Abstract
The dominant computational models of analogical thinking implicitly assume that the cognitive system searches long-term memory based on cues that are continuously extracted from the current contents of working memory. The studies reviewed in the present chapter shed light on a basic question grossly overlooked in the literature: Can access to distant analogs be enhanced by deliberately attempting to identify analogous sources? As in a Russian doll, a positive answer to this question would lead to another overlooked aspect of analogical thinking: whether analogical search works uniformly irrespective of the overarching activity in which the search is embedded. The core segment of the present chapter reviews a recent series of studies from our laboratory, which show that the potential of deliberate search to increase distant retrievals is strongest during argumentation activities, moderate during hypothesis-generation, and null during problem-solving. We advance some tentative conjectures about the uneven effectiveness of voluntary search across these educationally relevant activities, and argue for the need of more knowledge-intensive target elaborations.
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Notes
- 1.
At first sight, our prompting manipulation might appear to be highly related to Gick and Holyoak’s (1980) contrast between participants who solved the radiation problem before vs. after a hint to consider the stories read during a previous phase of their procedure. Despite this seeming commonality, the psychological constraints for capitalizing on such hint contrast sharply with those involved in our prompt to “think of analogous situations.” As opposed to the latter case, in which the reasoner would need to probe the whole of LTM for potential matches, Gick and Holyoak’s episodic reference to their learning set allows the reasoner to sequentially match the target against each of only three candidate situations, thus reducing an otherwise prohibitive computation to a much more manageable set.
References
Amorín, S., Martínez Frontera, L., Olguín, M. V., & Trench, M. (2017). Spontaneous vs. voluntary analogical retrieval across different cognitive activities. Paper presented at Analogy2017: The Fourth International Conference on Analogical Reasoning. Paris, France, July 2017.
Blanchette, I., & Dunbar, K. (2000). How analogies are generated: The roles of structural and superficial similarity. Memory & Cognition, 28, 108–124.
Catrambone, R., & Holyoak, K. J. (1989). Overcoming contextual limitations on problem-solving transfer. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 1147–1156.
Clement, J. (2008). Creative model construction in scientists and students. New York: Springer.
Dunbar, K. (1997). How scientists think: Online creativity and conceptual change in science. In T. B. Ward, S. M. Smith, & S. Vaid (Eds.), Creative thought: An investigation on conceptual structures and processes (pp. 461–493). Washington, DC: APA Press.
Duncker, K. (1945). On problem solving. Psychological Monographs, 58(5), i, Whole No. 270.
Gentner, D., Brem, S., Ferguson, R. W., Wolff, P., Markman, A. B., & Forbus, K. D. (1997). Analogy and creativity in the works of Johannes Kepler. In T. B. Ward, S. M. Smith, & J. Vaid (Eds.), Creative thought: An investigation of conceptual structures and processes (pp. 403–459). Washington, DC: American Psychological Association.
Gentner, D., & Forbus, K. D. (1991). MAC/FAC: A model of similarity-based access and mapping. In Proceedings of the Thirteenth Annual Conference of the Cognitive Science Society (pp. 504–509).
Gentner, D., & Jeziorski, M. (1989). Historical shifts in the use of analogy in science. In B. Gholson, W. R. Shadish Jr., R. A. Neimeyer, & A. C. Houts (Eds.), Psychology of science: Contributions to metascience (pp. 296–325). New York: Cambridge University Press.
Gentner, D., & Kurtz, K. J. (2005). Relational categories. In W. K. Ahn, R. L. Goldstone, B. C. Love, A. B. Markman, & P. W. Wolff (Eds.), Categorization inside and outside the laboratory: Essays in honor of Douglas L. Medin (pp. 151–175). Washington, DC: American Psychological Association.
Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12, 306–355.
Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15, 1–38.
Hofstadter, D. R., & Sander, E. (2013). Surfaces and essences: Analogy as the fuel and fire of thinking. New York: Basic Books.
Holyoak, K. J., & Koh, K. (1987). Surface and structural similarity in analogical transfer. Memory & Cognition, 15, 332–340.
Jamrozik, A. (2014). The effect of labels on relational retrieval. Unpublished Ph.D. Thesis, Northwestern University.
Jamrozik, A., & Gentner, D. (2020). Relational labeling unlocks inert knowledge. Cognition, 196, 104–146.
Jones, R. M., & Langley, P. (2005). A constrained architecture for learning and problem solving. Computational Intelligence, 21(4), 480–502.
Keane, M. T. (1987). On retrieving analogues when solving problems. Quarterly Journal of Experimental Psychology, 39, 29–41.
Keane, M. T., & Bohan, A. (2004). Should politicians stop using analogies? Whether analogical arguments are better than their factual equivalents. In D. Gentner, K. Forbus, & T. Regier (Eds.), Proceedings of the 26th annual conference of the cognitive science society (pp. 660–665). Austin, TX: Cognitive Science Society.
Klahr, D., & Dunbar, K. (1988). Dual space search during scientific reasoning. Cognitive Science, 12, 1–48.
Kurtz, K. J., & Loewenstein, J. (2007). Converging on a new role for analogy in problem solving and retrieval: When two problems are better than one. Memory & Cognition, 35, 334–341.
Lombrozo, T. (2006). The structure and function of explanations. Trends in Cognitive Sciences, 10, 464–470. https://doi.org/10.1016/j.tics.2006.08.004
Nersessian, N. J. (1992). How do scientists think? Capturing the dynamics of conceptual change in science. In R. N. Giere (Ed.), Cognitive models of science (pp. 5–22). Minneapolis, MN: University of Minnesota Press.
O’keefe, D., & Costello, F. (2008). A fast computational model of analogical retrieval (and mapping). In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th annual conference of the cognitive science society (pp. 2003–2008). Austin, TX: Cognitive Science Society.
Oberholzer, N., Trench, M., Kurtz, K., & Minervino, R. (2018). Analogies without commonalities? Evidence of re-representation via relational category activation. Frontiers in Psychology, 9, 2441. https://doi.org/10.3389/fpsyg.2018.02441
Olguin, V., Tavernini, M., Pacella, L., & Minervino, R. (2017). Analogical retrieval mediated by everyday schema-governed categories. Paper presented at Analogy 2017: The Fourth International Conference on Analogy, Paris.
Perkins, D. N. (2000). Archimedes' bathtub: The art and logic of breakthrough thinking. New York: Norton.
Raynal, L., Clement, E., & Sander, E. (2018). Structural similarity superiority in a free-recall reminding paradigm. In C. Kalish, M. Rau, J. Zhu, & T. Rogers (Eds.), Proceedings of the 40th annual conference of the cognitive science society (pp. 2324–2329). Austin, TX: Cognitive Science Society.
Saner, L., & Schunn, C. D. (1999). Analogies out of the blue: When history seems to retell itself. In M. Hahn & S. Stoness (Eds.), Proceedings of the 21st annual conference of the cognitive science society (pp. 619–624). Mahwah, NJ: Erlbaum.
Simon, H. A. (1992). Scientific discovery as problem-solving. International Studies in the Philosophy of Science, 6, 3–14.
Spencer, R. M., & Weisberg, R. W. (1986). Context-dependent effects on analogical transfer. Memory & Cognition, 14, 442–449.
Sternberg, R. (1990). Metaphors of mind: Conceptions of the nature of intelligence. New York: Cambridge University Press.
Trench, M., Oberholzer, N., & Minervino, R. (2009). Dissolving the analogical paradox. Retrieval under a production paradigm is highly constrained by superficial similarity. In B. Kokinov, D. Gentner, & K. Holyoak (Eds.), New frontiers in analogy research (pp. 443–452). Sofia: NBU Press.
Trench, M., Olguín, V., & Minervino, R. (2016). Seek, and Ye shall find: Differences between spontaneous and voluntary analogical retrieval. Quarterly Journal of Experimental Psychology, 69, 698–712.
Trench, M., Rivas, L. E., Diaz, M. V. & Minervino, R. (2020). Spontaneous and voluntary analogical retrieval during problem-solving and hypothesis generation. In S. Denison, M. Mack, Y. Xu, & B. Armstrong (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 1384-1390). Austin, TX: Cognitive Science Society.
Weisberg, R. W. (2006). Creativity: Understanding innovation in problem solving, science, invention, and the arts. Hoboken, NJ: John Wiley & Sons.
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Trench, M., Minervino, R.A. (2020). Boosting Retrieval via Deliberate Search. In: Distant Connections: The Memory Basis of Creative Analogy. SpringerBriefs in Psychology(). Springer, Cham. https://doi.org/10.1007/978-3-030-52545-3_6
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