Idea Transcript
Eolutionary Social Psychology human beings as it has been to the study of all other living species. See also: Comparative Psychology; Gender Differences in Personality and Social Behavior; Genes and Behavior: Animal Models; Primate Socioecology; Primates, Social Behavior of; Social Psychology: Research Methods; Sociality, Evolution of; Writing, Evolution of
Bibliography Alcock J 1998 Animal Behaior, 6th edn. Sinauer Associates, Sunderland, MA Burnstein E, Crandall C, Kitayama S 1994 Some neo-Darwinian decision rules for altruism: Weighing cues for inclusive fitness as a function of the biological importance of the decision. Journal of Personality and Social Psychology 67: 773–89 Buss D M 1999 Eolutionary Psychology: The New Science of Mind. Allyn and Bacon, Boston, MA Buss D M, Kenrick D T 1998 Evolutionary social psychology. In: Gilbert D T, Fiske S T, Lindzey G (eds.) Handbook of Social Psychology, 4th edn. McGraw-Hill, New York Cosmides L, Tooby J 1992 Cognitive adaptations for social exchange. In: Barkow J H, Cosmides L, Tooby J (eds.) The Adapted Mind: Eolutionary Psychology and the Generation of Culture. Oxford University Press, New York Crawford C, Krebs D L 1998 Handbook of Eolutionary Psychology: Ideas, Issues, and Applications. Erlbaum, Mahwah, NJ Crook J H, Crook S J 1988 Tibetan polyandry: Problems of adaptation and fitness. In: Betzig L, Borgerhoff-Mulder M, Turke P (eds.) Human Reproductie Behaiour: A Darwinian Perspectie. Cambridge University Press, Cambridge, UK Cunningam M R 1981 Sociobiology as a supplementary paradigm for social psychological research. In: Wheeler L (ed.) Reiew of Personality & Social Psychology. Sage, Beverly Hills, CA Daly M, Wilson M 1983 Sex, Eolution, and Behaior, 2nd edn. Willard Grant Press, Boston Daly M, Wilson M 1988 Homicide. de Gruyter, New York Daly M, Salmon C, Wilson M 1997 Kinship: The conceptual hole in psychological studies of social cognition and close relationships. In: Simpson J A, Kenrick D T (eds.) Eolutionary Social Psychology. Erlbaum, Mahwah, NJ Darwin C 1872 The Expression of Emotion in Man and Animals. Murray, London Gangestad S W, Thornhill R 1997 Human sexual selection and developmental stability. In: Simpson J A, Kenrick D T (eds.) Eolutionary Social Psychology. Erlbaum, Mahwah, NJ Graziano W G, Jensen-Campbell L A, Todd M, Finch J F 1997 Interpersonal attraction from an evolutionary perspective: Reactions to dominant and prosocial men. In: Simpson J A, Kenrick D T (eds.) Eolutionary Social Psychology. Erlbaum, Mahwah, NJ Gutierres S E, Kenrick D T, Partch J J 1999 Beauty, dominance, and the mating game: Contrast effects in self-assessment reflect gender differences in mate selection. Personality & Social Psychology Bulletin 25: 1126–34 Kenrick D T 1995 Evolutionary theory versus the confederacy of dunces. Psychological Inquiry 6: 56–61
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Kenrick D T, Gabrielidis C, Keefe R C, Cornelius J S 1996 Adolescents’ age preferences for dating partners: Support for an evolutionary model of life-history strategies. Child Deelopment 67: 1499–511 Kenrick D T, Keefe R C 1992 Age preferences in mates reflect sex differences in human reproductive strategies. Behaioral and Brain Sciences 15: 75–133 Kenrick D T, Neuberg S L, Zierk K L, Krones J M 1994 Evolution and social cognition: Contrast effects as a function of sex, dominance, and physical attractiveness. Personality & Social Psychology Bulletin 20: 210–17 Kenrick D T, Sadalla E K, Keefe R C 1998 Evolutionary cognitive psychology. In: Crawford C, Krebs D (eds.) Eolution and Human Behaior: Ideas, Issues, and Applications. Erlbaum, Mahwah, NJ Kenrick D T, Trost M R 1993 The evolutionary perspective. In: Beall A, Sternberg R J (eds.) Perspecties on the Psychology of Gender. Guilford Press, New York Sherman P W 1981 Kinship demography and Belding’s ground squirrel nepotism. Behaioral Ecology and Sociobiology 8: 251–59 Simpson J A, Kenrick D T (eds.) 1997 Eolutionary Social Psychology. Erlbaum, Mahwah, NJ Tooby J, Cosmides L 1992 The psychological foundations of culture. In: Barkow J H, Cosmides L, Tooby J (eds.) The Adapted Mind: Eolutionary Psychology and the Generation of Culture. Oxford University Press, New York Trivers R L 1972 Parental investment and sexual selection. In: Campbell B (ed.) Sexual Selection and the Descent of Man 1871–1971. Aldine, Chicago, IL Wilson E O 1975 Sociobiology: The New Synthesis. Belknap Press of Harvard University Press, Cambridge, MA
D. T. Kenrick
Evolutionary Theory and Education 1. Introduction In recent years, Darwin’s (1859) theory of evolution has guided the theoretical and empirical research of an increasing number of social and behavioral scientists, an approach that is often called evolutionary psychology. The goals here are to consider how evolutionary theory and research in evolutionary psychology can be used to understand children’s academic development and to explore related educational issues. Before these issues can be fully appreciated, an overview of the evolutionary approach to cognition and development is needed.
2. Eolution and Cognition One basic assumption of evolutionary psychologists is that natural selection has resulted in the evolution of cognitive competencies that facilitated the survival
Eolutionary Theory and Education and reproduction of our ancestors (Cosmides and Tooby 1994). It is further assumed that most of these competencies are modular and domain specific, that is, they are supported by neural and cognitive systems that are designed to process only certain types of information. For example, there are dedicated neural and cognitive systems that process basic language sounds (e.g., ‘ba,’ ‘pa’) and different systems that process other types of information, such as the visuospatial information involved in navigating in the environment. There are, of course, more general cognitive systems that coordinate and integrate the workings of these specialized systems (Smith and Jonides 1999), but research in evolutionary psychology tends to be focused on domain-specific cognitive modules, such as those associated with language. The issues of modularity, domain specificity, and the number and organization of any associated cognitive systems are currently debated. Nonetheless, it is clear that there is some degree of inherent and modular structure to the human brain and mind, in keeping with evolutionary theory. The associated neural and cognitive systems appear to be designed to process information corresponding to the domains of folk psychology, folk biology, and intuitive physics (Geary 1998), although there are other modules as well (e.g., for basic numerical abilities; Geary 1995). The cognitive modules associated with folk psychology include language, theory of mind (e.g., being able to make inferences about the intentions of other people), and competencies that allow people to interpret the body language and facial expressions of other people. These skills allow people to monitor and regulate dyadic social interactions and to establish and maintain social relationships. The competencies associated with folk biology include the ability to classify flora and fauna in the local ecology, and learn about the associated growth and behavioral patterns (Atran 1998, Keil 1992). This folk biological knowledge allows people in preindustrial cultures to classify and categorize local species, hunt some of these species, and use plants as medicines, for food and social rituals. Intuitive physics refers to the neural and cognitive systems that engage the physical world, and enable people to navigate in 3dimensional space; remember the location of objects in the environment, and use objects (e.g., stones) to make tools (Shepard 1994). The inherent structure and functioning of these modules appears to be skeletal in nature (Gelman 1990). Early in life, the associated neural and cognitive systems direct attention to and the initial processing of domain-specific information, but the normal development of these systems requires input from the environment. Environmental input, in turn, shapes the development of these cognitive modules so that they are adapted, during childhood, to local conditions— nature provides the skeletal structure of evolved cognitive domains and this structure is fleshed out with experience. For example, it appears that children
in all cultures are biologically prepared to process and respond to the sounds of all human languages, but the language that eventually emerges is the specific language to which they are exposed (Kuhl et al. 1997). In other words, the neural and cognitive systems that respond to language sounds—and later enable the comprehension and production of human language— are inherent, but the normal development and functioning of these systems requires exposure to language.
3. Eolution and Deelopment A long period of development, as is found in humans, has a clear risk—death before the age of reproduction—and thus would only evolve if there were benefits that outweighed this risk. Comparative studies suggest that one purpose, and an important adaptive benefit, of delayed maturation is the accompanying ability to refine the physical, social and cognitive competencies that support survival and reproduction. As an example, a long developmental period is found in all social mammals and the length of this period increases with the increases in the complexity of the species’ social system (Joffe 1997). These patterns suggest that one purpose of childhood is to practice and refine sociocognitive competencies, such as language and other social skills. In short, delayed maturation allows children to practice and refine the physical, social, and cognitive skills associated with the survival (e.g., hunting) and reproduction (e.g., parenting skills) of our ancestors. Play, social interactions, and exploration of the environment and objects appear to be the mechanisms through which these emerging competencies are practiced and refined during development. Child-initiated social play, exploration, and so forth are intimately linked to cognitive and neural development, in that these activities provide experiences with the social, biological, and physical world. These experiences, in turn, interact with the inherent, but skeletal structure of cognitive modules and ensure their normal development and adaptation to local conditions. In this view, children are biologically prepared to learn about other people, and the biological and physical world and are inherently motivated to seek out experiences that will facilitate this learning.
4. Implications for Education A basic assumption of evolutionary psychology is that modern humans evolved domain-specific cognitive abilities and behavioral strategies to deal with conditions in the environments of our ancestors, but these abilities and strategies may not always be well-suited to contemporary conditions. In fact, much formal education is ‘unnatural’ in that much of what children 5025
Eolutionary Theory and Education are expected to learn in school involves tasks never encountered by our ancestors (Geary 1995, Rozin 1976). The basic goals of schools and schooling are thus to organize the activities of children so that they acquire competencies, such as the ability to read, that are important in the wider culture but have no evolutionary history. There follows discussion on some of the basic issues that arise from this perspective of education.
4.1 Eolution and Academic Deelopment Geary (1995) referred to language and other evolved forms of cognition as biologically primary abilities, and skills that build upon these primary abilities but are principally cultural inventions (e.g., reading) as biologically secondary abilities. The mechanisms by which evolved systems are adapted to produce secondary competencies are not yet fully understood, but appear to involve the co-optation of primary systems for secondary learning and access to knowledge implicit in these primary systems (Geary 1995, Rozin 1976). As an example of the former, consider the relation between language, a primary ability, and reading, a secondary ability. The acquisition of reading-related abilities (e.g., word decoding) appears to involve the co-option of primary language and language-related systems, among others (e.g., visual scanning; Rozin 1976). Wagner et al. (1994), reported that individual differences in the fidelity of kindergarten children’s phonological processing systems, which are basic features of the language domain, are strongly predictive of the ease with which basic reading skills (e.g., word decoding) are acquired in first grade. In other words, the evolutionary pressures that are selected for phonological processing systems, such as the ability to segment language sounds, were unrelated to reading, but these systems are used, or co-opted, when children learn how to read. As an example of the latter, consider that the development of geometry may have been initially based on access to knowledge implicit in the primary systems that support navigation in the physical world. In the development of the basic principles of classical geometry, Euclid apparently ‘started with what he thought were self-evident truths and then proceeded to prove all the rest by logic’ (West et al. 1982, p. 220). For example, the implicit understanding that the fastest way to get from one place to another is to go ‘as the crow flies,’ was made explicit in the formal Euclidean postulate, ‘a line can be drawn from any point to any point (In Euclidean geometry, a line is a straight line)’ (West et al. 1982, p. 221). From an evolutionary perspective, the former reflects an implicit understanding of how to quickly get from one place to another and is knowledge that is built into the neural 5026
and cognitive systems that support navigation. The latter was discovered, that is, made explicit, by Euclid. Once explicit, this knowledge was integrated into the formal discipline of geometry and became socially transmittable and teachable.
4.2 Motiation to Learn One very important implication of the evolutionary perspective is that the motivation to acquire schooltaught secondary abilities is based on the requirements of the larger society and not on the inherent interests of children. Given the relatively recent advent of near universal schooling in contemporary societies, there is no reason to believe that the skills that are taught in school are inherently interesting or enjoyable for children to learn. In other words, one important difference between primary and secondary cognitive abilities is the level and source of motivation to engage in the activities that are necessary for their acquisition. This does not, however, preclude the selfmotivated engagement in some secondary activities. Even though reading is a secondary ability that involves the co-optation of primary language systems, many children and adults are motivated to read. The motivation to read, however, is probably driven by the content of what is being read rather than by the process itself. In fact, the content of many stories and other secondary activities (e.g., video games, television) might reflect evolutionarily relevant themes that motivate engagement in these activities, such as social relationships and social competition. Furthermore, the finding that intellectual curiosity is a basic dimension of human personality (Goldberg 1993) suggests that there will be a number of intellectually curious individuals who will pursue secondary activities. Euclid’s investment in formalizing and proving the principles of geometry is one example. However, this type of discovery typically reflects the activities and insights of only a few individuals, and the associated advances spread through the larger society only by means of informal (e.g., newspapers) and formal education. The point is, the motivation to engage in the activities that will promote the acquisition of secondary abilities is not likely to be universal.
4.3 Instructional Actiities The basic structure of primary abilities is inherent (Gelman 1990), that is, the supporting neural and cognitive systems automatically orient children to relevant features of the environment (e.g., other people) and process the associated information (e.g., facial expressions or language sounds). As noted above, children are inherently motivated to seek out
Eolutionary Theory and Education experiences, for example, through social play, that ensure the appropriate development of these primary systems. In contrast, there is no inherent structure supporting the acquisition of secondary abilities, nor are most children inherently motivated to engage in the activities that are necessary for secondary learning. While this conclusion might seem self evident, it runs counter to many assumptions about children’s learning in contemporary education; for example, that children are inherently motivated to learn secondary abilities and will do so through activities that involve play and social discourse. Thus, from the evolutionary perspective, one essential goal of schooling is to provide content, organization, and structure to the teaching of secondary abilities, features that have been provided by evolution to primary abilities. Moreover, it cannot be assumed that children’s inherent interests, such as social relationships, and preferred learning activities, such as play, will be sufficient for the acquisition of secondary abilities, even though they appear to be sufficient for the fleshing out of primary abilities. Instruction must therefore involve engaging children in activities that facilitate the acquisition of secondary abilities, whether or not children are inherently interested in engaging in these activities. This does not mean that play and social activities cannot be used to engage children in some forms of secondary learning. It does, however, mean that it is very unlikely that the mastery of many secondary domains (e.g., reading or algebra) will occur with only these types of primary activities. In fact, research in cognitive and educational psychology indicates that some forms of secondary learning will require activities that differ from those associated with the fleshing out of primary abilities (see Geary 1995, for related discussion). These would include, among others, direct instruction, where teachers’ provide the goals, organization and structure to instructional activities and explicitly teach basic competencies, such as how to sound out unfamiliar words or manipulate algebraic equations. The mastery of secondary domains also requires extensive exposure to the material, distributed over many contexts and oftentimes over many years, as well as extensive practice in using any associated procedures (e.g., to solve mathematics problems). Extensive exposure and practice also appear to be needed for the development of primary abilities, but this exposure and practice automatically occur as children engage in social discourse, play, and exploration. In contrast, most children will not automatically engage in the practice needed to master secondary domains, and, as a result, this practice needs to be built into instructional activities. For some domains, such as in the biological and physical sciences, mastery will also require many ‘hands on’ activities, as in conducting experiments, although more traditional methods will be needed as well (e.g., learning basic facts and principles, such as the theory of evolution).
In closing, although not enough is known to draw firm conclusions about which instructional practices can most effectively adapt primary cognitive systems for the secondary learning, the following principles can be used to guide future educational research. First, the process of evolution has provided the basic neural and cognitive structure to primary abilities, such as language, but for secondary abilities, such as reading, this basic structure and organization must come from instructional practices. Second, children are inherently motivated to engage in the types of activities, such as social play, that will facilitate the development of primary abilities, but it is not likely that these same activities will be sufficient for the acquisition of secondary abilities. This is because the brain and mind are inherently designed to be sensitive to and respond to primary activities, as they are related to the development of primary abilities. It cannot be assumed that the brain and mind are equally responsive to the activities that are needed to master secondary competencies, nor can it be assumed that children are inherently motivated to engage in these activities. Finally, primary abilities are universal, but secondary abilities are culturally derived. Thus, educational research must be an on-going process designed to determine the most effective means of instruction for the ever-changing array of secondary competencies needed to function in contemporary society. See also: Cognitive Development: Child Education; Cultural Evolution: Overview; Developmental Behavioral Genetics and Education; Evolutionary Theory, Structure of; Human Cognition, Evolution of; Lifespan Development: Evolutionary Perspectives; Modularity versus Interactive Processing, Psychology of; Psychological Development: Ethological and Evolutionary Approaches
Bibliography Atran S 1998 Folk biology and the anthropology of science: Cognitive universals and cultural particulars. Behaioral and Brain Sciences 21: 547–609 Cosmides L, Tooby J 1994 Origins of domain specificity: The evolution of functional organization. In: Hirschfeld L A, Gelman S A (eds.) Mapping the Mind: Domain Specificity in Cognition and Culture. Cambridge University Press, New York, pp. 85–116 Darwin C 1859 On the Origin of Species by Means of Natural Selection. John Murray, London Geary D C 1995 Reflections of evolution and culture in children’s cognition: Implications for mathematical development and instruction. American Psychologist 50: 24–37 Geary D C 1998 Male, Female: The Eolution of Human Sex Differences. American Psychological Association, Washington, DC Gelman R 1990 First principles organize attention to and learning about relevant data: Number and animate-inanimate distinction as examples. Cognitie Science 14: 79–106
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Eolutionary Theory and Education Goldberg L R 1993 The structure of phenotypic personality traits. American Psychologist 48: 26–34 Joffe T H 1997 Social pressures have selected for an extended juvenile period in primates. Journal of Human Eolution 32: 593–605 Keil F C 1992 The origins of an autonomous biology. In: Gunnar M R, Maratsos M (eds.) Modularity and Constraints in Language and Cognition: The Minnesota Symposia on Child Psychology. Erlbaum, Hillsdale, NJ, Vol. 25, pp. 103–37 Kuhl P K, Andruski J E, Chistovich I A, Chistovich L A, Kozhevnikova E V, Ryskina V L, Stolyarova E I, Sundberg U, Lacerda F 1997 Cross-language analysis of phonetic units in language addressed to infants. Science 277: 684–6 Rozin P 1976 The evolution of intelligence and access to the cognitive unconscious. In: Sprague J M, Epstein A N (eds.) Progress in Psychobiology and Physiological Psychology. Academic Press, New York, Vol. 6, pp. 245–80 Shepard R N 1994 Perceptual-cognitive universals as reflections of the world. Psychonomic Bulletin and Reiew 1: 2–28 Smith E E, Jonides J 1999 Storage and executive processes in the frontal lobes. Science 283: 1657–61 Wagner R K, Torgesen J K, Rashotte C A 1994 Development of reading-related phonological processing abilities: New evidence of bidirectional causality from a latent variable longitudinal study. Deelopmental Psychology 30: 73–87 West B H, Griesbach E N, Taylor J D, Taylor L T 1982 The Prentice-Hall Encyclopedia of Mathematics. Prentice-Hall, Englewood Cliffs, NJ
D. C. Geary
Evolutionary Theory, Structure of 1. The Structure of Eolutionary Models Much of evolutionary theory is represented at the beginning of the twenty-first century through mathematical models, especially through the models of population genetics, of the evolution of states of a given system, both in isolation and interaction, through time. This is done by conceiving of the model as capable of a certain set of states—these states are represented by elements of a certain mathematical space, the state space. (Generally speaking, ‘models’ and ‘systems’ always refer to ideal systems; when the actual biological systems are being discussed, they are called ‘empirical’ or ‘natural’ systems.) The variables used in each mathematical model represent distinct measurable or potentially quantifiable, physical magnitudes. Classically, any particular configuration of values for these variables is a ‘state’ of the system, the ‘state space’ being the collection of all possible configurations of the variables. The theory itself represents the behavior of the system in terms of its states: the rules or laws of the theory (i.e., laws of coexistence, succession, or interaction) can delineate various configurations and trajectories on the state space. A description of the
structure of the theory itself therefore only involves the description of the set of models, which make up the theory. Construction of a model within the theory involves assignment of a location in the state space of the theory to a system of the kind defined by the theory. Potentially, there are many kinds of systems that a given theory can be used to describe—limitations come from the dynamical sufficiency (whether it can be used to describe the system accurately and completely) and the accuracy and effectiveness of the laws used to describe the system and its changes. Thus, there are two main aspects to defining a model. First, the state space must be defined—this involves choosing the variables and parameters with which the system will be described; second, coexistence laws, which describe the structure of the system and laws of succession, which describe changes in its structure, must be defined. Defining the state space involves defining the set of all the states the system could possibly exhibit. Certain mathematical entities—in the case of many evolutionary models, these are vectors—are chosen to represent these states. The collection of all the possible values for each variable assigned a place in the vector is the state space of the system. The system and its states can have a geometrical interpretation: the variables used in the state description (i.e., state variables) can be conceived as the axes of a Cartesian space. The state of the system at any time may be represented as a point in that space, located by projection on the various axes. The family of measurable physical magnitudes, in terms of which a given system is defined, also includes a set of parameters. Parameters are values that are not themselves a function of the state of the system. Thus, a parameter can be understood as a fixed value of a variable in the state space—topologically, setting a parameter amounts to limiting the number of possible structures in the state space by reducing the dimensionality of the model. Laws, used to describe the behavior of the system in question, must also be defined in a description of a model or set of models. Laws have various forms: in general, coexistence laws describe the possible states of the system, while laws of succession describe changes in the state of the system. Let us discuss in more detail the description of the evolutionary models that make up evolutionary theory. The main items needed for this description are the definition of a state space, state variables, parameters, and a set of laws of succession and coexistence for the system. Choosing a ‘state space’ (and thereby, a set of state variables) for the representation of genetic states and changes in a population is a crucial part of population genetics theory. Paul Thompson suggests that the state space for population genetics would include the physically possible states of populations in terms of genotype frequencies. The state space would be ‘a Cartesian n-
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ISBN: 0-08-043076-7