Conceptual Change

Discussion of conceptual change is commonplace throughout cognitive science and is very much a part of understanding what CONCEPTS themselves are. There are examples in the history and philosophy of science (Kuhn 1970, 1977), in the study of SCIENTIFIC THINKING AND ITS DEVELOPMENT, in discussions of COGNITIVE DEVELOPMENT at least as far back as PIAGET (1930) and VYGOTSKY (1934), in linguistic analysis both of language change over history and of LANGUAGE ACQUISITION, and in computer science and artificial intelligence (AI) (Ram, Nersessian, and Keil 1997). But no one sense of conceptual change prevails, making it difficult to define conceptual change in uncontroversial terms. We can consider four types of conceptual change (see also Keil 1998) as being arrayed along a continuum from the simple accretion of bits of knowledge to complete reorganizations of large conceptual structures, with a fifth type that can involve little or no restructuring of concepts but radical changes in how they are used. Common to all accounts is the idea that either conceptual structure itself or the way that structure is used changes over time. The most discussed account focuses on structural change seen as a dramatic and qualitative restructuring of whole systems of concepts (type 4). All five types are critical to consider, however, because very often the phenomena under discussion have not been studied in sufficient detail to say which type best explains the change.

1. Feature or property changes and value changes on dimensions. With increasing knowledge, different clusters of features may come to be weighted more heavily in a concept, perhaps because they occur more frequently in a set of experiences. A young child might weight shape somewhat more heavily in her concept of a bath towel than texture, while an older child might do the opposite. In its simplest form, such a developmental change may not connect to any other relations or beliefs, such as why texture is now more important. An older child might disagree with a younger one on identifying some marginal feature of bath towels, and while we might thereby attribute this difference to conceptual change, we might not see the concepts as really being very different.

Changes in feature weightings and dimensional value shifts are ubiquitous in cognitive science studies of concepts. They are seen at all ages ranging from studies of infant categorization to adult novice-to-expert shifts (see INFANT COGNITIONand EXPERTISE). Any time that some bit of information is incrementally added to a knowledge base and results in a different feature weighting, such a change occurs. When such changes have no other obvious consequences for how knowledge in a domain is represented, they constitute the most minimal sense of conceptual change, and for many who contrast "learning" with true conceptual change, not a real case at all (Carey 1991).

2. Shifting use of different sorts of properties and relations. Conceptual change could occur because of changes in the kinds of feature used in representations. Infants and young children have been said to use perceptual and not conceptual features to represent classes of things, or perceptual and not functional ones, or concrete and not abstract ones (e.g., Werner and Kaplan 1963). More recently, young children are said to use one-place predicates and not higher-order relational ones (Gentner and Toupin 1988), or to rely heavily on shape-based features early on in some contexts (Smith, Jones, and Landau 1996). Similar arguments have been made about novice to expert shifts in adults (Chi, Feltovich, and Glaser 1981) and even about the evolution of concepts from those in "primitive" cultures to those in more "advanced" ones (cf. Horton 1967; see also LURIA).

Several forms of conceptual change can be captured by shifts in what feature types are used in concepts. Despite a wide range of proposals in this area, however, it is striking how many have always been controversial, especially in claims of cross-cultural differences (Cole and Means 1981). There is no consensus on changes in the sorts of properties, relations, or both available at different points in development, expertise, or historical change, nor on the very real possibility of no true changes in the availability of property types.

Part of the problem is the need for better theories of property types. It is difficult to make claims about perceptual to conceptual shifts, or perceptual to functional shifts, if the contrast between perceptual and conceptual features is murky. Claims of changes in feature types therefore need to attend closely to philosophical analyses of properties and relations, which in turn need to attend more to the empirical facts.

3. Changes in computations performed on features. Conceptual change can also arise from new kinds of computations performed on a constant set of features, such as from tabulations of features based on frequency and correlational information, to more rulelike organizations of the same features (Sloman 1996). In other cases, there have been claims of changes from prelogical to quasi-logical computations over features (Inhelder and Piaget 1958), or changes from integral to separable operations on features and dimensions (Kemler and Smith 1978); or changes from feature frequency tabulations to feature correlation tabulations.

Although most models tend to propose changes in computations that apply across all areas of cognition, such transitions can also occur in circumscribed domains of thought even as there are no global changes in computational ability (Chi 1992). Second, these models do not require that concepts be interrelated in a larger structure. They are neutral in that respect and thus allow each concept to change on its own. In practice, this is highly implausible and may in the end render such models inadequate because they fail to make stronger claims about links among concepts.

There are also cases where there is no absolute change in feature or computational types, but rather a strong change in the ratio of types. Thus a younger child may have true conceptual or functional features but may have ten times as many perceptual ones in her concepts, whereas an older child may have the opposite ratio. Similarly, a younger child may perform logical computations on feature sets, but may do so much more rarely and may more frequently resort to simpler probabilistic tabulations. This variant is important because it offers a very different characterization of the younger child in terms of basic competencies. Younger children are not incapable of representing certain feature types or engaging in certain computations; rather, they do so much less often, perhaps as a function of being much more inexperienced in so many domains (Keil 1989).

4. Theoretic changes, where theories spawn others and thereby create new sets of concepts. The most dramatic kinds of conceptual change, and those occupying most discussions in cognitive science at large, are those that view concepts as embedded in larger explanatory structures, usually known as "theories," and whose changes honor DOMAIN SPECIFICITY. Sweeping structural changes are said to occur among whole sets of related concepts in a domain. For example, a change in one concept in biology will naturally lead to simultaneous changes in other biological concepts because they as a cluster tend to complement each other symbiotically. Within this type, three kinds of change are normally described: (a) birth of new theories and concepts through the death of older ones (Gopnik and Wellman 1994); (b) gradual evolution of new theories and concepts out of old ones in a manner that eventually leaves no traces of the earlier ones (Wiser and Carey 1983); and (c) birth of new theories and attendant concepts in a manner that leaves the old ones intact (Carey 1985).

One key issue in choosing among these kinds of theoretic change is the extent to which concepts of one type are incommensurable or contradictory with those of another type (Kuhn 1970, 1982). Kuhn suggested that conceptual changes in domains could lead to "paradigm shifts" in which concepts in a prior system of beliefs might not even be understandable in terms of the new set of beliefs, just as concepts in that newer system might not be understandable in terms of the older one. The ideas of paradigm shifts and ensuing incommensurability have been highly influential in many areas of cognitive science, most notably in the study of conceptual change in childhood (Carey 1985). A related issue asks how contradictions and anomalies in an older theory precipitate change (Chinn and Brewer 1993; Rusnock and Thagard 1995).

Although most discussion of theoretic conceptual change has focused on these three kinds of restructuring, unambiguous empirical evidence for these systemic restructurings as opposed to the other four types of conceptual change (1, 2, 3, 5) is often difficult to come by. For example, when a child undergoes a dramatic developmental shift in how she thinks about the actions of levers, although that change might reflect a restructuring of an interconnected set of concepts in a belief system about physical mechanics, it might also reflect a change in the kinds of features that are most emphasized in mechanical systems, or how the child performs computations on correlations that she notices among elements in mechanical systems.

5. Shifting relevances. Children and adults often come to dramatic new insights not because of an underlying conceptual revolution or birth of a new way of thinking, but rather because they realize the relevance or preferred status of an already present explanatory system to a new set of phenomena. Because the realization can be sudden and the extension to new phenomena quite sweeping, it can have all the hallmarks of profound conceptual change. It is, however, markedly different from traditional restructuring notions. Children, for example, can often have several distinct theories available to them throughout an extensive developmental period but might differ dramatically from adults in where they think those theories are most relevant (e.g., Gutheil, Vera, and Keil 1998). Children might not differ across ages in their possession of the theories but rather in their application of them. These kinds of relevance shifts, combined with theory elaboration in each domain, may be far more common than cases of new theories arising de novo out of old ones.

An increasing appreciation of these different types of conceptual change is greatly fostered by a cognitive science perspective on knowledge; for as questions cross the disciplines, they become treated in different ways and different kinds of conceptual change stand out as most prominent. In addition, these types of conceptual change need not be mutually exclusive. For example, changes in the kinds of features that are emphasized and in the kinds of computations performed on those features can occur on a domain-specific basis and might result in a set of concepts having different structural relations among each other.

See also

Additional links

-- Frank Keil


Carey, S. (1985). Conceptual Change in Childhood. Cambridge, MA: MIT Press.

Carey, S. (1991). Knowledge acquisition: Enrichment or conceptual change? In S. Carey and R. Gelman, Eds., The Epigenesis of Mind: Essays on Biology and Cognition. Jean Piaget Symposium Series. Hillsdale, NJ: Erlbaum, pp. 257-291.

Chi, M. (1992). Conceptual change within and across ontological categories: Examples from learning and discovery in science. Minnesota Studies in the Philosophy of Science 15:129-186.

Chi, M., P. J. Feltovich, and R. Glaser. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science 5:121-152.

Chinn, C. A., and W. F. Brewer. (1993). The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science. Instruction Rev. Educ. Res. 63(1):1-49.

Cole, M., and B. Means. (1981). Comparative Studies of How People Think. Cambridge, MA: Harvard University Press.

Gentner, D., and C. Toupin. (1988). Systematicity and surface similarity in the development of analogy. Cognitive Science 10:277-300.

Gopnik, A., and H. M. Wellman. (1994). The theory theory. In L. A. Hirschfeld and S. A. Gelman, Eds., Mapping the Mind: Domain Specificity in Cognition and Culture. Cambridge: Cambridge University Press, pp. 257-293.

Gutheil, G., A. Vera, and F. C. Keil. (1998). Houseflies don"t "think": Patterns of induction and biological beliefs in development. Cognition, 66:33-49.

Horton, R. (1967). African traditional thought and Western science. Africa 37:50-71, 159-187.

Inhelder, B., and J. Piaget. (1958). The Growth of Logical Thinking from Childhood to Adolescence. New York: Basic Books.

Keil, F. C. (1989). Concepts, Kinds and Cognitive Development. Cambridge, MA: MIT Press.

Keil, F. C. (1998). Cognitive science and the origins of thought and knowledge. In R. M. Lerner, Ed., Theoretical Models of Human Development. vol. 1 of Handbook of Child Psychology, 5th ed. New York: Wiley.

Kemler, D. G., and L. B. Smith. (1978). Is there a developmental trend from integrality to separability in perception? Journal of Experimental Child Psychology 26:498-507.

Kuhn, T. S. (1970). The Structure of Scientific Revolutions. Chicago: University of Chicago Press.

Kuhn, T. S. (1977). A function for thought experiments. In T. Kuhn, Ed., The Essential Tension: Selected Studies in Scientific Tradition and Change. Chicago: University of Chicago Press.

Kuhn, T. S. (1982). Commensurability, comparability, and communicability. PSA 2:669-688. East Lansing: Philosophy of Science Association.

Piaget, J. (1930). The Child"s Conception of Physical Causality. London: Routledge and Keegan Paul.

Ram, A., N. J. Nersessian, and F. C. Keil. (1997). Conceptual change: Guest editors' introduction. Journal of the Learning Sciences 6(1):1-2.

Rusnock, P., and P. Thagard. (1995). Strategies for conceptual change: Ratio and proportion in classical Greek mathematics. Studies in the History and Philosophy of Science 26(1):107-131.

Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin 119(1):3-22.

Smith, L. B., S. S. Jones, and B. Landau. (1996). Naming in young children: A dumb attentional mechanism? Cognition 60:143-171.

Werner, H., and B. Kaplan. (1963). Symbol Formation: An Organismic-Developmental Approach to Language and the Expression of Thought. New York: Wiley.

Wiser, M., and S. Carey. (1983). When heat and temperature were one. In D. Gentner and A. Stevens, Eds., Mental Models. Hillsdale, NJ: Erlbaum.

Further Readings

Arntzenius, F. (1995). A heuristic for conceptual change. Philosophy of Science 62(3):357-369.

Bartsch, R. (1996) The relationship between connectionist models and a dynamic data-oriented theory of concept formation. Synthèse 108(3):421-454.

Carey, S., and E. Spelke. (1984). Domain-specific knowledge and conceptual change. In L. A. Hirschfeld and S. A. Gelman, Eds., Mapping the Mind: Domain Specificity in Cognition and Culture. New York: Cambridge University Press, pp. 169-200.

Case, R. (1996). Modeling the process of conceptual change in a continuously evolving hierarchical system. Monographs of the Society for Research in Child Development 61(1-2):283-295.

Dunbar, K. (1997). How scientists think: On-line creativity and conceptual change in science. In T. B. Ward, S. M. Smith, and J. Vaid, Eds., Creative Thought: An Investigation of Conceptual Structures and Processes. Washington, DC: American Psychological Association, pp. 461-493.

Gentner, D., S. Brem, R. W. Ferguson, et al. (1997). Analogical reasoning and conceptual change: A case study of Johannes Kepler. Journal of the Learning Sciences 6(1):3-40.

Greeno, J. G. (1998). The situativity of knowing, learning, and research. American Psychologist 53(1):5-26.

Hatano, G. (1994). Conceptual Change: Japanese Perspectives: Introduction. Human Development 37(4):189-197.

Kitcher, P. (1988). The child as parent of the scientist. Mind and Language 3:217-227.

Lee, O., and C. W. Anderson. (1993). Task engagement and conceptual change in middle school science classrooms. American Educational Research Journal 30(3):585-610.

Nersessian, N. J. (1989). Conceptual change in science and in science education. Synthèse 80(1):163-183.

Nersessian, N. J. (1992). How do scientists think? Capturing the dynamics of conceptual change in science. Minnesota Studies in the Philosophy of Science 15:3-44.

Nersessian, N. J. (1996). Child's play. Philosophy of Science 63:542-546.

Smith, C., S. Carey, and M. Wiser. (1985). On differentiation: A case study of the development of the concepts of size, weight, and density. Cognition 21:177-237.

Stinner, A., and H. Williams. (1993). Conceptual change, history, and science. Stories Interchange 24:87-103.

Thagard, P. (1990). Concepts and conceptual change. Synthèse 82:255-274.

Vosniadou, S., and W. F. Brewer. (1987). Theories of knowledge restructuring in development. Review of Educational Research 57:51-67.

Vosniadou, S., and W. F. Brewer. (1992). Mental models of the earth: A study of conceptual change in childhood. Cognitive Psychol. 24(4):535-585.

Vygotsky, L. S. (1934/1986). Thought and Language. Cambridge, MA: MIT Press.

Wiser, M. (1988). The differentiation of heat and temperature: History of science and novice-expert shift. In S. Strauss, Ed., Ontogeny, Phylogeny, and Historical Development. Norwood, NJ: Ablex, pp. 28-48.

Zietsman, A., and J. Clement. (1997). The role of extreme case reasoning in instruction for conceptual change. Journal of the Learning Sciences 6(1):61-89.