Preschool children learn about causal structure from conditional interventions

Developmental Science

Volumn 10, Issue 3, 2007, Pages 322-332

  Schulz, Laura E ^a   Gopnik, Alison ^b   Glymour, Clark ^c  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BAYES THEOREM; CHILD DEVELOPMENT; COGNITION; COMPARATIVE STUDY; FEMALE; HUMAN; LEARNING; MALE; PHYSIOLOGY; PRESCHOOL CHILD; PSYCHOLOGICAL MODEL;

ASSOCIATION LEARNING; BAYES THEOREM; CHILD DEVELOPMENT; CHILD, PRESCHOOL; COGNITION; FEMALE; HUMANS; MALE; MODELS, PSYCHOLOGICAL;

EID: 34247355431     PISSN: 1363755X     EISSN: 14677687     Source Type: Journal    
DOI: 10.1111/j.1467-7687.2007.00587.x     Document Type: Article

References (36)

1. Ahn, W., Gelman, S.A., Amsterlaw, J.A., Hohenstein, J., & Kalish, C.W. (2000). Causal status effects in children's categorization. Cognition, 76 (2), 35-43.
2. Bullock, M., Gelman, R., & Baillargeon, R. (1982). The development of causal reasoning. In W.J. Friedman (Ed.), The developmental psychology of time (pp. 209-254). New York: Academic Press.
3. Carey, S., & Spelke, E. (1994). Domain-specific knowledge and conceptual change. In L.A. Hirschfeld & S.A. Gelman (Eds.), Mapping the mind: Domain specificity in cognition and culture. Based on a conference entitled 'Cultural Knowledge and Domain Specificity,' held in Ann Arbor, MI, 13-16 October 1990 (pp. 169-200). New York: Cambridge University Press.
4. Chen, Z., & Klahr, D. (1999). All other things being equal: children's acquisition of the control of variables strategy. Child Development, 70 (5), 1098-1120.
5. Cheng, P.W. (1997). From covariation to causation: a causal power theory. Psychological Review, 104 (2), 367-405.
6. Cheng, P.W (2000). Causality in the mind: estimating contextual and conjunctive power. In F.C. Keil & R.A. Wilson (Eds.), Explanation and cognition (pp. 227-253). Cambridge, MA: MIT Press.
7. Gelman, S.A., & Wellman, U.M. (1991). Insides and essences: early understandings of the non-obvious. Cognition, 38 (3), 213-244.
8. Glymour, C. (2001). The mind's arrows: Bayes nets and causal graphical models in psychology. Cambridge, MA: MIT Press.
9. Gopnik, A., Glymour, C., Sobel, D., Schulz, L., Kushnir, T., & Danks, D. (2004). A theory of causal learning in children: causal maps and Bayes nets. Psychological Review, 111 (1), 1-30.
10. Gopnik, A., & Schulz, L.E. (in press). Causal learning: Psychology, philosophy, computation. New York: Oxford University Press.
11. Gopnik, A., Sobel, D.M., Schulz, L.E., & Glymour, C. (2001). Causal learning mechanisms in very young children: two-, three-, and four-year-olds infer causal relations from patterns of variation and covariation. Developmental Psychology, 37(5), 620-629.
12. Tnhelder, B., & Piaget, J. (1958). The growth of logical thinking from childhood to adolescence (A. Parsons & S. Milgram, trans.). New York: Basic Books.
13. Kuhn, D. (1989). Children and adults as intuitive scientists. Psychological Review, 96 (4), 674-689.
14. Kuhn, D., Amsel, E., & O'Laughlin, M. (1988). The development of scientific thinking skills. Orlando, FL: Academic.
15. Kushnir, T., & Gopnik, A. (2005). Young children infer causal strength from probabilities and interventions. Psychological Science, 16 (9), 678-683.
16. Kushnir, T., & Gopnik, A. (in press). Conditional probability versus spatial contiguity in causal learning: preschoolers use new contingency evidence to overcome prior spatial assumptions. Developmental Psychology.
17. Lagnado, D., & Sloman, S.A. (2002). Learning causal structure. In W Gray & C. Schunn (Eds.), Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society, Fairfax, VA (pp. 560-565). London: Erlbaum.
18. Leslie, A.M., & Keeble, S. (1987). Do six-month-old infants perceive causality? Cognition, 25 (3), 265-288.
19. Masnick, A.M., & Klahr, D. (2003). Error matters: an initial exploration of elementary school children's understanding of experimental error. Journal of Cognition and Development, 4 (1), 67-98.
20. Novick, L.R., & Cheng, P.W. (2004). Assessing interactive causal influence. Psychological Review, 111 (2), 455-485.
21. Pearl, J. (1988). Probabilistic reasoning in intelligent systems. San Mateo, CA: Morgan Kaufmann.
22. Pearl, J. (2000). Causality. New York: Oxford University Press.
23. Rehder, B., & Hastie, R. (2001). Causal knowledge and categories: the effects of causal beliefs on categorization, induction, and similarity. Journal of Experimental Psychology: General, 3, 323-360.
24. Schulz., L.E., & Gopnik, A. (2004). Causal learning across domains. Developmental Psychology, 40 (2) 162-176.
25. Shanks, D.R. (1985). Forward and backward blocking in human contingency judgment. Quarterly Journal of Experimental Psychology: Comparative and Physiological Psychology, 37(1), 1-21.
26. Shanks, D.R., & Dickinson, A. (1987). Associative accounts of causality judgment. In G.H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory, Vol. 21 (pp. 229-261). San Diego, CA: Academic Press.
27. Shultz, T.R. (1982). Rules of causal attribution. Monographs of the Society for Research in Child Development, 47 (1), 1-51.
28. Schulz, L.E. (2003, April). The play's the thing: interventions and causal inference. Paper presented at the biennial meeting of the Society for Research in Child Development, Tampa, FL.
29. Sobel, D.M., Tenenbaum, J., & Gopnik, A. (2004). Children's causal inferences from indirect evidence: backwards blocking and Bayesian reasoning in preschoolers. Cognitive Science, 28, 303-333.
30. Spelke, E.S., Breinlinger, K., Macomber, J., &.Tacobson, K. (1992). Origins of knowledge. Psychological Review, 99 (4), 605-632.
31. Spellman, B.A. (1996). Acting as intuitive scientists: contingency judgments are made while controlling for alternative potential causes. Psychological Science, 1 (6), 337-342.
32. Spirtes, P., Glymour, C., & Scheines, R. (1993). Causation, prediction, and search (Springer lecture notes in statistics). New York: Springer-Verlag.
33. Steyvers, M., Tenenbaum, J., Wagenmakers, E.J., & Blum, B. (2003). Inferring causal networks from observations and interventions. Cognitive Science, 27, 453-489.
34. Tenenbaum, J.B., & Griffiths, T.L. (2003). Theory-based causal inference. In S. Becker, S. Thrun, & K. Obemayer (Eds.), Advances in neural information processing systems 15. Cambridge, MA: MIT Press.
35. Waldmann, M.R., & Hagmayer, Y. (2001). Estimating causal strength: the role of structural knowledge and processing effort. Cognition, 1, 27-58.
36. Woodward, J. (2003). Making things happen: A theory of causal explanation. New York: Oxford University Press.