A contrastive account of explanation generation

Brief Report

Abstract

In this article, we propose a contrastive account of explanation generation. Though researchers have long wrestled with the concepts of explanation and understanding, as well as with the procedures by which we might evaluate explanations, less attention has been paid to the initial generation stages of explanation. Before an explainer can answer a question, he or she must come to some understanding of the explanandum—what the question is asking—and of the explanatory form and content called for by the context. Here candidate explanations are constructed to respond to the particular interpretation of the question, which, according to the pragmatic approach to explanation, is constrained by a contrast class—a set of related but nonoccurring alternatives to the topic that emerge from the surrounding context and the explainer’s prior knowledge. In this article, we suggest that generating an explanation involves two operations: one that homes in on an interpretation of the question, and a second one that locates an answer. We review empirical work that supports this account, consider the implications of these contrastive processes, and identify areas for future study.

Keywords

Explanation Contrast class Context 

References

  1. Brem, S. K., & Rips, L. J. (2000). Explanation and evidence in informal argument. Cognitive Science, 24, 573–604.CrossRefGoogle Scholar
  2. Chaigneau, S. E., Barsalou, L. W., & Sloman, S. A. (2004). Assessing the causal structure of function. Journal of Experimental Psychology: General, 133, 601–625. doi:10.1037/0096-3445.133.4.601 CrossRefGoogle Scholar
  3. Cheng, P. W., & Novick, L. R. (1992). Covariation in natural causal induction. Psychological Review, 99, 365–382.CrossRefPubMedGoogle Scholar
  4. Chi, M. T. (2000). Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. In R. Glaser (Ed.), Advances in instructional psychology (pp. 161–238). Mahwah, NJ: Erlbaum.Google Scholar
  5. Chi, M. T. H., de Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18, 439–477.Google Scholar
  6. Chin-Parker, S., & Bradner, A. (2010). Background shifts affect explanatory style: How a pragmatic theory of explanation accounts for background effects in the generation of explanations. Cognitive Processing, 11, 227–249.CrossRefPubMedGoogle Scholar
  7. Chin-Parker, S., & Cantelon, J. (2016). Contrastive constraints guide explanation-based category learning. Cognitive Science. Advance online publication. doi:10.1111/cogs.12405
  8. Cimpian, A. (2015). The inherence heuristic: Generating everyday explanations. In R. Scott & S. Kosslyn (Eds.), Emerging Trends in the Social and Behavioral Sciences (pp. 1–15). Hoboken, NJ: John Wiley and Sons.Google Scholar
  9. Colombo, M. (2017). Experimental philosophy of explanation rising: The case for a plurality of concepts of explanation. Cognitive Science, 41, 503–517.Google Scholar
  10. Craik, K. J. W. (1967). The nature of explanation (2nd ed.). Cambridge, UK: Cambridge University Press.Google Scholar
  11. Davis, T., & Love, B. C. (2010). Memory for category information is idealized through contrast with competing options. Psychological Science, 21, 234–242.CrossRefPubMedGoogle Scholar
  12. Dretske, F. (1981). The pragmatic dimension of knowledge. Philosophical Studies, 40, 363–378.CrossRefGoogle Scholar
  13. Dumas, D., Alexander, P. A., & Grossnickle, E. M. (2013). Relational reasoning and its manifestations in the educational context: A systematic review of the literature. Educational Psychology Review, 25, 391–427.CrossRefGoogle Scholar
  14. Ellman, T. (1989). Explanation-based learning: A survey of programs and perspectives. ACM Computing Surveys, 21, 163–221.CrossRefGoogle Scholar
  15. Garfinkel, A. (1990). Forms of explanation: Rethinking the questions in social theory. New Haven, CT: Yale University Press.Google Scholar
  16. Gentner, D., & Markman, A. B. (1997). Structure mapping in analogy and similarity. American Psychologist, 52, 45–56. doi:10.1037/0003-066X.52.1.45 CrossRefGoogle Scholar
  17. Gentner, D., & Stevens, A. L. (Eds.). (1983). Mental models. Hillsdale, NJ: Erlbaum.Google Scholar
  18. Goldman, A. I. (1976). Discrimination and perceptual knowledge. Journal of Philosophy, 73, 771–791.CrossRefGoogle Scholar
  19. Goldstone, R. L. (1996). Isolated and interrelated concepts. Memory & Cognition, 24, 608–628. doi:10.3758/BF03201087 CrossRefGoogle Scholar
  20. Griffiths, T. L., & Tenenbaum, J. B. (2009). Theory-based causal induction. Psychological Review, 116, 661–716. doi:10.1037/a0017201 CrossRefPubMedGoogle Scholar
  21. Hale, C. R., & Barsalou, L. W. (1995). Explanation content and construction during system learning and troubleshooting. Journal of the Learning Sciences, 4, 385–436.CrossRefGoogle Scholar
  22. Hilton, D. J. (1990). Conversational processes and causal explanation. Psychological Bulletin, 107, 65–81. doi:10.1037/0033-2909.107.1.65 CrossRefGoogle Scholar
  23. Hilton, D. J., & Erb, H. (1996). Mental models and causal explanation: Judgments of probable cause and explanatory relevance. Thinking & Reasoning, 2, 273–308.CrossRefGoogle Scholar
  24. Hilton, D. J., & Slugoski, B. R. (1986). Knowledge-based causal attribution: The abnormal conditions focus model. Psychological Review, 93, 75–88. doi:10.1037/0033-295X.93.1.75 CrossRefGoogle Scholar
  25. Hitchcock, C., & Knobe, J. (2009). Cause and norm. Journal of Philosophy, 106, 587–612.CrossRefGoogle Scholar
  26. Holyoak, K. J. (2012). Analogy and relational reasoning. In K. J. Holyoak & R. G. Morrison (Eds.), The Oxford handbook of thinking and reasoning (pp. 234–259). Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
  27. Hummel, J. E., Licato, J., & Bringsjord, S. (2014). Analogy, explanation, and proof. Frontiers in Human Neuroscience, 8, 867. doi:10.3389/fnhum.2014.00867 CrossRefPubMedPubMedCentralGoogle Scholar
  28. Johnson-Laird, P. N. (1983). Mental models. Cambridge, MA: Harvard University Press.Google Scholar
  29. Jones, M., & Love, B. C. (2011). Bayesian fundamentalism or enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition. Behavioral and Brain Sciences, 34, 169–188.CrossRefPubMedGoogle Scholar
  30. Keil, F. C. (2006). Explanation and understanding. Annual Review of Psychology, 57, 227–254.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Kemp, C., Tenenbaum, J. B., Niyogi, S., & Griffiths, T. L. (2010). A probabilistic model of theory formation. Cognition, 114, 165–196.CrossRefPubMedGoogle Scholar
  32. Legare, C. H., & Lombrozo, T. L. (2014). Selective effects of explanation on learning during early childhood. Journal of Experimental Child Psychology, 126, 198–212.CrossRefPubMedGoogle Scholar
  33. Lombrozo, T. (2006). The structure and function of explanations. Trends in Cognitive Sciences, 10, 464–470.CrossRefPubMedGoogle Scholar
  34. Lombrozo, T. (2007). Simplicity and probability in causal explanation. Cognitive Psychology, 55, 232–257.CrossRefPubMedGoogle Scholar
  35. Lombrozo, T. (2009). Explanation and categorization: How “why?” informs “what?”. Cognition, 110, 248–253.CrossRefPubMedGoogle Scholar
  36. Lombrozo, T. (2011). The instrumental value of explanation. Philosophy Compass, 6(8), 539–551.CrossRefGoogle Scholar
  37. Lombrozo, T. (2012). Explanation and abductive inference. In K. J. Holyoak & R. G. Morrison (Eds.), The Oxford handbook of thinking and reasoning (pp. 260–276). Oxford, UK: Oxford University Press.Google Scholar
  38. Lombrozo, T., & Carey, S. (2006). Functional explanation and the function of explanation. Cognition, 99, 167–204.CrossRefPubMedGoogle Scholar
  39. Lombrozo, T., & Gwynne, N. Z. (2014). Explanation and inference: Mechanistic and functional explanations guide property generalization. Frontiers in Human Neuroscience, 8, 700. doi:10.3389/fnhum.2014.00700 CrossRefPubMedPubMedCentralGoogle Scholar
  40. Macrae, C. N., Bodenhausen, G. V., & Milne, A. B. (1995). The dissection of selection in person perception: Inhibitory processes in social stereotyping. Journal of Personality and Social Psychology, 69, 397–407.CrossRefPubMedGoogle Scholar
  41. McGill, A. L., & Klein, J. G. (1993). Contrastive and counterfactual reasoning in causal judgment. Journal of Personality and Social Psychology, 64, 897–905.CrossRefGoogle Scholar
  42. Medin, D. L., Goldstone, R. L., & Gentner, D. (1993). Respects for similarity. Psychological Review, 100, 254–278. doi:10.1037/0033-295X.100.2.254 CrossRefGoogle Scholar
  43. Medin, D. L., & Ross, B. H. (1989). The specific character of abstract thought: Categorization, problem solving, and induction. In R. J. Sternberg (Ed.), Advances in the psychology of human intelligence (Vol. 5, pp. 189–223). Hillsdale, NJ; Erlbaum.Google Scholar
  44. Pacer, M., Williams, J., Chen, X., Lombrozo, T., & Griffiths, T. (2013). Evaluating computational models of explanation using human judgments. In A. Nicholson & P. Smyth (Eds.), Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Ninth Conference (2013) (pp. 498–507). Corvallis, OR: AUAI Press. arXiv:1309.6855Google Scholar
  45. Patalano, A. L., Chin-Parker, S., & Ross, B. H. (2006). The importance of being coherent: Category coherence, cross-classification, and reasoning. Journal of Memory and Language, 54, 407–424.CrossRefGoogle Scholar
  46. Prasada, S., & Dillingham, E. M. (2009). Representation of principled connections: A window onto the formal aspect of common sense conception. Cognitive Science, 33, 401–448.CrossRefPubMedGoogle Scholar
  47. Read, S. J. (1987). Constructing causal scenarios: A knowledge structure approach to causal reasoning. Journal of Personality and Social Psychology, 52, 288–302.CrossRefPubMedGoogle Scholar
  48. Richey, J. E., & Nokes-Malach, T. J. (2015). Comparing four instructional techniques for promoting robust knowledge. Educational Psychology Review, 27, 181–218.CrossRefGoogle Scholar
  49. Rips, L. J., & Edwards, B. J. (2013). Inference and explanation in counterfactual reasoning. Cognitive Science, 37, 1107–1135.CrossRefPubMedGoogle Scholar
  50. Ross, B. H., & Murphy, G. L. (1999). Food for thought: Cross-classification and category organization in a complex real-world domain. Cognitive Psychology, 38, 495–553.CrossRefPubMedGoogle Scholar
  51. Rottman, B. M., & Keil, F. C. (2011). What matters in scientific explanation: Effects of elaboration and content. Cognition, 121, 324–337. doi:10.1016/j.cognition.2011.08.009 CrossRefPubMedPubMedCentralGoogle Scholar
  52. Saatsi, J., & Pexton, M. (2013). Reassessing Woodward’s account of explanation: Regularities, counterfactuals, and non-causal explanations. Philosophy of Science, 80, 613–624.CrossRefGoogle Scholar
  53. Schaffer, J. (2008). The contrast-sensitivity of knowledge ascriptions. Social Epistemology, 22, 235–245.CrossRefGoogle Scholar
  54. Schank, R. C. (1982). Dynamic memory: A theory of learning in people and computers. New York, NY: Cambridge University Press.Google Scholar
  55. Shafto, P., Kemp, C., Mansinghka, V., & Tenenbaum, J. B. (2011). A probabilistic model of cross-categorization. Cognition, 120, 1–25.CrossRefPubMedGoogle Scholar
  56. Shemwell, J. T., Chase, C. C., & Schwartz, D. L. (2015). Seeking the general explanation: A test of inductive activities for learning and transfer. Journal of Research in Science Teaching, 52, 58–83.CrossRefGoogle Scholar
  57. Sinnott-Armstrong, W. (2008). A contrastivist manifesto. Social Epistemology, 22, 257–270.CrossRefGoogle Scholar
  58. Skow, B. (2014). Are there non-causal explanations (of particular events)? British Journal for the Philosophy of Science, 65, 445–467.CrossRefGoogle Scholar
  59. Sperber, D., & Wilson, D. (1986). Relevance: Communication and cognition. Cambridge, MA: Harvard University Press.Google Scholar
  60. Tenenbaum, J. B., Griffiths, T. L., & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences, 10, 309–318.CrossRefPubMedGoogle Scholar
  61. Thagard, P. (2006). Evaluating explanations in law, science, and everyday life. Current Directions in Psychological Science, 15, 141–145.CrossRefGoogle Scholar
  62. Van Bouwel, J., & Weber, E. (2008). A pragmatist defense of non-relativistic explanatory pluralism in history and social science. History and Theory, 47, 168–182.CrossRefGoogle Scholar
  63. van Fraassen, B. (1980). The scientific image. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
  64. Verheyen, S., De Deyne, S., Dry, M. J., & Storms, G. (2011). Uncovering contrast categories in categorization with a probabilistic threshold model. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 1515–1531.PubMedGoogle Scholar
  65. Voorspoels, W., Storms, G., & Vanpaemel, W. (2012). Contrast effects in typicality judgments: A hierarchical Bayesian approach. Quarterly Journal of Experimental Psychology, 65, 1721–1739.CrossRefGoogle Scholar
  66. Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92, 548–573. doi:10.1037/0033-295X.92.4.548 CrossRefPubMedGoogle Scholar
  67. Williams, J. J., & Lombrozo, T. (2010). The role of explanation in discovery and generalization: Evidence from category learning. Cognitive Science, 34, 776–806.CrossRefPubMedGoogle Scholar
  68. Williams, J. J., & Lombrozo, T. (2013). Explanation and prior knowledge interact to guide learning. Cognitive Psychology, 66, 55–84.CrossRefPubMedGoogle Scholar
  69. Wilson, R. A., & Keil, F. C. (2000). The shadows and shallows of explanation. In F. C., Keil, & R. A. Wilson (Eds.) Explanation and cognition (pp. 87–114). Cambridge, MA: MIT Press.Google Scholar
  70. Yeh, W., & Barsalou, L. W. (2006). The situated nature of concepts. American Journal of Psychology, 119, 349–384.CrossRefPubMedGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2017

Authors and Affiliations

  1. 1.Department of PsychologyDenison UniversityGranvilleUSA
  2. 2.Department of PhilosophyKenyon CollegeGambierUSA

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