Abstract
Judgments of learning (JOLs), as one type of metacognitive judgments, are assessments that people make about how well they have learned material. The effective use of JOLs depends on various factors, including task-specific variables and the learner’s own metacognitive resources. Little has been known about the relationship between JOL accuracy for memory predictions and metacognitive ability, which is an emerging theory-practice gap in the field of metacognition. The present study investigated the relationship between the absolute accuracy of JOLs and the metacognitive awareness inventory (MAI), using concrete and abstract word pairs through three study-test cycles. We found that participants who scored high on the MAI, also produced a high level of absolute accuracy on each study-test cycle. The results from mediation analyses yielded that the impact of the MAI on absolute accuracy on cycle 3 was completely mediated by absolute accuracy on the first two cycles for both concrete and abstract word pairs. In addition, the same pattern of results was obtained even when a subset of the MAI (either knowledge or regulation of cognition) was used. These indicate that trait-based metacognitive abilities can well explain the correspondence between JOLs and recall performance on the first test. However, their impact is reduced after study-test practice, suggesting that experience-based factors become critical to improving metacognitive accuracy.
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Notes
We are deeply indebted to an anonymous reviewer for bringing this to our attention.
Before conducting the experiment, we performed a series of pilot studies, choosing the semantic relatedness between the members of a pair, as used in Koriat et al. (2002). We found ceiling effects already in the second study-test cycle for related word pairs even when a shorter presentation duration was used. These results were consistent with those of Koriat et al. in which Hebrew word pairs were used.
References
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173.
Begg, I., Duft, S., Lalonde, P., Melnick, R., & Sanvito, J. (1989). Memory predictions are based on easy of processing. Journal of Memory and Language, 28, 610–632. https://doi.org/10.1016/0749-596X(89)90016-8.
Boekaerts, M., Pintrich, P. R., & Zeidner, M. (Eds.). (2000). Handbook of self-regulation. San Diego, CA: Academic Press.
Brown, A. L. (1987). Metacognition, executive control, self-regulation, and other more mysterious mechanisms. In F. Weinert & R. Kluwe (Eds.), Metacognition, motivation, and understanding (pp. 65–116). Mahwah, NJ: Erlbaum.
Carvalho, M. K. F. (2009). Confidence judgments in real classroom settings: Monitoring performance in different types of tests. International Journal of Psychology, 44, 93–108. https://doi.org/10.1080/00207590701436744.
Finn, B., & Metcalfe, J. (2007). The role of memory for past test in underconfidence with practice effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 238–244. https://doi.org/10.1037/0278-7393.33.1.238.
Hanczakowski, M., Zawadzka, K., Pasek, T., & Higham, P. A. (2013). Calibration of metacognitive judgments: Insights from the underconfidence-with-practice effect. Journal of Memory and Language, 69, 429–444. https://doi.org/10.1016/j.jml.2013.05.003.
Harrison, G. M., & Vallin, L. M. (2018). Evaluating the metacognitive awareness inventory using empirical factor-structure evidence. Metacognition and Learning, 13, 15–38. https://doi.org/10.1007/s11409-017-9176-z.
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, NY: Guilford Press.
Jang, Y., & Lee, H. (2019). Item repetition and retrieval processes in cued recall: Analysis of recall-latency distributions. Memory & Cognition, 47, 792–815. https://doi.org/10.3758/s13421-019-00902-y.
Jang, Y., Lee, H., & Huber, D. E. (2019). How many dimensions underlie judgments of learning and recall redux: Consideration of recall latency reveals a previously hidden nonmonotonicity. Journal of Mathematical Psychology, 90, 47–60. https://doi.org/10.1016/j.jmp.2018.10.006.
Jang, Y., Wallsten, T. S., & Huber, D. E. (2012). A stochastic detection and retrieval model for the study of metacognition. Psychological Review, 119, 186–200. https://doi.org/10.1037/a0025960.
Judd, C. M., & Kenny, D. A. (1981). Process analysis: Estimating mediation in treatment evaluations. Evaluation Review, 5, 602–619 http://dx.doi.org.weblib.lib.umt.edu:8080/10.1177/0193841X8100500502.
Kelemen, W. L., Frost, P. J., & Weaver, C. A. (2000). Individual differences in metacognition: Evidence against a general metacognitive ability. Memory & Cognition, 28, 92–107. https://doi.org/10.3758/BF03211579.
Koriat, A. (1997). Monitoring one’s own knowledge during study: A cue-utilization approach to judgments of learning. Journal of experimental psychology: General, 126(4), 349–370. https://doi.org/10.1037/0096-3445.126.4.349.
Koriat, A., Sheffer, L., & Ma’ayan, H. (2002). Comparing objective and subjective learning curves: Judgments of learning exhibit increased underconfidence with practice. Journal of Experimental Psychology: General, 131, 147–162. https://doi.org/10.1037/0096-3445.131.2.147.
Lee, H., Jang, Y., Kim, Y., & Min, K. (2020). Validating a comprehensive measure of metacognition. Manuscript under review.
Lovelace, E. A. (1984). Metamemory: Monitoring future recallability during study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 756–766. https://doi.org/10.1037/0278-7393.10.4.756.
MacKinnon, D. P. (2008). Introduction to statistical mediation analysis. New York, NY: Routledge.
MacKinnon, D. P., Fairchild, A. J., & Fritz, M. S. (2007). Mediation analysis. Annual Review of Psychology, 58, 593–614. https://doi.org/10.1146/annurev.psych.58.110405.085542.
Magno, C. (2010). The role of metacognitive skills in developing critical thinking. Metacognition and Learning, 5, 137–156. https://doi.org/10.1007/s11409-010-9054-4.
McFatter, R. M. (1979). The use of structural equation models in interpreting regression equations including suppressor and enhancer variables. Applied Psychological Measurement, 3, 123–135. https://doi.org/10.1177/014662167900300113.
Nelson, T. O. (1984). A comparison of current measures of the accuracy of feeling-of-knowing predictions. Psychological Bulletin, 95, 109–133. https://doi.org/10.1037/0033-2909.95.1.109.
Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and some new findings. In G. H. Bower (Ed.), The psychology of learning and motivation (pp. 125–173). New York, NY: Academic Press.
Park, T. (2004). Investigation of association frequency and imagery value of Korean words. The Korean Journal of Experimental Psychology, 16, 237–260.
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36, 717–731. https://doi.org/10.3758/BF03206553.
Schraw, G. (2009). A conceptual analysis of five measures of metacognitive monitoring. Metacognition and Learning, 4, 33–45. https://doi.org/10.1007/s11409-008-9031-3.
Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19, 460–475. https://doi.org/10.1006/ceps.1994.1033.
Sperling, R. A., Howard, B. C., Staley, R., & DuBois, N. (2004). Metacognition and self-regulated learning constructs. Educational Research and Evaluation, 10, 117–139. https://doi.org/10.1076/edre.10.2.117.27905.
Yi, K., Koo, M.-M., Nam, K., Park, K., Park, T., Bae, S., et al. (2017). The Korean lexicon project: A lexical decision study on 30,930 Korean words and nonwords. The Korean Journal of Cognitive and Biological Psychology, 29, 395–410.
Young, A., & Fry, J. D. (2008). Metacognitive awareness and academic achievement in college students. Journal of the Scholarship of Teaching and Learning, 8, 1–10.
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This research was partially supported by a Yamaguchi Opportunity Fund Award (Y. Jang).
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Jang, Y., Lee, H., Kim, Y. et al. The Relationship between Metacognitive Ability and Metacognitive Accuracy. Metacognition Learning 15, 411–434 (2020). https://doi.org/10.1007/s11409-020-09232-w
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DOI: https://doi.org/10.1007/s11409-020-09232-w