions about gender, age, educational background, and teaching and learning experience of the pre-service EFL teachers. The last part of the questionnaire, which was developed by the researcher and includes both Likert type and open-ended questions, is about the students’ perceptions of and participation in online learning environment. In qualitative one-on-one interviews, open-ended questions below were asked to the preservice EFL teachers: How do you describe yourself as a teacher/student? What are your goals (personal/academic/professional)? What do you do when you faced a very difficult academic task? What do you think about the relationship between ability and success? What do you do when you faced a challenging situation in the classroom? What do you do to get students to believe they can do well in English? How do you react when your students are confused? Do you participate in online learning environment? What is your intend use of online learning environment? Procedure A pilot study was conducted before the main quantitative study. The aims of conducting this pilot study were to find out whether the questions were clear or not and understandable enough and to learn whether an addition to the data collection tool was necessary. To conduct the pilot study, the researchers emailed all the pre-service EFL teachers. Out of the 588 teachers, 38 consented to participate voluntarily to the face-toface pilot study. After the piloting procedure, which lasted for a month, the researchers performed minor revisions regarding to language and grammar of the survey. The survey 19
link was then put on the online course room and the discussion board and participants were asked to complete the survey thoroughly. If the learner agreed to participate in the study, he/she completed the survey, and then submitted the completed the one-time survey through the secure online link. The participants voluntarily consented to participate in the study without incentives. At the end of the survey, which stayed for a month in the online learning environment, 186 participants were attended the study. To support the primary quantitative data, supportive qualitative data were added. Out of the 186 participants, 2 pre-service EFL teachers were purposefully selected for the one-on-one interviews. The representative pre-service teachers were contacted by telephone for the interview and each interview was scheduled for an hour. Data Analysis The quantitative data analysis was done using the SPSS program for Windows, and content analysis was conducted in order to analyse the qualitative data obtained from the interviews. The answers to each question in the interviews were coded and categorized by the authors. RESULTS Quantitative Data
Research Question 1: What is the level of self-efficacy beliefs of the pre-service EFL teachers? Descriptive statistics for self-efficacy belief are presented in Table 3.
Table: 3 Descriptive statistics and Cronbach alpha measures for self-efficacy beliefs scale (n=186)
The results shown in Table 3 suggest that most of the pre-service EFL teachers in the Distance English Language Teacher Education Program have high efficacy beliefs. That is to say, the pre-service EFL teachers believe that they are efficacious in engaging students learning, managing EFL classes, and implementing instructional strategies. This result is noteworthy as Bandura (1997) stated that teachers’ self-efficacy beliefs in their instructional efficacy affect the learning environment. In addition, as Lee & Yuan (2014) stated, pre-service teachers with high self-efficacy beliefs might be able to think positively of their future teaching practice and feel more motivated towards teaching despite the possible challenges they may encounter.
Research Question 2: What kind of achievement goal orientations do the pre-service EFL teachers have? Descriptive statistics for achievement goal orientations are presented in Table 4.
Table: 4 Descriptive statistics and Cronbach alpha measures for achievement goal orientations scale (n=186)
According to Table 4, results indicated a difference in the pre-service EFL teachers’ goal adoptions. These results suggest that the pre-service EFL teachers adopt more than one achievement goal, and mostly mastery goals for learning are adopted. This result can be interpreted as positive since teachers adopting mastery goal orientations seek challenging tasks and do well in difficult situations. However, mastery goal orientations involve the 20
Engaging Students Learning
Managing EFL Classes
Implementing Instructional Strategies
Managing EFL Classes
Implementing Instructional Strategies
development of competence through task mastery and the emphasis is placed on developing new skills (Lindsay, 2010). Table: 5 Difference in the pre-service EFL teachers’ goal adoptions
Research Question 3: Is there a relationship between the pre-service EFL teachers’ self-
efficacy beliefs and achievement goal orientations? The present study also aimed at exploring the possible association between the subscales of goal orientation and self-efficacy. The results of the third research question revealed the effect of mastery goal on self-efficacy and it showed among goal orientations, mastery goal is also positively but not significantly predicts self-efficacy. Correlation analyses performed between the pre-service EFL teachers’ self-efficacy beliefs and achievement goal orientations are reported in Table 5. According to the Table, there are significant correlations at p<0.01 level among pre-service EFL teachers’ self-efficacy subscales and achievement goal subscales. However, as expected, self-efficacy beliefs were correlated to achievement goal orientations (r=0.16, p<0.05). Mastery approach was positively but weakly related to engaging students learning (r=0.15, p<0.05), managing EFL classes (r=0.24, p<0.01), implementing instructional strategies (r=0.21, p<0.01), and general self-efficacy (r=0.23, p<0.01). The results also showed no significant relationship between performance approach and self-efficacy variables. In addition, performance avoidance had no significant relationship to self-efficacy subscales, either. These findings have been found to fit to several researchers’ studies (Coutinho & Neuman, 2008; Eryenen, 2008; Hsieh, Sullivan & Guerra, 2007). A research done by Coutinho and Neuman (2008) and Zafarmand, Ghanizadeh, and Akbabi (2014) stated that mastery-approach and performance-approach achievement goals were positive predictors of self-efficacy beliefs. However, Elliot and McGregor (2001) reported that mastery-avoidance has positive connection with fear of failure and negative connection related to self-determination. According to these researchers, it seems unlikely that individuals with this goal orientation would have confidence in their ability to achieve desired outcomes. In addition, performance-avoidance 21
is generally associated with poor performance, so individuals who routinely perform poorly are unlikely to believe that they have the ability to perform well (Lindsay, 2010).
Research Question 4: Do pre-service EFL teachers’ self-efficacy beliefs change according to
status of participation in the online learning environment? According to findings given in Table 6, there were no statistically significant difference between self-efficacy belief and participation in the online learning environment, t (184)= -0,111, p=0,912. It has not been found any study done about the relationship between these variables. However, a study conducted by Sakar (2009) revealed that senior students’ frequency of participation to online learning environment in this program was quite low. It can be concluded that attendance to the online courses makes no difference to the selfefficacy beliefs of the pre-service teachers, but in order to understand the exact relationships, more studies are needed. Table: 6 Self-efficacy beliefs based on status of participation in online learning environment Participation in Online Learning Environment Self-Efficacy Belief
Research Question 5: Do pre-service EFL teachers’ achievement goal orientations change according to status of participation in the online learning environment? As shown in Table 7, statistically no meaningful difference existed between achievement goal orientation and its subscales to status of participation in online learning environment, t (184) = 0,796, p= 0,427. It has not been found any study done in literature yet. Table: 7 Achievement goal orientations based on status of participation in online learning environment Participation in Online Learning Environment AGO
In addition to these questions, pre-service EFL teachers’ achievement goal orientations and self-efficacy beliefs are also examined according to gender, age, and work experience variables. As a result of t-test, it was found out that there were not noteworthy findings between pre-service EFL teachers’ achievement goal orientations, self-efficacy beliefs and gender, age and work experience. However, these findings were insufficient to note a statistically relationship among these variables. Qualitative Data In one-on-one interviews, open-ended questions below were asked to the pre-service EFL teachers. Data cited from the interviews. How do you describe yourself as a teacher/student? PST1 says “I am a hardworking student and teacher… and a quick learner.” She also sees herself as a competent learner and therefore she learns efficiently. “I was always a 22
successful student and I believe that if you study hard you do wonders.” She emphasized that her aim as a teacher was to learn for learning and this is her primary aim. PST2 says “I am not very smart student but I study all my lessons and I do my best in the exams… Mostly I get average grades … I am a student like that… that’s enough for me.” She adds that “If I didn’t study and get low grades I felt guilty… I don’t want to let my family down… I try hard to make them feel happy.” What are your goals (personal/academic/professional)? PST1 personal goal is to finish the school on time. She added “After I graduated I have to study harder to teach better… If I give up studying I couldn’t teach effectively… so my goal is to be a perfect teacher.” She thought that she is a successful teacher and her grades are proofs for this result. Her academic and professional goals were simple. She wanted to graduate with an honour degree and began to work as an instructor in a public university. She added that a teacher should be enthusiastic and wise. That’s why she wants to be an enthusiastic and wise teacher when she begins to work. For academic goal, PST2 responded that she wanted to finish the school on time. “The grade point average doesn’t matter for me … I just want to finish my school and make my father happy and believe in me because he doesn’t believe that I will finish the school on time.” As a personal goal, she says “After I graduate, I want to study in an elementary school because I love kids a lot… And I want to spend all my spare time in my house… with my children... after I graduate I don’t want to spend my time with challenging situations, exams… I feel tired of these.” What do you do when you faced a very difficult academic task? PST1 believes that every teacher can be successful if he/she studies hard. When she faces a difficult task, first she gets the bottom of the subject. If she didn’t understand it then she asks her teachers or friends. She emphasized that she never leaves the task incomplete. She says “When I learn, I learn completely.” PST2 says “It is hard for me to deal with that tasks… Mostly I lose my motivation on that occasions… so it is better for me not to think too much on that tasks.” She added that she tried to understand and overcome the difficult task but mostly she chose to get it out of her way. “If I do the simple tasks and have an idea about the difficult ones that is enough for me.” What do you think about the relationship between ability and success? PST1 believes that one can succeed only when he/she studies hard. “This is a psychological situation… I believe that ability is nothing without studying… If the teacher has an ability he/she needs to study to succeed but if he/she has an ability this does not enough for success…” PST2 responded that “ability is very important factor in success… for example when I am not good at subject or lesson, I know that I cannot do well, so I don’t force myself because I know that I don’t have the necessary ability.” She says “… for example I believe that I don’t have much ability in English so I study hard before the exams and mostly I get around 70 points… actually it is enough for me…some of my friends don’t study hard and they get 80-90 points… I think this is because they have the ability for that.” What do you do when you faced a challenging situation in the classroom? PST1 reported that challenging situations were always big problems for teachers. Moreover, she thinks of the school as her work place. “… and if I am a teacher, I should overcome these situations and establish a management system in the classroom… When I first enter 23
a classroom I always explain the students my expectations and warn them about their responsibilities and behaviours”. She says “If a student doesn’t follow the classroom rules, I speak to him/her separately and warn him/her to follow the classroom rules.” According to PST2, controlling the challenging situations were very difficult especially with today’s students. PST2 says “when a problem occurs my lesson entirely ruins … because it takes a lot time to overcome the challenging situations.” She adds “when I enter a classroom… I always pray for not to have troubled students because if I have students like these I don’t feel happy and I can’t motivate myself and the students for the lesson.” What do you do to get students to believe they can do well in English? For PST1, motivating the students was the first responsibility of a teacher. She says “I always smile to students. I believe that if a teacher smile and feel happy the students then believe in themselves and success. I always remind them that I believe in them.” She continues “I get through to all students, and make sure that they understand the lesson… this is very important.” PST2 says “As a teacher I believe in myself and I think every student should believe in himself or herself before the teacher believes in him or her. If a student doesn’t believe that he or she can do well…It takes a long time to get him or her to believe… I always say the students that I believe in them… and I motivate them.” How do you react when your students are confused? PST1 says “I am very patient in that situations…. I provide alternative examples to students, and mostly they understand”. She emphasized that she makes the necessary preparations to adjust the lesson to all levels of students. PST2 says “I know myself and I always do the best to motivate the students and help them understand.” She adds “If a student doesn’t study before he/she comes to classroom, most probably he/she will not understand the lesson completely and he/she confuses.” According to PST 2 “if a teacher and a student take care of their responsibilities, everything will be fine.” Do you participate in online learning environment? If Yes - What is your intend use of online learning environment? PST1 participates in the online learning environment. She says “I try to enter the system every day... I consider myself an active participant”. For the second question PST1 says “I use the online learning environment because it motivates me and reinforce my learning… If I don’t use it, I don’t feel myself happy and I feel something missing.” PST 2 says “I don’t use the online learning environment very frequently… It is not compulsory for us so I just follow the bulletin board sometimes in case of there is something important.” And she adds “I don’t think it is useful.” She also adds “Sometimes I enter the system but I can’t find the necessary materials.” The qualitative results revealed that the pre-service EFL teachers have different characteristics and views in terms of goal orientations, self-efficacy beliefs and participating in the online learning environment. The differences exist between mastery and performance goal oriented participants (PTS1 and PTS2) are shown on table 8. As seen in table 8, the characteristics identify the pre-service teachers in terms of achievement goal orientations, self-efficacy beliefs and perceptions of the online learning environment.
Table: 8 The characteristics and views of the pre-service EFL teachers about goal orientations, self-efficacy beliefs and participating in the online learning environment Variable
Achievement Goal Orientation
Perceptions of the Online Learning Environment
Can be developed
Interest in learning
Choose challenging tasks
Medium/Low Choose less challenging tasks
Motivate, improve and believe in sts
Control the classroom easily
Firstly, the sts should believe in themselves, motivate Afraid of disruptive behaviours
Make preparations for the lesson, implement alternative strategies
Make preparations for the lesson, sts have to take care of their learning first
Not very much/ not worthwhile
Useful to my learning but it should be improved
Useful but not necessary. It is not available when needed
Enhance leaning, reinforcement
Follow the bulletin board
DISCUSSIONS The main purpose of this study was to describe pre-service EFL teachers’ self-efficacy beliefs, goal orientations, and participations in the online learning environment. The quantitative and subsequent qualitative data and analysis provided consistent results on these variables. Firstly, self-efficacy beliefs of the pre-service EFL teachers are examined. Considering the results from the quantitative data, pre-service EFL teachers, by and large, believe that they are efficacious in engaging students learning, managing EFL classes, and implementing instructional strategies. This result is noteworthy as teachers’ self-efficacy beliefs in their instructional efficacy affect the learning environment (Bandura, 1997; Wyatt, 2013). The interviews and subsequent analysis revealed that high and medium efficacious teachers differ in instructional strategies, students’ engagement, and classroom management themes. These differences are close to existing researches (Coutinho, 2008; Egel, 2009; Henson, 2001). At this point, the most effective way of developing a strong sense of efficacy is through mastery experiences, as proposed by Bandura. That is, performing a task successfully strengthens the pre-service teachers’ sense of self-efficacy (Zafarmand et al., 2014). On the basis of the interviews, high efficacious teachers seem to enhance the students’ performance and success as prior researches have mentioned (Henson, 2001; Tschannen-Moran et al., 1998). Moreover, pre-service EFL teachers’ selfefficacy beliefs seem too fragile. In a similar vein, Yuksel (2014) found that pre-service teachers’ self-efficacy beliefs are not stable and change at certain stages of teacher education. New experiences and challenges disrupt their pre-existing beliefs and force 25
them to reassess their capabilities. However, at the pre-service phase they try to be efficacious but this can change in in-service phase. Secondly, pre-service EFL teachers’ achievement goal orientations are also examined. The pre-service EFL teachers adopt more than one achievement goal, and mostly mastery goals for learning are adopted. These teachers expected to be very successful as their motivations and achievement behaviours are high (Afsaneh & Safoura, 2015; Dweck & Leggett, 1988; Elliot, 1999; Yeung, Tay, Hui, Lin, & Low, 2014). In addition, this is important since teachers adopting mastery goal orientations do well in difficult situations. However, mastery goal orientations involve the development of competence through task mastery and the emphasis is placed on developing new skills (Lindsay, 2010). However, mastery goal oriented teachers are open to change and self-transcendence values (Pudelko & Boon, 2014). Considering the results from the interviews, the themes namely learning aim, motivation, ability, effort, interest in learning and improvement led to differences when mastery and performance orientations compared. The learning aim and motivation came up as a powerful determiners in adopting goal orientations. The differences between mastery and performance orientations are also stated in literature (Coutinho & Neuman, 2008; Elliot, 1999; Nitsche et al., 2011; Retelsdorf et al., 2010). The issue, however, of participation in the online learning environment showed up no statistically significant relationship between achievement goal orientation and self-efficacy beliefs. However, on the basis of interviews, some differences between mastery and performance oriented pre-service EFL teacher were found. The differences between quantitative and qualitative results can be context-based. As discussed in the literature review, self-efficacy beliefs and goal orientations are two important variables that affect pre-service teachers in many ways (Bandura, 1997; Beghetto, 2007). The results of the present study indicated significant relationships between achievement goal orientation and self-efficacy and this result is consistent with the prior researches (Coutinho & Neuman, 2008; Eryenen, 2008; Hsieh et al., 2007, Minnella, 2010). In addition, this study supported the importance of self-efficacy (Bandura, 1997) and goal orientations (Nitsche et al., 2011) for pre-service teachers. CONCLUSION Based on current self-efficacy and goal orientation research in EFL teacher education and educational psychology, this study explores pre-service EFL teachers’ self-efficacy beliefs, goal orientations, and participations in online learning environment, which adds to the existing self-efficacy and goal orientation knowledge in pre-service teacher education process. However, the research is not without limitations. First, the research is limited to Distance English Language Teacher Education program at Anadolu University, in Turkey. Second, the use of asynchronous Web-based management tool in the program could also be a limiting factor. Third, the class structure is another limiting factor. If the class were structured in a different way, the results of the research may be different. Thus in the future, studies should be replicated with a bigger population to better assess and evaluate the relationships between achievement goal orientations, self-efficacy beliefs, and participation in the online learning environment. In addition, qualitative study in a long term may give different and deep results. Mastery and performance goals need further interpretation with male and female balanced studies. Besides, the four quadrants of goal orientations and self-efficacy beliefs need to be studied on a long term. And more research is needed about how these orientations affect the students of these teachers adopting different goal orientations and self-efficacy beliefs. Age and gender issues in goal orientations and self-efficacy beliefs need further studies. Self-efficacy and goal orientation motives are difficult to study. So more focused qualitative studies should be conducted to understand these issues deeply. In addition, there should be qualitative studies that examine the online learning environments effects on pre-service teachers’ self-efficacy beliefs and goal orientations.
Authors’ Note: This study has been reproduced from the Master's thesis of Hasan Uçar "Preservice English Language Teachers’ Self-Efficacy Beliefs, Goal Orientations and Participation in Online Learning Environment: A Study of a Distance English Language Teacher Education Program” under the supervision of Prof. Dr. Müjgan Yazıcı Bozkaya, at Anadolu University, Graduate School of Social Sciences. BIODATA and CONTACT ADDRESSES of the AUTHORS Hasan UCAR is an English language instructor at the Department of Foreign Languages, Bilecik Seyh Edebali University, Turkey. He received his Bachelor’s degree from College of Open Education, English Language Teaching Department, Anadolu University. He holds a Master’s degree in the Department of Distance Education from Anadolu University. Currently, he is a doctoral candidate at the Department of Distance Education, Graduate School of Social Sciences, Anadolu University. Hasan’s current research agenda is motivational design of instruction in online learning environments. Additional areas of research include instructional design/technology, teaching and learning in online technologies, and motivation and engagement of online learners. Hasan UCAR Bilecik Seyh Edebali University, Bozuyuk Vocational School, 11300 Bozuyuk/Bilecik/Turkey Phone: +90 228 2141315 e-Mail: [email protected]
Prof. Dr. Mujgan YAZICI BOZKAYA earned her M.S. and Ph.D. degrees in Communication Sciences from Anadolu University. She is a full Professor at the Open Education Faculty, Anadolu University, Turkey. In her current position, she serves as a Coordinator and an Instructional Designer in Open Education Faculty. Her research interests are Distance Teaching and Learning, Interpersonal Communication, Social Presence, SelfEfficacy, New Technologies and Textbook Design in Distance Education. She has presented in recognized national and international conferences and published scholarly articles. Prof. Dr. Mujgan YAZICI BOZKAYA Anadolu University Open Education Faculty, 26470, Eskisehir, Turkey Phone: +90 222 3350580 / 5880 e-Mail: [email protected]
REFERENCES Afsaneh, G. & Safoura, J. (2015). An exploration of EFL learners' perceptions of classroom activities and their achievement goal orientations. International Journal of Research Studies in Education. 4 (3), 33-45. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman and Company. Beghetto, R. A. (2007). Prospective teachers’ beliefs about students’ goal orientations: A carry-over effect of prior schooling experiences? Social Psychology of Education, 10, 171–191.
Butler, R. (2007). Teachers’ achievement goal orientations and associations with teachers’ help seeking: Examination of a novel approach to teacher motivation. Journal of Educational Psychology, 99 (2), 241-252. Chacon, T. C. (2005). Teacher’ perceived efficacy among EFL teachers in middle schools in Venezuela. Teaching and Teacher Education, 21 (3), 257-272. Coutinho, S. (2008). Self-efficacy, metacognition, and performance. North American Journal of Psychology, 10 (1), 165-172. Retrieved March 11, 2012, from,http://findarticles.com/p/articles/mi_6894/is_1_10/ai_n28518811/ Coutinho, S.A. & Neuman, G. (2008). A model of metacognition, achievement, goal orientation, learning style, and self-efficacy. Learning Environment Research, 11, Cresswell, J. W. (2012). Educational research: planning, conducting, and evaluating quantitative and qualitative research. Fourth edition. Pearson: Boston, MA. 131-151. Daal, S., Donche, V. & De Maeyer, S. (2014). The impact of personality, goal orientation and self-efficacy on participation of high school teachers in learning activities in the workplace. Vocations and Learning, 7, 21-40. Dweck, C. S. & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95 (2), 256-273. Egel, I. P. (2009). The prospective English language teacher’s reflections of self-efficacy. Social and Behavioral Sciences, 1, 1561-1567. Elliot, A. J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34 (3), 169-189. Elliot, A. J. & McGregor, H. (2001). A 2 x 2 achievement goal framework. Journal of Personality and Social Psychology, 80 (3), 501-519. Elliot, A. J. & Murayama, K. (2008). On the measurement of achievement goals: Critique, illustration, and application. Journal of Educational Psychology, 100(3), 613-628. Eryenen, G. (2008). The relationships between goal orientations, academic self-efficacy, and teacher sense of efficacy and predictive roles of these variables on pre-service teachers’ academic achievement. Unpublished master’s thesis. İstanbul: İstanbul University. Henson, R. K. (2001). Teacher Self-Efficacy: Substantive Implications and Measurement Dilemmas, Paper Submitted in Annual Educational Research Exchange Conference, Texas A. M. University, 1-43. Hsieh, P.; Sullivan, J.R. & Guerra, N.S. (2007). A close look at college students: Selfefficacy and goal orientation. Journal of Advanced Academics, 18 (3), 454-476. Kucsera, J.V.; Roberts, R.; Walls, S.; Walker, J. & Svinicki, M. (2011). Goal orientation towards teaching (GOTT) scale, Teacher and Teaching: theory and practice, 17(3), 597-610. Lee, I. & Yuan R. (2014). Motivation change of pre-service English teachers: a Hong Kong study. Language, Culture and Curriculum, 27(1), 89-106. Lindsay, P.C. (2010). Assessing the relationships among goal orientation, test anxiety, self-efficacy, metacognitıon, and academic performance. Unpublished master’s thesis. İllionis. University of North İllionis. McMillian, J.H. (2004). Educational research: fundamentals for the consumers . Fourth edition. Pearson: New York. Minnella, J. M. (2010). Achievement goals, self-efficacy, metacognitıon, and learning strategies as predictors of asynchronous learners’ academic success. Unpublished doctoral dissertation. Capella: University of Capella.
Nitsche, S., Dickhäuser, O., Fasching, M.S., & Dresel, M. (2011). Rethinking teachers’ goal orientations: Conceptual and methodological enhancements. Learning and Instruction, 21(4), 574-586. Pajares, M. F. (2002). Overview of social cognitive theory and of self-efficacy.Retrieved May 19, 2012, from, http://www.emory.edu/EDUCATION/mfp/eff.html Pudelko, C. E., & Boon, H. J. (2014). Relations between Teachers’ Classroom Goals and Values: A Case Study of High School Teachers in Far North Queensland, Australia. Australian Journal of Teacher Education, 39(8). Retrieved from http://ro.ecu.edu.au/ajte/vol39/iss8/1 Retelsdorf, J.; Butler, R.; Streblow, L. & Schiefele, U. (2010). Teachers’ goal orientations for teaching: Associations with instructional practices, interests in teaching, and burnout. Learning and Instruction, 20, 30-46. Sakar, N. (2009). Online course support in distance learning: Student evaluation of English language teaching Bachelor of Arts program. Turkish Online Journal of Distance Education, 10 (2). Tang, E. L., Lee, J.C., & Chun, C. K. (2012). Development of teaching beliefs and the focus of change in the process of pre-service ESL teacher education. Australian Journal of Teacher Education, 37(5). http://dx.doi.org/10.14221/ajte.2012v37n5.8 Tschannen-Moran, M.; Hoy, A. W. & Hoy, W. K. (1998). Teacher efficacy: Its meaning and measurement. Review of Educational Research, 68 (2), 202-248. Tschannen-Moran, M. & Hoy, A. W. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17 (7), 783-80. Wyatt, M. (2013). Overcoming low self-efficacy beliefs in teaching English to young learners, International Journal of Qualitative Studies in Education, 26 (2), 238-255. Yeung, A. S., Tay, E., Hui, C., Lin, J. H. & Low, E. (2014). Pre-service Teachers’ Motivationin Using Digital Technology. Australian Journal of Teacher Education, 39(3). http://dx.doi.org/10.14221/ajte.2014v39n3.1 Yuksel, G. H. (2014). Becoming a teacher: tracing changes in pre-service English as a foreign language teachers' sense of efficacy. South African Journal of Education, 34
Zafarmand, A., Ghanizadeh, A. & Akbabi, O. (2014). A structural equation modeling of EFL learners' goal orientation, metacognitive awareness, and self-efficacy. Advances in Language and Literary Studies 5(6). 112-124.
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 3
INTERNET ACCESS AND USAGE IN IMPROVING STUDENTS’ SELF-DIRECTED LEARNING IN INDONESIA OPEN UNIVERSITY Djoko RAHARDJO Faculty of Social and Politiacl Sciences Universitas Terbuka, Indonesia Prof. Dr. SUMARDJO Faculty of Human Ecology Bogor Agricultural University, Indonesia Dr. Djuara P. LUBIS Faculty of Human Ecology Bogor Agricultural University, Indonesia Dr. Sri HARIJATI Faculty of Mathematics and Sciences Universitas Terbuka, Indonesia ABSTRACT Internet is well known nowadays, however higher distance education students who live in remote rural areas still have not been able to take advantages of this medium optimally for their learning process. For accessing the internet the students have to be available with the minimum prerequisites: the existence of adequate devices and the sufficient capabilities. For education purposes, the students use the internet to meet their information and fulfill learning needs, facilitate interpersonal communications, and provide groups of discussion, as well as to be connected with friends in social media. This study aims to analyze the relationship between internet access and usage in improving students' self-directed learning which is using structural equation model method. The survey is conducted in seven districts in Surakarta Regional Office of Indonesia Open University with a sample size of 320 respondents. The result shows that the internet usage is still low due to limited internet facilities that affect the knowledge and willingness of students to access the internet. The strategy in improving student internet usage is applying social media as guidance that can be accessed through cellular phones. Keywords: Internet access, internet usage, distance education, self-directed learning INTRODUCTION Internet is growth in popularity as learning media in higher distance education, unfortunately students in some rural areas are still not utilizing the internet to fulfill their need. Web-based distance education application has become increasingly playing an important role in the development of students learning, however it need some requirements to access the internet. To access it, they have to provide themselves, not only with the availability of devices, but also with the access capability. The use of internet in higher distance education particularly emphasizes on meeting the needs of information, interactive communications between educators and learners in the learning process, forums for students to discuss both teaching materials and other
academic administrations, as well as social communications which more open among students who are used as a venue for private disclosure or the interests of their learning processes. This is in line with Park in Dogruer et al. (2011) which stated that the function of the internet in education, among others, as (1) storing the information, (2) means of communication without bounds, (3) an interactive online learning. While Gaytan described in Stanciu and Inca (2014) confirmed that there are several levels in the use of the internet, namely, (1) gathering information, (2) sharing information with friends who have the same interest, (3) working on the internet as part which has been planned, (4) studying according to the curriculum that has been prepared by the tutor to be done through the help of it, and (5) designing activities which apply learning independently. Some researches have been carried out in order to identify and to solve the problem of access and use of internet. For example, Rye and Zubaidah (2008) focused on the problem of accessing the internet at graduate students of Pangkal Pinang Regional Office of Indonesia Open University (Universitas Terbuka/UT) in Bangka Belitung Islands which concluded that student adversity not only on the unavailability of the means but also the problem of unfamiliarity in the internet use. This would be a challenge for students since the absence of other appropriate means to support their learning process. Daulay (2008), which examined the interaction of students in the Online Communication Forum at the UT’s website, identified that the highest rating of communication was personal interactions, and the second rating was problems with tutorials and other administrative matters. The conclusion of the study stated that the biggest obstacle of the students was the lack of communication. Omotayo (2006) conducted a survey of internet use among undergraduates. The results showed that internet use is quite high, especially in internet café. Internet usage does not affect the use of the library. The common problem faced by students is the weak signal from the server and cost issues. Chen and Fu (2009) studied the association between internet use and academic achievement of the high school students in northern Taiwan. The findings confirmed that the search information through online help improve test scores. While the internet which was used in socializing, playing and accessing through internet cafes lowered the performance of their exams. Peou et.al. (2011) observed the relationship of the use and attitudes towards the internet, and the academic utilizing in Cambodia. Use of the internet for academic purposes was still rare among the students. It concluded that main reason was technology adoption costs. All the examples above, however, they were inadequately discussing on the students’ attitudes in the access and use of the internet, i.e. internet knowledge, willingness, and the ability to operate the devices. This research paper presents a survey on students’ internet access behavior (IAB) and internet usage (IU) especially their university’s website. On the basis of this investigation, it then describes how to improve students self-directed learning (SDL) index. The students who have the ability of SDL becomes importance concept in distance education (Moore and Kearsily, 2012). In online learning, SDL constitutes of the effect of communication process. Index of SDL according to Williamson (2007) can be described in five dimensions of learning, i.e. awareness, learning strategies, learning activities, evaluation, and interpersonal skill. The success of the students in learning processes can be identified by these dimensions. Departing from the above description, this research purposes can be formulated as follows: Ø To analyze the relationship between IAB, IU, and SDL? Ø To formulate a strategy that can be used to improve student SDL index? METHOD Population and Sample The population of the study included regular undergraduate students who registered the semester exams in the second academic year of 2013 in Surakarta Regional Office of
Universitas Terbuka, Indonesia. The random sample was obtained in research sites. The research sites were seven regencies of Surakarta namely Boyolali, Klaten, Karanganyar, Sragen, Sukoharjo, Surakarta, and Wonogiri. According to Kline (2011) that “typical” sample size in studies where structural equation model (SEM) is used is about 200 cases and the same as Hoyle (1995) that stated as “practically reasonable sample size”. While Bentler and Chou (1987) suggested the ratio sample size to number of free parameters may be able to go as low as 5:1. Three hundred twenty students (320 samples) responded to a questionnaire assessing their behavior related to the internet in the process of learning. Instrument The survey on Internet Access and Usage in improving Self-Directed Learning was based conceptually on the eleven factors. Specific questions were developed to measure selfdirected learning rate which was adopted from Williamson (2007). They were awareness, strategy of learning, activity of learning, evaluation of learning, and interpersonal skill. Internet access consisted of three main factors, i.e. cognitive, affective, and conative aspect which each of them have three dimensions of questions: using, searching and communicating. The Internet Usage contained three factors, i.e. learning, fulfilling information need, and communicating. Each of them consists of 5 questions. While the environment factor was composed of three factor i.e. availability of internet, social support, and environmental barriers. Face validity of the questions was established by three expert reviewers. Procedure After obtaining approval from the university, survey were conducted. The data collected when the students came to the classroom tutorial (face to face tutorial) places. Before data analysis carried out, the research instrument was examined to get its validity and reliability. These result of the test indicated that the instrument used were sufficiently valid and reliable; with each indicator had a count r > r-table (0.1946) and with Cronbach alpha values = 0.919. Data Analysis In order to get the map of relationships among the variables, SEM method was applied using AMOS 22. Because the result of multivariate test on the variable was non-normally distributed, bootstrapping method was applied, and resample was set to 500. The final result of model showed that Bollen-Stine bootstrap p = 0 .112, it meant that the model had a good fit. RESULTS AND DISCUSSION Account and Access Equipment Ownership From the analyzing data, it found generally that students owned equipment sufficient enough for them to access the internet, and it was only 6.9% of the students who do not have access to this equipment. However, it did not reduce the spirit of challenge them to access the internet in fact that half of the students who do not have the equipment have internet accounts (Table 1). To access the internet, they utilized internet café or internet available in the workplace. One fifth (21.3%) of the number of students did not have an account, although most have internet access equipments. This means that some students were not accustomed to communicating via the internet.
Table: 1 Number of students according to ownership of internet accounts and access equipments Access Equipment Ownership No equipment Cellular phone PC+Tablet+Laptop All kind of devices Total (%)
No internet account 10 39 5 14 68 (21.3)
Email 8 66 12 41 127 (39.7)
Internet account ownership Email Email+Facebook +Facebook +Twitter 3 1 38 12 18 2 36 21 95 36 (29.7) (11.3)
Total 22 155 37 106 320 (100)
(%) (6.9) (48.4) (11.6) (33.1) (100.0)
Variable Index: Environmental Factors, Internet Access, and Internet Usage The capability of students to access the internet was quite good, the students’ knowledge and willingness to access these media was high, the ability of the student to access the internet, however, was still in a medium rank (Table 2). Environmental factors were generally considered to be high with low resistance/barriers. It discovered that students' communication with other people using the internet rather low, while the level of the students to exploit the information in the university website was in a medium level. It can be concluded that environmental factors were sufficient to support height student access level, but it could not maintain the level of internet usage.
Table: 2 Variables and Score Values: Environment factors, Internet Access Behavior, Internet Usage Variables Score Value(%) Environmental factors Availability of internet 57.70 Social supports 68.13 Environmental Barriers 34.65 Internet Access Behavior Cognitive/ knowledge 75.28 Affective/ attitude 83.16 Conative/ ability 56.49 Internet use Information need 36.09 Learning activity 27.60 Communication 28.56
Level of availability of internet facilities are generally inadequate. These findings are similar to the study reported by Rye and Zubaidah (2008) in the Bangka Belitung Islands. It was thought to relate to the availability of telephone networks in the regions where they lived. Family support was an important element for the advancement of student education. With the support of family, students could be better motivated to learn. Support was generally due to economic problems, given that the costs used to access the internet is not cheap (Omotayo, 2006). Confirmatory Factor Analysis of Access and Use of Internet, and Environment Factors Using bootstrap method in AMOS version 22 and setting to be 500 resample, this analysis generated a model of confirmatory analysis as shown in Figure 1. It found that the model had a negative variance (eF2= -69,9), so variance value had to be changed into smaller (0.005). It found that there were 3 indicators which had loading factors < 0.5. These indicators had to be dropped for the next analysis.
Figure: 1 Confirmatory factor Analysis of Full Model In order to get a model with valid indicators, some indicators had to be dropped. The final result of confirmatory factor analysis can be seen in Figure 2.
Figure: 2 The Final Result of Confirmatory factor Analysis of Access and Use of Internet
Model of Access and Use of Internet, and Environment Factors The final result of model showed that Bollen-Stine bootstrap p = 0.056, it meant that the model had a good fit. As represented in Table 3, the model enjoys good fitness based on the above criteria. RMSEA equals 0.038 which is smaller than 0.8 and the indices GFI, AGFI, and CFI are all greater or near 0.90; therefore the model shows a good fitness and is confirmed. Table: 3 Goodness of Fit of Access and Usage of Internet Model CMIN
Figure 3 was the final model of Access and Usage of internet. This model illustrates that to improve the rate of the students’ internet usage, it needs to maintain environmental factors, however, these factors such as: home internet facilities, family support, environment barriers are personal condition that can not be reached by the institution. This model also reveals that the behavior of access that can be used to improve the use of the internet is the ability to search the information through the internet. Searching in the internet capability is an important aspect to be improved in order to increase their internet use. Students had enough knowledge to access the internet and they agreed to use internet, but they had inadequately abilities to access it. The students were capable of searching information on the internet. It was the basis for students to develop themselves in the use of the internet. This condition was a pretty good starting point for further development.
Figure: 3 Final Model of Access and Use of Internet
Students in the use of the internet for the benefit of the learning process was still deficient. These findings confirmed what has been studied by Peou et.al. (2011) in Cambodia. Online exercise was still underutilized by students, and it was suspected that students preferred to use offline exercises provided in their textbook for lower cost. That the use of online tutorial was at a low level showed that the students were not yet accustomed to taking the advantage of application. It was assumed that student still preferred traditional ways of learning, classroom tutoring. Students still rarely used email to communicate better with friends, faculty, and academic staff UT. This finding was similar to Daulay (2008) which stated that students were less communicate. The Relationship among the Internet Access and Use, Self-Directed Learning, and GPA In order to identify the relationship among the internet access and use, self-directed learning, and GPA, the data were correlated using SPSS. It found that students in accessing the internet was positively correlated with the use of the internet and self directed learning, but not positively correlated with GPA. Internet usage correlated with self directed learning but not correlated with GPA, while self directed learning was positively correlated with GPA (Table 4). Therefore any change in internet access behavior and internet usage will affect students’ self directed learning. The effect on internet access behavior to GPA was indirectly. It is similar to Chen and Fu (2009) who found that the search through the internet helps improve GPA. Table: 4 Correlation matrix between Internet access, Internet usage, Self-directed learning, and GPA (N=320) Spearman’s Internet Internet Self-Directed Variables rho Access usage learning Internet access Corr. Coef. 1 0.469** 0.307** Sig. (2. 0.000 0.000 tailed) Internet usage Corr. Coef. 1 0.178** Sig. (2. .001 tailed) Self-directed learning Corr. Coef. 1 Sig. (2. tailed) GPA Corr. Coef. Sig. (2tailed)
GPA 0.040 0.447 0.010 0.870 0.135* 0.015 1 .
Strategy to Improve Self Directed Learning Importance and Performance Analysis According to Pike (2004) the importance-performance analysis techniques could be used to assist in decision-making according to priority. Using scatter plot graphic in SPSS, this analysis results a matrix formed by the two axes, namely, the X axis was the score values, while the Y axis was the loading factors. The matrix formed four quadrants, i.e. quadrant-1 and quadrant-2 had a high priority, quadrant-3 and quadrant-4 had a low priority. In general, internet access behavior was a group of attributes that need to be maintained and receive the highest priority in improvement, while internet usage especially in the aspect of learning was the next priority needs to be increased (Figure 4).
Specification: itn1 =home internet facility itn3 = café availability itn4 = network availability supp1 = family support supp2 = government support barr2 = distance to cafe barr4 = barrier access time cog2 = internet knowledge cog3 = searching knowledge cog4 = communication knowledge aff2 = internet access willingness aff3 = searching willingness aff4 = communication willingness con2 = internet ability con3 = searching ability con4 = communication ability info1 = education systems info2 = enrollment information info3 = exam / tutorials schedule info4 = course syllabus info5 = online bookstore learn1 = online course guiding learn2 = enrichment of materials learn3 = online exercise learn4 = digital library learn5 = Online tutorial com1 = email to colleague com2 = email to lecturers com3 = email to staff com4 = discussion forum com5 = participate in facebook
Figure: 4 Matrix of Importance Performance Analysis on Indicators Attributes in first quadrant were generally dominated by the half of the group variable of internet usage. This attributes had a high importance but low in performance. This condition illustrated that these attributes should be encouraged to be improved. Attributes in second quadrant were a group variable of internet access on all aspects, cognitive, affective, and conative. The group had both high importance and performance. This condition described that these attributes should get the first priority for further development. While attributes in quadrant-3 and quadrant-4 were groups of environmental factors and the internet usage. This condition had both low in importance and performance. This exemplified that these attributes were in a low priority. Strategy to Improve Self- Directed Learning By improving access and use of the internet was expected to result in increased students’ self-directed learning, which in turn will affect the student achievement index or GPA. Based on the analysis that has been outlined, it can be formulated a strategy in order to improve student self-directed learning. Increasing Internet Access The access devices were tools that must be absolutely available so that students could access the internet. As alternatives, the students could rent these devices at the internet cafes or other ways that could be managed by the students. While UT as the source of information which serves disseminating information through the media should make the absorption rate of information better. To increase it, UT had to pay attention to the facilities covered by the students, cellular phones were generally available. Therefore, the application in accordance with their internet devices should be considered to be developed more comprehensively.
The ability of searching plays an influential aspect for the improvement of self-directed learning. Searching information capability needs to get serious attention from UT institutions. This capability will allow students to obtain information quickly, as well as select information related to their needs. Regional Offices, who serves as the representative of the university, already provided training on how to access and use of the internet to the students during the first year they enroll UT, however, these capabilities should be developed in more practical. Improving Internet Usage To improve students in using the internet, UT need to do things as follows: To accomplish the information need is the basic requirement that the student learning process can take place. UT as an institution has prepared a variety of information to meet the needs of students. To improve the internet usage rate, UT as the information source should apply more intensive socialization through meetings in Regional Offices or in student study groups to learn about the features that are available in the Website UT. This way will result increasing of student knowledge in the available information more efficiently. The internet usage for learning dimension is an important aspect in distance education. UT institutions fully understand that the internet has characteristics best suited to distance education system. The low level of internet usage in the dimension of learning is the consequence of failure devices used by the students that cannot retrieve the information available. Therefore, it needs the development of internet program which is more accessible by cheaper equipment and affordable for students. Internet usage for the communication needs is also an aspect that is no less important. The low level of the communication resulted in low student motivation to learn. The low of internet use in communication aspect can be fixed by the use of social media (Facebook or Twitter) as an alternative medium. Social media can solve the problem of technological limitations. Too large access charges lead to weaken the response rate of the server computer. Similarly, the addition of a new feature to the system that’s already established would increase to the load of the server computer. CONCLUSIONS Based on the results and discussion that has been described can be summarized as follows: Ø
Low levels of access equipment availability is a major factor for the lack of internet usage among UT students in the remote area. Access equipment owned by students, cellular phones, do not reach adequately the information provided by UT. The students’ searching capabilities including the aspects of knowledge, willingness, as well as ability, have a positive association with the students in using the internet. The lower capability of students in searching information becomes the one of factors that can determine the weakness of study completion. The level of internet usage in searching information and in learning dimensions generally remains at a low level. Since the internet usage has positively correlation with self-directed learning, the very low learning dimension in internet usage will affects the students’ self directed learning.. The strategy which is expected to enhance students’ SDL is aimed at strengthening the ability of searching information, increased the use of the internet on aspects of learning by using less expensive access equipment, and the development of the use of social media as a second media to cope with technological problems.
RECOMMENDATIONS Based on the results and conclusions of research can be put forward the following suggestions: Ø
In order to solved the problem of the low rate of internet usage with the condition of limited access devices, UT should develop an extension application that aims at expanding internet access and it should be strengthened to the devices which have been already owned by most of the students. Most devices in Indonesia from the cheapest to the most expensive ones (cellular phones or tablets) use “android” application, for that reason UT should take notice to this application. In order to increase self-directed learning it is necessary to strengthen the capability of students in searching the internet since SDL has positively correlation with internet searching capability. For that reason, Surakarta Regional Office and study groups should conduct comprehensive training on “how to search the information through the internet”, so that students can realistically use the internet for searching information. The use of social media is directed to be applied as second media for the purpose of their learning process. The students as adult people generally fond of using the social media e.g. facebook, twitter, or others to make contacts with their colleagues by means of cellular phones. By this, they can update their friends in their environments. To insert learning purposes to this “easy touch” media hopefully can overcome the limitations and cost of existing media technologies. Therefore it is necessary to develop the management information so that students can be more intense in communicating both with the tutor and other interested parties as well as obtaining information immediately.
BIODATA and CONTACT ADDRESSES of the AUTHORS Djoko RAHARDJO was born in Surakarta, Indonesia on June 25, 1958. He graduated from Magister of Librarian and Information Study, Faculty of Humanities, University of Indonesia in 2004. When he wrote this article he was a doctoral candidate of Development Communication Study Program at Bogor Agricultural University. He is a lecturer in Communication Science Department, Universitas Terbuka Indonesia. His main interests are communication media and distance education. Djoko Rahardjo, M. Hum Universitas Terbuka, Indonesia Faculty of Social and Political Science Jalan Cabe Raya Pamulang, Tangerang Selatan, Indonesia Email: [email protected]
, [email protected]
Prof. Dr. SUMARDJO was born in Sukoharjo Indonesia on February 25, 1958. He graduated from the Bogor Agricultural University, Department of Communication / Extension Development in 1999. He was professor of extension development at the Faculty of Human Ecology, Bogor Agricultural University. He graduated master of science in rural sociology Bogor Agricultural University in 1988. He serves as the head of the Research Center for Conflict Resolution and Social Empowerment. The main interest in the research is education development, cyber extension, community development, and conflict resolution. Prof. Dr. Sumardjo Bogor Agricultural University, Indonesia Jalan Dramaga, Bogor Indonesia Email: [email protected]
Djuara P. LUBIS was born in 1960. He received his PhD in Development Communication from University of the Philippines, College of Development Communication in 2000. Since 1985 he has been working as lecturer in Bogor Agricultural University, Indonesia, and serves as head of Development Communication Study Program. Dr. Djuara P. Lubis Bogor Agricultural University, Indonesia Jalan Dramaga, Bogor Indonesia Email: [email protected]
Dr. Ir. Sri HARIJATI, MA. was born in Madiun, East Java, Indonesia in 1962. She completed her doctoral program in the field of "extention of development" at Bogor Agricultural University in 2006. She works at Universitas Terbuka since 1988 on The Study Program of Agribusiness. She has been working as an online Tutor for several agricultural extension cources. Universitas Terbuka is an Indonesia university that implements open and distance education system. She is interested in areas of research in online learning. Dr. Ir. Sri Harijati, MA. Faculty of Mathematics and Natural Sciences, Universitas Terbuka, Indonesia Jalan Cabe Raya, Pondok Cabe, Pamulang Tangerang Selatan, Banten, Indonesia. Fax: (62)021 7434691 Phone: (62)021 7490941 E-mail: [email protected]
REFERENCES Bentler, P.M. and C.-P. Chou. (1987). Practical issues in structural modeling. Sociological Methods & Research 16(1): 78-117 Bucy, EP., and Newhagen, JE. (Ed) (2004). Media access: social and psychological dimensions of new technology use. London (GB): Lawrence Erlbaum Associates, Inc. Chen, SY. and Fu, YC. (2009) Internet use and academic achievement: gender differences in early adolescence. Adolescence, 44 (176), 797-812 Daulay, P. (2008). Analysis of the contents of an interactive discussion topics Open University student in the feature "Online UT Communications Forum". Scriptura 2, 135-149 Dogruer N, Eyyam R, and Menevis I. (2011). The use of the internet for educational purposes. Prosedia- Social and Behavioral Sciences 28, 606-611 Hoyle, RH. Editor. (1995). Structural Equation Modeling: Concepts, Issues, and applications. London(GB): Sage Publications Kline, Rex B. (2011). Principles and practice of structural equation modeling 3rd ed. New York(US): The Guilford Press Moore, MG, Kearsley, G. (2012). Distance Education: A system view of online learning. Edition-3. Belmont(US): Wadsworth Omotayo, BO. (2006). A survey of Internet access and usage among undergraduates in an African University. The International Information & Library Review, 38, 215-224
Peou, C. and Lwin, M. (2011). Integrating the internet into Cambodian higher education: exploring students' internet uses, attitudes and academic utilization. International Journal of Emerging Technologies and Society 9 (2), 95-115 Pike, S. (2004). The use of repertory grid analysis and importance-performance analysis to identify determinant attributes of universities. Journal of marketing for higher education, 14 (2), 1-14 Rye SA, Zubaidah I. 2008. Distance education and the complexity of accessing the internet. Open Learning. 23(2), 95–102. DOI: 10,1080/02680510802051897. Stanciu, V. and Inca, A. (2014). A critical look on the student's internet use- empirical study. Accounting and Management Information systems, 13 (4), 739-754 Williamson SN. (2007). Development of a self rating scale of self-directed learning. Nurse Researcher. 14(2), 66-83.
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 4
QR CODES IN EDUCATION AND COMMUNICATION Dr. Gurhan DURAK Necatibey Faculty of Education Balikesir University, Balikesir, TURKEY E. Emre OZKESKIN Open Education Faculty Anadolu University, Eskisehir, TURKEY Dr. Murat ATAIZI Communication Sciences Faculty Anadolu University, Eskisehir, TURKEY ABSTRACT Technological advances brought applications of innovations to education. Conventional education increasingly flourishes with new technologies accompanied by more learner active environments. In this continuum, there are learners preferring self-learning. Traditional learning materials yield attractive, motivating and technologically enhanced learning materials. The QR (Quick Response) Codes are one of these innovations. The aim of this study is to redesign a lesson unit supported with QR Codes and to get the learner views about the redesigned material. For this purpose, the redesigned lesson unit was delivered to 15 learners in Balıkesir University in the academic year of 2013-2014. The learners were asked to study the material. The learners who had smart phones and Internet access were chosen for the study. To provide sectional diversity, three groups were created. The group learners were from Faculty of Education, Faculty of Science and Literature and Faculty of Engineering. After the semi-structured interviews were held, the learners were asked about their pre-knowledge about QR Codes, QR Codes’ contribution to learning, difficulties with using QR Codes about and design issues. Descriptive data analysis was used in the study. The findings were interpreted on the basis of Theory of Diffusion of Innovations and Theory of Uses and Gratifications. After the research, the themes found were awareness of QR Code, types of QR Codes and applications, contributions to learning, and proliferation of QR Codes. Generally, the learners participating in the study reported that they were aware of QR Codes; that they could use the QR Codes; and that using QR Codes in education was useful. They also expressed that such features as visual elements, attractiveness and direct routing had positive impact on learning. In addition, they generally mentioned that they did not have any difficulty using QR Codes; that they liked the design; and that the content should include both superficial and in-depth information. Keywords: Mobile learning, QR Code, Communication, Distance education INTRODUCTION It is possible to say that wider use of the Internet and the decrease in the prices of mobile devices has increased the use of these devices. People can work without any restriction of place and make use of these devices for different purposes. According to AlKhalifa (2011), one of the most important aspects of mobile phones is their ability to access the Internet anywhere, which makes it possible to reach the information at any time they need. Mobile, namely ubiquitous learning is reshaping the learning environment. From SMSs to Smart Phones, it has changed the way of interaction 42
between learners and the learning materials. Learners can reach learning objects (video, text, sound etc.) faster than ever before. Since correspondence learning, hard copy materials (course books) are the base materials of learning for open and distance learning courses at Anadolu University (“Acikogretim Sistemi - Tarihcesi,” 2012). According to ABI research (2013), there were 1.4 billion smart phones in the World. A raport about the use of smart phones, which was published in 2014, shows that the number had reached to 1.75 billion (eMarketer, 2014). Another study revealed that 89% of the smart phones are used all day (Smartphone users around the World, 2012). Figure 1 presents the reasons for use of smart phones in the second half of 2011 around the World. According to the data presented in the Table, smart phone owners use their phones for gaming, which is followed by social networks, music and news. Using smart phones for educational purposes is about 11%.
Uses of Smart Phones communication entertainment music
Figure 1: Uses of Smart Phones Figure 2 presents the monthly data use for 2013 and 2014. According to the data, there was an increase of 69% in a year. Figure 3 shows the total Internet traffic data in 2000 and mobile Internet traffic data in 2014. According to Figure 3, mobile traffic data in 2014 were thirty times more than the total Internet traffic data in 2000.
20.000.000 18.000.000 16.000.000 14.000.000 Web/Data/VoIP
4.000.000 2.000.000 0 2015
Figure: 1 2015 – 2019 Mobile data traffic by application TB by month (Cisco, 2015) When the graph in Figure 4 is examined, it is seen that two-third of the mobile data traffic will be of videos. THEORETICAL BACKGROUND This study is grounded upon the Theory of Diffusion of Innovations and Theory of Uses and Gratifications. The data in this study were interpreted on the basis of these theories. Theory of Diffusion of Innovations The Theory of Diffusion of Innovations put forward by Rogers is based on four factors: innovation communication channel, time and social system. According to Rogers (2003), this diffusion is a process of communication via certain channels between the members of the social system regarding the “new”. In his theory, Rogers defined ‘innovation’ as an idea, an application or an object considered to be new by an individual or organization. An innovation does not have to be a concept or a design that is definitely unknown. It is enough that the individual or organization has not used it before (Berger, 2005). There are five phases in Roger’s model: Knowledge, persuasion, decision, implementation and confirmation. Ø Knowledge: The individual gets informed about the innovation and its use. Ø Persuasion: The individual evaluates the positive and negative aspects of the innovation and shapes his/her attitudes accordingly. Ø Decision: In this phase, the individual decides to accept or reject the innovation. Ø Implementation: This phase exists if the decision phase is completed positively. Ø Confirmation: The Individual affirms and strengthens the adoption decision (Orr, 2003).
Figure: 2 The innovation-decision process (Rogers, 1995) Theory of Uses and Gratifications The theory of Uses and Gratifications was first announced by Elihu Kats. According to Katz, research on communication always focused on the question of ‘What does media do for people?’ but the real question should actually be ‘What people do with media?’ (McQuail & Windahl, 2010, p.167).
There are social and
resulting in need
expectations of the mass media
gratificatioon and other (often unintended consequences
Figure: 3 The Uses and Gratifications approach (McQuail & Windahl, 2010, p.168) In many studies based on the theory of Uses and Gratifications, gratifications obtained were perceived as motivations necessary for certain internet activities. Studies in related literature demonstrated that gratifications mostly included searching for information, entertainment, surveillance, communication between individuals, identity, acquiring status and gains (Charney and Greenberg, 2001; LaRose, Mastro and Eastin, 2001; Papacharissi and Rubin, 2000). QR CODES QR Codes consist of black modules arranged in a square pattern on a white background. They are designed to decode the data quickly. It is quite easy to create and use these codes (Pons, 2011). Using QR Codes for education is another way of using the Internet. Quick Response (QR) codes are versatile. A piece of long multilingual text, a linked URL, an automated SMS 45
message, a business card or almost any information can be embedded into the twodimensional barcode. With moderate equipped mobile devices, QR Codes can connect users to the information quickly and easily (LAW, SO, & 蘇永華, 2010). Since 2011, using QR codes has been used in different forms. According to comScore MobiLens (2011), 1 out of 5 smart-phone owners in U.S. scanned QR codes. Canada and Germany both saw near 16% of smart-phone owners scanning QR codes in a month, while the UK and Spain (home to the most penetrated smart-phone markets) saw just 12% of their participants scanning QR codes. (Source: comScore MobiLens, 3 mon. avg. ending Dec-2011) QR codes are used in a wide range of areas like media, street banners, all places leading to web sites, music, video and social networks (Arslan, 2011). According to Walsh and Andrew (2011), some of the beneficial uses of QR Codes include bridging printed materials to electronic materials, reaching voiced materials, opening embedded videos, providing libraries with external resources and reaching appropriate help. QR Codes in Education It could be stated that studies on use of QR Codes in education were generally conducted in the field of mobile learning. Review of the related literature revealed that mobile devices were used while using QR Codes. According to So (2008), the most important aspect of mobile learning is the triology of ‘location independence’, ‘time independence’ and ‘meaningful content’. These three basic features are among characteristics of mobile learning, and they differ from e-learning and web-based learning due to these features (Law & So, 2010). The rising speed of mobile technology is increasing and penetrating all aspects of human life. Therefore, this technology plays a vital role in learning different dimensions of information. Today, a clear shift from teacher-centered learning to student-centered learning causes students to find technology more effective and interesting than ever before (Miangah, 2012). In an experimental study conducted on the use of QR codes in education (Rikala & Kankaanranta, 2012), the views of 76 learners and of their teachers from four different-level schools were determined. The results of the study revealed that the learners were eager and motivated to use the QR codes. As for the their teachers, they approached cautiously to the use of QR codes in education and mentioned the likelihood of various difficulties to be experienced in relation to the preparation of lesson units and time. In addition, in the study, it was found that QR codes could motivate learners and draw their attention to class since these codes support learning and provide opportunities both for independent learning and for cooperative learning. In another study carried out by McCabe and Tedesco (2012), QR codes were used via smart phones for direct connection with the subjects within the scope of the course of mathematics. In the study conducted with 14 learners, all the learners reported positive views about the QR codes prepared for the course of mathematics. In such a course process, 83% of the learners stated that they prepared for the following lesson better and did their homework more productively, and 67% of them stated that there was an increase in their course marks and that they found it easy to use QR codes. In addition, as revealed by the most important finding obtained in the study, 83% of the learner experienced less stress when they studied for the lessons with the help of QR codes. According to the learners, the reason was that it was instantly possible to access the necessary information via QR codes without having to ask their peers or teachers. Hernández-Julián & Peters (2012), in their study conducted to compare doing homework online with doing homework on paper, found that an electronic environment could make it easier to access an instructional material and that it did not significantly influence learning. Al-Khalifa (2011) developed a Mobile Snapshot Response system with QR Codes. The system aimed at helping improve the communication between teachers and their students. Rivers (2010) designed a task-based QR Code system for English language teaching. In the study, the researcher explained how the system was developed, applied and tested. It was found in 46
the study that the learners enjoyed and benefited from the system while using it to carry out the course activities. Liu, Tan and Chu (2007), in their study, developed a learning system to improve learners’ English language levels with the help of QR Codes. The study revealed that the QR Code system helped learn English. Chen, Teng, Lee and Kinshuk (2011) conducted a study to allow access to digital materials through QR Codes in paper-based reading tasks. The results suggested that direct access to digital resources using QR codes does not significantly influence students’ reading comprehension. In their study, Ozcelik and Acarturk (2011) aimed at reducing the spatial space between printed and online resources using QR Codes. In this empirical study carried out with 44 university students, the students were divided into two groups (paper + mobile phone and paper + computer). In the study, it was concluded that thanks to QR codes found in course books, mobile devices contribute to learning since it is easily possible to access information online. Baker (2010) used QR Codes in his study titled “Making Physical Objects Clickable: Using Mobile Tags to Enhance Library Displays”. The researcher reported that libraries should contain both physical and electronic media and that the mobile labeling technology between these two environments will provide a solid basis for new generation libraries. Hwang, Wu, Tseng and Huang (2011) developed a learning platform using QR codes via cell phones which are low-priced and which have a camera and internet connection. This empirical study showed that the learners using the platform demonstrated meaningful improvements in terms of learning efficiency and learning achievement.
Designing a Lesson Unit Supported with QR Codes In this study, QR Codes were added to a lesson unit of Computer-101 course book for Anadolu University Open Education Faculty. As can be seen on figure 7, we created a twitter account, a Facebook support page and QR links to the digital form of the course book. As Bolter & Grusin (2000) mentioned, hypermedia aims at addressing multiple and different senses of human. Use of more senses for hearing, seeing, smelling and touching, learning increases learning. Instead of the medium, the instructional methods cause the learning (Clark & Mayer, 2008), but using different media provides ability to use different strategies.
Figure: 4 Cover page showing Twitter and Facebook Support pages
In Figure 8, there are two different QR Codes from the lesson unit? The upper one leads to a video about the subject, and the other leads to a Wikipedia page.
Figure 9: Google images and Flash videos Figure: 8
Using QR Codes in the lesson unit
In Figure 9, the QR Codes link to Google images and Flash videos.
Figure: 9 Google images and Flash videos METHODOLOGY The present study was designed as a case study. According to Creswell (2009), case study is a qualitative approach in which the investigator explores a bounded system (a case) or multiple bounded systems (cases) over time through detailed, in-depth data collection involving multiple sources of information (e.g., observations, interviews, audiovisual material, documents and reports) and reports a case description and casebased themes. In this study, the researchers redesigned a lesson unit of the course book by adding QR codes. The QR codes linked the learner to web sites, applications and social networks related to the subject to be taught. Participants The participants in the study were 15 students from Faculty of Education, Faculty of Science and Literature and Engineering Faculty of Balıkesir University in the academic year of 2013-2014. In the study, the purposeful sampling method was used. In this 48
method, the researcher decides whom to include in the study and chooses the participants most appropriate to the purpose of the research (Balcı, 2004). The students who were chosen for the study met the criteria of having a “smart” phone and having access to the Internet using their phones. These students were divided in three groups: Ø Group 1: Second-grade students from the Department of Computer and Instructional Technologies in Necatibey Education Faculty Ø Group 2: Third-grade students from the Department of Mechanical Engineering in of Engineering Faculty Ø Group 3: Students from the departments of Physics, Chemistry and Biology in Faculty of Science and Literature The purpose of choosing these groups was to analyze different perspectives of students from different departments. Data Collection In this study, the researchers aimed at determining the learners’ views about the lesson unit supported with QR Codes. For this purpose, semi-structured interview questions were prepared. According to Ozguven (2004), semi-structured interviews provide an opportunity to make some changes during the interview for unpredictable situations. The process of preparing the interview questions began with draft questions and continued by getting expert opinion. After expert opinions, the necessary changes were made, and the interview questions were applied to three students as a pilot study. The purpose of the pilot study was to understand if the questions were clear, open-ended and consistent with the aim of the study. In line with the purpose of the study, there are six questions: Ø What was your level of knowledge about the subject before the study? After this lesson unit, what do you think your level of current knowledge about the subject is? Ø Did the QR Code supported lesson unit have positive influence on your learning? How effective it was on your learning? Ø What should the content of QR Codes be? (Text, Links to videos, texts, audios or images) Ø What problems did you experience while using the QR Codes? Ø What do you think about the design of QR Codes on pages? What are your suggestions? Ø Should QR Codes be used for details or for enhancement? (Enhancement; with same difficulty but with different perspectives, like a simple video, detailing; further information for whom it may concern)
Data Collection Process Interviews were held in one of the researcher room in Necatibey Education Faculty main campus. Total of 15 students participated the study. In the first phase, the participants were informed about aim of the research. During the meeting, detailed information was given to the participants about the purpose of the study and about the research method. The participants were also informed about such topics as installation of the necessary software, link to the support page and contact information. The students were asked for their consent and informed that the interview would be recorded and the recordings won’t be used for any other purpose. Following the first meeting, the course material (the computer course lesson unit supported with QR Code) was given to the participants, and they were asked to study the material for two weeks. In addition, a group was formed on a social network website, and the students joined to this group. The aim of the group was to provide technical support for the learners having trouble with QR Code application.
After two weeks, the time and place for the interviews were determined according to the participants’ choices. Each interview took approximately five minutes. After the interviews, the audio records were transcribed. According to the pre-prepared coding draft, the questions and the students’ answers were analysed and reviewed. Data Analysis For the analysis of the data, inductive coding and descriptive analysis were used. Inductive coding was used to reveal the concepts from the data and the connections between the concepts. In descriptive analysis, the data are summarized according to previously-set themes. For the purpose of emphasizing the views, direct quotations are frequently used. The findings obtained are interpreted based on the cause and effect relations (Yildirim and Simsek, 2008). The researchers, without making any changes on the records, converted them into written texts. For validity issues, an expert was asked for his opinion. According to Yildirim and Simsek (2008), if more than one researcher analyzes the data together, coding reliability must be studied. It is a must to reach .70 or higher for the reliability of the data. The researchers and the expert independently coded the data into appropriate themes. The codings were compared, and it was found that since the reliability value was higher than .70. Thus, the coding was found reliable. The data, which were placed according to the interview chart, were defined, and the results obtained were supported with direct quotations. FINDINGS After the analysis, the data were coded, and the themes were created. The findings were interpreted according to the theories of Diffusion of Innovations and Uses and Gratifications. The findings obtained via the research questions were as follows: Awareness of QR Code technologies, types and aims of using QR Codes, QR Code contribution to learning, and proliferation of QR Codes. Awareness of QR Code Technologies When the participants were asked about their awareness of QR Code technology, the following findings were obtained: Table: 1 Awareness of QR Code
Themes No knowledge Awareness Advertisements Medicine Boxes Posters TV – Internet
Frequency (f) 6 3 5 3 2
Types and Aims of Using QR Codes According to participants’ answers about their preferences of using QR Codes and about what their contents should be, the following findings were obtained: Table: 2 Types and Aims of Using QR Codes Frequency (f)
Themes Preferences of use Video Image Leading to social networks Audio files Download links Preferences to content Surface information Deep information Surface and deep information
14 5 7 4 5 3 1 11
When the participants’ views about using of QR Code were analyzed, it was found that almost all of the students agreed on video directing. The other ideas were linking to images, social networks, audio files and download links. On this topic student named Alper mentioned:
“... I prefer video and social networks. Because there are already images and texts in the book, but (using) videos wasn’t not possible. By using QR Codes it’s now possible to use videos. Also, I think social network sites used by a lot of people are easier and useful in terms of reaching the necessary information.” Most of the participants came to an agreement that separate QR Codes should be defined both for surface information and for detailed information abusing QR Codes. Regarding this, a student named Berk said:
“I think there must be both of them. Everyone should find something in an environment addressing large populations. There could be different levels of QR Codes.” QR Code Contribution to Learning The participants were asked about if using QR Codes for education had positive effect on their learning. If so, which features of QR Codes were contributing to their learning? The findings are presented in the Table below. Table: 3 QR Code Contribution to Learning Themes No positive effect on learning Positive effect on learning Visuals Ease of use Direct leading Attractiveness Updatable information resource
Frequency 15 9 5 8 9 5
About the reasons and positive effects on learning, all of the participants shared the same idea that QR Code supported lesson unit had positive effects on learning. When the reasons were investigated, the following themes were found: positive effect of visuals, ease of use, direct leading, attractiveness, and updatable information resource. A student named Mansur said:
“Of course it has positive effects on learning. It is more interesting than an ordinary book, so we can spend more time. In addition, there is an easier and updatable content. It is quickly updatable. I think I prefer someone teaching me to reading. That’s why I found it useful”. Proliferation of QR Codes The participants were asked for their ideas about proliferation of QR Codes to examine whether they would use QR codes or not; whether using QR Codes were effective; which factors would be the causes and which factors would restrain the use. The Table shows the findings obtained. Table: 4 Proliferation of QR Codes Themes The factors that would restrain the use Difficulties and technical problems in the process of transition to new technologies Lack of academic staff who know how to use QR Codes Preference of different technologies Lack of necessary equipment Need for technological knowledge It will be effective to use QR codes
Boredom with course books can be avoided Direct links reduce the loss of motivation Using multiple media together enriches the content
8 7 11
5 10 2 9 14
In addition, the participants listed the reasons for not using this technology as follows: lack of teachers/academic staff who know how to use the technology; other available technologies to prefer, lack of necessary equipment to use the technology, and if so, there is a need for technological knowledge. When the problems regarding the use of QR Codes in the lesson unit were examined, it was found that most of the learners did not experience any problem. Those who had problems reported that they experienced problems regarding fixing the cam angle, resolution and connection issues. The participants favoring the use of QR Codes reported that QR Codes acted like multimedia and that they could thus help reduce the routinized structure of books. In addition, according to the learners, they experienced less motivation loss, and enriched content would have positive effect on learning. One student, Alper, expressed his ideas as follows: “... when I become a teacher, I am planning to use QR codes. They help make learning more meaningful. Direct linking to the resources does not cause any loss of time helps reach where you want to We don’t lose time searching on the net. In addition, videos and audios available are very helpful.” Mansur said “I think it’s favorable. Young people may get bored while reading books, I think so, and I prefer this method.”
DISCUSSION This study aimed at identifying the views of the participants about the QR Code supported lesson unit. The results revealed that the participants achieved a consensus on the positive effects of QR Code on learning. They stated that they would use QR Codes in the future. This result could be explained with the theory of diffusion of innovations. According to the theory of innovations, throught five stages of the theory students got informed about QR Codes if they haven’t before, developed positive attitudes, accepted the innovation, impletmented by using the QR Code application and confirmed the would like use it in the future. In addition, the finding obtained is parallel to those reported in other studies conducted by Susono & Shimomuro (2006), Liu, Tun & Chu (2007), Hwang, Wu and Huang (2011) and Law & So (2010). According to the findings, participants find QR Codes effective in terms of visuals, ease of use, direct linking, attractiveness and updatable information sources. In addition the results of other studies carried out by Miangah (2012), Rivers (2010) and Law & So (2010) also support the results obtained in the present study. It was found that most of the participants were aware of QR Codes. Use of QR Codes in education was considered to be an innovation. This result shows similarity with the %65-response of ‘YES’ to the question of “Have you ever seen a QR Code before” directed in a study titled QR Code Usage and Interest Survey conducted by MGH (2011). The participants’ responses were listed as ads, medicine boxes and TV-internet. This result is also consistent with the findings reported by MGH (2011). The participants agreed that the QR Code technology should be used for the spread of QR Codes. This finding is consistent with those obtained in other studies carried out by Ozcelik and Acarturk (2011) and by Rikala & Kankaanranta, (2012). In this context, the participants’ expectations and gratification of these expectations were effective. The main factor preventing the use of QR Codes is the need for enough technological knowledge to install and use the application. Other factors can be summarized as difficulties in transition to a new technology, lack of academic staff who knows how to use QR Codes, learerns’ preferencing other technologies, and lack of necessary hardware. Mobile devices and improvements in Internet, both in terms of speed and content, have positive influence on diffusion of QR Codes. Similar findings were also obtained in a study carried out by Rikala & Kankaanranta, (2012). The difference from the this study is Rikala & Kankaanranta (2012) mentioned the probable difficulties to be experienced in preparing QR code contents and pointed out that such applications were likely to take a lot of time and that there was a need for more examples regarding its use. The participants mostly shared the same idea about using the QR Codes reporting that they preferred to access the videos. In addition, the participants also favored the feature of being directed towards social networks that leads learners to cooperate. Depending on this statement, it could be stated that the dimensions of communication and cooperation are necessary for learning. The dimensions of communication (Al-Khalifa, 2011) and cooperation (De pretro & Frontera, 2012) are findings obtained in studies conducted on the use of QR codes in education. When considered from the perspective of institutions, it could be stated on the basis of Uses and Gratifications Theory that the participants were satisfied with easy access to the learning content, direct linking and accessing rich content using QR Codes. The diffusion of innovation theory has five phases namely knowledge, persuasion, decision, implementation and confirmation (Rogers, 1995). In the knowledge stage, the learners were mostly familiar with QR Codes. Although they mentioned that they had never seen QR Codes in the field of education. The participants and the researcher 53
discussed whether using QR Codes for education would be effective or not. All of the students stated that there will be positive effect on learning. This can be named as persuasion stage.. At the decision phase, the participants were asked for the reasons that made them use course material supported with QR Codes. It was found that rich media, high motivation, ease of use, and direct link affected their choice of use. The findings obtained in this phase were similar to those reported in other studies conducted by Law & So (2010) and Rikala & Kankaanranta, (2012) (easy use and motivation). During the two-week review of the lesson unit, all of the learners used all the QR Codes. There is a time difference between users, some did it in a faster than the others. At the confirmation phase, the participants were directed questions about whether they were thinking of using QR Codes in the future. All of the students answered answered that if possible they would use QR Codes in the future. The interviews revealed that using QR Codes for education would be beneficial and attractive. That would have positive effect on learning. This result is consistent with the view reported by Rikala & Kankaanranta (2012) that learners want to re-experience QR code-aided learning and that such applications better be used for education. It is possible to say that the learners who had reviewed the QR Code supported lesson unit experienced the confirmation phase. The participants previously had knowledge about what the QR Code is, what is it used for and how it can be helpful for learning. They expressed positive opinions about increasing QR Code use for educational purposes. In addition, it is also possible to say that QR Codes completed its diffusion among the learners who reviewed the lesson unit. Conclusion CONCLUSION Its’ possible to argue that augmented reality applications offer novel interations between human and environment using mobile devices. The ubiquity of information systems dilutes the boundaries of electronic and non-elecronic tools, devices and environments. The era of information societies requires processing, transmitting and storing more data and information in an increasing trend. QR Codes can contain more information when compared to a regular barcode. Digital equipments like camera equipped mobile devices and related applications lead the proliferation of QR Codes. On the other hand the printed or the paper-based materials are still essential for deployment of information like books, newspapers, research papers, letters etc. Using QR Codes on printed materials like course books may enhance the attractive and elucidative aspects of printed materials. Although not many related studies have been conducted in the field of education, they are generally used for supportive purposes. The research on QR Codes shows that they were favored because of direct linking, merging rich contents and making them more enjoyable. Motivation is one of the key factors of learning for open and distance-learning learners. QR Code supported enjoyable learning environments may help learners to maintain their motivation. QR Codes especially used in libraries are becoming more common worldwide by uses and gratification (of QR technology?). It acts as a bridge linking the physical environment to the virtual environment. As in the rest of the World, In terms of Turkey, it is generally used in health-related environments, ads and bulletins. Although it is easier to use QR Codes, it is not possible to use them without technological necessities. It is also possible to argue that being accustomed to a technology may make the new technology easier to learn and use. In this perspective the use of QR Codes would increase in line with the increase in the related technologies like smart phones and tablets. 54
BIODATA and CONTACT ADDRESSES of the AUTHORS Dr. Gurhan DURAK has been working as a lecturer in Computer Education & Instructional Technology department at Balıkesir university since 2006. He recieved B.S and M.S degree in Computer Education & Instructional Technology Department at Balıkesir university. He has completed his doctoral degree on Distance Education at Anadolu University. He gives lessons about instuctional design, technology integration and distance education. He interested in online learning, instructional design, educational social networking sites, computer programming and distance education.
Gurhan DURAK Balikesir University Necatibey Faculty of Education Balıkesir TURKEY Phone: 90-266-2412762 ext: 150 Email: [email protected]
Emrah Emre OZKESKIN is lecturer at Open Education Faculty, Anadolu University. He graduated from Çukurova University Faculty of Education, English Language Teaching Department in 2001. He received his master degree in Computer and Instructional Technologies from the same university. He is also a Distance Education PhD candidate at Anadolu University. His research areas are adaptive learning environments, social network analysis and learning analytics. Lecturer Emrah Emre OZKESKIN Department of Distance Education, Anadolu University, Yunusemre Campus, 26470, Eskisehir, TURKEY Phone: +90 222 335 0580 / 2704 eMail: [email protected]
Dr. Murat ATAIZI is an associate professor in Communication Sciences Faculty at Anadolu University, Turkey. His research studies are communication technologies, problem solving, creativity, distance learning, and gamification in education and communication. His researches resulted in many articles and multiple chapters in published books, which investigate communication and educational communication context. He is currently managing a number of projects focused on using games in communication education and universal design in distance learning. Currently he teaches several graduate and undergraduate courses on communication technologies, creativity, problem solving, and distance learning both at the communication sciences faculty, and social sciences institute. Assoc. Prof. Dr. Murat ATAIZI Communication Sciences Faculty, Anadolu University, Yunus Emre Campus, Eskisehir, TURKEY, 26470 Fax: +90 222 3204520 Phone: +90 335 0581-5334, +90 542 5947244 Email: [email protected]
REFERENCES ABI (2013). Q4 2013 Smartphone OS Results: Is Google Losing Control of the Android Ecosystem? Retrieved from: https://www.abiresearch.com/press/q4-2013smartphone-os-results-is-google-losing-con. Anadolu University (2012). The History of Open Education. Retrieved August 20, 2014, from http://w2.anadolu.edu.tr/aos/aos_tanitim/aos.aspx Al-Khalifa, H.S. (2011). An M-Learning System Based on Mobile Phones and Quick Response Codes. Journal of Computer Science 7 (3): 427-430. Arslan, M. (2011). Kare kodlar ile hayatimiz degisecek [QR Codes will change our lives]. Bilim ve Teknik, 44 (523), 78- 79. Baker, L. (2010). Making physical objects clickable: Using mobile tags to enhance library displays. Journal of Library Innovation 1(2):22-28. Balci, A. (2004). Sosyal Bilimlerde Arastirma: Yontem, Teknik ve Ilkeler [Research in Social Sciences: Methods, Techniques and Principles],(4.Baskı). Ankara: Pegema Yayıncılık. Berger, J. I. (2005). Perceived consequences of adopting the Internet into adult literacy and basic education classrooms. Adult Basic Education, 15(2), 103–121. Bolter, J. D., & Grusin, R. A. (2000). Remediation : understanding new media. Cambridge, Mass.: MIT Press. Charney, T., & Greenberg, B.S. (2001). Uses and gratifications of the Internet. In C.A. Lin & D. J. Atkin (Eds.). Conzinunicatiorz teclznology and society: Audience adoptioiz and uses of the new inedia (pp. 379-407). Cresskill, NJ: Hampton. Chen, N. S., Teng, D. C. E., & Lee, C. H. (2011). Augmenting paper-based reading activity with direct access to digital materials and scaffolded questioning. Computers & Education, 57(2), 1705–1715. Cisco. (2015). Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2014–2019 (White Paper). Retrieved from http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visualnetworking-index-vni/white_paper_c11-520862.pdf Clark, R. C., & Mayer, R. E. (2008). E-learning and the science of instruction : proven guidelines for consumers and designers of multimedia learning. San Francisco, CA: Pfeiffer. Creswell, J.W. (2009). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (3.ed.). Los Angeles: Sage Publications, Inc. De Pietro, O., & Fronter, G. (2012). Mobile Tutoring for Situated Learning and Collaborative Learning in AIML Application Using QR-Code. In 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (pp. 799-805). Dogan, A. (2012). Hanehalki Bilisim Teknolojileri Kullanım Arastirmasi [Households Use of Information Technologies Research], Retrieved from http://www.tuik.gov.tr/PreHaberBultenleri.do?id=10880#
eMarketer. (2014). Smartphone Users Worldwide Will Total 1.75 Billion in 2014. Retrieved from: http://www.emarketer.com/Article/Smartphone-UsersWorldwide-Will-Total-175-Billion-2014/1010536#sthash.aW4Ti7aR.dpuf. Hernández-Julián, R., & Peters, C. (2012). Does the Medium Matter? Online versus Paper Coursework. Southern Economic Journal, 78(4), 1333–1345. Huang, H. W., Wu, C. W., & Chen, N. S. (2012). The effectiveness of using procedural scaffoldings in a paper-plus-smartphone collaborative learning context. Computers & Education, 59(2), 250–259. Hwang, G. J., Wu, C. H., Tseng, J. C. R., & Huang, I. (2011). Development of a ubiquitous learning platform based on a real-time help-seeking mechanism. British Journal of Educational Technology, 42(6), 992–1002. Intel Corporation. (2012). Intel Genc Turkiye Arastirmasi [Intel Young Turkey Research]. Retrieved from: http://www.slideshare.net/gayekokten/genc-turkiye-arastirmasi. LaRose, R., Mastro, D. A., & Eastin, M. S. (2001). Understanding Internet usage: A social cognitive approach to uses and gratifications. Social Science Computer Review, 19, 395-413. Law, C. & So, S. (2010). QR codes in education. Journal of Educational Technology Development and Exchange, 3(1), 85-100. LAW,C.Y., SO, W.W. S., & 蘇永華. (2010). QR codes in education. Journal of Educational Technology Development and Exchange, 3(1), 85–100. Liu, T., Tan, T., & Chu, Y. (2007). 2D Barcode and Augmented Reality Supported English Learning System. Proceeding of the 6th IEEE/ACIS International Conference on Computer and Information Science (pp 5-10). IEEE Computer Society McCabe, M. Tedesco, S. (2012). Using QR Codes and Mobile Devices to Foster a Learning Environment for Mathematics Education. International Journal of Technology Inclusive and Inclusive Education,1 (6), 37-43. Mcquail, D., Windahl, S. (2010). Iletisim Modelleri [Mass Communication Theory] (6.ed). (Çev: K.Yumlu). Ankara: İmge Kitabevi Yayınları MGH.(2011). QR Code Usage and Interest Survey. Retrieved from: http://cn.cnstudiodev.com/uploads/document_attachment/attachment/11/qr_co de_stats_3_23_11.pdf. Miangah, T. M. (2012). Mobile-Assisted Language Learning. International Journal of Distributed and Parallel systems, 3(1), 309–319. doi:10.5121/ijdps.2012.3126 Ozcelik, E., & Acarturk, C. (2011). Reducing the spatial distance between printed and online information sources by means of mobile technology enhances learning: Using 2D barcodes. Computers & Education, 57(3), 2077–2085. Ozguven, I. (2004). Gorusme Ilke ve Teknikleri[Interview Principles and Techniques]. Ankara: PDREM Yayınları. Papacharissi, Zizi and Alan M. Rubin (2000) “Predictors of Internet use”. Journal of Broadcasting &Electronic Media, 44 (2), 175–196. Pons, D. (2011). QR Codes in Use: The Experience at The UOV Library. Serials-24 (3), 4756. 57
Rikala, J., & Kankaanranta, M., 2012. The Use of Quick Response Codes in the Classroom. In 11th Conference on Mobile and Contextual Learning (pp.148-155). Rivers, D.J., 2010. Utilizing the Quick Response (QR) Code within a Japanese EFL environment. J. Jalt Call Sig, 5: 15-28. Rogers, M. E. (2003). Diffusion of innovation (5.ed.). New York: The Free Press. So, S. (2008). A Study on the Acceptance of Mobile Phones for Teaching and Learning with a group of Pre-service teachers in Hong Kong. Journal of Educational Technology Development and Exchange, 1(1), 81-92. Susono, H., & Shimomura, S. (2006). Using Mobile Phones and QR Codes for Formative Class Assessment. in A. Méndez-Vilas, A. Solano Martín,, J.A. Mesa González & J. Mesa González (Eds.). Current Developments in Technology-Assisted Education. Badajoz, Spain: FORMATEX. Uluyol, C., & Agca, R. K. (2012). Integrating mobile multimedia into textbooks: 2D barcodes. Computers & Education, 59(4), 1192–1198. doi:10.1016/j.compedu.2012.05.018 Walsh, Andrew (2011) Blurring the boundaries between our physical and electronic libraries: Location aware technologies; QR codes and RFID tags. The Electronic Library, 29 (4). pp. 429-437. ISSN 0264-0473
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 5
TEACHING AND LEARNING METHODOLOGIES SUPPORTED BY ICT APPLIED IN COMPUTER SCIENCE Dr. Jose CAPACHO Systems and Computer Science Engineering Department Universidad del Norte Barranquilla, COLOMBIA ABSTRACT The main objective of this paper is to show a set of new methodologies applied in the teaching of Computer Science using ICT. The methodologies are framed in the conceptual basis of the following sciences: Psychology, Education and Computer Science. The theoretical framework of the research is supported by Behavioral Theory, Gestalt Theory. Genetic-Cognitive Psychology Theory and Dialectics Psychology. Based on the theoretical framework the following methodologies were developed: Game Theory, Constructivist Approach, Personalized Teaching, Problem Solving, Cooperative Collaborative learning, Learning projects using ICT. These methodologies were applied to the teaching learning process during the Algorithms and Complexity – A&C course, which belongs to the area of Computer Science. The course develops the concepts of Computers, Complexity and Intractability, Recurrence Equations, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Shortest Path Problem and Graph Theory. The main value of the research is the theoretical support of the methodologies and their application supported by ICT using learning objects. The course aforementioned was built on the Blackboard platform evaluating the operation of methodologies. The results of the evaluation are presented for each of them, showing the learning outcomes achieved by students, which verifies that methodologies are functional. Keywords: Methodologies for virtual learning, virtual education, ICTs, virtual learning platforms, virtual assessment. INTRODUCTION The theoretical development of the research in relation to the teaching methodologies supported by ICT has the following phases: (i) Foundations of the behaviorist theory; (ii) Gestalt theory; (iii) Foundations of Genetic- Cognitive Psychology; iv) Bases of the Dialectical Psychology; and v) Bases of Computer Science. The research integrates theoretical part with the practice, as represented by the construction of the virtual course under the Blackboard platform. Finally, the research uses teaching methodologies, through the platform, based on the above-mentioned theories, in order to ensure students’ learning in virtual spaces supported ICTs. THEORETICAL BASIS OF THE METHODOLOGIES Pavlolv and Skinner are the main representatives of the behaviorist or associating approach regarding to classical and instrumental conditioning respectively. In behaviorism, human behavior receives the influences of the external world, which act as enhancers of it. Education becomes a technology represented by a sequence of actions consisting of mechanical stimulus- response - reinforcements, aimed at achieving the conditioning of the
conduct of the subject. This conception is based on the principle "man is the product of the environmental reinforcing contingencies" (Perez, A., 1995, p. 37). The conditioning involves a sequence of mechanical stimulation (S) presented to the subject, waiting for a response (R) and giving a reinforcement (E), generating a repetitive cycle of sequences S/R/E/ . . . S/R/E. The relationship of this cycle to a space of virtual training is represented by tutorial-type learning environments of virtual training, exercising and practice, or conditioning software, among others. The above mentioned environments are represented by learning objects, which integrate theoretical concepts with practice making the students learn about real world concepts. These learning objects can be built into the platform through games. Real and complex world cases in virtual spaces such as: “Design and implementation for location-based learning games” (Melero Gallardo, 2014); “The use of virtual worlds, with text-based, voice-based and a feeling of ‘presence’ naturally is allowing for more complex social interactions and designed learning experiences and role plays, as well as encouraging learner empowerment through increased interactivity” (De Freitas, Rebolledo-Mendez, Liarokapis, Magoulas, & Poulovassilis, 2010); or “Pervasive augmented reality games to experience tourism destinations” (Linaza, Gutierrez, & García, 2013). The Gestalt theory is interpreted as the figure and ground to give meaning to the student's learning, assessed via an observable behavior (a final exam). The Gestalt approach views the conduct as an organized whole (Perez, A., 1995, p. 41). Then, a platform supported by ICTs, in order to comply with processes of virtual training, is a system with hardware and software components, comware (communications) to which it is necessary to add the orgware (human talent) or the organization of the entire system of virtual training; if one of the parties fails, the system does not work. Considering the virtual space as a whole, the problem-solving teaching methodology supports the more complex learning; this is confirmed by the fact that: "An important educational application of Gestalt theory is in the area of productive thinking (problem solving) ". (Duncker, 1945; Luchins, 1942; Wertheimer, 1945 cited by Schunk, D., 1997, p. 57) .Thus, in a holistic sense, the virtual spaces of training through the teaching methodologies set out; allow the development of higher learning in the subject. In cognitive genetic psychology the two basic functional invariant of the intellectual functioning of the subject are the organization and adaptation. Assimilation and accommodation are the bases of the adaptation. The constant operation of these allow the formation of units of knowledge calls diagrams, whose development in the time form systems of knowledge and allow the subject to pass from a concrete thought to a formal one, in its biological-intellectual development . One of the support to better understand Piaget's theory has its basis on the Psychoanalytic theory of transference “…by regarding transferences as schemas in which assimilation predominates over accommodation" (Wachtel, 1980). The student in the learning process initially has some specific structures of knowledge. The student interacts with the platform supported by ICT and if she/he understands the structures of knowledge presented in the virtual course, then these diagrams are assimilated into her/his mind. This brings about the change of concrete cognitive structures to formal ones which corresponds to the stages of development of the subject (Hipsky, 2008), and the virtual learning of the student. Based on Piaget’s postulates, the course of A&C uses the personalized learning supported by ICT (Keane, Keane, & Blicblau, 2014; Lyashenko & Frolova, 2014) in order to evaluate the change of the cognitive structures of the student when interacting with the virtual course. For the Dialectical Psychology based on the materialist philosophy the concept of psyche is "(a) The psyche is a function … (b) the psyche of man is social,” (Montealegre, R., 1992, p. 11). Then, if the psyche of man is social, then the subject learns through the culture and the interaction with the other (Anh & Marginson, 2013). The culture is present in the form of signs through the digital network. These signs are stimuli-means for the subject, within which is the human language and accordingly the language contained in the virtual course. 60
It is important to mention that the language in the ICT impacts the cognitive domains of the subject’s audio, vision, touch, and smell. Therefore, "the main factor in the formation of concepts, and its generative cause, is a specific use of words as functional instruments". (Vygostky, L. 1995, new edition of the book Thought and Language in charge of Alex Kozulin p. 125). The signs or functional tools of language in the network supported by ICT allow the student to activate the Zone of Proximal Development - ZPD. The interrelationship of the ZPD with the ICTs is based on the fact that the cognitive functional structures of the brain are built in the ZPD or area of knowledge construction; and this area is influenced by the virtual learning space, generating in this way the student's learning influenced by the virtual course. The application of the learning in the interaction with the other strategy based on Vigostky’s postulates is performed in the course of A&C using the methodology of learning by projects. The projects are constructed based on the contents of the virtual course, the information of the Internet macro network, and the interaction between the students and the lecturer in charge. (Mukama, 2014). Constructivism is based on the Cognitive genetic psychology (Piaget), and on the dialectic psychology (Vigostky). In constructivism, learning is achieved by establishing relations between the new knowledge and knowledge structures already existing in the mind of the subject. In this sense, the design of the learning environment should allow the learners explore their preconceptions and interact with the virtual space supported by ICT; besides, it should generate new knowledge in the student, and finally, validate the new knowledge generated by the student through the network, with the teacher's guide, or with their peers, using learning communities. (S. Sergis, Zervas, & Sampson, 2014). In the virtual teaching-learning process, Constructivism must be understood not only as a philosophy but also as pedagogy. Then, it is necessary to associate constructivist teaching that comply with the process of social learning to virtual level. Thus, constructivist learning involves that the student must commit themselves to the social discourse using the network, and validate the status of truth of the concepts presented in the virtual course, for the students will generate their own concepts and their contribution to the construction of knowledge. The social discourse in the network makes it possible for the apprentice: understand other approaches in the resolution of problems, argue their solution, to negotiate their ideas, expand or decrease the complexity of the problems, validate the solution of problems in terms of effectiveness and efficiency, project new learning experiences and research of constructivist nature (virtual worlds) (Shieh, 2012; Kotsilieris & Dimopoulou, 2014). Collaborative learning is based on Vigostky’s Social and Cultural theory. The virtual course is a communication bridge between the student and the world, through the Internet. This network enables the communication of the pupil in the virtual course and with other virtual courses, providing opportunities to the student to interact with social and cultural contexts different from which they belong to (Dabbagh & Kitsantas, 2012). In this sense students’ learning is not only influenced by their preconceptions but by the culture in which they have been trained before applying to the virtual course. Based on the apprenticepreconceptions, the collaborative learning is achieved through social interaction (Dalgarno & Lee, 2010) that is presented in the learning process of the subject in their relationship with the other through the communication media, in this case the virtual course supported by ICT. The construction of knowledge in the subject has aspects both individual and social, allowing an active participation of the student and a more constructive role in the learning process. Therefore, the collaborative learning is an approach that allows the subject be aware of the process of acquiring their cognitive structures. As an active students, they must observe, compare and contrast their learning with that of their colleagues, through the socialization of the work as a team to achieve both their personal understanding as their sense of identity through social interaction (Hughes, 2007). The basics of Computer Science are related to the following areas: i) Software Engineering, as a basis for the construction of the virtual course learning objects. ii) Programming 61
languages needed to program the virtual learning environment supported by ICT. iii) Databases, to manage the status of student learning to navigate the virtual course. iv) Computer Networks, for the operation of the course under the macro virtual Internet. v) Security in computing, in order to meet security processes data stored in the course. vi) Operating Systems in order to manage both the virtual course within the Blackboard platform, and management processes processing requirements of both users (students) in the virtual learning and teachers in virtual teaching. vii) Quality standars, to be met by the construction of the virtual course supported by ICT, such as SCORM and IMS. DEVELOPMENT OF METHODOLOGIES SUPPORTED BY ICT IN THE BLACKBOARD PLATFORM The development of the methodologies proposed in this research paper will be applied using the virtual course Algorithms and Complexity – A&C, designed (Capacho, J, 2004) and programmed (Cure, V., & Fandiño, E (2005)) in the the Blackboard platform. In development it is important to mention that the course – A&C was designed in Web_CT; but as Web_CT was acquired by Blackboard, the virtual course – A&C is currently running on this platform. The teaching methodology of the subject Computers, complexity and intractability – CCI is Game theory which is based on the behaviorist approach. The Game has the following steps: 1) Presentation of the topics of CCI. 2) Activation of drill and practice games, structured on learning objects within the Blackboard platform. 3) Operation of the object of learning by the student. 4) Evaluation of the student learning or Assessment. 5) Reinforcement given to the student via the learning object. 6) Decision on the level of student learning. This decision allows: 7) Browse again learning objects or alternatively 8) continue with the next module of the course of A&C. It should be borne in mind that each game has a difficulty level, which represents the highest or lowest learning achievement acquired by the student during the game. The application of the methodology is shown in Figure 1, below:
Game theory with difficulty levels
Game theory using mazes Figure: 1 Virtual learning using Game Theory.
Greedy algorithms module was developed based on the Gestalt theory, applying the methodology of problem solving in virtual environments. The steps of this method are: 1) Student applies previous knowledge to new situations. 2) State the problem to be solved algorithmically. 3) Use the basic skills for the construction of greedy algorithms. 4) Define the figure and ground of the resolution of the problem (Human Computer Interface). 4) Translate the algorithms in a high-level languages (Java). 5) Run the program (JAVA). 6) Evaluate the results generated by the program. 7) Improve the program in terms of response time and memory space used. The results of the interfaces for the problems solved by Greedy Algorithms: Make Change and Memory Management in Operative systems are shown in Figure 2. 62
Figure: 2 Methodology of problem solving in virtual environments The problem of the shortest path in A&C was developed based on the postulates of Piaget's theory, and the teaching methodology used was the personalized teaching supported by ICT. The steps in this methodology are: 1) Organization of the learning structures in the virtual course on the problem of the shortest path. 2) Explore the student‘s preconceptions on the topic of algorithmic cases of the shortest route problem, or student’s concrete knowledge structure. 3) Interaction of students with learning objects related to the topic. 4) Assimilation and accommodation of the virtual environment content structures with students’ cognitive structures. 5) Self assessment of student’s knowledge structure change through the same learning objects. 6) Assessment of the student’s learning by the professor. 7) Design the student's learning improving plan in the virtual environment. The evidence of the use of the personalized teaching using ICT is represented by: 1) Conceptual map of the organization of the shorter route problem on the virtual course (Figure 3. 2) Test exploring student’s preconceptions. 3) Use of learning objects for the shortest route (Figure 4). 4) Check the assimilation of knowledge structures in the student, through the construction of a Java program (Figure 5). 5) Assessment and improvement of student’s learning process. 63
Figure: 3 Conceptual map of the shorter route problem (Shortest Path Problem).
Figure: 4 Learning object for the study of the Shortest Path Problem.
Figure: 5 Check student learning using personalized teaching (Communication interface in JAVA for the Shortest Path Problem). 64
Project based approach has its foundations on the Dialectical Psychology and Vigotsky’s postulates, and it was used in the Module Graphs Theory with the following steps: 1) Navigate the contents of the virtual module Graph Theory applications. 2) Interact with learning objects (Figure 6) module related to the coloring of graphs and Ford and Fulkerson’s algorithms. 3) Review research articles of the Association for Computing Machines and the IEEE Computer Society (ACM/IEEE-CS) related with the development of the module. 4) Write a representative essay of the theoretical and practical part of the reviewed article. 5) Socialize the writing by placing it in the forum of the Blackboard virtual platform. At this point student’s learning improves due to the interaction with their peers and professor in the virtual course. 6) Build a second version of the writing based on the results obtained in the forum. 7) Assessing student learning content in the final writing essay. This not only represents the student’s research level in Graph theory but also knowledge threshold applying Dialectical Psychology concepts in virtual spaces.
Figure: 6 Learning object representative of Graph Coloring.
The constructivist approach was implemented in the teaching methodology of the module ‘Recurrence Equations’ with the following steps: 1) Interaction of the student (knowing subject) with the virtual course.2) Exploration of the initial student knowledge structures. 3) Interaction of students with recurrence equations learning objects (Figure 7).. 4) Constructivist activities implementation (social discourse among participants using the network in order to understand and transform student learning with their peers and teacher). Socialization of virtual classroom activities supported by ICT. 5) Generation of cognitive imbalances in the student. 6) Socialization of the module learning through the network and between peers. 7) Assessment of student learning in the virtual module. The results of the progress in the student's learning in solving recurrence equations are shown in Figure 8 (Difficulty levels by solving the equations: i) Easy O(n) , ii) Intermediate O(2n+1) , iii) Difficult O(n2)). Solving recurrence equations by constructivism, allowed students identifying the preconceptions of this type of equations, investigating the theoretical methods of solving recurrence equations, and obtaining the solution of the equation (T(n)) and the order of complexity (O(n)).
Figure: 7 Learning object supporting the resolution of recurrence equations. 66
𝑻 𝒏 = 𝑻 𝒏 − 𝟏 + 𝟏 , 𝑺𝒊 𝒏 > 𝟏 𝑻 𝒏 = 𝟏 , 𝑺𝒊 𝒏 = 𝟏
𝑻 𝒏 = 𝟒 ∗ 𝑻
𝒏 + 𝒏 , 𝑺𝒊 𝒏 𝟐 ≥𝟐
𝑻 𝒏 = 𝟐𝒏𝟐 − 𝒏
𝑻 𝒏 = 𝒏
𝒂𝒏 = 𝒂𝒏1𝟏 + 𝒂𝒏1𝟐 𝒂𝟎 = 𝟏 𝒚 𝒂𝟏 = 𝟏 𝑻 𝒏 = 𝑪𝟎 𝟐𝒏 + 𝑪𝟏 (−𝟏)𝒏 𝒂𝒏 ≅ 𝑶( 𝟐𝒏9𝟏 )
𝑻 𝒏 ≅ 𝑶(𝒏𝟐 ) Figure: 8 Student progress using the constructivist approach.
𝑻 𝒏 ≅𝑶 𝒏
Recognizing the difficulties of the collaborative learning with ICT in educational practice because of the time to develop the activities and the evaluation of the learning of students (Fung*, 2004), this teaching methodology was used in the course of A&C in the module Dynamic Programming - DP, carrying out a collaborative project of coding algorithms in a programming language on DP. The method of teaching virtual collaborative projects to develop the theme of Dynamic Programming is supports by conceptual maps and learning objects. One of these objects shows the resolution of the Knapsack Problem. The problem is given a backpack of capacity M, fill its capacity with the combination of N objects. Each object has a weight (Pi) and a utility value (Vi). The aim is to fill the Knapsack so that the gain of all objects carried in the backpack is maximized. These contents should be studied by students with the guidance of the teacher and the virtual tutor before applying the collaborative project. The learning object Knapsack Problem is shown in Figure No. 9.
Figure: 9 Learning Object: Knapsack Problem.
The collaborative project was structured as following: 1) The class was divided into subgroups of students, who were equivalent in their academic performance in accordance with the previous grades of Dynamic Programming topic. 2) Students and professor identify problems feasible to be solved by Dynamic Programming. 3) State the problem to be solved in the project. 4) Solve the problem algorithmically by using Dynamic Programming. In this step, the student receives reinforcement guides by the assistant professor (Rua, 2015). 6) Encode the problem to be solved in Java language. 7) Socialize the results of the problem through the network in the forum. 7) Improve problem algorithmic solution, in accordance with the recommendations of the professor and fellow-students of the class. Interface of one of the reinforcement guides for the collaborative project is shown in Figue 9.
Figure: 9 Matrix Chain Product using Dynamic Programming (Sedgewick, 1992, p. 598). The main objective of Product Chain Matrix is to find the minimum number of scalar operations of a set of matrices, which can multiply. Given the matrices A34 B43 C32 D25 E54 F46 G63 H32, then the minimum number of scalar multiplications is 196. The optimal parentización is (A(B(C((((DE)F)G)H)))). Keep in mind that mathematically the number of ways in which you can parentizar n variables is equal to Catalan Number. This number is represented by the mathematical expression 𝟒(𝒏1𝟏) 𝑵𝑪 = 𝟐 𝒏∗ 𝝅∗𝒏 FUTURE RESEARCH The virtual teaching methodology presented in this paper has a formal support in Psychology, Education and Computer Science. Therefore, the following step is to do an analysis of the relationship that currently exists between the theories of psychology and education with the learning processes in virtual spaces supported by ICT. If this relationship is made, it can be ensured that the process of virtual learning is done with an educational, pedagogical and teaching sense, aiming at achieving a significant student learning. The proven teaching methodologies ensure the student's learning from an initial state to a final state of learning, i.e. since before interacting with the virtual course until after receiving the support of the course. Therefore, in the process of virtual training it is required intermediate states of student's learning, where the points of improvement of the teaching-learning virtual process can be identified. The course was built in the Blackboard 68
platform with connection to the Java programming language; objects work in the domain of the vision, then, it is important to investigate and build learning objects in the domains of touch and smell associated with the Algorithms and the Theory of Complexity. CONCLUSION The research process to create and test teaching-learning methodologies applied to the learning in virtual spaces supported by ICT, leads to conclude: i) The research was carried out in time series of the year 2011 to 2014 (8 semesters). ii) In these years around 175 students were training in the subject Algorithms and Complexity - A&C, with a maximum of 30 students and a minimum of 15 students per course. iii) Taking into account the status of learning of the pretest (before using the virtual module) and those of the post- test (after learning with the support virtual module), students achieved their best performance in the module ‘Greedy Algorithms’; (iv) The methodology with the best student learning performance level was that of problem solving, with an efficiency of 70 % (Figure 10). The reasons of this qualitative performance are: Allow solving complex problems using the computer (Traveling Salesman problem, in Computer Science). Verify the theoretical results with those shown in the computer. Designing communication interfaces in the platform supported by ICT. Improve the programming language JAVA in Greedy Algorithms; v) The maximum increase in average of learning achieved by students was 43.8 per cent of the pretest to the test. vi) The minimum increase in average of learning was 21.5% in the topic of computers, complexity and intractability. (vii) The average of the total increase of learning supported by the platform Blackboard was 22.3%.
2014 02 2014 01 2013 02 2013 01 2012 02 2012 01 2011 02 2011 01 Average
Computers, Complexity and Intractability
P 2. 0 3. 0 2. 3 2. 5 2. 1 1. 6 2. 4 2. 9 2. 4
P 2. 6 2. 5 3. 1 2. 8 1. 2 2. 6 2. 4 2. 2 2. 4
T 3. 1 3. 5 3. 3 3. 0 3. 6 4. 0 3. 7 3. 2 3. 4
PIL 22. 0 10. 0 20. 0 10. 0 30. 0 48. 0 26. 0 6.0 21. 5
T 3. 6 3. 7 3. 6 3. 7 3. 3 3. 4 3. 4 3. 6 3. 5
PIL 20. 0 24. 0 10. 0 18. 0 42. 0 16. 0 20. 0 28. 0 22. 3
Divide and Conquer P 2. 1 1. 0 2. 6 2. 4 3. 0 1. 6 2. 4 1. 5 2. 1
T 3. 6 3. 7 3. 6 3. 7 3. 3 3. 2 3. 4 3. 6 3. 5
PIL 30. 0 54. 0 20. 0 26. 0 6.0 32. 0 20. 0 42. 0 28. 8
Greedy Algorithms P 2. 0 1. 3 2. 1 2. 0 2. 6 1. 1 1. 6 2. 5 1. 9
T 3. 7 4. 8 3. 7 4. 0 4. 5 4. 0 4. 0 4. 0 4. 1
PIL 34. 0 70. 0 32. 0 40. 0 38. 0 58. 0 48. 0 30. 0 43. 8
Dynamic Programmin g P 1. 6 2. 1 2. 0 1. 8 1. 4 1. 7 3. 0 2. 3 2. 0
T 4. 3 4. 2 3. 7 3. 5 3. 5 3. 5 3. 3 3. 0 3. 6
PIL 54. 0 42. 0 34. 0 34. 0 42. 0 36. 0 6.0 14. 0 32. 8
Shortest Path Problem P 2. 0 2. 0 1. 6 1. 4 1. 8 2. 6 2. 9 2. 9 2. 2
T 4. 1 4. 1 3. 7 4. 0 3. 7 4. 2 3. 3 3. 0 3. 8
PIL 42. 0 42. 0 42. 0 52. 0 38. 0 32. 0 8.0 2.0 32. 3
Graph Theory P 2. 0 3. 0 2. 5 1. 5 2. 9 3. 2 3. 0 1. 0 2. 4
T 4. 1 3. 9 3. 4 2. 7 4. 2 3. 5 3. 3 3. 0 3. 5
PIL 42. 0 18. 0 18. 0 24. 0 26. 0 6.0 6.0 40. 0 22. 5
P : Pre-Test T : Test PIL : Percentage Increase in e-Learning
Figure: 10 Results of assessment in teaching and learning methologies supported by ICT applied in Algorithms and Complexity. The qualitative results of applying game theory are: i) A high level of motivation. ii) Learning at student’s own pace, according to the choice of game difficulty level. iii) The ability to receive feedback from the game in order to improve their learning. iv) Students’ highest level of attention to handle learning objects in the domain of audio, vision and touch. However, the difficulties in using the methodology are: High response time of learning objects for large values of input data (n >> 1 million); lack of stability in the 69
operation of the game, because of the type of student computer browser. It is of utmost importance to note that the above problems are technical ones in the process of communication between the server hosting the virtual course and the student computer, and are not relevant to the virtual educational concept of the game. The use of Gestalt theory applied to the process of learning with ICT gave the following qualitative results: i) A high interest from students. This interest is evidenced by the use of algorithm in solving practical problems. ii) Allows the design of human-machine communication interfaces. iii) Makes possible the practical resolution of problems by using a programming language (Java), which is motivating for students for the possibility of designing software elements. iv) Students can check the results through operating results JAVA programs. The aforementioned qualitative results validate the high performance of students in the module Greedy algorithms. The actions to improve the application of this methodology are: homogenize students’ learning level at the beginning of the virtual module; and a higher level of attention of the virtual tutor to students in order to develop the problems of high level of complexity related to operating systems or computers´ networks using algorithmic. Applying personalized teaching (based on Piaget’s principles) using ICT in virtual methodology brings about the following results: i) Students’ understanding of the conceptual structure of shortest path problem module. This is evidenced by the use of concept maps and the correct organization of teaching content in a tree structure. ii) Students’ learning achievement from a concrete thinking to a formal one, evidenced by the fact of 32.3% increase in learning. This implies student’s formal thought to achieve the learning object requirements (Figure 5.). Although, the methodology is appropriate to virtual education, it is necessary to take into account that the virtual tutor should design an outline for each student, greatly increasing the professor’s and virtual tutor’s times to attend students. The implementation of the project-based methodology in algorithms course allowed the starting of research processes in algorithmic complexity. This is one of the most difficult virtual methodologies. The difficulty is justified not only by the research level but also for technological resources required. Based on the above mentioned, the qualitative analysis of the project-based methodology allows in virtual education: Review the state of the art of the topic of the project that the student is virtually developing. Motivate the students because they themselves selected algorithmic topic to research in complexity. Writing a research paper from the undergraduate generates multidisciplinary interaction between undergraduate and graduate level training because students participate competitively for the best paper at the time of socializing research results in the virtual classroom as part of Psychology Vygotsky dialectic. Students then expect feedback to generate a second version of the research paper. Finally this virtual learning approach demands a high amount of time for the teacher to guide and correct the state of development of all research papers of students. This methodology was applied to assess the students’ learning output according to ABET (American Boarding for Engineering and Technology) Standard h). This standard is related to the competencies the student must learn to understand the impact of engineering solutions in a global, economic, environmental and social context. The related results use a rubric, and for the first half of 2015 used the scales: Very poor, poor, good and very good for a sample of twenty two research projects. Regarding the standard mentioned the results are: i) In global and environmental contexts: 9% very poor, 0% poor, 50% good, and 41% very good. ii) Meanwhile the relevant results values for economic and social contexts are: 5%very poor, 0% poor, 23% good, and finally, 73% very good. The need for linking this methodology in this paper is to demonstrate the importance of ensuring the quality of training students in learning processes in virtual spaces using the project-based methodology, and to make relevant that virtual actions are essential to support international accreditation processes. 70
Applying the constructivist approach supported by ICT is a challenge when it is used in Algorithms. The challenge is to get students preconceptions evolve from a state of early learning to a final moment of learning. Before starting the virtual module, all students have different preconceptions. These are supported by the mathematical knowledge. The structure of the process is that this knowledge is different in all students. Then, starting from different bases all students must achieve the same response to solve the equation of recurrence. Therefore, the approach application time is high, and it is also high the diversity of mathematical approaches to reach the same response. This was the reason why the advancement of learning level was not as high as it was expected. The level of learning achieved in the approach was 22.3%. Collaborative projects methodology implemented in the virtual Dynamic Programming module produced the following results in qualitative terms: Students integrated theoretical and practical strengths in project groups. Development time of projects in the JAVA programming was shorter than when programmed individually. Solving problem results are most effective. The time of consultations to virtual tutor and teacher decreased considerably when making virtual collaboration projects. Then, students classified the methodology functional and useful as an activity prior to a real job in a company. Aditionally, the teaching methodologies presented in this paper meet the teaching competencies and learning methods in accordance with the UNESCO suggestion. They also help constructing virtual courses that increase both knowledge and learning of the curriculum in both virtual and face-to-face modalities. (S. E. Sergis & Sampson, 2014). BIODATA and CONTACT ADDRESSES of the AUTHOR Jose CAPACHO is an assistant professor at the Universidad del Norte (Barranquilla , Colombia). He did his doctoral studies at the University of Salamanca (2008) (Spain), in Learning Processes in Virtual Spaces. Professor Capacho earned his Master studies in Education at the Pontificia Universidad Javeriana (Colombia, 1996). His undergraduate was made in Systems Engineering in the Universidad Industrial de Santander – UIS (Colombia, 1982). Professor has over 30 years of service at Universidad del Norte. During this time, as Coordinator of the System Program, he has led projects of National and International Accreditation of the System Program (Universidad del Norte), with institutions such as the Colombian National Accreditation Council (NAC) (1998,2005,2012);and the Agency Accreditation Board for Engineering and Technolgy (2003, 2005). As a teacher he has participated in the renewal accreditation process of the System Program with ABET Accreditation International (2013, 2014). Jose CAPACHO University del Norte, Barranquilla, COLOMBIA Phone: 57 3509379 Email: [email protected]
REFERENCES Anh, D. T. K., & Marginson, S. (2013). Global learning through the lens of Vygotskian sociocultural theory. Critical Studies in Education, 54(2), 143-159. Capacho, J. (2004). Design: Course of Algorithms and Complexity supported by ICT. Universidad del Norte (Barranquilla, Colombia). Department of Systems Engineering. Cure, V., & Fandiño, E. (2005). Programming: Course of Algorithms and Complexity supported by ICT. Universidad del Norte (Barranquilla, Colombia). Department of Systems Engineering. 71
Dabbagh, N., & Kitsantas, A. (2012). Personal Learning Environments, social media, and self-regulated learning: A natural formula for connecting formal and informal learning. The Internet and higher education, 15(1), 3-8. Dalgarno, B., & Lee, M. J. (2010). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10-32. De Freitas, S., Rebolledo-Mendez, G., Liarokapis, F., Magoulas, G., & Poulovassilis, A. (2010). Learning as immersive experiences: Using the four-dimensional framework for designing and evaluating immersive learning experiences in a virtual world. British Journal of Educational Technology, 41(1), 69-85. Fung*, Y. Y. (2004). Collaborative online learning: Interaction patterns and limiting factors. Open Learning: The Journal of Open, Distance and e-Learning, 19(2), 135-149. Hipsky, S. (2008). Piaget’s Developmental Stages. Information Resources Management Association. Hughes, G. (2007). Diversity, identity and belonging in e-learning communities: some theories and paradoxes. Teaching in higher education, 12(5-6), 709-720. Ingram, N. R. (2014). Time past: impacts of ICT on the pedagogic discourse in the Interactive project. Technology, Pedagogy and Education, (ahead-of-print), 1-18. Keane, T., Keane, W. F., & Blicblau, A. S. (2014). Beyond traditional literacy: Learning and transformative practices using ICT. Education and Information Technologies, 113. Kotsilieris, T., & Dimopoulou, N. (2014). The evolution of e-learning in the context of 3D virtual worlds. Linaza, M. T., Gutierrez, A., & García, A. (2013). Pervasive augmented reality games to experience tourism destinations. En Information and Communication Technologies in Tourism 2014 (pp. 497-509). Springer. Lyashenko, M. S., & Frolova, N. H. (2014). LMS projects: A platform for intergenerational e-learning collaboration. Education and Information Technologies, 19(3), 495513. Melero Gallardo, J. (2014). Design and implementation techniques for location-based learning games. Mukama, E. (2014). Bringing Technology to Students’ Proximity: A Sociocultural Account of Technology-Based Learning Projects. International Journal for Research in Vocational Education and Training, 1(2). Pérez, A. (1995). Los procesos de enseñanza-aprendizaje: análisis didáctico de las principales teorías del aprendizaje. En J. Gimeno, y Pérez, A. Comprender y transformar la enseñanza, (pp. 34-62). Madrid, España: Ediciones Morata, S. L. Rua, M. (2015). Learning object: Matrix Chain Product. Assistant Professor of A&C, Universidad del Norte (Barranquilla, Colombia). Department of Systems Engineering.
Sergis, S. E., & Sampson, D. G. (2014). From Teachers’ to Schools’ ICT Competence Profiles. En Digital Systems for Open Access to Formal and Informal Learning (pp. 307-327). Springer. Sergis, S., Zervas, P., & Sampson, D. G. (2014). Towards Learning Object Recommendations Based on Teachers’ ICT Competence Profiles. En Advanced Learning Technologies (ICALT), 2014 IEEE 14th International Conference on (pp. 534-538). IEEE. Shieh, R. S. (2012). The impact of Technology-Enabled Active Learning (TEAL) implementation on student learning and teachers’ teaching in a high school context. Computers & Education, 59(2), 206-214. Schunk, D. (1997). Teorías del Aprendizaje. Mexico: Prentice-Hall Hispanoamericana, S. A.. Sedgewick, R. (1992). Algorithms in C++. Addinson-Wesley Publishing Company, Inc. Vygostky, L. (1995). Pensamiento y lenguaje. Barcelona. España: Nueva edición a cargo de Alex Kozulín. Ediciones Paidós Ibérica S. A.. Wachtel, P. L. (1980). Transference, schema, and assimilation: The relevance of Piaget to the psychoanalytic theory of transference. The annual of psychoanalysis.
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 6
INSTRUCTIONAL SCREENCAST: A RESEARCH CONCEPTUAL FRAMEWORK Muhammad Razuan ABDUL RAZAK University Pendidikan Sultan Idris, MALAYSIA Ahmad Zamzuri MOHAMAD ALI University Pendidikan Sultan Idris, MALAYSIA ABSTRACT The literature review indicates that the benefit of screencast as an instructional media has not clearly proved effective for all categories of students. This is due to the individual differences in processing the information. Inadequate screencast design will cause strain to students’ cognitive process which might impede learning. This shortcoming can be reduced by imposing principles of reducing the external processing in screencast design. However, the exact design effectiveness of screencast also depends on the cognitive style and learning style of the students. The cognitive style will ultimately affect how information is processed in the students’ memory structure. Students will also easily process the given information, if it is performed in accordance with their dominant learning style. Taken together, this article discusses the conceptual framework design of screencasts for instructional purpose. Key words: Cognitive style, instructional media, learning style, screencast. INTRODUCTION Multimedia technology usage in the teaching makes learning process more fun as well as it facilitates understanding of a content more effectively (Fook, Sidhu, Nursyaidatul & Norazah, 2011). This process becomes more comfortable with the availability of Internet access that allows learning to be done online anytime and anywhere (Loch, 2011). This as a result has opened a new dimension to the process of distance learning which appeared to be beneficial for both instructors and students (Ahmad Zamzuri, Khairulanuar, Mohammad & Salman Firdaus, 2011).The effective teaching and learning process would obviously make the conveyed knowledge and skills more meaningful (Lloyd & Robertson, 2012) and this can be achieved sufficiently if suitable instructional media is used (Baghdadi, 2011). One of the multimedia-based instructional media is screencast; the medium that will be the main focus of the conceptual framework design of this study. Screencast is a digital video that displays a part or the entire capture of the computer screen, where the narration or voice may be included to describe the activity on the screen (Udell, 2005). The use of screencast as instructional media in the teaching and learning process is important, especially in learning the use of a software application (Brown, Luterbach, & Sugar, 2008; Carr & Ly, 2009; Lloyd & Robertson, 2012). This is due to the screencast’s capability in creating an identical presentation condition in every learning sessions (Carr & Ly, 2009). Thus, the use of screencast is perceived useful as an additional resource to aid students in learning the software applications independently and effectively (Ahmad Zamzuri et al., 2011). 74
Although screencast is beneficial for independent learning, its use has not been proven effective for all categories of students. This is because the perception of students in the process of selecting information needed for effective learning is different from one learner to another (Bailey, 2012). This is due to the students’ dissimilar cognitive style in translating the obtained course contents into easy to understood information (Ahmad Rizal & Yahya, 2008; Renumol, Janakiram & Jayaprakash, 2010). In addition, the manner of information selection also depends on the learning styles of the students which was formed since their early childhood (Rosniah, 2007). Therefore, this conceptual framework will look at the impact of different multimedia elements in screencast presentations on learning of students with different cognitive styles and learning styles. INSTRUCTIONAL SCREENCAST Screencast is derived from the terminology used by Jon Udell in 2005, which refers to digital video presentation (Fancett-Stooks, 2012). It was widely used for all levels of students from the lowermost up to tertiary (Fraser & Maclaren, 2012; Winterbottom, 2007). Thus, screencast is an effective method in explaining the procedure of computer-based work, especially the features of particular software application (Brown et al., 2008; Carr & Ly, 2009; Lloyd & Robertson, 2012). Findings from previous researches clearly indicate that screencast as an instructional media has positive impact on its users, which includes instructors or students at any level (Ahmad Zamzuri et al., 2011; Bailey, 2012; Budgett, Cumming, & Miller, 2007; Fancett-Stooks, 2012; Fraser & Maclaren, 2012; Kraft, 2009; Lloyd & Robertson, 2012; Loch, 2012; Mullamphy, Higgins, Ward, & Belward, 2010; Oehrli, Piacentine, Peters, & Nanamaker, 2011; Peterson, 2007; Pinder-Grover, Millunchick, & Bierwert, 2008; Rocha & Coutinho, 2010; Winterbottom, 2007). By using screencast, information can be delivered and processed effectively compared to conventional printed media (Lloyd & Robertson, 2012). The usage of printed media involves complex cognitive processes in the memory structure. This is because, printed texts have to compete with the illustrative presentations which have to go through the same visual channels (Mayer, 2005a). Therefore, by using screencast, the load of the working memory of the visual channel and the verbal channel can be minimized to facilitate learning more effectively. However, the question arises is, will all the students from the same class will get identical benefits from the developed screencasts? This is because, from various screencast design, none are more prominent between one another, which might due to different cognitive ability of students (Oehrli et al., 2011). This happens because only limited information can be processed in the working memory at one time; based on the principle of limited capacity of working memory (Mayer, 2005a; Jong, 2010). Therefore, in order to reduce the load in the working memory throughout the learning process, instructional material developer must take into consideration on how to reduce external processing (Mayer, 2005b; Oud, 2009). External processing is the integration of the external information (extraneous material) with the essential information (essential material) in an instructional medium (Mayer, 2005b). By reducing the extraneous materials, students can focus in processing the essential material without being burdened with unwanted external information. However, the question arises again, whether the verbal assistance (narration and text) serves as extraneous material or essential material in achieving the objectives of the screencasts presentation, especially in learning software applications. Basically, screencast presentations integrated with narration or text will facilitate the learning process (Oehrli et al., 2011). This elements serve as additional information in the 75
screencast to ensure effective learning (Fancett-Stooks, 2012). Thus, the inclusion of text along with screencast or screencast with recorded narration helps in emphasizing the understanding of software application (Fancett-Stooks, 2012). However, text can only contribute to learning improvement for students who tend to learn through visual or lack of learning through listening (Educause, 2006). This is contrary to a study by Bailey (2012), which stated that screencast gives an advantage to students who learn better by seeing and hearing from students who learn through reading. Bailey's (2012) study was supported by Nafaidilah (2012) who found that the use of narration in screencast application is necessary to ensure its effectiveness. However, Nafaidilah (2012) did not cover the effect of text or combination of narration and text in screencasts in her study. Diverse modalities in screencasts can actually deliver a better understanding of learning than narration or text alone (Ozsvald, 2010). This can be done through the addition of subtitles or narration in the language that is easily understood by majority of users (Ozsvald, 2010). However, the study by Veronikas and Maushak (2005), did not support this assumption. Veronikas and Maushak (2005) found that there were no significant differences on the use of a combination of narration and text in the screencasts instead screencasts with narration or text only. This is because students tend to learn in a multimedia approach in diverse modalities to help them get a better understanding (Veronikas & Maushak, 2005). The question is whether the diversity of modalities in screencast really affects in improvement of practical skills of students, especially in learning software application? The usage of screencasts with diverse modalities is said to have a positive impact, however, the imbalance of the effectiveness in learning a software application still exist (Bailey, 2012; Educause, 2006; Fancett-Stooks, 2012; Nafaidilah, 2012; Oehrli et al., 2011; Ozsvald, 2010; Veronikas & Maushak, 2005). This is due to the fact that its usage will provide a high load to the working memory or short-term memory based on the diversity of the information presented as text, graphics, audio and movement which will be processed simultaneously (Bétrancourt, 2005). Thus, by reducing the load of the working memory, the students' attention can be diverted to important information in the process of learning. As such, this framework will focus on the design of the screencast with various modality strategies in reducing external processing to assist in meaningful learning. Cognitive Style and Learning Style Beside the design aspects, cognitive style is an important element that needs to be considered in the study on the effectiveness of instructional media. This is because, most of the instructional media developers often assume that every students will learn in the same style (Riding & Sadler-Smith, 1997). This assumption has actually denied the importance of individual differences in cognitive style outlook (Riding & Sadler-Smith, 1997). Cognitive style is an individual approach in organizing and conveying information during the process of thinking consistently (Riding & Sadler-Smith, 1997). Cognitive style can also be described as an individual’s personality dimension that influences the attitudes, values and social interactions (Zabedah & Wah, 2005). Cognitive styles are categorized into two, which are Field Dependent (FD) and Field Independent (FI) (Witkin, Moore, Goodenough & Cox, 1977). FI individuals are found to be more likely to separate a bigger matter into smaller things (Azizi, Asmah, Zurihanmi & Fawziah, 2005). Thus, it will enable them to analyse the smaller components compared to FD individuals who view a component as a whole (Azizi et al., 2005). FI students are more individualistic and requires no external reference to process information (Chen, Magoulas, & Dimakopoulos, 2005). This is in contrast with FD individuals who are socially-orientated and influenced by the opinions of others and needs external support to process information 76
(Chen et al., 2005). However, both FI and FD cognitive styles are interconnected with specific abilities of students and often have a positive impact in computer-based learning (Hall, 2000). This was supported through research by Angeli and Valanides (2004), who found that the usage of text and visual modalities for FI students improved their performance in learning compared to FD students. This outcome was also supported by Jailani, Wan Mohd Rashid and Ahmad Rizal (2007), who found that the diversity of modality in the development of an instructional media is able to increase FI students’ performance compared to FD students. Therefore, FI students are found to have more benefits than FD students through a complex mix of media in the instructional media (Chuang, 1999). However the study by Angeli dan Valanides (2004), found that FI students do not show significant effects of improvement on the performance compared to FD if the media only integrates the text. The question that arises is whether FI and FD individuals will show a different level of understanding in screencast learning methods. The different cognitive styles is actually closely influence the learning depending on how the instructors convey information of their lesson (Ahmad Rizal & Yahya, 2008; Renumol et al., 2010). Students who fail to extract necessary information from the instructor will face problem in translating the received information into meaningful understanding. This consequently will be the factor of failure of students in the performance test. Thus, students with different cognitive styles will definitely limit the information that they have received and also processed. Therefore, instructional media such as screencast should be able to provide a positive impact on students with different cognitive styles, during the teaching and learning process (Renumol et al., 2010). Beside cognitive style, the effectiveness of instructional media is also influenced by the students’ learning style. Students’ learning style refers to the different skills of individuals in processing information effectively (Mestre, 2012; Norasmah & Mohd Hasril, 2010). It is a particular individual ability to process, store and retrieve all the received information (Felder & Henriques, 1995). Thus, the developer of instructional media such as screencast should also take into consideration the aspects of students’ learning styles in their design phase. The formation of a students’ learning style actually happens through the learning process that begins since early childhood (Rosniah, 2007). This formation process occurs naturally and continues until the formation of individual learning styles. Hence, instructors need to know their students’ learning styles to help them get a better understanding of a topic that is being learnt (Alhosban, Fuad, Hamad & Mousa, 2011). This can be achieved if the instructor practices the teaching styles that matches the students’ learning styles (Felder, 2010; Felder & Silverman, 1988), which would eventually lead to the retention of new information naturally in the memory structure (Bastable, 2008). The right usage of graphic processing, text and audio in screencast is seen to meet the needs of the dominant learning styles of students (Fancett-Stooks, 2012; Loch, 2012; Pinder-Grover et al., 2008; Rocha & Coutinho, 2010; Winterbottom, 2007). Therefore, it is important to carry out research to identify the appropriate strategies to address this issue. Learning styles of a student can be identified through studies related to the learning style models including the learning styles model by Felder-Silverman (1995), Dunn and Dunn (1979), Kolb (1984), Honey and Munford (1982) and VARK (Visual, Aural, Read or Write and Kinesthetic) (2001). However, this study will concentrate on the VARK learning style, because this learning style is significant to the multimedia-based instructional medias (Norasmah & Mohd Hasril, 2010). Study by Yosep, Wawan Setiawan and Waslaludin (2012), also supported the usage of VARK learning style because they are more dominant in multimedia-based learning.
THEORITICAL FRAMEWORK For the purpose of this study, the conceptual framework that was developed is based on the Cognitive Theory of Multimedia Learning (CTML) (Mayer, 2005a), cognitive style and learning style models. It is the multimedia principle in reducing the external processing (reducing extraneous processing) which puts strain on the working memory, namely, the Principle of Coherence, Principle of Signalling, Principle of Redundancy, Principle of Spatial Contiguity and Principle of Temporal Contiguity (Mayer, 2005b). Besides, the theory of cognitive styles is Field Independent (FI) and Field Dependent (FD) and VARK learning style. Cognitive Theory of Multimedia Learning CTML is based on students attempt to build a meaningful relationship between the words and pictures (Mayer, 2005a). This is grounded on the three principles of cognitive science, namely dual-channel assumption, limited capacity assumption and active processing assumption (Mayer, 2005a). The principle of dual-channel assumption refers to working memory that has auditory and visual channels. The principle of limited capacity assumption refers to the internal system with limited working memory. The principle of active processing assumption refers to the construction of knowledge in a meaningful way. When attention is given to the relevant material, the compilation of mental model structure in a coherent form is integrated with the existing knowledge to be registered in the long-term memory in schema form (Mayer, 2005a). There are three memory storages in CTML, namely sensory memory, working memory and long-term memory. Sensory memory will store the presented media for only around 0.25 seconds. The working memory will select information from the sensory memory to be processed and integrated with the existing information. It processes the presented media and is generally in less than thirty seconds as well as can only process some part of media at a time (Mayer, 2010). Meanwhile, the long-term memory stores information in the form of a schema in an unspecified period of time. The learning process will generally be restricted when the cognitive load increases as a result of the working memory capacity reaching its limit (Jong, 2010). To overcome this problem, Mayer (2009) has outlined twelve multimedia instructional principles namely, the Principle of Coherence, Principle of Signalling, Principle of Redundancy, Principle of Spatial Contiguity, Principle of Temporal Contiguity, Principle of Segmenting, Principle of Pre-training, Principle of Modality, Principle of Multimedia, Principle of Personalization, Principle of Voice and Principle of Image. Multimedia instructional principles according to Mayer (2009) can be categorized in three cognitive load frames as shown in Table 1.
Table: 1 The Framework of Cognitive Load and Instructional Principles Framework of Cognitive Load Reducing Extraneous Processing
Principles Of Instruction Principle of Coherence Principle of Signalling Principle of Redundancy Principle of Spatial Contiguity Principle of Temporal Contiguity
Managing Essential Processing
Principle of Segmenting Principle of Pre-training Principle of Modality
Fostering Generative Processing
Principle Principle Principle Principle
of Multimedia of Personalization of Voice of Image
The focus of this study is based on an outline of Reducing External Processing that involves five principles which is Coherence, Signalling, Redundancy, Spatial Contiguity and Temporal Contiguity. Thus, reducing the external processing is seen as the first process that should take place before the process of managing important processing to encourage the process of generative processing. This is because, this process occurs in the sensory memory before being processed in the working memory and subsequently in the long-term memory. These five principles are described and shown in Table 2. Table: 2 Five Principles of Reducing the External Processing Principles Of Instruction Principle of Coherence
Description Students will learn better if external elements are removed. Example: Issuing interesting but irrelevant statements or graphics used.
Principle of Signalling
Students will learn better if the signal to process the information is given. Example: Insert signals, signs or assertion of important information for students to show what to do and how to organize them.
Principle of Redundancy
Students will learn better if information is not provided within the same sensory channels. Example: Redundancy - print text and narration are presented simultaneously with the display screen. Non Redundancy - narration is presented simultaneously with the display screen. Students will learn better if the printed text is near the graphics that corresponds to reduce the need for visual scanning. Example: The text is placed close to the same part of the illustration (on paper) or animation (on the screen). Students will learn better if the narrative and animation displayed at the same time to reduce stake memory. Example: Narration and animation are presented simultaneously than either individually before presenting new text animation or animation before the new text.
Principle of Spatial Contiguity
Principle of Temporal Contiguity
Cognitive Styles To produce meaningful learning, the development of instructional strategies should be student-centred rather than technology-centred (Mayer & Johnson, 2008). It is acknowledged that each student has different methods and styles in processing the information given. For that reason, the cognitive style of the students in the learning process is also different. As been discussed, cognitive styles of students are categorized into two, Field Dependent (FI) and Field Independent (FI) (Witkin et al., 1977). FI students are more individualistic and require no external reference to process information. This is in contrast with FD individuals who are socially-oriented and influenced by the opinions of others and need external support to process information (Chen et al., 2005). Table 3 shows the individual differences in FI individual cognitive styles compared to FD individuals cognitive styles in more detail.
Table: 3 Field Independent (FI) and Individual Field Dependent (FD) Individual differences Individual Field Dependent Field Independent 1. Fast isolate simple geometric form of complex geometric shapes 2. Can overcome the effects of background elements that interfere 3. Be analytical 4. Skilled in building the structure of a structure that does not have structure 5. A short time completing task without much offense 6. Need help to focus on matters involving social 7. Inclined to have personal goals and enforcement 8. Less influenced by criticism 9. Able to analyse situations and organize things 10. More likely to solve problems without instructions from outside and outdoor observation
Facing the difficulty to discriminate
Unable to overcome the effects of background elements that interfere. Global Nature Not skilled in building the structure of a structure that does not have structure Hours completing task but slightly more correct Has the advantage of social learning
Requires self-goal structure and enforcement
Easily swayed by criticism Looking globally and cannot organize things
3. 4. 5.
10. Need directions from outside to solve the problem
VARK Learning Style The VARK learning style is the second underlying theory of this framework. VARK learning style is classified as students’ learning styles in four different modes which are visual, aural (auditory), read / write, kinesthetic (Fleming & Baume, 2006). Fleming and Baume (2006), classifies in visual category, students prefer to learn through charts, diagrams and pictures. Aural category (auditory) is ideal for students who learn through discussions and listening. While in The read/ write category students can easily access information through reading the printed or written words, for example taking lecture notes. Finally kinesthetic category students learn better through touching, feeling, seeing and hearing as well as to do their own learning activities. With regards to this, the different cognitive styles and learning styles of students demand that instructional materials to be developed in a more student-centred manner.
CONCEPTUAL FRAMEWORK DESIGN Based on the theoretical framework, the conceptual framework suggest screencast to be developed based on five principles to reduce external processing as in Figure 1. Through these five principles, the students’ learning process will occur when they are able to focus to process essential information compared to processing both essential information and extraneous information simultaneously. Thus, by applying the principle of Coherence and Redundancy in the development of screencast, external information processing can be minimized. Once this external information is minimized, next, the students’ focus and attention to essential information could be improved through the Signalling Principle and Spatial Contiguity Principle within an emphasis on the usage of appropriate images, text or language. Lastly, through the Temporal Contiguity Principle, the needs of students’ working memory in processing important information before it can be transformed into meaningful information could be simplified by essential information presented simultaneously in the visual channel and auditory channel. Working Memory
Principles of Reducing External Processing
Instructional Strategy 1. Screencast + Narrative. 2. Screencast + Text. 3. Screencast + Narrative + Text. 4. Screencast.
Long Term Memory
Practical skills of students
Figure: 1 Conceptual Framework for Screencast Research Essential information from the screencast will go through the selection process of words and images. The sense of hearing will choose the sound of words in the form of narration and visual sense will select the images in the form of screencasts and the text displayed on the screen. Next, through the auditory channel and visual channel in working memory or shortterm memory, words and images will be compiled to form a mental model which will be integrated with the existing knowledge of the students. The information from working memory or short-term memory which is integrated with the students’ existing knowledge will then be stored permanently in the long-term memory in the schema form. The schema developed and stored in permanent basis in the long-term memory can be retrieved by the students in solving the problems given in the practical skill tests or assignments. The question arises, among the instructional strategies of screencasts, which can contribute maximum effects to the perfection of the students’ mental model formation? Various modalities that were used in the screencast presentation are likely to influence the students’ mental model formation. Thus, all four strategies suggested will probably may or may not 81
impose redundancy in the students’ memory structures. This can be seen from inconsistent outcome of past studies Therefore, proper design of the screencasts can help in the formation of accurate mental models and it will affect the formation of meaningful schema in the long-term memory. The formation of students’ mental models is also likely related to their cognitive style. FI cognitive style students may not face problems in utilizing the four instructional strategies as they prefer to solve problems without external instructions and external observation. This is contrary with FD cognitive style students since they need specific and clear instructions to solve the problems given. The question that arises here, is whether the FI students will easily master the content of the delivered lessons compared to FD students, especially in mastering the software through any screencast presentation strategies? Thus, the different cognitive styles might produce different results for the four suggested instructional strategies of screencast. Apart from the different cognitive styles, the formation of mental models is also likely to be influenced by students’ learning styles. This is because, students learning styles has been formed at the early stages of childhood and subsequently forms their own learning styles until adulthood. Hence, a students’ learning style will be influenced by their dominant learning styles either visual, aural (auditory), read/write or kinesthetic. The question is which are the students’ dominant learning styles that are used mainly in learning the software? Therefore, by identifying the most dominant learning style, then, a more accurate result in the construction of effective instructional strategies can be delivered. Finally, the load of the working memory or the short-term memory of students would be reduced through the use of appropriate principles of reducing the external processing in all four screencast designs. Thus, the adequate design approach of text and narration usage in the screencast should give maximum impact on students’ learning. This will assist them in the formation of accurate mental models and then formation of perfect schemas in the longterm memory. CONCLUSION The use of screencast as an instructional material in the process of teaching and learning is important, especially in studying the use of a software application. It has the ability to create a delivery that equals the classroom lecture as well as useful additional resource in learning the application independently and effectively. Results from previous studies have acknowledged that screencasts can be used as an additional tool in teaching. However, its use has not been proven effective for all the categories of students in the same class. This is due to the students’ own perception which differs in terms of the selection of the required information. It depends on the students’ cognitive style and learning style in forming and translating the information into knowledge that could be easily understood. The conceptual framework developed in this study can be a useful guide in addressing this matter. However, the conceptual framework was developed merely based on literature reviews. Therefore, it is important to conduct related studies to further affirm the framework. The studies that look on the effects of various screencast designs on learning of students with different cognitive styles and learning style is important to be discovered. Specifically, study in looking on the relation and correlation between various screencast designs with various learning styles and cognitive styles must first be established. Studies in looking on the interactions between various screencast designs and various learning styles and cognitive styles are also important. Finally, experimental studies in determining the ideal screencast design for specific learning style and cognitive style are also important to further detail the conceptual framework developed. 82
BIODATA and CONTACT ADDRESSES of the AUTHORS Muhammad Razuan ABDUL RAZAK, born in Malaysia. Currently, a PhD student in the Faculty of Art, Computing and Creative Industry, University Pendidikan Sultan Idris, Malaysia. He has a Bachelor Degree in Biological and Agricultural Engineering from University Putra Malaysia and a Master in Education from University Tun Hussein Onn Malaysia. His research interest is focused on Instructional Technology and Multimedia Design. Has taught both face-to-face and online classes in higher education for over 7 years. Muhammad Razuan ABDUL RAZAK Faculty of Art, Computing & Creative Industry Universiti Pendidikan Sultan Idris Tanjong Malim, 35900, Perak, MALAYSIA Email: [email protected]
Dr. Ahmad Zamzuri MOHAMAD ALI, born in Malaysia. Currently, an Associate Professor of Multimedia in the Faculty of Art, Computing and Creative Industry, University Pendidikan Sultan Idris, Malaysia. He has a Bachelor Degree in Electrical Engineering from University Teknology Malaysia, a Master in Education from University Teknology Malaysia and PhD in Multimedia Design from University Sains Malaysia. His research and publication interest is focused on Multimedia Design and Instructional Technology. Has taught both face-to-face and online classes in higher education for over 15 years. Assoc. Prof. Dr. Ahmad Zamzuri MOHAMAD ALI Faculty of Art, Computing & Creative Industry Universiti Pendidikan Sultan Idris Tanjong Malim, 35900, Pera, MALAYSIA Email: [email protected]
REFERENCES Ahmad Rizal M., & Yahya B. (2008). Gaya kognitif dan visualisasi pelajar melalui perisian Multimedia. Masalah Pendidikan, 31(1), 181–192. Retrieved from http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:GAYA+KOGNITIF+D AN+VISUALISASI+PELAJAR+MELALUI+PERISIAN+MULTIMEDIA#0 Ahmad Zamzuri M. A., Khairulanuar S., Mohamad H., & Salman F. S. (2011). Does screencast teaching software application needs narration for effective learning ? The Turkish Online Journal of Educational Technology, 10(3), 76–82. Alhosban, Fuad, Hamad, & Mousa. (2011). The effectiveness of aural instructions with visualisations in e-Learning environments. Retrieved from http://etheses.dur.ac.uk/3201/ Angeli, C., & Valanides, N. (2004). Examining the effects of text-only and text-and-visual instructional materials on the achievement of Field-Dependent and Field-Independent learners during Problem-Solving with Modeling Software. Educational Technology Research and Development, 52(4), 23–36. doi:10.1007/BF02504715 83
Azizi Y., Asmah S., Zurihanmi Z., & Fawziah Y. (2005). Aplikasi kognitif dalam pendidikan. Kuala Lumpur: PTS Profesional Publishing. Baghdadi, Z. (2011). Best practices in online education : Online instructors, courses, and administrators. Turkish Online Journal of Distance Education, 12(3), 109–117. Bailey, J. (2012). Informal screencasting: results of a customer-satisfaction survey with a convenience sample. New Library World, 113(1/2), 7–26. doi:10.1108/03074801211199013 Bastable, S. B. (2008). Nurse as Educator : Nurse as Educator Principles of Teaching. (S. B. Bastable, Ed.) (3rd ed.). Boston: Jones and Bartlett Publishers. Bétrancourt, M. (2005). The Animation and Interactivity Principles in Multimedia Learning. In The Cambridge Handbook of Multimedia Learning (1st ed., pp. 287–296). NY. doi:10.1017/CBO9780511816819.019 Brown, A., Luterbach, K., & Sugar, W. (2008). The current state of screencast technology and what is known about its instructional effectiveness. In Proceedings of Society for Information Technology & Teacher Education International Conference. Budgett, S., Cumming, J., & Miller, C. (2007). The role of screencasting in statistics courses. In International Statistical Institute, 56th Session. Lisbon, Portugal. Retrieved from https://researchspace.auckland.ac.nz/handle/2292/16851 Carr, A., & Ly, P. (2009). “More than words”: screencasting as a reference tool. Reference Services Review, 37(4), 408–420. doi:10.1108/00907320911007010 Chen, S. Y., Magoulas, G. D., & Dimakopoulos, D. (2005). A flexible interface design for Web directories to accommodate different cognitive styles. Journal of the American Society for Information Science and Technology, 56(1), 70–83. doi:10.1002/asi.20103 Chuang, Y. R. (1999). Teaching in a multimedia computer environment: A study of the effects of learning style, gender, and math achievement. Retrived from http://imej.wfu.edu/articles/1999/1/10/ Educause. (2006). 7 things you should know about screencasting. Retrieved from https://net.educause.edu/ir/library/pdf/eli7012.pdf Fancett-Stooks, D. J. (2012). The efficacy of screencasting technology in the classroom. Retrieved from https://docushare.sunyit.edu/dsweb/Get/Document-225433/fancettstooks_efficacy_screencasting_assembled.pdf Felder, R. M., & Henriques, E. R. (1995). Learning and teaching styles in foreign and second language education. Foreign Language Annals, 28(1), 21–31. doi:10.1111/j.19449720.1995.tb00767.x Fleming, N., & Baume, D. (2006). Learning styles again: VARKing up the right tree ! Educational Developments, SEDA Ltd, 7(4), 4–7.
Fook, C. Y., Sidhu, G. K., Nursyaidatul Kamar M. S., & Norazah A. Z. (2011). Pre-service teachers’training in Information Communication and Technology for The ESL classrooms in Malaysia. The Turkish Online Journal of Distance Education, 11(3), 97–108. Fraser, A., & Maclaren, P. (2012). Patterns of instruction: Using screencasts in the teaching of Textile Design. In Proceedings ascilite Wellington 2012 (pp. 331–332). doi:10.1007/s10798-005-4327-y Hall, J. K. (2000). Field dependence-independence and computer-based instruction in geography. Doctoral Dissertation, Virginia Polytechnic Institute and State University. Jailani M. Y., Wan Mohd Rashid W. A., & Ahmad Rizal M. (2007). Field DependenceIndependence students and animation graphic courseware based Instruction. Retrieved from http://www.academia.edu/download/30587759/medcejournal.pdf#page=22 Jong, T. de. (2010). Cognitive load theory, educational research, and instructional design: Some food for thought. Instructional Science, 38(2), 105–134. doi:10.1007/s11251009-9110-0 Kraft, E. (2009). Screencasts as a learning resource to enhance a quantitative business methods course. Business Education & Accreditation, 1(1), 65–78. Retrieved from http://www.theibfr.com/ARCHIVE/BEA-V1N1-2009.pdf#page=67 Lloyd, S. A., & Robertson, C. L. (2012). Screencast Tutorials Enhance Student Learning of Statistics. Teaching of Psychology, 39(1), 67–71. doi:10.1177/0098628311430640 Loch, B. (2012). Screencasting for mathematics online learning–a case study of a first year operations research course at a dual-mode Australian university. In Teaching mathematics online: emergent technologies and methodologies (pp. 43–59). Retrieved from http://stan.cc.swin.edu.au/~lochb/download/Loch2011.pdf Mayer. (2009). Multimedia Learning, Second Edition. Cambridge, UK: Cambridge University Press. Mayer, R. E. (2005a). Cognitive theory of Multimedia learning. In The Cambridge handbook of multimedia learning (1st ed., pp. 31–48). NY: Cambridge University Press. Mayer, R. E. (2005b). Principles for managing essential processing in multimedia learning: Segmenting, pretraining, and modality principles. In Mayer, R. (Ed), The Cambridge handbook of multimedia learning (169-182), Cambridge, UK: Cambridge Unibversity Press. Mayer, R. E. (2010). Applying the science of learning to medical education. Medical Education, 44(6), 543–549. doi:10.1111/j.1365-2923.2010.03624.x Mayer, R., & Johnson, C. (2008). Revising the redundancy principle in multimedia learning. Journal of Educational Psychology, 100(2), 380-386. doi: 10.1037/002206126.96.36.1990. Mestre, L. S. (2012). Student preference for tutorial design: A usability study. Reference Services Review, 40(2), 258–276. doi:10.1108/00907321211228318
Mullamphy, D. F., Higgins, P. J., Ward, L. M., & Belward, S. R. (2010). To screencast or not to screencast. ANZIAM, 51(1), 446–460. Nafaidilah N. (2012). Kesan Persembahan Video Screencast Dengan Narasi Dan Video Screencast Tanpa Narasi Terhadap Pembelajaran. Unpublished master’s thesis, Universiti Pendidikan Sultan Idris, Tanjung Malim. Norasmah O., & Mohd Hasril A. (2010). Different perspectives of learning styles from VARK model. In Procedia - Social and Behavioral Sciences (Vol. 7, pp. 652–660). doi:10.1016/j.sbspro.2010.10.088 Oehrli, J., Piacentine, J., Peters, A., & Nanamaker, B. (2011). Do screencasts really work? Assessing student learning through instructional screencasts. In ACRL Conference, 2011 (Vol. 30, pp. 127–44). Retrieved from http://www.ala.org/acrl/sites/ala.org.acrl/files/content/conferences/confsandpreconf s/national/2011/papers/do_screencasts_work.pdf Oud, J. (2009). Guidelines For Effective Online Instruction Using Multimedia Screencasts. Reference Services Review, 37(2), 164–177. doi:10.1108/00907320910957206 Ozsvald, I. (2010). The Screencasting Handbook. London: ProCasts. Peterson, E. (2007). Incorporating screencasts in online teaching. The International Review of Research in Open and Distance Learning, 3(3), 3–4. Retrieved from http://www.irrodl.org/index.php/irrodl/article/viewArticle/495 Pinder-Grover, T., Millunchick, J. M., & Bierwert, C. (2008). Work in progress - using screencasts to enhance student learning in a large lecture Material Science and Engineering course. 38th Annual Frontiers in Education Conference, 1, 13–14. doi:10.1109/FIE.2008.4720446 Renumol, V. G., Janakiram, D., & Jayaprakash, S. (2010). Identification of cognitive processes of effective and ineffective students during computer programming, 10(3), 1– 21. doi:10.1145/1821996.1821998.http Riding, R. J., & Sadler-Smith, E. (1997). Cognitive style and learning strategies: Some implications for training design. International Journal of Training and Development, 1(3), 199–208. doi:10.1111/1468-2419.00020 Rocha, A., & Coutinho, C. P. (2010). Screencast and vodcast: an experience in secondary education. In Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 1043–1050). San Diego, United States: Association for the Advancement of Computing in Education (AACE). Retrieved from http://repositorium.sdum.uminho.pt/handle/1822/10592 Rosniah M. (2007). Mengadaptasikan gaya pembelajaran pelajar ESL : Satu kajian kes pelajar tahun satu di UKM. GEMA Online Journal of Language Studies, 7(1), 1–32. Udell, J. (2005). What is screencasting. Retrieved from http://www.oreilly.com/pub/au/32 Veronikas, S., & Maushak, N. (2005). Effectiveness of audio on screen captures in software application instruction. Jurnal of Educational Multimedia and Hypermedia, 14(2), 199– 205. 86
Winterbottom, S. (2007). Virtual lecturing: Delivering lectures using screencasting and podcasting technology. Planet, (18), 6–8. doi:10.11120/plan.2007.00180006 Witkin, H. a., Moore, C. a. C., Goodenough, D., & Cox, P. W. (1977). Field-Dependent and Field-Independent Cognitive Styles and Their Educational Implications. Review of Educational Research, 47(1), 1–64. doi:10.3102/00346543047001001 Yosep, Wawan Setiawan, & Waslaludin. (2012). Model pembelajaran gaya belajar VARK dalam mata pelajaran Teknologi Informasi dan Komunikasi berbasis Multimedia interaktif, 1–6. Zabedah A. A., & Wah, L. L. (2005). Pencapaian kemahiran membaca pelajar-pelajar pemulihan sekolah rendah berasaskan kaedah fonetik. In Prosiding Seminar Pendidikan JPPG (pp. 48–51).
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 7
ESSENTIAL COMPONENTS IN STRUCTURING ASYNCHRONOUS DISCUSSION FORUMS Dr. Moanes H. TIBI Head of Computer Science Department Faculty of Education, Beit Berl Academic College Kfar Saba, Israel ABSTRACT Online learning has been used over the past decade in most disciplines at higher education while the asynchronous online courses are one of the more popular modes of conducting online learning. Within the asynchronous online course, the asynchronous discussion forum plays an important role since it can replace the face to face interaction of the traditional classroom. Since discussions are critical in any learning process, the question is what are the essential components of the asynchronous discussion forum that can make asynchronous discussions more effective for learning and knowledge construction? This paper reviews the literature regarding the main elements and components that makes an asynchronous discussion forum more effective for knowledge acquisition and thereby increases the quality of online learning. Keywords: Online Learning, asynchronous discussion forums, structured discussion forums, online collaborative learning INTRODUCTION The principles of constructivism emphasize social interaction as a basis for knowledge construction. Most educators agree that interaction and discussion between students and their instructor and among the students themselves are critical in promoting and enhancing online learning (Anderson, 2003; Curtis & Lawson, 2001; Gokhale, 1995; Harasim, 2002; McAlpine, 2000; Muirhead & Juwah, 2004; Palloff & Pratt, 2007; Swan, 2002). According to Walls (2005), the lack of interaction and discussion is an important impediment to the effectiveness of online courses. The most widely used asynchronous tool for the purpose of increasing interaction, group discussion and collaboration among participants in online courses is the discussion forum. Discussion forums are basically used for establishing discussions focused on the content of an online course (Dringus & Ellis, 2004; Trevino, 2015). They also allow the construction of collaborative knowledge since learners can work together, exchange information and ideas, and comment on each other's work (Markel, 2001; Preece, 2000). Researchers have reported that while online discussions can facilitate deep learning, that does not happen spontaneously; therefore careful and ongoing instructor mediation and support is required (Al-Shalchi, 2009; Anderson, 2008; Lall & Lumb, 2010; Lee-Baldwin, 2005; Wu & Hiltz, 2004). It has been also argued that without proper structure and management of the discussion forum, students may not achieve the expected learning goals (Ali & Salter, 2004; Andresen, 2009; Biesenbach-Lucas, 2004; Ioannou, Demetriou, & Mama, 2014; Nandi, Hamilton, & Harland, 2015; Salter & Conneely, 2015; Wozniak & Silveira, 2004). Consequently, the question is what are the main components of an asynchronous discussion forum, which can make discussions more effective for high levels of learning and knowledge construction? 88
MAIN COMPONENTS OF AN EFFECTIVE ASYNCHRONOUS DISCUSSION It is clear that the process of Interactions and discussions is a critical component of any learning process, especially when learning is conducted online via CMC tools, such as the learning management system "Moodle" or other environments. Research also shows that simply forming a discussion forum, providing the technology and topics for discussion is not enough to ensure successful and effective online discussion and collaborative learning (Andresen, 2009; Ioannou et al., 2014; Lall & Lumb, 2010; Nandi et al., 2015; Salter & Conneely, 2015). Following sections describe the main elements and components that need to be within a discussion forum in order to make discussions more effective for knowledge construction and collaborative learning (Figure 1). These components are based on the theory of constructivism, on pedagogical principles and on principles of group interaction and collaboration.
Figure: 1 Main components (MOC) of an effective asynchronous discussion. Preparatory Instructions about Individual Participation Clear and simple directions for online discussion and setting out expectations are important in making student to student interactivity more effective (Mayne & Wu, 2011; Wozniak & Silveira, 2004) and in helping and motivating students to contribute to the discussions within the discussion forum (Al-Shalchi, 2009; Ioannou et al. ,2014; Lall & Lumb, 2010; Roper, 2007). At the beginning of an online course students should receive clear information about how they will be evaluated and other preparatory instructions about the purpose of the discussion forum and how to use it. This information can be described through the following main points: Assessment rubric: besides the important information regarding the course content, resources and other information, the course syllabus needs also to show the students how they will be evaluated during the course. Giving students clear information about how they will be assessed during the course will provide them with extrinsic motivation which, in turn, may have a positive effect on their performance and learning outcomes (Dennen, 2000). The assessment rubric can consist of a set of elements such as: (1) grade weight of the participation in the discussion forums, (2) grade weight of the individual and of the group assignments, (3) grade weight of the examination, and (4) grade weight of the 89
final group project. In more details, for each assignment in the course students should know about the score and the evaluation criteria of the assignment. Purpose of the discussion forum: the purpose of using the discussion forum should be clearly explained to students at the beginning of the course. Roper (2007) claimed that instructors who establish clear expectations about the purpose of the discussion forum and how to use it can expect to encourage richer online dialogue. Also Rose and Smith (2007) argued that instructors must provide the students with clear and simple directions for online discussions that do not cause any confusion among the students. Usually, a discussion forum in an online course is used for enhancing learning through in-depth discussion of the learning topics (Dringus & Ellis, 2004). Students in online courses need to be encouraged to exchange information and ideas with each other and to post their questions about the learning materials to the discussion forum in order to get answers and support from other students and from the instructor. Students need also to be asked to participate actively and consistently in the discussion forum at whatever time of day was most convenient for them and to relate their discussions to the readings that were set for each week. In addition, students should be informed about the importance of the quality and not the quantity of postings sent to the discussion forum. In principle, students have to know that an educational discussion forum is used only for discussing the learned materials and learning activities of the course and it is not designed for having social discussions. Students may continue to communicate with each other through different CMC tools such as E-mail and other web messaging tools. Instructions about using the discussion forum: the preparatory instructions givento the students at the beginning of the online course should also include basic rules about how to use the discussion forum. The purpose of these rules is to preserve the order and organization of the discussions and can be summarized in the following main points: o When writing a response to a given message in the discussion forum, post it as a reply to that message so that participants will find it easy to follow the thread of a topic. o When introducing a new topic, question or idea to the discussion forum, post it as a new message that makes the subject of your message clear to all. o When quoting, use quotation marks and include the location of the original text. o Avoid “yes,” “no,” or repeated responses that clutter the forum and do not add to the discussion. Since this is an educational discussion forum, it is important to maintain the quality of posts rather than the quantity.
Instructions about Group Collaboration As noted by Ikpeze (2007), group collaboration allows students to become active learners rather than passive recipients of teaching and it helps to distribute the cognitive load among the members of a group through the exchange of ideas. Students working in small groups tend to learn more of what is taught and retain it longer than when the same content is presented in other instructional design (Davis, 1993; Johnson & Johnson, 1986, 2004). In order to support online group collaboration the students of the online course can participate in two levels of discussion groups. One level is the small group discussion forum and the other level is the central discussion forum (Figure 2).
Small Group Discussion Forum
Small Group Discussion Forum
Central Discussion Forum
Small Group Discussion Forum
Small Group Discussion Forum
Figure: 2 Levels of the discussion groups. Small Group Discussion Forum For each small group of students, a discussion forum can be specially established in order to support students' interaction and collaboration around the learning subjects and group learning activities. As a part of the instructions, students should be encouraged to discuss the learning subjects and help each other's understanding of the materials of the course as well as to exchange information and collaborate around the group learning activities. The participation in a small group discussion forum is allowed only for the members of that small group and not for other students. The instructor's role in the small group discussion forums is to facilitate students' interaction with the materials and with each other in their knowledge constructing endeavor. This role was described in Benfield (2002) and Mazzolini and Maddison (2007) as a more constructivist "guide on the side" role. Small groups of students can be constructed according to the following main characteristics: Group goal: it should be clearly stated to the members of each small group that they should work together toward the building of a learning group and try to maximize learning for each group member. Thus, students need to be guided to work in their groups for the purpose of sharing and exchanging information and knowledge in order to achieve a deeper understanding of the subjects taught and to complete the required group learning activities. Group dynamic: the dynamic of the interaction and collaboration between the students of each small group discussion forum can be determined by the group members themselves. The instructor needs not to be involved in the dynamics of the groups and should not assign roles for the group members. The instructor's role in this case is more to observe and motivate the participation in the small group discussion forums, while giving guidance and support to the students whenever they request it. MacDonell (1992), suggested that the instructor who aims to be conscious of group dynamic should adopt a more "democratic teaching style and be prepared to step aside to give the learner a meaningful role" (p. 169), only intervening when necessary. Group structure: group members shape the structure of their group within the general rules and norms that were explained by the instructor at the beginning of the online course. The instructor should not be involved in shaping the patterns of relationships and interactions that can appear within a group. Group size: each small group can be composed of three or four students. Davis (1993) claimed that, in general, groups of four or five learners work best. Felder and Brent (1994) argued that "when students work in pairs, one of them tends to 91
dominate and there is usually no good mechanism for resolving disputes, and in teams of five or more it becomes difficult to keep everyone involved in the process" (p. 6). Rau and Heyl (1990) mentioned that in larger groups it is difficult to ensure that all members participate. It would seem that small groups made up of three or four students are suitable for collaboration and therefore this group size can be used for constructing the small groups in online courses. Group selection: the concept of collaborative learning involves groups of students working together as a team to solve a problem or complete an assignment (Dillenbourg & Schneider, 1995; Garfield, 1993). Collaborative groups can be formed using different concepts, such as self-selection, random selection, or criterion-based selection (Gokhale, 1995). In selecting collaborative groups, Garfield (1993) noted that the instructor may allow students to self-select groups or groups may be formed by the instructor to be either homogeneous or heterogeneous on particular characteristics. Collaborative groups need to be heterogeneous since students working in small heterogeneous groups learn the subject matter content, appropriate problem-solving and critical thinking skills, as well as skills necessary to work together collaboratively (Roberts, 2004). Felder and Brent (1994) suggested that the "drawbacks of a group with only weak students are obvious, but having only strong students in a group is equally undesirable" (p. 6). They claimed that strong groups have an unfair advantage over other groups and that the members of a strong team tend to divide up the homework and communicate only cursorily with one another, omitting the dynamic interactions that lead to most of the proven benefits of collaborative learning. On the other hand, in groups with mixed knowledge levels or abilities, the weaker students gain from seeing how better students study and approach problems. The stronger students who teach others often find that teaching someone else leads to their own improved understanding of the material allowing them to gain a deeper understanding of the subject (Felder & Brent, 1994; Garfield, 1993). Therefor small groups of students can be formatted by the instructor to be heterogeneous in the knowledge level. This way of forming the small group assures at least that the best students in the class do not cluster together, leaving the weaker ones to fend for themselves. The knowledge level of the students can be determined according to a pre-test that can be given to all students before starting the online course. It is also possible to determine the knowledge level of the students according to their scores in a course that students were required to take as a prerequisite.
Central Discussion Forum As previously mentioned, besides the discussion forums that can be constructed for small groups of students, a central discussion forum should be also established. In the central discussion forum, all students from all groups are requested to participate actively. The discussions in the central discussion forum should be administered by the instructor of the course who needs to play an active, visible part in the forum discussions keeping them on the right track. The increased number of postings to the central discussion forum all over the course can make it difficult for the students to find specific information. Therefore, for each central topic in the course a new central discussion forum can be established in order to contribute to a clear and a better organization to the whole process. Instructors' Role in Organizing the Discussion The instructor can organize the content of the discussion forum through questioning, learning activities and feedback. Following are the descriptions of these components. Questioning: discussion questions encourage students to explore the topic and the assigned reading more deeply (Bender, 2003) and are a critical means for achieving learning objectives (Benson, 2007). The instructor should created appropriate discussion questions and activities on different levels and kinds of knowledge (know-what, know-how, and know-why) including higher order questions that ask students to make comparisons, suggest causes and solve given 92
problems. Bender (2003) argued that higher order questions provoke constructive thought and open the gates for meaningful discussion. The motivation for this approach is constructivist in nature in that it assumes that student knowledge can be drawn out through student-student and instructor-student interaction involving the asking and answering of questions (Anderson, 2003; Gold, 2001; Markel, 2001; Nandi et al., 2015; Salter & Conneely, 2015; Trevino, 2015; Weimer, 2013). Additionally, the instructor can post a list of questions and problems to be solved and refer each question to a different student. Students are then required to response to these questions, as well as to make critique and comments on other students' answers, within a given period of time in order to initiate a debate around the learned subjects and thereby promote higher levels of thinking. This questioning activity is more appropriate if the number of students enrolled in the course is not large. Otherwise, the instructor can repeat this kind of activity during the course while taking each time a different group of students with a different set of questions. Other types of clarification and support, such as offering explanations, clarification of students' understanding and offering suggestions that guide and improve deeper and further discussions, should also be made. This part of the discussion needs to continue over the entire course aiming to encourage more interaction among the participants in order to enhance knowledge acquisition on different levels. Group activities: Online collaborative learning aims to provide an environment that supports and enhances online collaboration between students in order to enhance students’ learning processes (Kreijns, Kirschner & Jochems, 2003; Weimer, 2013). Despite the popularity of online collaborative learning, simply putting students together in an online learning group and asking them to work collaboratively does not guarantee that they will engage in meaningful collaborative inquiry (An, Kim & Kim, 2008; Biesenbach-Lucas, 2004; Johnson & Johnson, 1986, 2004). Fortunately, there is a growing literature describing how online collaborative learning can be implemented successfully (Achtemeir, Morris & Finnegan, 2003; Harasim, 2002; Ioannou et al., 2014; Schrum & Hong, 2002). The key appears to be preparation by the instructor in scheduling collaborative learning activities throughout the experience (Hiltz, 1997) including projects for co-production (Harasim, 2002). Hiltz and Turoff (2002) suggested that collaborative learning activities, which are well-suited for online environments, include debates, group projects, case study discussions, simulations, role-playing exercises, the sharing of solutions for homework problems, and the collaborative composition of essays, stories, and research plans. However, in reality, most online collaborative work is usually relegated to discussion forum conversations, in which students merely generate a dialogue with each other about the weekly readings (An et al., 2008). Although this type of activity can clearly be of relevance, the extent of actual collaboration is usually limited, the reason why well-designed collaborative learning activities need to be combined with online collaborative learning. Small group discussion forums are basically designed in order to let students work collaboratively on group tasks and projects and thereby increase their knowledge. Each small group can receive well designed collaborative learning activities during the course and use its own discussion forum as a place for work in order to accomplish these activities. Results of each small group can then be posted to the central discussion forum in order to allow for a wide discussion around the activities between all students from all small groups. This opportunity can open the gate for more meaningful discussions and can contribute to a deeper understanding of the learned subjects as well as of the principles underlying the performance of the activities suggested by each group since group members will be requested to defend their proposed solutions in front of the other groups. The whole process of such activities should be observed by the instructor with feedback and support when it is necessary Feedback: giving feedback to the students is important since it can help them to reflect upon what they have learned and what they still need to know (Bender, 93
2003). Mazzolini and Maddison (2007) recognized that frequent instructor participation is often assumed to encourage students' participation. Kearsley (2000) argued that one factor that strongly affects the amount of student interaction and participation is the level of instructor involvement. However, the instructor needs to maintain a balance between too little and too much participation and should therefore determine the appropriate time to jump in (Mazzolini & Maddison, 2007). Thus, the instructor should not response to every student post immediately when it is not directed to him in order to give other students the opportunity to response and comment on each other posts. This, in turn, can motivate the students to construct meanings through interaction with each other. However, the instructor should participate regularly in the discussion forum giving feedback, answers, new and follow-up questions and other comments to the students, in order to keep discussions on track and to support the learning process. In addition to ongoing feedback the instructor can give a positive personal feedback for each student at least once or twice during a semester. In this feedback students can be informed about their level of participation. Students who did not participated enough should be requested to participate more as well as to explain to the instructor about the reasons for their low participation. This personal feedback aims to motivate and help the students to be more active in the discussion forum. CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE RESEARCH Online discussions are an essential part of online courses so the adoption of communication technologies, particularly discussion forums, will continue to grow in online learning environments. It is clear that discussion forums can achieve high levels of learning, but this goal cannot be reached without proper preparations, structuring and management of the discussion and especially intensive instructor interaction with the learners. Using structured discussion forums, which involves problem and project based learning activities, can help in building a community of learners which allows students to become part of a vibrant learning community, rather than an just an independent learner. In fact, the use of structured discussion forums in online courses can be as instructor intensive (instructor to content, instructor to student and assessment of students) as the traditional classroom, if not more. Thus, future work should aim to design and develop better online collaborative learning management systems or platforms that support the sharing and construction of knowledge more easily and effectively. Additionally, these tools should support the instructor in assessing online collaboration and knowledge construction processes. This in turn can reduce the amount of time spent by the instructors on assessment allowing them to invest more time in designing the online course including the teaching and learning activities. BIODATA and CONTACT ADDRESSES of the AUTHOR Dr. Moanes H. TIBI holds Bachelor's and Master's degrees in Computer Science from the Rheinische Friedrich-WilhelmsUniversität Bonn in Germany. He earned his Ph.D. from Bar-Ilan University. Dr. Tibi has been lecturing in this field since 1995 and has served as the head of the Computer Science Department at Beit Berl Academic College since 2012. Over the years, he has written various articles and books, participated in national and international Conferences. His principal fields of research and interest include developing teaching and learning models in online environments, and exploring the effect of information technologies on teaching and learning among students and on society in general. Lately, He has been taking an interest in computer science teaching programs for young people.
Dr. Moanes H. TIBI, Head of Computer Science Department, Faculty of Education, Beit Berl Academic College, Kfar Saba, Israel. Phone: +97297473109 Email: [email protected]
REFERENCES Achtemeir, S.D., Morris, L.V. & Finnegan, C. L. (2003). Considerations for developing evaluations of online courses. Journal of Asynchronous Learning, 7(1). Ali, S., & Salter, G. (2004). The use of templates to manage on-line discussion forums. Electronic Journal on e-Learning 2(1), 11-18. Al-Shalchi, O. (2009). The effectiveness and development of online discussion. (Electronic version). MERLOT Journal of Online Learning and Teaching, 5(1), 104-108. An, H., Kim, S., & Kim, B. (2008). Teacher perspectives on online collaborative learning: Factors perceived as facilitating and impeding successful online group work. Contemporary Issues in Technology and Teacher Education, 8(1). Retrieved April 25, 2014 from http://www.citejournal.org/vol8/iss4/general/article1.cfm Anderson, T. (2003). Getting the mix right again: An updated and theoretical rationale for interaction. The International Review of Research in Open and Distance Learning , 4(2). Retrieved March 02, 2014 from http://www.irrodl.org/index.php/irrodl/article/view/149/230 Anderson, T. (2008). Towards a theory of online learning. (Electronic version). In T. Anderson (Ed.), The theory and practice of online learning (2nd ed., pp.45-74). Edmonton, AB: Athabasca University Press. Andresen, M. A. (2009). Asynchronous discussion forums: Success factors, outcomes, assessments, and limitations. Educational Technology & Society, 12(1), 249-258. Bender, T. (2003). Discussion-based online teaching to enhance student learning: Theory, practice and assessment. Sterling, Virginia: Stylus Publishing. Benfield, G. (2002). Designing and managing effective online discussions. Learning and Teaching Briefing Papers Series, OCSLD Oxford Brooks University. Retrieved Mai 01, 2014 from http://www.brookes.ac.uk/services/ocsd/2_learntch/briefing_papers/online_disc ussion.pdf Benson, R. (2007). How to Develop Effective Discussion Questions - Part I: Introduction and Discussion Question Objectives. An Online Learning Magazine for University of Maryland University College Faculty. Retrieved Mai 01, 2014 from http://deoracle.org/online-pedagogy/classroom-communication/effectivediscussion-questions-part-one.html Biesenbach-Lucas, S. (2004). Asynchronous web discussions in teacher training courses: Promoting collaborative learning—or not? AACE Journal, 12(2), 155-170. Curtis, D. D., & Lawson, M. J. (2001). Exploring collaborative online learning. (Electronic version). JALN, 5(1), 21-34. Davis, B. G. (1993). Collaborative learning: Group work and study teams. In B.G. Davis (Ed.), Tools for Teaching. San Francisco: Jossy-Bass Publishers. Retrieved March 10, 2014 from the University of California at Berkeley web site: http://teaching.berkeley.edu/bgd/collaborative.html Dennen, V. P. (2000). Task structuring for on-line problem based learning: a case study. Educational Technology & Society 3(3), 329-336. Dillenbourg, P., & Schneider, D. (1995). Collaborative learning and the internet. ICCAI. Retrieved December 17, 2014 from http://tecfa.unige.ch/tecfa/research/CMC/colla/iccai95_1.html
Dringus, L. P., & Ellis, T. J. (2004). Building the SCAFFOLD for evaluating threaded discussion forum activity: Describing and categorizing contributions . 34th ASEE/IEEE Frontiers in Education Conference. Savannah, GA. Retrieved September 10, 2014 from http://fie.engrng.pitt.edu/fie2004/papers/1080.pdf Felder, R. M., Brent, R. (1994). Cooperative learning in technical courses: Procedures, pitfalls, and payoffs. National Science Foundation Division of Undergraduate Education. Retrieved March 10, 2014 from http://www.eric.ed.gov/PDFS/ED377038.pdf Garfield, J. (1993). Teaching statistics using small-group cooperative learning. Journal of Statistics Education, 1(1). Retrieved September 26, 2014 from http://www.amstat.org/publications/jse/v1n1/garfield.html. Gokhale, A. A. (1995). Collaborative learning enhances critical thinking. Journal of Technology Education 7(1). Retrieved January 11, 2014 from http://scholar.lib.vt.edu/ejournals/JTE/v7n1/gokhale.jte-v7n1.html Gold, S. (2001). A constructivist approach to online training for online teachers. Journal of Asynchronous Learning Networks, 5(1), 35–57. Harasim, L. (2002). What makes online learning communities successful? The role of collaborative learning in social and intellectual development. In C. Vrasidas & G. V Glass, Distance Education and Distributed Learning (pp. 181-200). Charlotte, NC: Information Age Publishing. Hiltz, S. R. (1997). Impacts of college-level courses via asynchronous learning networks: Some preliminary results. Journal of Asynchronous Learning Networks, 1(2). Hiltz, S. R., & Turoff, M., (2002). What Makes Learning Networks Effective? (Electronic version). CACM, 45(4), 56-59. Ikpeze, C. (2007). Small group collaboration in peer-led electronic discourse: An analysis of group dynamics and interactions involving preservice and inservice teachers. Journal of Technology and Teacher Education, 15(3), 383-407. Ioannou, A., Demetriou , S. & Mama, M. (2014). Exploring Factors Influencing Collaborative Knowledge Construction in Online Discussions: Student Facilitation and Quality of Initial Postings. American Journal of Distance Education, 28(3), 183195. Johnson, R. T., & Johnson, D. W. (1986). Action research: Cooperative learning in the science classroom. Science and Children, 24(2), 31-32. Johnson, D. W., & Johnson, R. T. (2004). Cooperation and the use of technology. In D. H. Johansson (Ed.). (2nd ed.), Handbook of research on educational communications and technology (pp. 785-811). Mahwah, NJ: Lawrence Erlbaum Associates. Kearsley, G. (2000). Online Education: Learning and teaching in cyberspace. Belmont, CA: Wadsworth Publishing. Kreijns, K., Kirschner, P. A., & Jochems, W. (2003). Identifying the pitfalls for social interactions in computer-supported collaborative learning environments: A review of the research. Computers in Human Behaviors, 19, 335-353. Lall, V., & Lumb, R. (2010). Successful design, development and delivery of online courses: Lessons from operations management and global leadership. Indian Journal of Economics & Business, 9(2), 377-384. Lee-Baldwin, J. (2005). Asynchronous discussion forums: A closer lock at the structure, focus and group dynamics that facilitate reflective thinking. (Electronic version) Contemporary Issues in Technology and Teacher Education, 5(1), 93-115. MacDonell, W. (1992). The role of the teacher in the cooperative learning classroom. In C. Kessler (Ed.), Cooperative language learning: A teacher resource book. (PP. 163174). Englewood Cliffs, NJ: Prentice Hall. Mayne, L., & Wu, Q. (2011). Creating and measuring social presence in online graduate nursing courses. Nursing Education Perspectives, 32(2), 110-114. Markel, S. L. (2001). Technology and education online discussion forums: It's in the response. Online Journal of Distance Learning Administration, 4(2). Retrieved Mai 15, 2014 from http://www.westga.edu/~distance/ojdla/summer42/markel42.hml Mazzolini, M., Maddison, S. (2007). When to jump in: The role of the instructor in online discussion forums. Computers & Education, 49(2), 193-213. 96
McAlpine, I. (2000). Collaborative learning online. (Electronic version). Distance Education, 21(1), 66-80. Muirhead, B., & Juwah, C. (2004). Interactivity in computer-mediated college and university education: A recent review of the literature. Educational Technology & Society, 7(1), 12-20. Nandi, D., Hamilton, M., & Harland, J. (2015). What Factors Impact Student – Content Interaction in Fully Online Courses. I.J. Modern Education and Computer Science, 7, 28-35. Palloff, R., & Pratt, K. (2007). Building online learning communities: Effective strategies
for the virtual classroom. Jossey-Bass Wiley. Retrieved from Google books database
Preece, J. (2000). Online communities: Supporting sociability, designing usability. Chichester, UK: Wiley. Rau, W. & Heyl, B. S. (1990). Humanizing the college classroom: Collaborative learning and social organization among students. Teaching Sociology, 18(2), 141-155. Roberts, T. S. (Ed.) (2004). Online collaborative learning: Theory and practice. Hershey, PA: Information Science Publishing. Roper, A. R. (2007). How students develop online learning skills. Educause Quarterly, 30(1), 62-65. Rose, R., & Smith, A. (2007). Online discussions. In C., Cavanaugh & R., Blomeyer (Eds.), What works in k-12 online learning (pp. 143-160). Washington, D.C.: International Society for Technology in Education. Rudestam, K. E. & Schoenholtz-Read, J. (Eds.) (2010). Handbook of Online Learning. London: Sage publications, 2nd edition. Retrieved from Google Books database. Salter, N., P., & Conneely, M. R. (2015). Structured and unstructured discussion forums as tools for student engagement. Computers in Human Behavior, 46(1), 18-25. Schrum, L. & Hong, S. (2002). Dimensions and strategies for online success: Voices from experienced educators. Journal of Asynchronous Learning Networks, 6(1), 57-67. Swan, K. (2002). Building learning communities in online courses: the importance of interaction (Electronic version). Education, Communication & Information, 2(1), 2349. Walls, C.M. (2005). Some strategies for balancing economies of scale and interaction in online/distance education courses. E-Journal of Instructional Science and Technology (e-JIST) 8(1). Retrieved June 11, 2014 from http://www.eric.ed.gov/PDFS/EJ850357.pdf Weimer, M. (2013). Structuring Discussions: Online and Face-to-Face. Teaching Professor Blog. Retrieved June 20, 2015 from http://www.facultyfocus.com/articles/teaching-professor-blog/structuringdiscussions-online-and-face-to-face/ Wozniak, H., & Silveira, S. (2004). Online discussions: Promoting effective student to student interaction. In R. Atkinson, C. McBeath, D. Jonas-Dwyer & R. Phillips (Eds.), Beyond the Comfort Zone: Proceedings of the 21st ASCILITE Conference, (pp. 956960) Wu, D. & Hiltz, S. (2004). Predicting learning from asynchronous online discussions . Journal of Asynchronous Learning Networks, 8(2), 139-152.
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 9
OPEN EDUCATIONAL RESOURCES (OER): OPPORTUNITIES AND CHALLENGES FOR INDIAN HIGHER EDUCATION Dr. Indrajeet DUTTA College of Teacher Education, Bhopal Maulana Azad National Urdu University, Hyderabad, INDIA ABSTRACT Creation of knowledge workers holds key for success of a country. Unfortunately, many of the countries though having chain of human resources yet are unable to transform human resources to their advantage as they face multiple challenges like poverty, poor economy, poor infrastructure, limited access to education and inadequate technological growth. Fortunately, India is one of among such countries in the recent past which has improved its position in the world forum and has taken a big stride by transforming human resource into knowledge workers. The entire credit goes to government of India, their schemes and most importantly the people working tirelessly in the higher education institutions. But, the percentage is very low.The reason is higher education of India is plagued with several challenges like poor quality of teachers, poor infrastructure, poor libraries and poor educational resources. Unless high quality of education both in terms of infrastructure and academic is not provided and sustained in all higher education institutes, it will be difficult to match with global world. One way it could be done at least in academic front is developing and disseminating quality educational material among the institutes of higher education. National Knowledge Commission has recommended that problems of educational material to a large extent can be reduced by Open Educational Resources (OER) and Open Access (OA). The easy and widespread availability of high quality educational material will change the paradigm of teaching and learning and thus improve the quality of education. Government of India has started several innovative programs and schemes like SHAKSHAT, NMEICT, NPTEL, OSCAR, E-grid etc. related to developing and disseminating educational resources. The national and global level are tremendous but it comes with many challenges specifically in a country like India which has a diversified population.The present paper will try to focus on the opportunities and challenges with respect to OER in Indian higher education. Key Words: OER, higher education, challenges, opportunities. INTRODUCTION
“Open Educational Resources (OERs) are any type of educational materials that are in the public domain or introduced with an open license. The nature of these open materials means that anyone can legally and freely copy, use, adapt and re-share them. OERs range from textbooks to curricula, syllabi, lecture notes, assignments, tests, projects, audio, video and animation.” - UNESCO, Home Page dated 2nd October2013 Over the past two decades the electronic revolution has changed the world scene. Never in the history, has technology influenced education so much as it is doing today. In recent years, the rate of technological change happened in electronic medium has never been so fast, what is used to be two decades ago. Technology has changed our world in ways previously unimaginable. No one has ever imagined that with a click of mouse the money can be transferred one place to other place, one can talk live face to face via mobile(3G)across the country, one can attend conferences, workshop almost virtually.
Educators’ tryst with technology has a long history. The influence of technology in the learning process starts right from the time of Thomas Edison in 1922 where he predicted that “that the motion picture is destined to revolutionize our educational system and that in a few years it will supplant largely, if not entirely, the use of textbooks”. With the passage of time, use of technology has dominated educational discourse especially in the 21st century. The advent of internet has brought revolution not only in the field of trade and commerce, technology, but also in the field of education. Many people would tend to think education as perpetually lagging behind technology; but there are numerous instances in history where education has provoked technical innovation. The present society is often called “information society” or “knowledge Society” as, the development in technology has led to the widespread diffusion of information that give rise to new opportunities for learning. At the same time, the challenge of established views and practices regarding how teaching and learning should be organised and carried out. Higher educational institutions have been using the Internet and other digital technologies to develop and distribute education for several years. Yet, until recently, much of the learning materials were locked up behind passwords within proprietary systems, unreachable for outsiders. The open educational resource (OER) movement break down the barriers and thus encourage to use or share content. According to the Hewlett Foundation:
“Open Educational Resources are teaching, learning, and research resources that reside in the public domain or have been released under an intellectual property license that permits their free use or re-purposing by others. Open Educational Resources (OER) is one of the ways of sharing the resources specifically the faculty and the content by keeping it in public domain. The vision behind creating OER is to lower the cost of educational materials, develop innovations and improve the quality of content and thus it can be accessed anytime, anywhere and anyplace by anyone. The easy and widespread availability of high quality educational resources will change the paradigm of teaching and improve the quality of education for all students. In addition, students will have access to inaccessible information as well as the knowledge on how to access global educational resources. UNESCO believes that universal access to high quality education is key to the building of peace, sustainable social and economic development, and intercultural dialogue. Open Educational Resources (OER) provide a strategic opportunity to improve the quality of education as well as facilitate policy dialogue, knowledge sharing and capacity building. OER started its journey in 2001, when Massachusetts Institute of Technology (MIT), in an unprecedented move, announced the release of nearly all its courses on the internet for free access. The term Open Educational Resources (OER) was coined at UNESCO’s 2002 Forum on Open Courseware and designates “teaching, learning and research materials in any medium, digital or otherwise, that reside in the public domain or have been released under an open license that permits no-cost access, use, adaptation and redistribution by others with no or limited restrictions. Open licensing is built within the existing framework of intellectual property rights as defined by relevant international conventions and respects the authorship of the work”. Thereafter, the number of institutions offering free or open courseware increased. With the support of the Hewlett Foundation, UNESCO created a global OER Community wiki in 2005 to share information and work collaboratively on issues surrounding the production and use of Open Educational Resources. Open Educational Resources (OERs) have become significantly important in education systems across the world. They represent the efforts of a worldwide community, empowered by the internet, to help equalize the access to knowledge and educational opportunities. These are teaching, learning and research resources that reside in public domain that permits their free use or customization by others (Bissell, 2007). According to Smith and Casserly (2006), OERs are sharable assets. Between 2005 and 2007, a large community of interest of more than 600 members from more than half of the 192 members states of UNESCO took part in online discussions on OERs.The National Knowledge Commission (NKC) recommended the increase the amount of Open Educational Resources (OER) and
Open Access (OA).On its recommendation, Indian government has started several innovative programmes like SHAKSHAT-(an academic portal), National Mission on Education through Information and Communication Technology (NMECIT), National Programme on Technology enhanced Learning (NPTEL), OSCAR(Open Source Courseware Animations Repository), E-grid(E-Grid an educational portal is a project which is supported by MHRD at IIIT, Kerala) etc. In India, OER movement is picking up and government has realized its strength and that’s why it is investing huge amount of money to develop quality OER in different disciplines and in different languages. It has entrusted various elite institutions like Indian Institute of Technology (IITs), Indian Institute of Management (IIMs), Indian Institute of Science(IIS), Indian Institute of Information Technology(IIIT), National Institute of Open Schooling (NIOS), Indira Gandhi National Open University (IGNOU), National Council of Educational Research and Training(NCERT) and many other private organizations to create and develop teaching, learning and research materials for students, research scholars and teachers for various levels of education. Networking of libraries of universities is one such step in this direction. Various foreign institutions and international organizations are also spending huge amount of money to develop and store OER in the repository for educational use. MAJOR INNOVATIVE INITIATIVES ON OER BY INDIAN GOVERNMENT NMECIT National Mission on Education through Information and Communication Technology is a centrally sponsored scheme to leverage the potential of ICT, in providing high quality personalized and interactive knowledge modules over the internet/intranet for all kind of learners in higher education in anytime, anywhere mode. This scheme has two major components one content generation and other connectivity along with provision for access devices for institutions and learners. In this project requires all the universities and the colleges of the country are to be connected. The universities are to be connected with National Knowledge Network (NKN) and the colleges are to be connected with broadband connectivity. This scheme was launched on February 3, 2009 by government of India through its Union Ministry of Human Resource development. The objectives of the mission are: Ø Empowering and enabling students by ensuring equity and access to education through the use of ICT; Ø Connecting over 400 Universities and 22,000 Colleges all over India through high-speed data networks; Ø Improving faculty quality by using a unique synchronous training methodology; Ø Ensuring equity by providing access to expensive equipment to students even in remote corners through innovative use of ICT; and Ø Making available e-content and educational videos created by the best teachers across all disciplines for UG and PG classes. The Mission provides an opportunity for all the teachers and experts in the country to pool their collective wisdom for the benefit of every Indian learner and, thereby, reducing the digital divide and reaching out hitherto deprived sections of the society in rural/ under-developed areas of the country. Under this Mission, a proper balance between content generations, research in critical areas relating to imparting of education and connectivity for integrating our knowledge with the advancements in other countries is being attempted. It is an endeavour through which MHRD is synergising the efforts taken by the educational institutions vis. IITs, UGC, NITs, CEC, IGNOU and other higher education institutions in the country to develop world class content and educational applications. Senior faculty members from different universities, research institutes and institutions of higher learning are contributing to the development of e-learning resources, virtual labs, open source applications etc. The Mission aims to extend computer infrastructure and connectivity to over 26000+ colleges and 2000 polytechnics in the country including each of the department of 419 universities/deemed universities and institutions of national importance as a part of its motto to provide connectivity up to the last mile. Connectivity to universities and colleges is in progress and as on date, 400
universities and nearly 26000 colleges in the country have been connected (MHRD Report, 2014). Under NMEICT till date almost 368 universities are connected through National Knowledge Network. NKN This project is running under NMEICT. The NKN is a state-of-the-art multi-gigabit panIndia network for providing a unified high speed network backbone for all knowledge related institutions in the country. The purpose of such a knowledge network goes to the very core of the country's quest for building quality institutions with requisite research facilities and creating a pool of highly trained professionals. The NKN will enable scientists, researchers and students from different backgrounds and diverse geographies to work closely for advancing human development in critical and emerging areas. The target users for the NKN are all institutions engaged in the generation and dissemination of knowledge in various areas, such as research laboratories, universities and other institutions of higher learning, including professional institutions. NKN has already connected 1038 institutions and aims to connect over 1500 Institutions/Organizations/Laboratories under various categories throughout the country (Home page of NKN, 2015). SHAKSHAT It is a landmark initiative of the Ministry of Human Resource Development (MHRD) to develop a One Stop Education Portal for addressing all the education and learning related needs of students, scholars, teachers and lifelong learners. It is a free portal launched by the Hon’ble President of India on 30th October 2006. It contains many e-repositories for school and higher education. The portal is expected to be the main delivery platform for the contents developed under the National Mission on Education through ICT (NMEICT). For Mission related information and to facilitate public scrutiny, feedback and transparency for the projects undertaken by the Mission a new website has been created. There are more than hundred projects ongoing under the NMEICT ranging from e-content development, access to e-resources, development of software tools etc. In its home page there are four navigation as SAKSHAT repository, picture gallery, SAKSHAT SAARC and what’s new. Within Sakshat repository various links are provided wherein stakeholders can access course wise e-content being developed for under graduate, post graduate, engineering education programme are available prepared by eminent teachers in the form of videos, animation, recorded lectures etc. For UG courses, Consortium of Educational Communication (CEC) has been tasked for e-content generation. In phase-I, e-content for 19 UG subjects and in phase-II e-content for 68 subjects are being generated by the CEC in collaboration with its media centres. For 77 PG subjects, e-content generation activity has been assigned to University Grants Commission (UGC). The process of content creation has been initiated for 72 subjects. Under NPTEL, free online courses for engineering education are available. Apart from it spoken tutorial, talk to teacher and Amrita Virtual interactive E-learning World (A-VIEW) virtual classrooms are also operating. NPTEL NPTEL is a joint initiative of IITs and IISc funded by this Mission provides e-learning through online Web and Video based courses in engineering, science and humanities streams. The Mission of NPTEL is to enhance the quality of engineering education in the country by providing free online courseware. Over 329 courses are complete and made available in NPTEL website. More than 990 courses in various disciplines in engineering and science are getting generated in phase-II of NPTEL A set of 5 separate DVDs containing ready NPTEL course material--one each in the areas of Electrical, Civil, Computer Science, Electronics and Mechanical Engineering were distributed to the AICTE approved Engineering Colleges during the dissemination workshop for engineering colleges of NCR Region held on 8th Oct 2013.
EKLAVYA Eklavya project launched jointly by IIT, Bombay and IGNOU on 26th January, 2003 aims at a free exchange of knowledge and ideas, by placing all the relevant academic material in the Open Source. The project has developed an Open Source Educational Resources Animation Repository (OSCAR) to create a repository of web-based, interactive animations for teaching various concepts and technologies. Its e-GURU programme provides the students with a list of relevant and challenging projects, which encourage them to think of innovative technical solutions to various real life problems and its eOUTREACH programme produces high quality digital text, audio, video and HTML contents of educational value for wider dissemination. The e-CONTENT programme of the project creates open source digital contents in Indian languages through translation and new writing on topics of relevance to education for all levels (Gani, 2010). OSCAR OSCAR (Open Source Courseware Animations Repository) is an initiative of IIT Bombay to build a large repository of web based interactive animations for teaching and learning of science and technology based concepts. E-Grid Launched by IIIT, Kerala and supported by the MHRD, E-Grid portal has been designed to increase and facilitate access to education resources by the educational community and to facilitate collaboration, sharing of knowledge and best practices to improve the quality of education and learning. The Digital Library of India project, being coordinated by the IIS, Bangalore, along with Carnegie Mellon University, aims at digitising the books in India. More than 450,000 books, including those in Indian languages, have already been digitized under this initiative out of which about 220,000 are already available free on the So far 21 centres spanning academic institutions, social organisations, and government agencies have partnered in creating this repository of knowledge (Gani, 2010). OPPORTUNITIES FOR INDIAN HIGHER EDUCATION Today society is knowledge based and it is driven by knowledge workers. It has been said that the society which can produce or create knowledge workers in coming decades will govern the universe. Due to large force of young human resource, world has recognised India as the potential knowledge superpower house. We have one of the fastest and the robust economies of the world (average growth rate is 7%).Various social indicators like health and care, employment, infrastructure, etc. are improving at a phenomenal rate. In the last two decade, India has achieved much more than what the world has expected. The quality of life has improved both in rural and urban set up. The reason of this high achievement is due to good policies and programmes started by government. Another reason being, common man has the access to education specifically at school level. But, the task of converting large huge human resource (16-24 years) into knowledge workers rests on the kind and quality of tertiary education being provided to the common man. If we look at the past decade (2001-2011) there is a phenomenal growth not only in number of institutes of higher education, but also in numbers of students enrolled in higher education. As per the latest figure given almost 19% of total population in the age group of 18-23 are studying in higher education in almost 712 universities, 36,671 colleges and 11,445 stand alone educational institutions in management, technical, medical and other professional institutes(Educational Statics at a Glance,MHRD,2014). Though, this number is well short of what is required as per the report of the National Knowledge Commission (2006). It is an estimate this percentage will touch to almost 30% by the end of 2020. With such a huge expansion what is required is the quantitative and qualitative expansion of resources-infrastructural, educational, technological human and more so economical. Government has opened the private sector and thinking on the lines of Foreign Direct Investment (FDI) in education sector. Several important bills related to higher education has been pending in the parliament like Foreign Education Institution Bill, National Accreditation Regulatory Authority for Higher Educational Institutions, Education Tribunals Bill, Higher education and Research Bill which will pave
new way to the higher education sector. Since equity, access and quality in higher education is the prime concern of the government, therefore government has realized that Information and Communication Technology(ICT) sector will play a crucial role in expanding higher education and that’s why it has launched nationwide centrally sponsored mission called National Mission on Education through Information and Communication Technology (NMEICT) and National Knowledge Network (NKN) through which universities are as well as colleges of higher education will be connected. National Knowledge Network will connect all the universities whereas along with other projects related to education like National Programme on Technology enhanced Learning (NPTEL), Eklavya (An open educational portal of Indian Institute of Bombay), National Repository of Open Educational Resource (NROER), etc has been launched to not only to connect the higher education institutes but also help the stakeholders to access the good quality educational resources material. Therefore, OER present a range of opportunities to institutions of higher education, teachers and learners of higher education as well as administrators of higher education. Unlimited Opportunities for Creating Open Education Resources In the recent years there is rapid technological advancement both in hardware as well as in software. We have move beyond classrooms, textbooks and face to face teaching. Today, we have classrooms which is almost virtual and education is available in the form of e-material i.e. education is deeply influenced by technology. Today’s learner is access to devices like I-Pad, smart phones, tablets coupled with 3G and 4G technologies.Learning is highly individualized and self-paced.Furthermore, the growing capabilities of the internet (site engines) has made knowledge explosion. But unfortunately, all this technological development has reached tofew whereas majority of the population has been deprived of it. This has been the case with Indian higher education also. Majority of the students who are studying in higher education are in colleges or in state universities. These colleges and universities face severe crunch of good teachers and good educational materials. Due to absence of both these factors students are the worst sufferers. Teachers and technological experts (both hardware and software professional) have unprecedented opportunitiesfor creation of the OER material. Apart from it there is whole lot of opportunities for other professionals’ right from technopedagogic specialist, editor, e-content developer to web developer. Recently in the report of Evaluation Committee on NMEICT it has been reported that NPTEL programme was launched in 2003 for creation of e-content for engineering, science and management studies. Initially it was envisage to create 990+ web and video courses for both undergraduate and post graduate courses but till date it was only 600 web courses were created and rest is in progress. Moreover, report also indicated that creation of e-content in other subjects and languages is most warranted. Therefore, in these areas too lot of scope and opportunities is there to design e-content. Massive Teacher Empowerment In the institutes of higher education there is growing usage of technology enabled teaching-learning.Learners are more familiar in usage of ICT in their learning process in comparison to teachers. Thisincreasing usage of ICT is changing the learning landscape rapidly. In this changing paradigm, there is growing need to bridge the gap between learners and teachers. Hence, there is a massive opportunity for the teachers to empower themselves in terms in order to get the full benefit of ICT based education scenario. Breaking Language Barriers India being a country with rich-multilingual diversity, it is commonly observed that a large percentage of population is more comfortable with their regional languages rather than English.Presently most of the educational material which has been developed in the English language.If we are developing the educational material only in one language it means we are depriving majority of our students from rich educational material. Therefore, it is important that the content in English language is also made available in regional languages either through translation or through creation in original language so
as to have wider impact. This provides immense opportunity for content developers to not only develop the content in other regional languages. Equalization of Opportunities through Outreach Programmes Indian higher education is suffering from inequality of learning opportunities. One hand we have group of learners who are aware of these resources and have access to all kind of technological facilities to access these educational resources. On other hand, there is large group of learners who neither have the awareness on the availability of free educational resources nor access to technological devices through which they access it. Therefore, it is indeed important through mission such as NMECIT and NKN one can reached to the unreached and publicise the importance of OER and orient the learnershow to utilize it for their benefits. This will help the in bridging of gaps between learners of “have” and “have not” and hence bring both the groups at par. Private-Initiative In last one decade there is an appreciable increase in the participation of private enterprises in education sector. Big corporate houses are investing huge amount of money in education. Many corporate houses like Wipro, HCL have set up their own universities. These corporate houses are also the leading IT sector companies of India which have global impact. Therefore, these companies can use their resources to create such educational materials which could be help to government institutions also. CHALLENGES FOR HIGHER EDUCATION This vertical expansion requires consolidation at horizontal level. But, presently higher education is facing several challenges like quality of higher education, faculty shortage; quality teachers, unable to keep pace with market demands, poor quality of curriculum, poor quality of research, poor quality of teaching etc. in majority of tertiary institutes. Recently, in a survey it was reported that many of our top institutes like IITs, IIMs not been in the top 200 list of universities in the world ranking. The reason is the teaching and researches in Indian universities are far below the standard of European or American and even among some of the Asian countries. If we compare it within our countries we will find wide disparities in terms of quality of teaching, quality of research etc. India has only fewer numbers of creditable institutes of higher education and it benefits fewer numbers of students. Since large force of human resource (youths) are studying in substandard institutions, transforming them into human capital is a challenge for Indian education system. Unfortunately, that advantage cannot be sustained unless we upgrade our education system. One area that is in desperate need of change is our higher education network. Networking of higher education institutes will help these institutes in more than one way. First, quality educational resources which is being created or stored in their repository is available free of cost. Secondly, it will improve the teaching learning standard in the universities or colleges which are suffering from poor quality of educational resources. Thirdly, it will also meet the paucity of teachers. Fourthly, it will enhance the capacity of students as well as teachers. Finally, it will enable students to compete globally. Transforming Higher Education Institutes into E-Hub Resources India has one of the biggest higher education systems in the world. But sorry state of affairs is that it has only a handful of quality institutes of higher education. Most of these are engineering, science or management institutes. The entire responsibility of creating these OER for other institute lies in the hand of these institutes. Among these are mostly IITs, IISc and few regional engineering colleges. One of the greatest challengeis to equip the faculty of the higher education and other human resources involved in it with necessary skills so that they are able to create e-resources within their institutes across the different courses and thus in the way make each institutes a hub of OER material.
Sustainability The development cost of open educational resources materials is high, but the much higher translatable, measurable rewards resulting from an expansion of the OER universe makes it a clear case for the government to ensure its sustainability. Initially, the government can create a grant for the generation and distribution of OER material to students and teachers from all over the country. Private industry should be the second major source of funding for developing OER on an ongoing basis since the industry stands to benefit immensely from the improved quality of education. Private industry should be offered tax credits in return for funding and developing OER content. These partnerships with private industry will help defray the costs of development of OER material. High Capital One of the biggest challenges related to OER is the infrastructural development which Indian higher education system is facing. In last one a decade huge amount of money is invested in higher education almost. Though, government of India is already sanctioned 4612crores in XI five year plans for the project NMEICT for development of e-learning material, installation of infrastructure, usage of space satellites, broadband connectivity etc to connect linkages institutions of higher education, development of repository resources like Shodhganga-an open repository of doctoral theses submitted by students in various universities in various disciplines, and INFLIBNET-Information and Library Network Centre, an autonomous Inter-University Centre of the University Grants Commission (UGC) of India. It is a major National Programme initiated by the UGC in March 1991 with its Head Quarters at Gujarat University Campus, Ahmadabad. Initially started as a project under the IUCAA, it became an independent Inter-University Centre in June 1996. INFLIBNET is involved in modernizing university libraries in India and connecting them as well as information centres in the country through a nation-wide high speed data network using the state-of-art technologies for the optimum utilization of information. It is set out to be a major player in promoting scholarly communication among academicians and researchers in India etc (Inflibnet, Home page, 2015). Beyond robust connectivity for access, infrastructure considerations for sustainable educational impact through OER must support a variety of requirements – for development and delivery of customized materials, providing tailored learning experiences, interoperable applications as well as evaluation and governance. Design and technology considerations often limit the productive use and adoption of OER, rendering tools incompatible with infrastructure, content to be trapped in repositories, and ultimately limiting adaptation and adoption as well as sustainability. This all require huge sums of money which in itself is challenged where the spending on higher education is on reducing trend. Developing Network-enabled Delivery Infrastructure A national backbone that provides high-bandwidth connections and advanced networking capabilities is critical for reliable access and quality. Connectivity with globalnetworks like Internet2 in the United States is also essential for the kind of collaborationand sharing that is recommended as an important element of the educational strategy.It is important to recognize that while the Internet and high-performance networks arelargely seen as relevant only in the context of advanced research, they are critical infrastructurefor educational quality and access. The government’s lead in developing thisinfrastructure, complemented by partnerships in the private sector to provide local andinstitutional infrastructure, will be an important determinant of progress. In recognitionof the urgency to develop an Indian Research and Education Network/Knowledge Network, the NKC has developed detailed recommendations whereby each connected institution will have at least of 1Gbps connectivity. This level of connectivitywill advance open education activities nationally, and ensure global connectivity as well. Open Access and Issue of Intellectual Property Rights Open Access is a term used to describe published academic papers, books, reports, and other periodicals that are electronically available to readers without financial or technological barriers. But, only a small proportion of the information generated
throughout the world is in the open access domain. Recent studies have shown that Open Access articles are cited 25-50% more than non-Open Access articles from the same journal and year. The researchers are benefited due to the Open Access policies as their research work gets widely disseminated and can be read by anyone with Internet access without any restriction. Similarly books, articles, and art forms will enjoy worldwide patronage when available in open access domain. In India, there are a large number of educational materials like books, journals etc are in electronic form but they are held in a few libraries scattered across the country and their content is not widely available to the scholars and students of our country. Open Access will drastically change the availability of these books and the knowledge contained in these texts. This will reduce the skewed nature of libraries in India. Open Access also help by allowing socially and economically disadvantaged individuals to access all the information if there is a free internet connection. But open access of the educational material also brings in the concept of intellectual property right. Normally it has been perceived, once the educational resources developed by the author and puts it into public domain in the form of OER, it means the author losses the ownership of the material. This fear resulted that many of the authors do not put their materials into OER. This is actually not so.The author retains the ownership of the material. In fact, OER is exploring new ways of creating, distributing and sharing educational materials. It is not become anti-copyright. Instead, itbuilds on different kinds of open licenses. The vision behind the creation of open licenses is a space in the internet world, a creative commons, where people can share and reuse copyright material without fear of being sued. This requires copyright owners to agree or give permission for their material to be shared through a generic license that gives permission in advance. Thus; it is no way an infringement into the intellectual property rights. Globalization The globalization of the world’s economies is leading to increased permeability of national educational boundaries as well as greater emphasis on the internationalization of curricula. The internationalization of higher education seems to be a double-edged phenomenon, inducing growingcollaboration and growing competition among countries and among institutional providers. The OECD’s Education Policy Analysis (2006a) reports that cross-border higher education has grown significantly over the past decades and this is expected to continue. This growth has been driven by several interlinked forces: greater mobility of skilled workers in an increasingly knowledge-based economy; the drive to develop export industries and expand international collaboration in higher education; the need to build a more educated workforce in sending countries, where study options may be limited; the desire of students andacademics to have international experience and promote mutual understanding; and the decline in the cost of transport and communications. According to Education Policy Analysis, this growth has, in turn, fuelledgreater competition for students and academics between countries and higher education institutions. At the same time, domestic higher education systems increasingly face international pressures and competition, under voluntary harmonization agendas under the pressures of international comparison, manifested byquality labels, ranking efforts and consumer choice; or owing to theincreasing frequency of partnerships and recognition agreements. Like theolder established research universities, higher education institutions of alltypes increasingly see themselves not simply in terms of their domestic roleor agenda but as actors in a global market.Through greater collaboration between higher educational institutionsaround the world and enhanced reuse of learning materials, both in theiroriginal form or translated or otherwise adapted, the phenomenon of OERcontributes to the globalization of higher education. At the same time itincreases competition between institutions by making teaching content and processes within individual institutions visible to a potentially worldwide audience. Prospective students
can be better informed not only by studyingthe general offer from institutions but also by viewing the curriculum andlearning materials, and sometimes videotaped lectures, of individualdepartments. Demography India has one of the largest populations in the age group of 18-25 years andincreasingly concerned about the impact of demographic factors on higher education. With the increasing participations of this age group in higher education, the demand for variety of courses, more flexible delivery and tailor-made programmes are required. Moreover, longer working lives with more career changes, and the possible growing enrolment of learners beyond the age group of 25 years in higher education, might indeed be a transformative force in the medium run. Most countries need to increase participation in higher education, but higher education institutions generally have not so far been able to meet this challenge. OER initiatives might serve higher educational institutions as vehicles for outreach to non-traditional groups of students, widening participation in higher education, and provide learning opportunities for those unable to use more traditional offerings or who are not parts of the traditional groups of higher education entrants. Such initiatives can bridge the gap between non-formal, informal and formal learning. At the same time OER can be used by professionals for in-service training and home study by older people, opening new lifelong learning strategies as a means of tackling the challenges of aging societies. CONCLUSION OER movement is just started in India. The creation of open education materials in various disciplines by the experts from the institutions of repute will help the teachers to access these materials at the click of the mouse which will help them in classroom teaching. Moreover, it is more beneficial for the students as they will get the opportunity to hear the lectures from the teachers of international repute. Open educational resources which are generally made web based are interactive in nature therefore it helps the learner to interact didactically with the teachers and thus clarify the doubts instantaneously. Moreover, it could be accessed from any remote area as it requires internet connectivity. The additional benefit is that one can register oneself in these open education resources portals for the different online courses (subject to availability of course) and thus get additional certificates. It will be boon to those educational institutions which lacks good library resources. Through NMEICT and NKN colleges and universities can connect themselves and avail the facilities for their students and teachers. The effort and support from government side is visible by launching NMEICT and NKN along with allocating a substantial budget for it. Initiative from private enterprises and corporate houses is what needed by the government to support and sustained its efforts of making India hub of open educational resources. The biggest challenge for the academic fraternity is to create open educational material for diverse demographical population in diverse vernacular languages as majority of our students belong to different vernacular medium. Another challenge is to make different stakeholders aware of the different open educational resources available to them free of cost. Last the learners and teachers need to utilize it to the optimum level. Since, globalization has transform the education and its system therefore, it is indeed necessary that we teachers collaborate, adapt and adopt, translate the educational resources with the external world as it is very difficult to create all kind of materials. In all, one can say success of OER movement means success for higher education.
BIODATA and CONTACT ADDRESSES of the AUTHOR Dr. Indrajeet DUTTA is working as an Assistant Professor in the constituent college of the Maulana Azad National Urdu University, Hyderabad, India. He has just been awarded Doctoral Degree on Educational Psychology from Guru Gobind Singh Indraprastha University, New Delhi India on Parenting Style of Indian parents. He has almost ten years of experience in teaching to undergraduate and post graduate students. His area of research and interest is open and distance learning; ICT based pedagogical practices in school and teacher education, social psychology of parenting practices of parents and education evaluation at school, higher and teacher education. Assist. Prof. Dr. Indrajeet DUTTA Maulana Azad National Urdu University, School of Education & Training College of Teacher Education MHK ITC Campus Bhopal-462001 Phone: +917552744515 Email: [email protected]
, [email protected]
REFERENCES Atkins,D.E., Brown,J.S., & Hammond, A.L. (2007) A Review of the Open Educational Resources (OER) Movement: Achievements, Challenges, and New Opportunities, California, USA. Bisell,A.(2007). Some guiding principles for legal and technical interoperability in OER. In proceedings of Open Education, Localizing and learning, Logan, Utah State University, USA. COL and UNESCO (2011) Guidelines for Open Educational Resources (OER) in Higher Education, Commonwealth of learning, Canada. COL and UNESCO (2012) Report on Survey on Governments’ Open Educational Resources (OER) Policies, Commonwealth of learning, Canada downloads/documents/wg_open_course.pdf. Gani, A.(2010).Mapping open educational resources for access and equity in higher education in India. Paper presented in Pan-Conference Commonwealth Forum of Open Learning 24th-28th November Kochi, India. Retrieved http://oldwebsite.col.org/pcf6/fp/zIN1110.doc. Inflibnet (2015) Home page of Inflibnet Retrieved from http://www.inflibnet.ac.in/ on 22nd July 2015. Kanwar, A. and Trumbic, S. U. (Ed.)(2011) A Basic Guide to Open Educational Resources Commonwealth of Learning, Canada MHRD (2011) Report of the Evaluation committee on NMEICT, GOI, New Delhi. MHRD (2014) NMEICT: Document on Achievement http://www.sakshat.ac.in/Document/Achievements.pdf NKC (2007). Report of the working group on open access and open educational resources. New Delhi, India: National Knowledge Commission, Government of India. Retrieved October, 2013, from http://knowledgecommission.gov.in/ NKN (2015). Home page of National Knowledge Network http://nkn.in/connectedinstitutes-nmeict.php Retrieved on 22nd July 2015 OECD (2006a). Education Policy Analysis: Focus on Higher Education Edition, OECD, Paris OECD (2007) Giving Knowledge for Free: The emergence of open educational resources. OECD publication, Paris, France
Smith, M.S. & Casserly, C.M. (2006).The promise of open educational resources. Change, 38(5).8-17. UNESCO (2012). What are Open Educational Resources? http://www.unesco.org/new/en/communication-and-information/access-toknowledge/open-educational-resources/what-are-open-educational-resourcesoers/ Vijay Kumar, M.S. (2009). Open Educational Resources in India’s national Development, Open Learning: The Journal of Open, Distance and e-Learning, 24:1, 77-84 DOI: 10.1080/02680510802627860 William and Flora Hewlett Foundation. (2008). Open educational resources (OER) – makinghigh quality educational content and tools freely available on the web. Retrieved October,2013, from http://www.hewlett.org/Programs/Education/OER/openEdResources.htm
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Article 8
CRITICAL COMPONENTS OF ONLINE LEARNING READINESS AND THEIR RELATIONSHIPS WITH LEARNER ACHIEVEMENT Dr. Harun CIGDEM Department of Computer Technologies Land Forces Non-Commissioned Officer Vocational College, Balikesir, TURKEY Dr. Mustafa OZTURK School of Foreign Languages Hacettepe University, Ankara, TURKEY ABSTRACT This study aimed to examine the relationship between certain factors of online learning readiness and learners’ end-of-course achievements. The study was conducted at a twoyear post-secondary Turkish military school within the scope of the course titled Computer Literacy, which was designed and implemented in a blended way. The data were collected from 155 post-secondary military students through an online questionnaire. Three sub-scales of Hung et al.’s Online Learning Readiness Scale were used to collect the data during the first two weeks of the course. Descriptive and inferential statistics, such as Pearson correlation coefficients and linear regression analyses were performed to analyze the data. The descriptive results of the study indicated that students’ motivation for online learning was higher than both their computer/Internet self-efficacy and their orientations to self-directed learning. The inferential results revealed that the students’ end-of-course grades had significantly positive relationships with their computer/Internet self-efficacy and self-directed learning orientations. Finally, the students’ self-direction towards online learning appeared to be the strongest predictor of their achievements within the course; whereas computer/Internet self-efficacy and motivation for learning did not predict the learner achievement significantly. Keywords: Online learning readiness, learner achievement, blended learning, computer literacy INTRODUCTION In this day and age, technology affects almost every aspect of our lives and continually change the way we learn, teach, and work on the information. With the help of the Internet technologies, e-learning or online learning that makes new instructional practices convenient for students, which was not possible in traditional classroom settings due to time and space constraints, has become a noteworthy method (Cigdem, 2015). Online learning can be described as an action of delivering course materials such as lecture notes, videos, exams, and slides to the learners by devices using Internet technology, although “e-learning”, and “distance education” have also been used. Demiray (2011) has emphasized the importance of online learning and online learning tools, for making better learning and teaching in higher education. Online learning has become more and more popular as online technologies and improved educational pedagogy have supplied educators with constantly enlarging opportunities to build high quality, efficient, rigorous, and valuable instructive access to constantly increasing numbers of students. There are many existing online learning tools such as Atutor, Blackboard, Claroline, CanvasLMS and MOODLE that offer many educational tools. 98
MOODLE (Modular Object-Oriented Dynamic Learning Environment) is one of the learning management systems (LMSs) which have been used most. MOODLE serves as a free open source platform for LMSs and offers an environment that allows sharing course content to support conventional instruction. It is flexible since it can be accessed anywhere as long as student has a personal device with Internet connection such as smart phone, tablet or computer. In a flexible learning environment, the content of a course is easier to access for learners and learners are able to study at their own speed via the Web, and this plays an important role on their achievement (Chen et al., 2009; Liao, 2007). As a result, educational institutions have assigned great efforts to develop blended learning environments, which stand for the use of key features belonging to face to face and online instructional methods for learners to share and obtain information (Akkoyunlu & Soylu, 2008; Cigdem & Topcu, 2013; Lynch & Dembo, 2004; Osguthorpe & Graham 2003; Owston, York, & Murtha, 2013). Many studies have found the positive results of blended learning, and also a positive impact of blended learning on student achievement has been shown (Lee, Yoon, & Lee 2009). Escobar-Rodriguez and Mongo-Lozano (2012) claimed that learning–teaching process has become better by using MOODLE. Martín-Blas and Serrano-Fernández (2009) used MOODLE to prepare more interesting activities thus making the learning process friendlier and more interesting for their learners. In the use of MOODLE there are some difficulties appeared as a result of the lack of capabilities and skills for its use, that can reduce these results or even turn down them (Paragia, Paragin, Jipa, Savu, & Dumitrescu, 2011). Online learning and MOODLE have been established in a number of faculties. Still, many universities fail to take benefits of such attempts and face difficulties in achieving effective strategies, as well as in delivery, efficiency, and acceptance of online courses (Park, 2009; Wang & Wang, 2009).. Learners are considered to be the most important elements of online learning processes (Aydin & Tasci, 2005). Learner needs and skills should be central while designing and developing blended courses (Sahin & Shelley, 2008), when a course become unsuccesful to meet learner hopes and needs it may result with reducing levels of learner participation and motivation (Bradford, 2011) However, one of the key factors shaping the effectiveness of online learning environments is readiness factor (Artino, 2009; Galy, Downey & Johnson, 2011; Kruger-Ross & Waters, 2013). Yukselturk (2009) found that online learning readiness was one of the strongest predictors of satisfaction for students in online courses. Online learning readiness plays a significant role to encourage learners to be involved in online learning activities. So readiness for online learning readiness can be perceived as a crucial factor to be taken into account in any development of online learning environments (Ilgaz & Gulbahar, 2015). Although research studies in online learning has risen significantly in the last years, much is still unknown regarding factors influencing learner achievement in these online learning environments utilizing LMSs. There are many unanswered questions. One of these questions is which the critical factors affect learner achievement in online mode of blended courses. In this sense, learners’ online learning readiness along with online contents must be reviewed carefully in order to improve the quality of those attempts, and schools are to consider improving learners’ readiness to use online learning systems more efficiently (Cigdem & Yildirim, 2014; Wang et al. 2009). BACKGROUND OF THE STUDY Online learning readiness can be described in three major features: choices for online learning as opposed to face-to-face learning instructions; competence and confidence in using the technological tools; and ability to learn seperately (Tang & Lim, 2013). According to Guglielmino and Guglielmino (2003), online learning readiness can be estimated by evaluating a user’s competency in using technological tools (Schreurs, Sammour, & Ehlers, 2008). Within this framework, McVay (2001) focused on student behaviors and attitudes to determine readiness, and Hung et al. (2010) added some new 99
dimensions to the readiness concept such as computer/Internet self-efficacy, learner control, motivation for learning, online communication self-efficacy and self-directed learning. Bearing in mind that the learners’ pre-existing readiness for online learning might influence their cognitions and actions regarding the online mode of blended learning environments, it is essential to understand their online learning readiness. Therefore, in this research, learners’ online learning readiness and its effects on blended learning outcomes were investigated. Within this framework, these three major components were discussed and examined in this study: self-directed learning, computer/Internet selfefficacy, and motivation for learning. To start with the first one, Knowles (1975) defines self-directed learning as “a process in which individuals take the initiative, with or without the help of others, in diagnosing their learning needs, formulating goals, identifying human and material resources, choosing and implementing appropriate learning strategies, and evaluating learning outcomes” (p. 18). In this regard, self-directed learning has been characterized as an active and constructive process by which learners make plans and set objectives prior to learning, monitor their own progress during learning, and subsequently self-evaluate their achievement after learning (Pintrich, 2000; Zimmerman, 2008). According to Zimmerman (2002) self-regulated learning helps students learn more effectively and performance better. Together with the increase in online enrollments, academicians have started to show an interest in students’ academic motivation and self-regulation in online courses (Artino, 2008; Dabbagh & Kitsantas, 2004). Students should manage time and information effectively to be more active and responsible in their learning, complete work on time, and participate in class works in online learning environments (Hung et al., 2010). Researchers have reached a consensus that students’ self-directed learning readiness has been positively associated with students’ readiness for online study (Demir Kaymak & Horzum, 2013) and achievement in online courses (Artino, 2008; 2009a; Lee, Shen, & Tsai, 2008; Liaw & Huang, 2013; Paechter, Maier & Macher, 2010; Pintrich, 2000; Puzziferro, 2008; Wang, Shannon & Ross, 2013; Yukselturk & Bulut, 2007). There are also studies disconfirming the significant relationship between academic achievement and self-regulation (Cigdem, 2015; Ergul, 2004). As for the second component, motivation for learning encompasses learners’ all kinds of movements towards and engagements with learning activities. As Wolters (2010) clarifies, the primary factor that facilitates students’ persistence in their academic tasks is their motivational beliefs. Motivated learners are attributed to have low latency and high perseverance about task engagement (Artino & Stephens, 2009), and therefore, their motivational orientation towards a task has significant influences on their performances (Hung et al. 2010) and facilitate their efforts to get higher grades, awards, or prizes (Baeten, et al. 2010; Hung et al. 2010; Saadé, He, & Kira 2007). Considering this chain, learners’ motivational beliefs and self-regulatory behaviors would be related to the nature of an online course and how that course relates to them personally (Artino, 2009b). With the rising of online modes of learning, educators and researchers have come to figure out that self-regulated and highly-motivated learners are most likely to be successful in blended learning. Since online learning appears as a sort of studentcentered environment, highly-motivated students possibly achieve better outcomes (Baeten, Kyndt, Struyven, & Dochy, 2010). The last component, self-efficacy is defined as “people’s judgments of their capabilities to organize and execute courses of action required to attain designated types of performances” (Bandura 1986, p. 391). In this context, users’ beliefs about their abilities to use a technological tool to accomplish a specific task is known to be computer selfefficacy (Compeau & Higgins, 1995), which operates at two distinct levels: general computing level and specific application level (Yi & Hwang, 2003) such as the Internet 100
use. It is claimed that task-specific self-efficacy might be used as a reliable indicator predicting the task performance (Bandura 1986; Zimmerman 2000). That is why selfefficacy is critical to be identified before starting to implement a new technology. Learners with higher self-efficacy towards learning through online courses are usually considered to be more motivated, more persistent and better achievers in such courses (Ergul, 2004; Linnenbrink & Pintrich, 2002; Lynch & Dembo, 2004). Moreover, learners with lower self-efficacy are thought to hold negative perceptions related to requested tasks, consider the tasks not as challenging but threatening and feel confused or even lost when they meet new technologies (Simsek, 2011). Technical skills including computers and the Internet have a connection with learners’ achievement and performance in online learning environments (Hung et al., 2010). Although, learners’ self-efficacy regarding online learning is claimed to be a key predictor of their achievement (Cigdem, 2015), some conflicting research indicated that selfefficacy of online technologies was either a poor predictor of success in online courses (DeTure, 2004) or was not correlated with achievement at all (Puzziferro, 2008). Nevertheless, a number of studies emphasized the role of self-efficacy in online learning achievements. For instance, Joo, Bong, and Choi (2000) examined the relationship between self-efficacy and learners’ achievement in a web-based instruction and found that technological self-efficacy is a significant variable that determining learners’ achievement in distance education. Similarly, Wang and Newlin (2002) concluded that performance in an online course can be predicted from self-efficacy for online technologies. In Lynch and Dembo’s (2004) study, self-efficacy, among other factors, was one of two main predictors of learners’ performance in a blended learning course. In another study, Bell and Akroyd (2006) found that learners’ self-efficacy was one of the primary predictors of achievement. It is important to determine the factors that affect achievement of learners at blended learning environment. Few studies exist in the literature about the influences of online learning readiness and possible factors that influence the outputs of online learning (Keramati, Afshari-Mofrad & Kamrani, 2011). Blended Computer Literacy course achievement is based on students’ performances. Therefore, this study is conducted to determine the relationship of online learning readiness factors and learners’ achievement in blended Computer Literacy course that using MOODLE LMS. Putting all the critical components portrayed above together, this study aimed to answer the following research questions: What are military vocational college students’ perceptions about the following dimensions of online learning readiness: (a) computer/internet self-efficacy, (b) self-directed learning, and (c) motivation for learning? Is there any significant correlation between learner achievement and the three dimensions (computer/internet self-efficacy, self-directed learning, and motivation for learning)? Can learner achievement be predicted from computer/internet self-efficacy, selfdirected learning, and motivation for learning in a blended Computer Literacy course? METHODOLOGY Research Context This study was conducted at a two-year post-secondary Turkish military school within the scope of the course titled Computer Literacy, which was designed and implemented in a blended way. Course materials were deployed over the intranet on MOODLE. Videos related to word processing software and spreadsheet were produced by the lecturer. Students were able to review the videos at anytime and anywhere within the college campus. The course lasted 15 weeks each of which included a 100-minute face-toface session. In each face-to-face session, the content of the week was presented to the 101
students and the students were left to practice word processing and spreadsheet activities in computer laboratories. Students were allowed to read the content, download the resources such as lecture notes, videos, slides and journal papers, and follow the instructions to complete activities of the week at anytime they want. Screenshot example of the course website is displayed in Figure 1.
Figure: 1 A Screenshot of Computer Literacy Website Participants As one of the researchers works as an instructor who gives the Computer Literacy course in the research context, convenient sampling strategy was adopted and 155 postsecondary military students were included as the participants of the study. All of the participants were male staying in the college campus as it was a military school. 60% of them were studying at the department of Electronics and Communication Technologies and the rest (40%) at the department of Automotive Technologies. A great majority of the participants graduated from vocational high schools (n=126), and the others from general high schools (n=29). Finally, most of the participants did not have a prior experience on web-based education (n=120), while the remains had (n=35). As the study was carried out in a military school with male students, the applicability and generalizability of its findings are limited (see Table 1 for the demographic information of the participants). Table: 1 Demographics Background Dimensions Academic program
Automotive Technologies Electronics and Communication Technologies
Type of High School
Vocational High School General School (non-vocational)
Owning a computer
Web-based education experience
Data Collection Tools The data were collected through an online questionnaire consisting of two sections: (a) items to gather demographic information about the participants and (b) items aimed to measure the participants’ online learning readiness. The second section included items adopted from Hung et al.’s (2010) Online Learning Readiness Scale (OLRS) which was translated into Turkish by Yurdugul and Alsancak Sarıkaya (2013). Meaningful work on developing and testing online learning readiness scales has been done. Hung et al. (2010) declared a belief that McVay’s (2000) questionnaire was without an emphasis on selfdirected learning, motivation for learning, and learner control. So, Hung et al. (2010) advanced their version of the OLRS to include these factors and other factors of computer and Internet self-efficacy and online communication self-efficacy. They tested the internal consistency and construct validity as well as confirming the factor structure. All factors displayed adequate reliability and discriminant validity. Although the original scale included five dimensions (computer/Internet self-efficacy, self-directed learning, motivation for learning, learner control, and online communication self-efficacy), the first three dimensions were used in the current study with the purpose of measuring military students’ readiness for online learning. In order to ensure that the items constitute a reliable scale, reliability analysis was performed for each dimension and Cronbach’s alpha levels ranged from .75 to .80 (see Table 2 for the alpha values). Table: 2 Cronbach’s Alpha Coefficients Hung et al. Items (2010)
Dimensions Computer/Internet efficacy Self-directed learning Motivation for learning
RESULTS In relation to the first research question investigating whether the participants are ready for online learning, the findings obtained from descriptive analyses indicated that students’ motivation for learning ( M=4.15) is higher than both their computer selfefficacy (M=3.55) and their self-directed learning inclinations (M=3.82) (see Table 3). Table: 3 Descriptive Results Dimensions Computer/Internet self-efficacy Self-directed learning Motivation for learning
155 155 155
3.55 3.82 4.15
1.0 .67 .69
In order to see the correlations between the factors of online learning readiness and the participants’ course grades, Pearson correlation coefficients were conducted. At this point, a p value of less than .008 (.05 / 6 = .008) was required for significance by using the Bonferroni approach to control Type I error across the 6 correlations. The correlational analyses revealed that the participants’ course grades had significantly positive relationships with computer/Internet self-efficacy, r(153)=.21, p<.001, and selfdirected learning, r(153)=.32, p<.001. These findings could mean that as the participants’ self-efficacy and self-directed learning orientations tend to increase, their achievements in a blended course would also increase (see Table 4). 103
Table: 4 Correlations between Course Grades and Online Readiness Factors Variable
Computer/Internet self-efficacy Self-Directed Learning Motivation For Learning
.21 .32 .16
.011 . 001 . 050
155 155 155
As for the third research question, regression analysis conducted to see whether learner achievement was predicted from the factors of online learning readiness put forward a significant result indicating that course grades, which means meeting all the requirements of the course and achieving the tests, were predicted only from the following factor of online learning readiness: self-directed learning, R2=.104, F(3,151) =5.873, p<.005 (see Table 5). The findings could mean that it is hard to explain learner achievement through computer/Internet self-efficacy and motivation for learning as they did not seem to be significant predictors of the Computer Literacy course grades of military students. However, students’ inclinations towards self-directed learning happened to significantly contribute to students’ course grades in the Computer Literacy course, as it appeared as the most important predictor in the current study. Table: 5 Regression Analysis Results Variables Computer/Internet self-efficacy Self-directed learning Motivation for learning
1.408 8.030 -.280
1.625 2.711 2.432
.075 .287 -.010
.867 2.963 -.115
.388 .004 .908
DISCUSSION AND CONCLUSION On the basis of the descriptive results of the study, military students seemed to be highly motivated to learn thorough a blended design, as they rated the items pertaining to motivation for learning more positively than the other two dimensions. This finding was consistent with the related literature (Cigdem & Yildirim, 2014; Hung et al. 2010; Tang & Lim, 2013) putting forward that students are ready for online learning processes. However, in Hung et al.’s study (2010), the highest ratings were given by the participants to the dimension of computer/Internet self-efficacy. In the current study, it was seen that the participants could carry out their own study plan and have expectations from their learning to some extend. Additionally, they could comfortably use the Internet as well as online learning software. They also seemed to be confident in performing the basic functions of office programs. In order to design effective blended learning environments, it is crucial to examine what would assist students’ learning and achievement as well as the characteristics of successful learners (Yukselturk & Bulut, 2007). With the purpose of investigating what factors of online learning readiness are able to predict learner achievement in a blended computer literacy course, three dimensions were inquired within the scope this study: self-efficacy, self-directed learning, and motivation factors. Looking into the correlational analyses between the factors of online learning readiness and learner achievement, it was seen that computer literacy course grades were 104
significantly and positively correlated with self-efficacy and self-directed learning factors. As new generations of online learning technologies, such as videos, podcasts, and online quizzes enter educational environments, being ready to use them for learning purposes becomes a valuable skill because it means students can try different tools, and choose which ones fit their needs best. The results of regression analysis revealed that learner’s self-direction was the strongest significant predictor of achievement in the Computer Literacy course. This point is similar to the findings of Artino (2008; 2009), Lee, Shen, and Tsai (2008), Liaw and Huang (2013), Paechter et al. (2010), Pintrich (2000), Puzziferro (2008), Wang, Shannon, and Ross (2013), and Yukselturk and Bulut (2007). In this regard, students with higher levels of self-direction towards the online mode of a blended learning course tend to have better learning achievements. There are also studies (Cigdem, 2015; Ergul, 2004) contradicting with this point as they did not claim learners’ self-direction as an important predictor of achievement. As a suggestion, learners might improve self-directed learning skills, especially for online mode of blended learning environment. It is also recommended that learners need full support towards the use of LMS and manage their time for the LMS participation. Another striking point derived from the regression analysis is that self-efficacy and was not a significant predictor of learners’ achievement. This finding justifies DeTure’s (2004) and Puzziferro’s (2008) studies. As computer and the Internet technologies have been upgraded over time, problems related to the use of such technologies seem to be declining. Because of the continuing spread of technology usage across the educational spectrum, today’s students enter colleges with a greater computer experience than their predecessors. This point might be explained through such developments. At the first weeks of the online learning process, learners should have known to how online learning environment suitable their needs and also, they should have learnt what properties it has. In addition to previous statements, LMS should be well performed and have friendlier use. Also, the network technology is highly important if we implement such systems. If LMS server has a breakdown, this will cause a problem to learner participation in online mode of blended class. This issue will diminish learner motivation on online learning participation. Hence, it will have a direct impact on learner’ achievement. Therefore, for future research it should be discussed on usability of LMS and how to improve the implementation of current system in higher education. BIODATA and CONTACT ADDRESSES of the AUTHORS Dr. Harun CIGDEM holds a bachelor’s degree in Computer Education and Instructional Technologies and a master’s degree in Educational Sciences from Uludag University. He received his PhD in Computer Education and Instructional Technologies from Anadolu University in 2012. He is the administrator of Course Portal of Non-Commisioned Officer Vocational College. He teaches operating systems, computer networks, and system and network administration courses in the college. His research interests involve instructional design, elearning, e-assessment and self-regulation. Harun CIGDEM, Ph.D. Turkis Land Forces Noncommissioned Officer School Department of Computer Technologies Cayirhisar, Balıkesir, TURKEY Phone: +902662212350; +90 533 315 16 00 Email: [email protected]
Dr. Mustafa OZTURK holds a bachelor’s degree in Foreign Language Education and a master’s degree in Educational Sciences from Middle East Technical University. In 2007, he completed a non-degree postgraduate study in Learning, Learning Environments and Educational Systems in University of Turku, Finland. He received his PhD in Curriculum and Instruction from Middle East Technical University in 2014. He is currently conducting a postdoctoral research at Columbia University Teachers College. His research interests lie in the areas of curriculum studies, teacher education, language teaching, instructional design, e-learning, and education for sustainable development. Mustafa OZTURK, Ph.D. Hacettepe University, School of Foreign Languages, Department of Basic English Beytepe Campus, Cankaya, Ankara, TURKEY Phone: +903122978085 Fax: +903122992158 Email: [email protected]
REFERENCES Akkoyunlu, B., & Soylu, M. Y. (2008). A study of student's perceptions in a blended learning environment based on different learning styles. Educational Technology & Society, 11 (1), 183-193. Artino, A. R. (2008). Motivational beliefs and perceptions of instructional quality: Predicting satisfaction with online training. Journal of Computer Assisted Learning, 24, 260−270 Artino, A. R. (2009a). Online learning: Are subjective perceptions of instructional context related to academic success? Internet and Higher Education, 12, 117-125. Artino, A.R. (2009b). Think, feel, act: motivational and emotional influences on military students’ online academic success. J Comput High Educ Artino, A. R., Jr., & Stephens, J. M. (2009). Beyond grades in online learning: Adaptive profiles of academic self-regulation among Naval Academy undergraduates. Journal of Advanced Academics, 20(4), 568-601. Aydin, C. H. & Tasci, D. (2005). Measuring readiness for e-Learning: Reflections from an emerging country. Educational Technology & Society, 8 (4), 244-257. Baeten, M., Kyndt, E., Struyven, K. & Dochy, F. (2010). Using student-centred learning environments to stimulate deep approaches to learning: factors encouraging or discouraging their effectiveness. Educational Research Review, 5(3), 243–260. Bandura, A. (1986). Social foundations of thought and action; a social cognitive theory . Prentice Hall. Eaglewood Cliffs. NJ. Bell, P. D., & Akroyd, D. (2006). Can factors related to self-regulated learning predict learning achievement in undergraduate asynchronous Web-based courses? International Journal of Instructional Technology and Distance Learning, 3 (10), 516. Bradford, G. R. (2011). A relationship study of student satisfaction with learning online and cognitive load: Initial results. Internet and Higher Education, 14(4), 217–226. Chen, S. W., Stocker, J., Wang, R. H., Chung, Y. C. & Chen, M. F. (2009). Evaluation of selfregulatory online learning in a blended course for post-registration nursing students in Taiwan. Nurse Education Today, 29 (2009), 704–709. Cigdem, H. (2015). How does self-regulation affect computer-programming achievement in a blended context? Contemporary Educational Technology, 6 (1), 19-37 106
Cigdem, H. & Topcu, A. (2013). Students’ perception of e-learning in the technical vocational school. Science Journal of Turkish Military Academy, 23(2), 1-19. Cigdem, H. & Yildirim, O.G. (2014). Effects of students’ characteristics on online learning readiness: a vocational college example. Turkish Online Journal of Distance Education-TOJDE, 15(3), 80-93. Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure initial test. MIS Quarterly, 19(2), 189–211. Dabbagh, N., & Kitsantas, A. (2004). Supporting self-regulation in student-centered webbased learning environments. International Journal on E-Learning, 3(1), 40–47. Demir Kaymak, Z.& Horzum, M. B. (2013). Relationship between online learning readiness and structure and interaction of online learning students. Educational Sciences: Theory and Practice 13 (3), 1792–1797. Demiray, U. (2011). Distance education and eLearning practices: In Turkey and Eastern countries. eLearning Papers, No. 24, April. Retrieved from http://www.openeducationeuropa.eu/hu/download/file/fid/22301 DeTure, M. (2004). Cognitive style and self-efficacy: Predicting student success in online distance education. American Journal of Distance Education, 18(1), 21-38. Ergul , H. (2004). Relationship between student characteristics and academic achievement in distance education and application on students of Anadolu University. Turkish Online Journal of Distance Education-TOJDE, 5(2). Escobar-Rodriguez, T., & Monge-Lozano, P. (2012). The acceptance of Moodle technology by business administration students. Computers & Education, 58, 1085–1093. Galy, E., Downey, C., & Jhonson, J. (2011). The effect of using e-learning tools in online and campus-based classrooms on student performance. Journal of Information Technology Education, 10, 209-230. Guglielmino, P. & Guglielmino, L. (2003). Are your learners ready for e-learning? In G. Piskurich (Ed.), The AMA handbook of e-learning. New York: American Management Association. Hung, M., Chou, C., Chen, C. & Own, Z. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55, 1080– 1090. Ilgaz, H. & Gulbahar, Y. (2015). A Snapshot of Online Learners: e-Readiness, eSatisfaction and Expectations. International Review of Research in Open and Distributed Learning, 16 (2), 171-187. Joo, Y., M. Bong, and H. Choi. 2000. Self-efficacy for self-regulated learning, academic self-efficacy, and Internet self-efficacy in Web-based instruction. Educational Technology Research and Development 48 (2), 5–17. Keramati, A., Afshari-Mofrad, M. & Kamrani, A. (2011). The role of readiness factors in elearning outcomes: An empirical study. Computers & Education, 57(3), 1919-1929. Knowles, M. (1975). Self-directed learning: A guide for learners and teachers. New York: Association Press. Kruger-Ross, M.J. & Waters, R.D. (2013). Predicting online learning success: Applying the situational theory of publics to the virtual classroom. Computers & Education, 53, 761–774. Lee, B. C., J. O. Yoon, & I. Lee. 2009. ‘‘Learners’ Acceptance of E-Learning in South Korea: Theories and Results.’’ Computers and Education 53: 13201329. Lee, T.H., Shen, P.D., & Tsai, C.W. (2010). Enhance students’ computing skills via webmediated self-regulated learning with feedback in blended environment. International Journal of Technology and Human Interaction, 6(1), 15–32. 107
Liao, Y. K. C. (2007). Effects of computer-assisted instruction on students’ achievement in Taiwan: a meta-analysis. Computers & Education 48, 216–233. Liaw, S. S. & Huang, H.M. (2013). Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments. Computers & Education 60 (2013), 14-24. Linnenbrink, E. A. & Pintrich, P. R. (2002). Motivation as an enabler for academic success. The School Psychology Review 31(3), 313 – 327. Lynch, R. & Dembo, M. (2004). Online learning in a blended learning context. International Review of Research in Open and Distance Learning, 5(2), Retrieved February 25, 2014 from http://www.irrodl.org/index.php/irrodl/article/view/189/271 Martín-Blas, T., & Serrano-Fernández, A. (2009). The role of new technologies in the learning process: Moodle as a teaching tool in Physics. Computers & Education, 52, 35–44. McVay, M. (2001). How to be a successful distance learning student: Learning on the Internet. New York: Prentice Hall. Osguthorpe, R. T., & Graham, C. R. (2003). Blended learning systems: Definitions and directions. Quarterly Review of Distance Education, 4(3), 227–234. Owston, R., York, D., & Murtha, S. (2013). Student perceptions and achievement in a university blended learning strategic initiative. Internet and Higher Education, 18, 38-46. Paechter, M., Maier, B., & Macher, D. (2010). Students' expectations of and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computers & Education, 54(1), 222–229. Paragia, F., Paragin, S., Jipa, A., Savu, T., & Dumitrescu, A. (2011). The benefits of using MOODLE in teacher training in Romania. Procedia Social and Behavioural Sciences, 15, 1135–1139. Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Educational Technology & Society, 12(3), 150–162. Pintrich, P. R. (2000). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95, 667–686. Puzziferro, M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. American Journal of Distance Education, 22(2), 72-89. Saadé, R. G., He, X. & Kira, D. (2007). Exploring dimensions to online learning. Computers in Human Behavior, 23(4), 1721–1739. Sahin, I., & Shelley, M. (2008). Considering students’ perceptions: The distance education student satisfaction model. Educational Technology & Society, 11(3), 216–223. Schreurs, J., Sammour, G. & Ehlers, U. (2008). E-learning Readiness Analysis (ERA): an ehealth case study of e-learning Readiness. Int. J. Knowledge and Learning, 4 (5), 496-508. Simsek, A. (2011). The relationship between computer anxiety and computer selfefficacy. Contemporary Educational Technology, 2(3), 177-187. Tang, S. F. & Lim, C. L. (2013). Undergraduate students’ readiness in e-learning: a study at the business school in a Malaysian private university. International Journal of Management & Information Technology, 4 (2). 198-204.
Wang, A.T. & Newlin, M.H. (2002). Online lectures: Benefits for the virtual classroom. THE Journal, 29, 17-22. Wang, C., Shannon, D., & Ross, M. (2013). Students' Characteristics, Self-Regulated Learning, Technology, Self-Efficacy, and Course Outcomes in Online Learning. Distance Education, 34(3), 302-323. Wang, W.-T. & Wang, C.-C. (2009). An empirical study of instructor adoption of webbased learning systems. Computers & Education, 53, 761–774. Wang, Q., Zhu, Z., Chen, L. & Yan, H. (2009). E-Learning in China. Campus-Wide Information Systems, 26, 47–61. Wolters, C. A. (2010). Self-regulated learning and the 21st century competencies. Retrieved from: http://www.hewlett.org/uploads/Self_Regulated_Learning__21st_Century_Compe tencies.pdf Yi, M., & Hwang, Y. (2003). Predicting the use of web-based information systems: Selfefficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59, 431–449. Yukselturk, E. & Bulut, S. (2007). Predictors for Student Success in an Online Course. Educational Technology & Society, 10(2), 71-83. Yurdugül, H. & Alsancak Sarıkaya, D. (2013). The scale of online learning readiness: a study of validity and reliability. Education and Science, 38 (169), 391-406 Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25, 82–91. Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64–70. Zimmerman, B. J. (2008). Investigating self-regulation and motivation: historical background, methodological developments, and future prospects. American Educational Research Journal, 45 (1), 166–183
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Book Review 1
BOOK REVIEW E-LEARNING PARADIGMS AND APPLICATIONS Agent-Based Approach Edited by Mirjana Ivanovic and Lakhmi C. Jain
Res. Assist. Hakan ALTINPULLUK Department of Distance Education Open Education Faculty Anadolu University, Eskisehir, TURKEY ISBN
978-3-642-41964-5 (Hardcover) 978-3-642-41965-2 (eBook)
e-Book (PDF) and Hardcover
E-learning involves the use of digital technology applications in learning and teaching processes, and grows out of an interdisciplinary field, in which are contained a variety different approaches and components. Since the field of e-learning requires the use of high-level technology, it is very much affected by technological developments. Software agents are computer systems that have features such as autonomy, reactivity, intentionality and interactivity. The integration of software agents into elearning mediums strengthens e-learning systems and allows for higher quality learning outcomes. In this book, “E-Learning Paradigms and Applications: Agent-based Approach”, which is the 528th volume of the “Studies in Computational Intelligence” series, the focus is on an agent-based approach, and shifts in e-learning paradigms and innovative applications. Editorship of the book has been jointly assumed by Mirjana Ivanovic´ from the Department of Mathematics and Informatics at the University of Novi Sad and Lakhmi C. Jain of the Faculty of Education, Science, Technology and Mathematics at the University of Canberra. The book contains 9 chapters and 273 pages. In each chapter, e-learning applications are associated with different software agents. The chapters reflect on the e-learning fields of robotics, artificial intelligence, game-based systems, fuzzy-logic, mobile learning, augmented reality, virtual reality, virtual learning environments, collaborative learning, grid services, pedagogical interface agents, the importance of quality and fit-to-purpose open educational resources, new e-
assessment approaches in e-learning, and emotional agents. The applicability of innovative ideas to e-learning systems is discussed in general throughout the book. The book argues that educational practices supported by software agents improve the learning process and produce positive learning outcomes. In the first chapter of the book a system called RoboNewbie is introduced, which is a product of artificial intelligence. Being different from other Robotics experiments, the authors outline the RoboNewbie experiments to be lacking in danger, independent of any special hardware, low cost and easy to understand. Since there are certain requirements involved in making real robots, simulated virtual robots were used. The constructed framework was used in e-learning environments and tested in different conditions and with different participants. In this way the usability of e-learning systems integrated with artificial intelligence and the field of robotics is proven. The RoboNewbie project can be considered an impressive example of how (particularly simulated) humanoid robots will enrich and strengthen e-learning environments. In the 2nd chapter intelligent agents are designed and game-based modules are used for elearning purposes. It is claimed that intelligent agents and fuzzy logic are the most important components for e-learning environments, and a game-based learning system is built on these two foundations. The authors mention that this work, which is related to intelligent agent models that are developed and used for adaptive game-based learning and virtual learning environments, will be applied in learning management systems such as Moodle. At the end of the study, it is observed that, according to the data gathered in a Computer Science Course, game-based modules can be effective in e-learning processes. In the 3rd chapter, based on the idea that e-learning could be a solution to protecting cultural heritage, the authors introduce a mobile augmented reality-based e-learning system, which is supported by social media integration. It is emphasized that when software agents are integrated with artificial intelligence, some intelligent educational applications will be created, and particularly narrative tools, digital storytelling and virtual reality applications are examples of complex applications produced by software agents. In this chapter, in addition to software agents, other components of the Agent-Based Learning Paradigm are elaborated in detail. In this study, in which artificial intelligence elements are integrated with software agents, it is concluded that software agents are effective in the development, application and assessment of e-learning tools. In the 4th chapter problems in inter-university collaboration and cooperation are emphasized, and the virtual learning environment ITC-Euromaster (ITCEM) is introduced. In this study, which was prepared as a case study, the objective is to enhance cooperation between ITCEM and distributed students, and instructors living in different nations and continents, and to develop effective e-learning environments. In the 5th chapter, based on the notion that e-learning services should be scalable, flexible and secured, Grid environments are introduced with the aim that geographically dispersed users utilize their resources in a dynamic, distributed, and heterogeneous way. Within this context, an agent-based e-learning framework for Grid services has been developed. In the 6th chapter it is asserted that pedagogical interface agents could solve the problem of deficiency in computer literacy, seen as one of the biggest problems in developing countries. The authors applied pedagogical interface agents to adult learners to improve their computer usage skills and reached the conclusion that, compared to traditional teaching methods, the use of interface agents are more effective from the perspective of knowledge, attitude and aspiration. The 7th chapter discusses the importance of open educational resources and open courseware for instructors and learners. It then underlines that learning materials in these resources should
be appropriate to requirements and should be of high quality. However, acknowledging that this process is difficult, a system called MASECO has been developed. As a multi-agent system, MASECO allows for the assessment and classification of educational materials, and provides instructors and learners with high quality educational materials which are appropriate to requirements. In addition to introducing MASECO the authors emphasize the importance of quality assurance with regard to educational resources. In the 8th chapter the authors concentrate on adaptive testing and an innovative assessment approach in online learning. The adaptive testing in the developed online learning tool contains some software agents and defines different behavioral patterns. The study presents clues regarding how e-assessment systems will be constructed and how e-testing will be implemented in e-learning systems. In the 9th and final chapter, research is presented about how emotional agents are used in elearning environments. The author laments the difficulty of the group decision-making process, and discusses personality, emotions and mood agents that are important in group-wide decision-making processes. The author then tackles patience and experience as constituents in emotional agents. The study offers an example of how emotional agents are used in e-learning. E-learning is a field which can be used with many different technologies and which contains many components. This book presents a variety of innovations in traditional learning methods, and concentrates on new applications and paradigm shifts in regards to the field of e-learning, all of which enrich current learning environments. The authors share their results and experiences, obtained by the integration of software agents and e-learning tools. All the chapters in the book have been prepared on the basis of an agent-based approach, but each offers a different perspective. Different experiences and perspectives enhance the value of the book, and provide a diversity of opinions. This book, which is grounded on discussion of how elearning systems can be made more effective and stronger via software agents, will be a highly useful reference source, particularly for those who work or who want to work in the fields of Computer Science, Open and Distance Education, and Educational Technology. Due to the multidisciplinary nature of e-learning, this book has the potential to appeal to many different audiences, including postgraduate students, instructors and researchers, in a diverse range of fields.
BIODATA and CONTACT ADRESSES of the AUTHOR Hakan ALTINPULLUK is a Research Assistant in Distance Education at the College of Open Education of Anadolu University, Turkey. He undertook undergraduate studies in the field of Computer Education and Instructional Technologies (CEIT) between the years of 20052009 at Anadolu University. Also, he is currently a PhD candidate in the Department of Distance Education at Anadolu University. Hakan Altınpulluk continues to work in the field of Open and Distance Learning, Augmented Reality, Mobile Learning, Massive Open Online Courses, Personal Learning Environments, and E-Learning Systems. Hakan ALTINPULLUK Open Education Faculty, Anadolu University, 26470 Eskisehir, TURKEY Phone: +90 222 335 0580 #2432 E-mail: [email protected]
REFERENCES Ivanovic, M., & Jain, L. C. (Eds.). (2014). E-learning paradigms and applications: Agentbased approach. Springer.
Turkish Online Journal of Distance Education-TOJDE April 2016 ISSN 1302-6488 Volume: 17 Number: 2 Book Review 2
BOOK REVIEW EDUCATIONAL DATA MINING: APPLICATIONS AND TRENDS Edited by Alejandro Pena-Ayala Res. Assist. Aylin OZTURK Department of Distance Education Open Education Faculty Anadolu University, Eskisehir, TURKEY
978-3-319-02737-1 (Hardcover) 978-3-319-02738-8 (e-Book)
Hardcover and e-Book (PDF)
Springer International Publishing
INTRODUCTION Educational Data Mining (EDM) is a developing field based on data mining techniques. EDM emerged as a combination of areas such as machine learning, statistics, computer science, education, cognitive science, and psychometry. EDM focuses on learner characteristics, behaviors, academic achievements, the process of learning, educational functionalities, domain knowledge content, assessments, and applications. Educational data mining is defined by Baker (2010) as ‘‘an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in’’. EDM is concerned with improving the learning process and environment. In this book, entitled “Educational Data Mining: Applications and Trends” and edited by Peña-Ayala, computer-based learning environments such as e-Learning, LMS and MOOCs are mainly considered. This book includes four parts and sixteen chapters that are prepared with contributions of experts in different fields. In the first part of this book, EDM is explained with a conceptual view. In the second part, applications of student modeling are examined. In the third part, studies in the field of assessment are discussed. In the last part, new trends in EDM field such as text mining and social network analysis are mentioned. 125
This book is important in terms of explaining the theoretical base and sample applications of EDM and leading new studies. In this book review, topics discussed in each section are summarized and the importance of the book for researchers has attempted to highlight., Part 1: Profile With a conceptual view of the EDM, as described in this section, it is indicated that valuable information about learning process can be obtained by analyzing the raw data produced in the educational systems. In e-learning systems by using DM techniques, new and different paths can be found in the solution of learning problems, and also learner behaviors and performance can be predicted. The first section of the book consists of three chapters. In the first chapter, bibliographic review of the studies conducted in EDM field is made. It is indicated that prediction and clustering techniques are usually used in this field. In the second chapter, preprocessing of educational data is examined. Main tasks and issues in the preprocessing of educational data are explained with Moodle data. It is emphasized that preprocessing is one of the most important phases for EDM. In this chapter, steps of preprocessing are explained, but in addition, it is stated that there is no formula for this process. The third chapter illustrates that EDM can support government policies for enhancing education. For this reason, an application that includes EDM for enhancing learning quality performed in Mexico is explained. Part 2: Student Modeling Student Modeling is one of the most important applications, especially for Computer-Based Educational Systems. With Student Modeling, learning environments can be designed according to learners’ needs and expectations. This part consists five chapters which are focused on developing systems for identifying learners and estimate their performance automatically with machine learning, especially in intelligent tutoring systems and adaptive learning environments. Learner attributes such as learner characteristics, behaviors, learning styles, educational experiences, personality, academic achievements, learning system usage data, and assessment results are used for the development of these systems. It is aimed to assist tutors and to increase the quality of education, learners’ satisfaction and achievement with these systems. It is emphasized that estimating performance is especially important for determining at-risk students in the first years and for retention of those students. It is stated that student models can be used in all learning environments. However, using them especially in e-learning systems in which learners and instructors are not in the same place can be more effective. In the fourth chapter, knowledge discovery processes and development of the Student Knowledge Discovery Software which is created with the determination of learner features has been explained. Student performance is modeled using data mining techniques. In the fifth chapter, automatic learner modeling is proposed towards detecting personality of the players with data mining techniques in educational games. It is emphasized that determining learner behaviors are important in order to develop user adaptable systems. In the sixth chapter, it has tried to predict learners’ performance using the Multi-Channel Decision Fusion. In the seventh chapter, the model which is developed in the study entitled “Predicting Student Performance from Combined Data Sources” is tested in Open University (OU) modules. In this chapter, it is emphasized that virtual learning environment activities are beneficial data sources for predicting learner outcomes and it has been demonstrated that different modules require different methods. In the eighth chapter, the accuracy of the learners’ answers by following their eye movements has been tried to estimate by using random forest. It is indicated that estimates can be made, especially in e-learning systems, intelligent tutoring systems, and online quizzes by using learners’ eye movements and mouse clicks. 126
Part 3: Assessment This section which consists of four chapters is focused on techniques that can be used in the evaluation process. In the assessment process, learners’ domain knowledge acquisition, skills development, and achieved outcomes are taken into account. In addition to these, it is underlined that reflection, inquiring, and sentiments are significant for computer-based educational systems. In the ninth chapter, a coherence analyzer is designed to be used in an Intelligent Tutoring System. With this kind of work, learners can evaluate their drafts early and simplify the reviewing process of the instructor. The tenth chapter offers an approach to create test automatically. In this chapter, a model has been developed by using EDM techniques to estimate the difficulty of the items in the computerbased tests. In the eleventh chapter, an instrument has been developed to support instructors’ understanding of learner activities and visualize them. In the study, new techniques for augmenting substantial pedagogical software have been developed. In the twelfth chapter, a new approach to find the most dependent test items in learner response data has been proposed. It is highlighted that students’ response data can be used to identify what is learned by learners and it can also be used to discover the relationship between the test items. These data can be used effectively in the development of the test. Part 4: Trends This part which consists of five chapters includes new applications in the field of EDM. In particular, text mining and social network analysis (SNA) applications are described. In the thirteenth chapter, evaluation of learners’ productions with text mining is described. The ReaderBench software is used for this evaluation. The authors stated that text mining techniques based on advanced natural language processing and machine learning algorithms. Text mining software allow users for cohesion-based assessment, reading strategies identiﬁcation and textual complexity evaluation and to make a positive contribution to evaluation process of instructors. In the fourteenth chapter, learners’ comments are evaluated by using statistical methods and text mining techniques. This kind of studies can be used particularly for revealing views of learners in online learning environments and MOOCs which have a high number of learners. In the fifteenth chapter, an application for the use of SNA and data mining in the field of education was conducted. Social network analysis becomes necessary in conjunction with the proliferation of the use of social networks in educational environments. Learner interaction in e-learning environments can be understood by using SNA methods. SNA is the methodical study that examines relationships occurs in the connected actors from a social point of view. In the sixteenth chapter, it is indicated that at-risk learners can be identified by analyzing users’ interaction data collected from LMS and MOOC platforms and thus learning processes can be supported and developed. In this chapter it is stated that EDM and Learning Analytics (LA) is not very far from each other; however, at the same time, it is emphasized that they are different from each other. In EDM; prediction, classiﬁcation, clustering, and association methods are used for the purpose of answering questions about educational practice. On the other hand, LA focuses on data collection, measurement, and reporting by analyzing. This book which consists of four parts will be a valuable source of interest to researchers, practitioners, academicians, and learners who aim to have information on the EDM field, to learn current practices related to the EDM and to see the trends in this area.
BIODATA and CONTACT ADDRESSES of the AUTHOR Aylin OZTURK is currently working as a Research Assistant in the Department of Distance Education, Open Education Faculty at Anadolu University, Turkey. She graduated from Primary Education Mathematics Teaching Department and Computer Education and Instructional Technology Department of Eskisehir Osmangazi University. OZTURK had her master’s degree in Distance Education Department at Anadolu University and currently she is a PhD candidate at the same university in Department of Distance Education. Her research interests are open and distance education, online learning, educational data mining, personal learning environments, adaptive learning, information and communication technologies, learning analytics, and differentiated instructional design. Research Assistant Aylin OZTURK Open Education Faculty, Anadolu University, 26470 Eskisehir, TURKEY Phone: +90 (222) 335 0580 ext:2772 E-mail: [email protected]
REFERENCES Pena-Ayala, A. (Ed.) (2014). Educational Data Mining: Applications and Trends (Vol. 524). Springer. Baker, R. S. J. D. (2010). Data mining for education. In McGaw, B., Peterson, P., Baker, E. (Eds.) International Encyclopedia of Education (3rd edition), 7, 112-118. Oxford, UK: Elsevier.