1932

Abstract

Young children are adept at several types of scientific reasoning, yet older children and adults have difficulty mastering formal scientific ideas and practices. Why do “little scientists” often become scientifically illiterate adults? We address this question by examining the role of intuition in learning science, both as a body of knowledge and as a method of inquiry. Intuition supports children's understanding of everyday phenomena but conflicts with their ability to learn physical and biological concepts that defy firsthand observation, such as molecules, forces, genes, and germs. Likewise, intuition supports children's causal learning but provides little guidance on how to navigate higher-order constraints on scientific induction, such as the control of variables or the coordination of theory and data. We characterize the foundations of children's intuitive understanding of the natural world, as well as the conceptual scaffolds needed to bridge these intuitions with formal science.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-devpsych-060320-092346
2020-12-15
2024-03-28
Loading full text...

Full text loading...

/deliver/fulltext/devpsych/2/1/annurev-devpsych-060320-092346.html?itemId=/content/journals/10.1146/annurev-devpsych-060320-092346&mimeType=html&fmt=ahah

Literature Cited

  1. Alonzo AC, Steedle JT. 2009. Developing and assessing a force and motion learning progression. Sci. Educ. 93:389–421
    [Google Scholar]
  2. Amsterlaw J, Wellman HM. 2006. Theories of mind in transition: a microgenetic study of the development of false belief understanding. J. Cogn. Dev. 7:139–72
    [Google Scholar]
  3. Au TKF, Chan CK, Chan TK, Cheung M, Ho J, Ip G 2008. Folkbiology meets microbiology: a study of conceptual and behavioral change. Cogn. Psychol. 57:1–19
    [Google Scholar]
  4. Baillargeon R. 2004. Infants’ physical world. Curr. Dir. Psychol. Sci. 13:89–94
    [Google Scholar]
  5. Blacker KA, LoBue V. 2016. Behavioral avoidance of contagion in childhood. J. Exp. Child Psychol. 143:162–70
    [Google Scholar]
  6. Bonawitz EB, Schijndel TJV, Friel D, Schulz L 2012. Children balance theories and evidence in exploration, explanation, and learning. Cogn. Psychol. 64:215–34
    [Google Scholar]
  7. Bonawitz EB, Shafto P, Gweon H, Goodman ND, Spelke E, Schulz L 2011. The double-edged sword of pedagogy: Instruction limits spontaneous exploration and discovery. Cognition 120:322–30
    [Google Scholar]
  8. Borst A, Egelhaaf M. 1989. Principles of visual motion detection. Trends Neurosci 12:297–306
    [Google Scholar]
  9. Buchsbaum D, Gopnik A, Griffiths TL, Shafto P 2011. Children's imitation of causal action sequences is influenced by statistical and pedagogical evidence. Cognition 120:331–40
    [Google Scholar]
  10. Bullock M, Ziegler A. 1999. Scientific reasoning: developmental and individual differences. Individual Development from 3 to 12: Findings from the Munich Longitudinal Study FE Weinert, W Schneider 38–54 Cambridge, UK: Cambridge Univ. Press
    [Google Scholar]
  11. Butler LP, Markman EM. 2012. Preschoolers use intentional and pedagogical cues to guide inductive inferences and exploration. Child Dev 83:1416–28
    [Google Scholar]
  12. Callanan M, Legare CH, Sobel DM et al. 2020. Exploration, explanation, and parent–child interaction in museum settings. Monogr. Soc. Res. Child Dev. 85:1–137
    [Google Scholar]
  13. Carey S. 1985. Conceptual Change in Childhood Cambridge, MA: MIT Press
  14. Carey S. 2009. The Origin of Concepts Oxford, UK: Oxford Univ. Press
  15. Chang HY, Linn MC. 2013. Scaffolding learning from molecular visualizations. J. Res. Sci. Teach. 50:858–86
    [Google Scholar]
  16. Chen Z, Klahr D. 1999. All other things being equal: acquisition and transfer of the control of variables strategy. Child Dev 70:1098–120
    [Google Scholar]
  17. Chi M. 2000. Self-explaining expository texts: the dual processes of generating inferences and repairing mental models. Advances in Instructional Psychology: Educational Design and Cognitive Science R Glaser 161–238 Mahwah, NJ: Erlbaum
    [Google Scholar]
  18. Chi MT, Roscoe RD, Slotta JD, Roy M, Chase CC 2012. Misconceived causal explanations for emergent processes. Cogn. Sci. 36:1–61
    [Google Scholar]
  19. Chiang WC, Wynn K. 2000. Infants’ tracking of objects and collections. Cognition 77:169–95
    [Google Scholar]
  20. Chinn CA, Brewer WF. 1998. An empirical test of a taxonomy of responses to anomalous data in science. J. Res. Sci. Teach. 35:623–54
    [Google Scholar]
  21. Chouinard MM, Harris PL, Maratsos MP 2007. Children's questions: a mechanism for cognitive development. Monogr. Soc. Res. Child Dev. 72:1–129
    [Google Scholar]
  22. Clement J. 1993. Using bridging analogies and anchoring intuitions to deal with students’ preconceptions in physics. J. Res. Sci. Teach. 30:1241–57
    [Google Scholar]
  23. Clement J, Brown DE, Zietsman A 1989. Not all preconceptions are misconceptions: finding ‘anchoring conceptions’ for grounding instruction on students’ intuitions. Int. J. Sci. Educ. 11:554–65
    [Google Scholar]
  24. Clough E, Driver R. 1985. Secondary students’ conceptions of the conduction of heat: bringing together scientific and personal views. Phys. Educ. 20:176–82
    [Google Scholar]
  25. Coenen A, Ruggeri A, Bramley NR, Gureckis TM 2019. Testing one or multiple: how beliefs about sparsity affect causal experimentation. J. Exp. Psychol. Learn. Mem. Cogn. 45:1923–41
    [Google Scholar]
  26. Cook C, Goodman ND, Schulz LE 2011. Where science starts: spontaneous experiments in preschoolers’ exploratory play. Cognition 120:341–49
    [Google Scholar]
  27. Croker S, Buchanan H. 2011. Scientific reasoning in a real-world context: the effect of prior belief and outcome on children's hypothesis-testing strategies. Br. J. Dev. Psychol. 29:409–24
    [Google Scholar]
  28. Curtis V, Aunger R, Rabie T 2004. Evidence that disgust evolved to protect from risk of disease. Proc. R. Soc. B 271:S131–33
    [Google Scholar]
  29. Dar-Nimrod I, Heine SJ. 2011. Genetic essentialism: on the deceptive determinism of DNA. Psychol. Bull. 137:800–18
    [Google Scholar]
  30. DeJesus JM, Shutts K, Kinzler KD 2015. Eww she sneezed! Contamination context affects children's food preferences and consumption. Appetite 87:303–9
    [Google Scholar]
  31. Denison S, Xu F. 2019. Infant statisticians: the origins of reasoning under uncertainty. Perspect. Psychol. Sci. 14:499–509
    [Google Scholar]
  32. Duncan RG, Reiser BJ. 2007. Reasoning across ontologically distinct levels: students’ understandings of molecular genetics. J. Res. Sci. Teach. 44:938–59
    [Google Scholar]
  33. Engle J, Walker CM. 2018. Considering alternatives facilitates anomaly detection in preschoolers. Proceedings of the 40th Annual Conference of the Cognitive Science Society N Miyake, D Peebles, RP Cooper 348–53 Austin, TX: Cogn. Sci. Soc.
    [Google Scholar]
  34. Evans EM. 2001. Cognitive and contextual factors in the emergence of diverse belief systems: creation versus evolution. Cogn. Psychol. 42:217–66
    [Google Scholar]
  35. Fallon AE, Rozin P, Pliner P 1984. The child's conception of food: the development of food rejections with special reference to disgust and contamination sensitivity. Child Dev 55:566–75
    [Google Scholar]
  36. Frederick S. 2005. Cognitive reflection and decision making. J. Econ. Perspect. 19:25–42
    [Google Scholar]
  37. Fugelsang JA, Thompson VA. 2003. A dual-process model of belief and evidence interactions in causal reasoning. Mem. Cogn. 31:800–15
    [Google Scholar]
  38. Galinsky AD, Moskowitz GB. 2000. Counterfactuals as behavioral primes: priming the simulation heuristic and consideration of alternatives. J. Exp. Soc. Psychol. 36:384–409
    [Google Scholar]
  39. Geerdts MS, Van de Walle GA, LoBue V 2015. Daily animal exposure and children's biological concepts. J. Exp. Child Psychol. 130:132–46
    [Google Scholar]
  40. Gelman SA, Roberts SO. 2017. How language shapes the cultural inheritance of categories. PNAS 114:7900–7
    [Google Scholar]
  41. Gelman SA. 2003. The Essential Child: Origins of Essentialism in Everyday Thought Oxford, UK: Oxford Univ. Press
  42. Gopnik A, Glymour C, Sobel DM, Schulz LE, Kushnir T, Danks D 2004. A theory of causal learning in children: causal maps and Bayes nets. Psychol. Rev. 111:3–32
    [Google Scholar]
  43. Gopnik A, Wellman HM. 2012. Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory. Psychol. Bull. 138:1085–108
    [Google Scholar]
  44. Gopnik A. 2012. Scientific thinking in young children: theoretical advances, empirical research, and policy implications. Science 337:1623–27
    [Google Scholar]
  45. Griffiths TL, Sobel DM, Tenenbaum JB, Gopnik A 2011. Bayes and blickets: effects of knowledge on causal induction in children and adults. Cogn. Sci. 35:1407–55
    [Google Scholar]
  46. Gropen J, Clark‐Chiarelli N, Hoisington C, Ehrlich SB 2011. The importance of executive function in early science education. Child Dev. Perspect. 5:298–304
    [Google Scholar]
  47. Gutheil G, Vera A, Keil FC 1998. Do houseflies think? Patterns of induction and biological beliefs in development. Cognition 66:33–49
    [Google Scholar]
  48. Gweon H, Tenenbaum JB, Schulz LE 2010. Infants consider both the sample and the sampling process in inductive generalization. PNAS 107:9066–71
    [Google Scholar]
  49. Hardy I, Jonen A, Möller K, Stern E 2006. Effects of instructional support within constructivist learning environments for elementary school students’ understanding of floating and sinking. J. Educ. Psychol. 98:307–26
    [Google Scholar]
  50. Harlow DB, Swanson LH, Nylund‐Gibson K, Truxler A 2011. Using latent class analysis to analyze children's responses to the question, “What is a day?. Sci. Educ. 95:477–96
    [Google Scholar]
  51. Hayes BK, Goodhew A, Heit E, Gillan J 2003. The role of diverse instruction in conceptual change. J. Exp. Child Psychol. 86:253–76
    [Google Scholar]
  52. Herrmann P, Waxman SR, Medin DL 2010. Anthropocentrism is not the first step in children's reasoning about the natural world. PNAS 107:9979–84
    [Google Scholar]
  53. Hickling AK, Gelman SA. 1995. How does your garden grow? Early conceptualization of seeds and their place in the plant growth cycle. Child Dev 66:856–76
    [Google Scholar]
  54. Howe C, Tavares JT, Devine A 2012. Everyday conceptions of object fall: explicit and tacit understanding during middle childhood. J. Exp. Child Psychol. 111:351–66
    [Google Scholar]
  55. Inagaki K, Hatano G. 2004. Vitalistic causality in young children's naive biology. Trends Cogn. Sci. 8:356–62
    [Google Scholar]
  56. Jee BD, Anggoro FK. 2019. Relational scaffolding enhances children's understanding of scientific models. Psychol. Sci. 30:1287–302
    [Google Scholar]
  57. Jirout J, Klahr D. 2012. Children's scientific curiosity: in search of an operational definition of an elusive concept. Dev. Rev. 32:125–60
    [Google Scholar]
  58. Kaiser MK, Proffitt DR, McCloskey M 1985. The development of beliefs about falling objects. Percept. Psychophys. 38:533–39
    [Google Scholar]
  59. Kalish CW. 1996. Preschoolers’ understanding of germs as invisible mechanisms. Cogn. Dev. 11:83–106
    [Google Scholar]
  60. Kelemen D, Emmons NA, Seston Schillaci R, Ganea PA 2014. Young children can be taught basic natural selection using a picture-storybook intervention. Psychol. Sci. 25:893–902
    [Google Scholar]
  61. Kim E, Pak SJ. 2002. Students do not overcome conceptual difficulties after solving 1000 traditional problems. Am. J. Phys. 70:759–65
    [Google Scholar]
  62. Kimura K, Gopnik A. 2019. Rational higher-order belief revision in young children. Child Dev 90:91–97
    [Google Scholar]
  63. Kirschner PA, Sweller J, Clark RE 2006. Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educ. Psychol. 41:75–86
    [Google Scholar]
  64. Klahr D. 2000. Exploring Science: The Cognition and Development of Discovery Processes Cambridge, MA: MIT Press
  65. Klahr D, Fay AL, Dunbar K 1993. Heuristics for scientific experimentation: a developmental study. Cogn. Psychol. 25:111–46
    [Google Scholar]
  66. Klahr D, Nigam M. 2004. The equivalence of learning paths in early science instruction: effects of direct instruction and discovery learning. Psychol. Sci. 15:661–67
    [Google Scholar]
  67. Klahr D, Zimmerman C, Jirout J 2011. Educational interventions to advance children's scientific thinking. Science 333:971–75
    [Google Scholar]
  68. Köksal-Tuncer Ö, Sodian B 2018. The development of scientific reasoning: hypothesis testing and argumentation from evidence in young children. Cogn. Dev. 48:135–45
    [Google Scholar]
  69. Koslowski B. 1996. Theory and Evidence: The Development of Scientific Reasoning Cambridge, MA: MIT Press
  70. Kuhn D. 2012. The development of causal reasoning. WIREs Cogn. Sci. 3:327–35
    [Google Scholar]
  71. Kuhn D, Dean JD. 2004. Metacognition: a bridge between cognitive psychology and educational practice. Theory Pract 43:268–73
    [Google Scholar]
  72. Kuhn D, Dean JD. 2005. Is developing scientific thinking all about learning to control variables. ? Psychol. Sci. 16:866–70
    [Google Scholar]
  73. Kuhn D, Garcia-Mila M, Zohar A, Andersen C, White SH et al. 1995. Strategies of knowledge acquisition. Monogr. Soc. Res. Child Dev. 60:1–157
    [Google Scholar]
  74. Kuhn D, Katz J. 2009. Are self-explanations always beneficial. ? J. Exp. Child Psychol. 103:386–94
    [Google Scholar]
  75. Kuhn D, Ramsey S, Arvidsson TS 2015. Developing multivariable thinkers. Cogn. Dev. 35:92–110
    [Google Scholar]
  76. Lapidow E, Walker CM. 2020a. Informative experimentation in intuitive science: Children select and learn from their own causal interventions. Cognition 201:104315
    [Google Scholar]
  77. Lapidow E, Walker CM. 2020b. The search for invariance: repeated positive testing serves the goals of causal learning. Language and Concept Acquisition from Infancy Through Childhood J Childers 197–219 Berlin: Springer
    [Google Scholar]
  78. Lederman JS, Lederman NG, Bartos SA, Bartels SL, Meyer AA, Schwartz RS 2014. Meaningful assessment of learners’ understandings about scientific inquiry: the Views About Scientific Inquiry (VASI) questionnaire. J. Res. Sci. Teach. 51:65–83
    [Google Scholar]
  79. Legare CH, Lombrozo T. 2014. Selective effects of explanation on learning during early childhood. J. Exp. Child Psychol. 126:198–212
    [Google Scholar]
  80. Legare CH, Opfer JE, Busch JT, Shtulman A 2018. A field guide for teaching evolution in the social sciences. Evol. Hum. Behav. 39:257–68
    [Google Scholar]
  81. Lewis EL, Linn MC. 2003. Heat energy and temperature concepts of adolescents, adults, and experts: implications for curricular improvements. J. Res. Sci. Teach. 40:S155–75
    [Google Scholar]
  82. Masnick AM, Klahr D, Knowles ER 2017. Data-driven belief revision in children and adults. J. Cogn. Dev. 18:87–109
    [Google Scholar]
  83. Mason L, Zaccoletti S. 2020. Inhibition and conceptual learning in science: a review of studies. Educ. Psychol. Rev. https://doi.org/10.1007/s10648-020-09529-x
    [Crossref] [Google Scholar]
  84. Mayer RE. 2004. Should there be a three-strikes rule against pure discovery learning. ? Am. Psychol. 59:14–19
    [Google Scholar]
  85. Mayr E. 1982. The Growth of Biological Thought Cambridge, MA: Harvard Univ. Press
  86. McCloskey M. 1983. Naïve theories of motion. Mental Models D Gentner, AL Stevens 299–324 Mahwah, NJ: Erlbaum
    [Google Scholar]
  87. McCormack T, Bramley NR, Frosch C, Patrick F, Lagnado DA 2016. Children's use of interventions to learn causal structure. J. Exp. Child Psychol. 141:1–22
    [Google Scholar]
  88. McPhetres J, Rutjens BT, Weinstein N, Brisson JA 2019. Modifying attitudes about modified foods: Increased knowledge leads to more positive attitudes. J. Environ. Psychol. 64:21–29
    [Google Scholar]
  89. Mead LS, Mates A. 2009. Why science standards are important to a strong science curriculum and how states measure up. Evol. Educ. Outreach 2:359–71
    [Google Scholar]
  90. Medin D, Waxman S, Woodring J, Washinawatok K 2010. Human-centeredness is not a universal feature of young children's reasoning: Culture and experience matter when reasoning about biological entities. Cogn. Dev. 25:197–207
    [Google Scholar]
  91. Meltzoff AN, Waismeyer A, Gopnik A 2012. Learning about causes from people: observational causal learning in 24-month-old infants. Dev. Psychol. 48:1215–28
    [Google Scholar]
  92. Mills CM. 2013. Knowing when to doubt: developing a critical stance when learning from others. Dev. Psychol. 49:404–18
    [Google Scholar]
  93. Natl. Res. Counc 2000. Inquiry and the National Science Education Standards: A Guide for Teaching and Learning Washington, DC: Natl. Acad. Press
  94. Natl. Sci. Board 2018. Science & Engineering Indicators–2000 Arlington, VA: Natl. Sci. Found.
  95. Nenciovici L, Brault Foisy LM, Allaire‐Duquette G, Potvin P, Riopel M, Masson S 2018. Neural correlates associated with novices correcting errors in electricity and mechanics. Mind Brain Educ 12:120–39
    [Google Scholar]
  96. Nyhout A, Iannuzziello A, Walker CM, Ganea PA 2019. Thinking counterfactually supports children's ability to conduct a controlled test of a hypothesis. Proceedings of the 41st Annual Meeting of the Cognitive Science Society A Goel, C Seifert, C Freska 2488–94 Austin, TX: Cogn. Sci. Soc.
    [Google Scholar]
  97. Pacer M, Lombrozo T. 2017. Ockham's razor cuts to the root: simplicity in causal explanation. J. Exp. Psychol. 146:1761–80
    [Google Scholar]
  98. Penner DE, Klahr D. 1996. The interaction of domain-specific knowledge and domain-general discovery strategies: a study with sinking objects. Child Dev 67:2709–27
    [Google Scholar]
  99. Pew Res. Cent 2015. Public and scientists’ views on science and society Rep., Pew Res. Cent Washinton, DC:
  100. Piaget J. 1929. The Child's Conception of the World London: Routledge
  101. Piekny J, Maehler C. 2013. Scientific reasoning in early and middle childhood: the development of domain-general evidence evaluation, experimentation, and hypothesis generation skills. Br. J. Dev. Psychol. 31:153–79
    [Google Scholar]
  102. Plummer JD, Krajcik J. 2010. Building a learning progression for celestial motion: elementary levels from an earth‐based perspective. J. Res. Sci. Teach. 47:768–87
    [Google Scholar]
  103. Potvin P, Masson S, Lafortune S, Cyr G 2015. Persistence of the intuitive conception that heavier objects sink more: a reaction time study with different levels of interference. Int. J. Sci. Math. Educ. 13:21–43
    [Google Scholar]
  104. Reiner M, Slotta JD, Chi MT, Resnick LB 2000. Naive physics reasoning: a commitment to substance-based conceptions. Cogn. Instrum. 18:1–34
    [Google Scholar]
  105. Rosander K, von Hofsten C 2004. Infants’ emerging ability to represent occluded object motion. Cognition 91:1–22
    [Google Scholar]
  106. Rozin P, Haidt J, McCauley CR 2008. Disgust. Handbook of Emotions M Lewis, JM Haviland-Jones, LF Barrett 757–76 New York: Guilford
    [Google Scholar]
  107. Ruggeri A, Lombrozo T. 2011. Children adapt their questions to achieve efficient search. Cognition 143:203–16
    [Google Scholar]
  108. Ruggeri A, Sim ZL, Xu F 2017. “Why is Toma late to school again?” Preschoolers identify the most informative questions. Dev. Psychol. 53:1620–32
    [Google Scholar]
  109. Ruggeri A, Swaboda N, Sim ZL, Gopnik A 2019. Shake it baby, but only when needed: Preschoolers adapt their exploratory strategies to the information structure of the task. Cognition 193:104013
    [Google Scholar]
  110. Samarapungavan A, Bryan L, Wills J 2017. Second graders’ emerging particle models of matter in the context of learning through model‐based inquiry. J. Res. Sci. Teach. 54:988–1023
    [Google Scholar]
  111. Samarapungavan A, Vosniadou S, Brewer WF 1996. Mental models of the earth, sun, and moon: Indian children's cosmologies. Cogn. Dev. 11:491–521
    [Google Scholar]
  112. Sandoval WA, Sodian B, Koerber S, Wong J 2014. Developing children's early competencies to engage with science. Educ. Psychol. 49:139–52
    [Google Scholar]
  113. Saxe R, Carey S. 2006. The perception of causality in infancy. Acta Psychol 123:144–65
    [Google Scholar]
  114. Schauble L, Klopfer LE, Raghavan K 1991. Students transition from an engineering model to a science model of experimentation. J. Res. Sci. Teach. 28:859–82
    [Google Scholar]
  115. Schauble L. 1990. Belief revision in children: the role of prior knowledge and strategies for generating evidence. J. Exp. Child Psychol. 49:31–57
    [Google Scholar]
  116. Schneider W. 2008. The development of metacognitive knowledge in children and adolescents: major trends and implications for education. Mind Brain Educ 2:114–21
    [Google Scholar]
  117. Scholl BJ, Pylyshyn ZW. 1999. Tracking multiple items through occlusion: clues to visual objecthood. Cogn. Psychol. 38:259–90
    [Google Scholar]
  118. Schulz LE, Bonawitz E. 2007. Serious fun: Preschoolers engage in more exploratory play when evidence is confounded. Dev. Psychol. 43:1045–50
    [Google Scholar]
  119. Schulz LE, Goodman ND, Tenenbaum JB, Jenkins AC 2008. Going beyond the evidence: abstract laws and preschoolers’ response to anomalous data. Cognition 109:211–23
    [Google Scholar]
  120. Schulz LE, Gopnik A, Glymour C 2007. Preschool children learn about causal structure from conditional interventions. Dev. Sci. 10:322–32
    [Google Scholar]
  121. Schulz LE, Sommerville J. 2006. God does not play dice: causal determinism and children's inferences about unobserved causes. Child Dev 77:427–42
    [Google Scholar]
  122. Schwichow M, Croker S, Zimmerman C, Höffler T, Härtig H 2016. Teaching the control-of-variables strategy: a meta-analysis. Dev. Rev. 39:37–63
    [Google Scholar]
  123. Shtulman A. 2006. Qualitative differences between naïve and scientific theories of evolution. Cogn. Psychol. 52:170–94
    [Google Scholar]
  124. Shtulman A. 2013. Epistemic similarities between students’ scientific and supernatural beliefs. J. Educ. Psychol. 105:199–212
    [Google Scholar]
  125. Shtulman A. 2017. Scienceblind: Why Our Intuitive Theories About the World Are So Often Wrong New York: Basic
  126. Shtulman A. 2019. Doubly counterintuitive: cognitive obstacles to the discovery and the learning of scientific ideas and why they often differ. Advances in Experimental Philosophy of Science R Samuels, D Wilkenfeld 97–121 London: Bloomsbury
    [Google Scholar]
  127. Shtulman A, Legare CH. 2020. Competing explanations of competing explanations: accounting for conflict between scientific and folk explanations. Top. Cogn. Sci. In press. https://doi.org/10.1111/tops.12483
    [Crossref] [Google Scholar]
  128. Shtulman A, Neal C, Lindquist G 2016. Children's ability to learn evolutionary explanations for biological adaptation. Early Educ. Dev. 27:1222–36
    [Google Scholar]
  129. Shtulman A, Schulz L. 2008. The relation between essentialist beliefs and evolutionary reasoning. Cogn. Sci. 32:1049–62
    [Google Scholar]
  130. Siegal M, Butterworth G, Newcombe PA 2004. Culture and children's cosmology. Dev. Sci. 7:308–24
    [Google Scholar]
  131. Slaughter V, Lyons M. 2003. Learning about life and death in early childhood. Cogn. Psychol. 46:1–30
    [Google Scholar]
  132. Slotta JD, Chi MT, Joram E 1995. Assessing students’ misclassifications of physics concepts: an ontological basis for conceptual change. Cogn. Instrum. 13:373–400
    [Google Scholar]
  133. Slotta JD, Chi MT. 2006. Helping students understand challenging topics in science through ontology training. Cogn. Instrum. 24:261–89
    [Google Scholar]
  134. Smith CL. 2007. Bootstrapping processes in the development of students’ commonsense matter theories: using analogical mappings, thought experiments, and learning to measure to promote conceptual restructuring. Cogn. Instrum. 25:337–98
    [Google Scholar]
  135. Smith CL, Solomon GE, Carey S 2005. Never getting to zero: elementary school students’ understanding of the infinite divisibility of number and matter. Cogn. Psychol. 51:101–40
    [Google Scholar]
  136. Smith CL, Wenk L. 2006. Relations among three aspects of first‐year college students’ epistemologies of science. J. Res. Sci. Teach. 43:747–85
    [Google Scholar]
  137. Sobel DM, Erb CD, Tassin T, Weisberg DS 2017. The development of diagnostic inference about uncertain causes. J. Cogn. Dev. 18:556–76
    [Google Scholar]
  138. Sobel DM, Legare CH. 2014. Causal learning in children. WIREs Cogn. Sci. 5:413–27
    [Google Scholar]
  139. Sobel DM, Letourneau SM. 2018. Preschoolers’ understanding of how others learn through action and instruction. Child Dev 89:961–70
    [Google Scholar]
  140. Sodian B, Zaitchik D, Carey S 1991. Young children's differentiation of hypothetical beliefs from evidence. Child Dev 62:753–66
    [Google Scholar]
  141. Solomon GE, Cassimatis NL. 1999. On facts and conceptual systems: young children's integration of their understandings of germs and contagion. Dev. Psychol. 35:113–26
    [Google Scholar]
  142. Solomon GE, Johnson SC, Zaitchik D, Carey S 1996. Like father, like son: young children's understanding of how and why offspring resemble their parents. Child Dev 67:151–71
    [Google Scholar]
  143. Sousa P, Atran S, Medin D 2002. Essentialism and folkbiology: evidence from Brazil. J. Cogn. Cult. 2:195–223
    [Google Scholar]
  144. Spelke ES. 1994. Initial knowledge: six suggestions. Cognition 50:431–45
    [Google Scholar]
  145. Springer K. 1995. Acquiring a naive theory of kinship through inference. Child Dev 66:547–58
    [Google Scholar]
  146. Stahl AE, Feigenson L. 2015. Observing the unexpected enhances infants’ learning and exploration. Science 348:91–94
    [Google Scholar]
  147. Stavy R, Wax N. 1989. Children's conceptions of plants as living things. Hum. Dev. 32:88–94
    [Google Scholar]
  148. Tardiff N, Bascandziev I, Carey S, Zaitchik D 2020. Specifying the domain-general resources that contribute to conceptual construction: evidence from the child's acquisition of vitalist biology. Cognition 195:104090
    [Google Scholar]
  149. Tenenbaum JB, Griffiths TL, Kemp C 2006. Theory-based Bayesian models of inductive learning and reasoning. Trends Cogn. Sci. 10:309–18
    [Google Scholar]
  150. Thagard P. 2000. How Scientists Explain Disease Princeton, NJ: Princeton Univ. Press
  151. Tschirgi JE. 1980. Sensible reasoning: a hypothesis about hypotheses. Child Dev 51:1–10
    [Google Scholar]
  152. Valanides N, Papageorgiou M, Angeli C 2014. Scientific investigations of elementary school children. J. Sci. Educ. Technol. 23:26–36
    [Google Scholar]
  153. van der Graaf J, Segers E, Verhoeven L 2016. Scientific reasoning in kindergarten: cognitive factors in experimentation and evidence evaluation. Learn. Individ. Differ. 49:190–200
    [Google Scholar]
  154. van Schijndel TJV, Visser I, Bers BMV, Raijmakers ME 2015. Preschoolers perform more informative experiments after observing theory-violating evidence. J. Exp. Child Psychol. 131:104–19
    [Google Scholar]
  155. Venkadasalam VP, Ganea PA. 2018. Do objects of different weight fall at the same time? Updating naive beliefs about free-falling objects from fictional and informational books in young children. J. Cogn. Dev. 19:165–81
    [Google Scholar]
  156. Venville G, Gribble SJ, Donovan J 2005. An exploration of young children's understandings of genetics concepts from ontological and epistemological perspectives. Sci. Educ. 89:614–33
    [Google Scholar]
  157. Vosniadou S 2009. International Handbook of Research on Conceptual Change New York: Routledge
  158. Vosniadou S, Brewer WF. 1992. Mental models of the earth: a study of conceptual change in childhood. Cogn. Psychol. 24:535–85
    [Google Scholar]
  159. Vosniadou S, Ioannides C, Dimitrakopoulou A, Papademetriou E 2001. Designing learning environments to promote conceptual change in science. Learn. Instrum. 11:381–419
    [Google Scholar]
  160. Vosniadou S, Pnevmatikos D, Makris N, Lepenioti D, Eikospentaki K et al. 2018. The recruitment of shifting and inhibition in on-line science and mathematics tasks. Cogn. Sci. 42:1860–86
    [Google Scholar]
  161. Walker CM, Bonawitz E, Lombrozo T 2017. Effects of explaining on children's preference for simpler hypotheses. Psychon. Bull. Rev. 24:1538–47
    [Google Scholar]
  162. Walker CM, Gopnik A. 2014. Toddlers infer higher-order relational principles in causal learning. Psychol. Sci. 25:161–69
    [Google Scholar]
  163. Walker CM, Lombrozo T, Legare CH, Gopnik A 2014. Explaining prompts children to privilege inductively rich properties. Cognition 133:343–57
    [Google Scholar]
  164. Walker CM, Lombrozo T, Williams JJ, Rafferty AN, Gopnik A 2016. Explaining constrains causal learning in childhood. Child Dev 88:229–46
    [Google Scholar]
  165. Walker CM, Lombrozo T. 2017. Explaining the moral of the story. Cognition 167:266–81
    [Google Scholar]
  166. Walker CM, Nyhout A. 2020. Asking “why?” and “what if?”: the influence of questions on children's inferences. The Questioning Child: Insights from Psychology and Education L Butler, S Ronfard, K Corriveau 252–80 Cambridge, UK: Cambridge Univ. Press
    [Google Scholar]
  167. Walker CM, Rett A, Bonawitz E 2020. Design drives discovery in causal learning. Psychol. Sci. 31:129–38
    [Google Scholar]
  168. Ware EA, Gelman SA. 2014. You get what you need: an examination of purpose‐based inheritance reasoning in undergraduates, preschoolers, and biological experts. Cogn. Sci. 38:197–243
    [Google Scholar]
  169. Weissman MD, Kalish CW. 1999. The inheritance of desired characteristics: children's view of the role of intention in parent–offspring resemblance. J. Exp. Child Psychol. 73:245–65
    [Google Scholar]
  170. Williams JJ, Lombrozo T. 2010. The role of explanation in discovery and generalization: evidence from category learning. Cogn. Sci. 34:776–806
    [Google Scholar]
  171. Xu F, Garcia V. 2008. Intuitive statistics by 8-month-old infants. PNAS 105:5012–15
    [Google Scholar]
  172. Xu F. 2019. Towards a rational constructivist theory of cognitive development. Psychol. Rev. 126:841–64
    [Google Scholar]
  173. Young AG, Shtulman A. 2020a. Children's cognitive reflection predicts conceptual understanding in science and mathematics. Psychol. Sci. In press
    [Google Scholar]
  174. Young AG, Shtulman A. 2020b. How children's cognitive reflection shapes their science understanding. Front. Psychol. 11:1247
    [Google Scholar]
  175. Zaitchik D, Iqbal Y, Carey S 2014. The effect of executive function on biological reasoning in young children: an individual differences study. Child Dev 85:160–75
    [Google Scholar]
  176. Zaitchik D, Solomon GE. 2008. Animist thinking in the elderly and in patients with Alzheimer's disease. Cogn. Neuropsychol. 25:27–37
    [Google Scholar]
  177. Zimmerman C. 2007. The development of scientific thinking skills in elementary and middle school. Dev. Rev. 27:172–223
    [Google Scholar]
  178. Zimmerman C, Cuddington K. 2007. Ambiguous, circular and polysemous: students’ definitions of the “balance of nature” metaphor. Public Underst. Sci. 16:393–406
    [Google Scholar]
/content/journals/10.1146/annurev-devpsych-060320-092346
Loading
  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error