Abstract
The accuracy of judgments of learning (JOLs) in forecasting later recall of cue–target pairs is sensitive to associative direction. JOLs are generally well calibrated for forward associative pairs (e.g., credit-card), but recall accuracy is often overestimated for backward pairs (e.g., card-credit). The present study further examines the effect of associative direction on JOL accuracy by comparing forward and backward pairs to unrelated pairs and symmetrical associates (e.g., salt–pepper)—a novel comparison. The correspondence between initial JOLs and recall accuracy was examined when study was either self-paced with concurrent JOLs (Experiment 1), when study/JOL duration was equated across pair types (Experiment 2), when JOLs were made immediately following study (Experiment 3), and when JOLs were made after a delay (Experiment 4). Across experiments, JOLs accurately estimated correct recall for forward pairs, but overestimated recall for symmetrical, backward, and unrelated pairs—an overestimation that was particularly robust for backward pairs. Calibration plots depicting JOL ratings against their corresponding recall accuracy indicated overestimations occurred for all pair types, though overestimations only occurred at high JOL ratings for symmetrical and forward pairs, a qualitative difference that was not captured in standard analyses of mean JOL and recall rates.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Analyses were also conducted on datasets with no imputation and with the imputation done only for participants missing 5% or less of their total JOL responses. Since similar data were found using each imputation method, we report the results using the 10% cutoff criterion which maximized the number of observations available for analyses. Datasets using no imputation and the 5% cutoff criterion are available via our OSF page (https://osf.io/hvdma/).
References
Arbuckle, T. Y., & Cuddy, L. L. (1969). Discrimination of item strength at time of presentation. Journal of Experimental Psychology, 81(1), 126–131.
Aust, F., & Barth, M. (2018). papaja: Create APA manuscripts with R Markdown. R Package. https://github.com/crsh/papaja. Accessed 19 Dec 2019.
Balota, D. A., Yap, M. J., Hutchsison, K. A., Cortese, M. J., Kessler, B., Loftis, B., et al. (2007). The English lexicon project. Behavior Research Methods, 39(3), 445–459.
Blake, A. B., & Castel, A. D. (2018). On belief and fluency in the construction of judgments of learning: Assessing and altering the direct effects of belief. Acta Psychologica, 186, 27–38.
Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior Research Methods, 41, 977–990.
Castel, A. D., McCabe, D. P., & Roediger, H. L. (2007). Illusions of competence and overestimation of associative memory for identical items: Evidence from judgments of learning. Psychonomic Bulletin & Review, 14(1), 107–111.
Connor, L. T., Dunlosky, J., & Hertzog, C. (1997). Age-related differences in absolute but not relative metamemory accuracy. Psychology & Aging, 12(1), 50–71.
Dunlosky, J., & Matvey, G. (2001). Empirical analysis of the intrinsic–extrinsic distinction of judgments of learning (JOLs): Effects of relatedness and serial position on JOLs. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27(5), 1180–1191.
Dunlosky, J., & Nelson, T. O. (1992). Importance of the kind of cue for judgments of learning (JOL) and the delayed-JOL effect. Memory & Cognition, 20(4), 374–380.
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146.
Goodman, L., & Kruskal, W. (1954). Measures of association for cross classifications. Journal of the American Statistical Association, 49, 732–764.
Hertzog, C., Dixon, R. A., Hultsch, D. F., & MacDonald, S. W. S. (2003). Latent change models of adult cognition: Are changes in processing speed and working memory associated with changes in episodic memory? Psychology and Aging, 18(4), 755–769.
Hutchison, K. A. (2003). Is semantic priming due to association strength or feature overlap? A microanalytic review. Psychonomic Bulletin & Review, 10(4), 785–813.
Juslin, P., Olsson, N., & Winman, A. (1996). Calibration and diagnosticity of confidence in eyewitness identification: Comments on what can be inferred from the low confidence-accuracy correlation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(5), 1304–1316.
Koriat, A. (1981). Semantic facilitation in lexical decision as a function of prime-target association. Memory & Cognition, 9(6), 587–598.
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.
Koriat, A., & Bjork, R. A. (2005). Illusions of competence in monitoring one’s knowledge during study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(2), 187–194. https://doi.org/10.1037/0278-7393.31.2.187.
Koriat, A., & Bjork, R. A. (2006). Illusions of competence during study can be remedied by manipulations that enhance learners’ sensitivity to retrieval conditions at test. Memory & Cognition, 34(5), 959–972.
Maki, W. S. (2007). Judgments of associative memory. Cognitive Psychology, 54(4), 319–353. https://doi.org/10.1016/j.cogpsych.2006.08.002.
Miller, T. M., & Geraci, L. (2014). Improving metacognitive accuracy: How failing to retrieve practice items reduces overconfidence. Consciousness and Cognition, 29, 131–140.
Mueller, M. L., Dunlosky, J., & Tauber, S. K. (2015). Why is knowledge updating after task experience incomplete? Contributions of encoding experience, scaling artifact, and inferential deficit. Memory & Cognition, 43(2), 180–192.
Nelson, D. L., McEvoy, C. L., & Dennis, S. (2000). What is free association and what does it measure? Memory & Cognition, 28(6), 887–899. https://doi.org/10.3758/BF03209337.
Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (2004). The University of South Florida free association, rhyme, and word fragment norms. Behavior Research Methods, Instruments, & Computers, 36(3), 402–407. https://doi.org/10.3758/BF03195588.
Nelson, T. O., & Dunlosky, J. (1991). When people’s judgments of learning (JOLs) are extremely accurate at predicting subsequent recall: The delayed-JOL effect. Psychological Science, 2, 267–270.
Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new findings. In G. Bower (Ed.), The psychology of learning and motivation. Washington, DC: American Psychologist.
Psychology Software Tools, Inc. [E-Prime 3.0]. (2016). https://www.pstnet.com.
Rhodes, G. M. (2016). Judgments of learning: Methods, data, and theory. In J. Dunlosky & S. K. Tauber (Eds.), The oxford handbook of metamemory (pp. 90–117). Oxford: Oxford University Press.
Rhodes, G. M., & Castel, A. D. (2008). Memory predictions are influenced by perceptual information: Evidence for metacognitive illusions. Journal of Experimental Psychology: General., 137(4), 615–625.
Rhodes, G. M., & Tauber, S. K. (2011). The influence of delaying judgments of learning on metacognitive accuracy: A meta-analytic review. Psychological Bulletin, 137, 131–148. https://doi.org/10.1037/a0021705.
Roediger, H. L., Wixted, J. H., & DeSoto, K. A. (2012). The curious complexity between confidence and accuracy in reports from memory. In L. Nadel & W. P. Sinnott-Armstrong (Eds.), Memory and law (pp. 84–108). Oxford: Oxford University Press.
Sauer, J., Brewer, N., Zweck, T., & Weber, N. (2010). The effect of retention interval on the confidence—accuracy relationship for eyewitness identification. Law and Human Behavior, 34, 337–347.
Scheck, P., Meeter, M., & Nelson, T. O. (2004). Anchoring effects in the absolute accuracy of immediate versus delayed judgments of learning. Journal of Memory and Language, 51, 71–79.
Tekin, E., & Roediger, H. L. (2017). The range of confidence scales does not affect the relationship between confidence accuracy in recognition memory. Cognitive Research: Principles and Implications, 2(1), 49–62.
Tiede, H. L., & Leboe, J. P. (2009). Metamemory judgments and the benefits of repeated study: Improving recall predictions through the activation of appropriate knowledge. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(3), 822–828.
Tulving, E. (1974). Cue-dependent forgetting. American Scientist, 62(1), 74–82.
Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task dependent? Journal of Memory and Language, 28, 127–154.
Valentine, K. D., & Buchanan, E. M. (2013). JAM-boree: An application of observation oriented modelling to judgements of associative memory. Journal of Cognitive Psychology, 25(4), 400–422.
Van Buuren, S., & Groothuis-Oudshoorn, K. (2011). Mice: Mulitvariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67.
Van Overschelde, J. P., & Nelson, T. O. (2006). Delayed judgments of learning cause both a decrease in absolute accuracy (calibration) and an increase in relative accuracy (resolution). Memory & Cognition, 34(7), 1527–1538.
Weber, N., & Brewer, N. (2003). The effect of judgment type and confidence scale on confidence-accuracy calibration in face recognition. Journal of Applied Psychology, 88(3), 490–499.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethical approval
The studies reported were approved by the University of Southern Mississippi Institutional Review Board (Protocol #IRB-19-429) and found to be in accordance with the 1964 Helsinki Declaration ethical principles. Informed consent was obtained from all individuals who participated in this study. The authors report no completing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
R code used for data screening and analyses as well as all applicable stimuli and data files have been made available on our OSF page (https://osf.io/hvdma/). All code is embedded inline within the manuscript in an R markdown document written with the papaja package (Aust & Barth, 2018).
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Maxwell, N.P., Huff, M.J. The deceptive nature of associative word pairs: the effects of associative direction on judgments of learning. Psychological Research 85, 1757–1775 (2021). https://doi.org/10.1007/s00426-020-01342-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00426-020-01342-z