135
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Leaping across the mental canyon: higher-order long-distance analogical retrieval

ORCID Icon, ORCID Icon & ORCID Icon
Pages 856-875 | Received 25 Jul 2022, Accepted 27 Aug 2023, Published online: 05 Sep 2023

References

  • Ahmed, S., & Christensen, B. (2009). An in situ study of analogical reasoning in novice and experienced design engineers. Journal of Mechanical Design, 131(11), 111004. https://doi.org/10.1115/1.3184693
  • Alfieri, L., Nokes-Malach, T. J., & Schunn, C. D. (2013). Learning through case comparisons: A meta-analytic review. Educational Psychologist, 48(2), 87–113. https://doi.org/10.1080/00461520.2013.775712
  • Aust, F., & Barth, M. (2022). papaja: Prepare reproducible APA journal articles with R Markdown. https://github.com/crsh/papaja.
  • Ball, L. J., Ormerod, T. C., & Morley, N. J. (2004). Spontaneous analogising in engineering design: A comparative analysis of experts and novices. Design Studies, 25(5), 495–508. https://doi.org/10.1016/j.destud.2004.05.004
  • Barnett, S. M., & Ceci, S. J. (2002). When and where do we apply what we learn? A taxonomy for far transfer. Psychological Bulletin, 128(4), 612–637. https://doi.org/10.1037/0033-2909.128.4.612
  • Barth, M. (2022). tinylabels: Lightweight variable labels. https://cran.r-project.org/package=tinylabels.
  • Ben-Shachar, M. S., Lüdecke, D., & Makowski, D. (2020). effectsize: Estimation of effect size indices and standardized parameters. Journal of Open Source Software, 5(56), 2815. https://doi.org/10.21105/joss.02815
  • Bernardo, A. B. I. (2001). Analogical Problem Construction and Transfer in Mathematical Problem Solving. Educational Psychology, 21(2), 137–150. https://doi.org/10/fbvqqp
  • Beveridge, M., & Parkins, E. (1987). Visual representation in analogical problem solving. Memory and Cognition, 15(3), 230–237. https://doi.org/10/d54wkj
  • Boden, M. A. (1994). What is creativity? In M. A. Boden (Ed.), Dimensions of creativity. MIT Press.
  • Burns, B. D. (1996). Meta-analogical transfer: Transfer between episodes of analogical reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(4), 1032–1048. https://doi.org/10.1037/0278-7393.22.4.1032
  • Casakin, H., & Goldschmidt, G. (1999). Expertise and the use of visual analogy: Implications for design education. Design Studies, 20(2), 153–175. https://doi.org/10.1016/S0142-694X(98)00032-5
  • Catrambone, R., & Holyoak, K. J. (1989). Overcoming contextual limitations on problem-solving transfer. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15(6), 1147–1156. https://doi.org/10.1037/0278-7393.15.6.1147
  • Chen, Z. (1995). Analogical transfer: From schematic pictures to problem solving. Memory and Cognition, 23(2), 255–269. https://doi.org/10/d94bg4
  • Christensen, B. T., & Schunn, C. D. (2007). The relationship of analogical distance to analogical function and preinventive structure: The case of engineering design. Memory & Cognition, 35(1), 29–38. https://doi.org/10.3758/BF03195939
  • Dunbar, K. (1995). How scientists really reason: Scientific reasoning in real-world laboratories. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 365–395). The MIT Press.
  • Dunbar, K. N., & Blanchette, I. (2001). The in vivo/in vitro approach to cognition: The case of analogy. Trends in Cognitive Sciences, 5(8), 334–339. https://doi.org/10.1016/S1364-6613(00)01698-3
  • Firke, S. (2023). Janitor: Simple tools for examining and cleaning dirty data. https://CRAN.R-project.org/package=janitor.
  • Funder, D. C., & Ozer, D. J. (2019). Evaluating effect size in psychological research: Sense and nonsense. Advances in Methods and Practices in Psychological Science, 2(2), 156–168. https://doi.org/10.1177/2515245919847202
  • Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy*. Cognitive Science, 7(2), 155–170. https://doi.org/10.1207/s15516709cog0702_3
  • Gentner, D., Loewenstein, J., & Thompson, L. (2004). Analogical encoding: Facilitating knowledge transfer and integration. In K. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the twenty-sixth annual conference of the cognitive science society (pp. 452–457). Cognitive Science Society.
  • Gentner, D., Loewenstein, J., Thompson, L., & Forbus, K. D. (2009). Reviving inert knowledge: Analogical abstraction supports relational retrieval of past events. Cognitive Science, 33(8), 1343–1382. https://doi.org/10.1111/j.1551-6709.2009.01070.x
  • Gentner, D., Rattermann, M. J., & Forbus, K. D. (1993). The roles of similarity in transfer: Separating retrievability from inferential soundness. Cognitive Psychology, 25(4), 524–575. https://doi.org/10.1006/cogp.1993.1013
  • Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12(3), 306–355.
  • Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive Psychology, 15(1), 1–38. https://doi.org/10.1016/0010-0285(83)90002-6
  • Goldstone, R. L., Gentner, D., & Medin, D. L. (1989). Relations relating relations. Paper presented at the 11th Annual Conference of the Cognitive Science Society, Ann Arbor, MI.
  • Goldstone, R. L., & Sakamoto, Y. (2003). The transfer of abstract principles governing complex adaptive systems. Cognitive Psychology, 46(4), 414–466. https://doi.org/10/cds9q4
  • Goldstone, R. L., & Son, J. Y. (2005). The Transfer of Scientific Principles Using Concrete and Idealized Simulations. Journal of the Learning Sciences, 14(1), 69–110. https://doi.org/10/bx58x7
  • Goldwater, M. B., & Gentner, D. (2015). On the acquisition of abstract knowledge: Structural alignment and explication in learning causal system categories. Cognition, 137, 137–153.
  • Green, A. E. (2016). Creativity, within reason semantic distance and dynamic state creativity in relational thinking and reasoning. Current Directions in Psychological Science, 25(1), 28–35. https://doi.org/10.1177/0963721415618485
  • Hester, J., & Bryan, J. (2022). Glue: Interpreted string literals. https://CRAN.R-project.org/package=glue.
  • Hofstadter, D. R. (1995). Fluid concepts and creative analogies: Computer models of the fundamental mechanisms of thought. Basic Books.
  • Holyoak, K. J., & Thagard, P. (1989). Analogical mapping by constraint satisfaction. Cognitive Science, 13(3), 295–355. https://doi.org/10.1207/s15516709cog1303_1
  • Holyoak, K. J., & Thagard, P. (1995). Mental leaps: Analogy in creative thought. MIT press.
  • Jamrozik, A., & Gentner, D. (2020). Relational labeling unlocks inert knowledge. Cognition, 196, 104146. https://doi.org/10.1016/j.cognition.2019.104146
  • Jung, W., & Hummel, J. E. (2015). Making probabilistic relational categories learnable. Cognitive Science, 39(6), 1259–1291. https://doi.org/10.1111/cogs.12199
  • 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(2), 334–341. https://doi.org/10.3758/BF03193454
  • Makowski, D., Lüdecke, D., Patil, I., Thériault, R., Ben-Shachar, M. S., & Wiernik, B. M. (2023). Automated results reporting as a practical tool to improve reproducibility and methodological best practices adoption. CRAN. https://easystats.github.io/report/.
  • Mandler, J. M., & Orlich, F. (1993). Analogical transfer: The roles of schema abstraction and awareness. Bulletin of the Psychonomic Society, 31(5), 485–487. https://doi.org/10/gjscrb
  • Markman, A. B. (1997). Constraints on analogical inference. Cognitive Science, 21(4), 373–418. https://doi.org/10.1207/s15516709cog2104_1
  • Minervino, R. A., Olguín, V., & Trench, M. (2017). Promoting interdomain analogical transfer: When creating a problem helps to solve a problem. Memory & Cognition, 45(2), 221–232. https://doi.org/10.3758/s13421-016-0655-2
  • Novick, L. R. (1990). Representational transfer in problem solving. Psychological Science, 1(2), 128–132. https://doi.org/10.1111/j.1467-9280.1990.tb00081.x
  • Novick, L. R., & Hmelo, C. E. (1994). Transferring symbolic representations across nonisomorphic problems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20(6), 1296–1321. https://doi.org/10.1037/0278-7393.20.6.1296
  • Pedone, R., Hummel, J. E., & Holyoak, K. J. (2001). The use of diagrams in analogical problem solving. Memory and Cognition, 29(2), 214–221. https://doi.org/10/c2fcrr
  • Penn, D. C., Holyoak, K. J., & Povinelli, D. J. (2008). Darwin’s mistake: Explaining the discontinuity between human and nonhuman minds. Behavioral and Brain Sciences, 31(2), 109–130. https://doi.org/10.1017/S0140525X08003543
  • Perneger, T. V. (1998). What’s wrong with Bonferroni adjustments. BMJ, 316(7139), 1236–1238. https://doi.org/10.1136/bmj.316.7139.1236
  • R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/.
  • Reed, S. K. (1987). A structure-mapping model for word problems. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13(1), 124–139. https://doi.org/10.1037/0278-7393.13.1.124
  • Ross, B. H., & Kennedy, P. T. (1990). Generalizing From the Use of Earlier Examples in Problem Solving. Journal of Experimental Psychology: Learning, Memory, and Cognition, 16(1), 42–55. https://doi.org/10/dtjhwv
  • Trench, M., Tavernini, L. M., & Goldstone, R. L. (2017). Promoting spontaneous analogical transfer by idealizing target representations. In Proceedings of the 39th annual conference of the cognitive science society (pp. 1206–1211). Cognitive Science Society.
  • Wickham, H. (2022). Stringr: Simple, consistent wrappers for common string operations. https://CRAN.R-project.org/package=stringr.
  • Wickham, H., & Bryan, J. (2023). readxl: Read Excel Files. https://readxl.tidyverse.org, https://github.com/tidyverse/readxl.
  • Wickham, H., François, R., Henry, L., Müller, K., & Vaughan, D. (2023a). Dplyr: A grammar of data manipulation. https://CRAN.R-project.org/package=dplyr.
  • Wickham, H., & Henry, L. (2023). Purrr: Functional programming tools. https://CRAN.R-project.org/package=purrr.
  • Wickham, H., Miller, E., & Smith, D. (2023b). Haven: Import and export ‘SPSS’, ‘stata’ and ‘SAS’ files. https://CRAN.R-project.org/package=haven.
  • Wickham, H., Vaughan, D., & Girlich, M. (2023). Tidyr: Tidy messy data. https://CRAN.R-project.org/package=tidyr.
  • Xie, Y. (2015). Dynamic documents with R and knitr (2nd ed.). Chapman; Hall/CRC. https://yihui.org/knitr/.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.