The ability to selectively focus on and remember important information, referred to as value-directed remembering, may be crucial for effective memory functioning. In the present study, we investigated the relationships between metacognitive monitoring and control accuracy, selectivity for valuable information, and fluid intelligence. Mediation analyses demonstrated that participants’ monitoring assessments and later recall were influenced by the value of the to-be-learned words and the accuracy of participants’ judgments was moderated by fluid intelligence. Moreover, recall, selectivity, metacognitive awareness of selectivity, and metacognitive accuracy all generally increased with task experience, demonstrating participants’ ability to improve their memory by utilizing cognitive resources more effectively. Together the results suggest that people may be aware of the need to be selective, and engaging in value-directed remembering may be related to higher-level cognitive skills associated with problem-solving and reasoning. Specifically, the strategic use of memory may be involved in focusing on important information, and the metacognitive processes that allow for this prioritization of memory may be related to more general problem-solving abilities that involve identifying important features of information to guide cognition in a broader context.
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Although our sample size is somewhat small for individual differences research, the use of multilevel regression models improves power compared to traditional ANOVAs. Additionally, we were able to find significant effects despite the smaller sample size; however, these findings should be replicated with larger samples in future work.
Ariel, R. (2013). Learning what to learn: The effects of task experience on strategy shifts in the allocation of study time. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 1697–1711.
Ariel, R., & Dunlosky, J. (2013). When do learners shift from habitual to agenda-based processes when selecting items for study? Memory & Cognition, 41, 416–428.
Ariel, R., Dunlosky, J., & Bailey, H. (2009). Agenda-based regulation of study-time allocation: When agendas override item-based monitoring. Journal of Experimental Psychology: General, 138, 432–447.
Ariel, R., Price, J., & Hertzog, C. (2015). Age-related associative memory deficits in value-based remembering: The contribution of agenda-based regulation and strategy use. Psychology and Aging, 30, 795–808.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.
Bandura, A. (1989). Regulation of cognitive processes through perceived self-efficacy. Developmental Psychology, 25, 729–735.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman.
Beaudoin, M., & Desrichard, O. (2011). Are memory self-efficacy and memory performance related? A meta-analysis. Psychological Bulletin, 137, 211–241.
Berry, J. M. (1999). Memory self-efficacy in its social cognitive context. In T. M. Hess & F. Blanchard-Fields (Eds.), Social cognition and aging (pp. 69–96). San Diego: Academic Press.
Berry, J. M., Williams, H. L., Usubalieva, A., & Kilb, A. (2013). Metacognitive awareness of the associative deficit for words and names. Aging, Neuropsychology and Cognition, 20, 592–619.
Bolger, N., & Laurenceau, J.-P. (2013). Intensive longitudinal methods: An introduction to diary and experience sampling research. New York: Guilford.
Castel, A. D. (2008). The adaptive and strategic use of memory by older adults: Evaluative processing and value-directed remembering. In A. S. Benjamin & B. H. Ross (Eds.), The psychology of learning and motivation (Vol. 48, pp. 225–270). London: Academic Press.
Castel, A. D., Balota, D. A., & McCabe, D. P. (2009). Memory efficiency and the strategic control of attention at encoding: Impairments of value-directed remembering in Alzheimer’s disease. Neuropsychology, 23, 297–306.
Castel, A. D., Benjamin, A. S., Craik, F. I. M., & Watkins, M. J. (2002). The effects of aging on selectivity and control in short-term recall. Memory & Cognition, 30, 1078–1085.
Castel, A. D., Farb, N. A. S., & Craik, F. I. M. (2007). Memory for general and specific value information in younger and older adults: Measuring the limits of strategic control. Memory & Cognition, 35, 689–700.
Castel, A. D., McGillivray, S., & Friedman, M. C. (2012). Metamemory and memory efficiency in older adults: Learning about the benefits of priority processing and value-directed remembering. In M. Naveh-Benjamin & N. Ohta (Eds.), Memory and aging: Current issues and future directions (pp. 245–270). New York: Psychology Press.
Cervone, D., & Peake, P. K. (1986). Anchoring, efficacy, and action: The influence of judgmental heuristics on self-efficacy judgments and behavior. Journal of Personality and Social Psychology, 50, 492–501.
Double, K. S., Birney, D. P., & Walker, S. A. (2018). A meta-analysis and systematic review of reactivity to judgements of learning. Memory, 26, 741–750.
Dunlosky, J., & Ariel, R. (2011a). Self-regulated learning and the allocation of study time. Psychology of Learning and Motivation, 54, 103–140.
Dunlosky, J., & Ariel, R. (2011b). The influence of agenda-based and habitual processes on item selection during study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 899–912.
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, 1180–1191.
Dunlosky, J., & Metcalfe, J. (2009). Metacognition. Thousand Oaks: Sage.
Dunlosky, J., Mueller, M. L., & Thiede, K. W. (2016). Methodology for investigating human metamemory: Problems and pitfalls. In J. Dunlosky & S. K. Tauber (Eds.), Oxford library of psychology. The Oxford handbook of metamemory (p. 23–37). Oxford University Press.
Elliott, B. L., McClure, S. M., & Brewer, G. A. (2020). Individual differences in value-directed remembering. Cognition, 201, 104275.
Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12, 121–138.
Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. A. (1999). Working memory, short-term memory and general fluid intelligence: A latent variable approach. Journal of Experimental Psychology: General, 128, 309–331.
Fritz, M. S., & MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychological Science, 18, 233–239.
Fritz, M. S., Taylor, A. B., & MacKinnon, D. P. (2012). Explanation of two anomalous results in statistical mediation analysis. Multivariate Behavioral Research, 47, 61–87.
Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. New York: Cambridge University Press.
Griffin, M. L., Benjamin, A. S., Sahakyan, L., & Stanley, S. E. (2019). A matter of priorities: High working memory enables (slightly) superior value-directed remembering. Journal of Memory and Language, 108, 104032.
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.
Hauck, K. B., Mingo, M. A., & Williams, R. L. (2017). A review of relationships between item sequence and performance on multiple-choice exams. Scholarship of Teaching and Learning in Psychology, 3, 58–75.
Hennessee, J. P., Patterson, T. K., Castel, A. D., & Knowlton, B. J. (2019). Forget me not: Encoding processes in value-directed remembering. Journal of Memory and Language, 106, 29–39.
Hertzog, C., Hultsch, D. F., & Dixon, R. A. (1989). Evidence for the convergent validity of two self-report metamemory questionnaires. Developmental Psychology, 25, 687–700.
Hertzog, C., McGuire, C. L., & Lineweaver, T. T. (1998). Aging, attributions, perceived control, and strategy use in a free recall task. Aging, Neuropsychology and Cognition, 5, 85–106.
Higham, P. A., Zawadzka, K., & Hanczakowski, M. (2016). Internal mapping and its impact on measures of absolute and relative metacognitive accuracy. In J. Dunlosky & S. Tauber (Eds.), The Oxford handbook of metamemory (pp. 39–61). New York: Oxford University Press.
Horn, J. L. (1982). The theory of fluid and crystallized intelligence in relation to concepts of cognitive psychology and aging in adulthood. In E. I. M. Craik & S. Trehub (Eds.), Aging and cognitive processes (pp. 237–278). New York: Plenum Press.
Jaeger, T. F. (2008). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59, 434–446.
Jarosz, A. F., Raden, M. J., & Wiley, J. (2019). Working memory capacity and strategy use on the RAPM. Intelligence, 77, 101387.
Kenny, D. A., Kashy, D., & Bolger, N. (1998). Data analysis in social psychology. In D. Gilbert, S. Fiske, & G. Lindzey (Eds.), Handbook of social psychology (4th ed., pp. 233–265). New York: McGraw-Hill.
Klosner, N. C., & Gellman, E. K. (1973). The effect of item arrangement on classroom test performance: Implications for content validity. Educational and Psychological Measurement, 33, 413–418.
Koriat, A. (1997). Monitoring one’s own knowledge during study: A cue-utilization approach to judgments of learning. Journal of Experimental Psychology: General, 126, 349–370.
Kruschke, J. K. (2014). Doing Bayesian data analysis: A tutorial introduction with R (2nd ed.). Burlington: Academic Press.
Locke, E. A., Frederick, E., Lee, C., & Bobko, P. (1984). Effect of self-efficacy, goals, and task strategies on task performance. Journal of Applied Psychology, 69, 241–251.
Loftus, G. R., & Wickens, T. D. (1970). Effect of incentive on storage and retrieval processes. Journal of Experimental Psychology, 85, 141–147.
MacKinnon, D. P., Lockwood, C. M., & Williams, J. (2004). Confidence limits for the indirect effect: Distribution of the product and resampling methods. Multivariate Behavioral Research, 39, 99–128.
Maqsud, M. (1997). Effects of metacognitive skills and nonverbal ability on academic achievement of high school pupils. Educational Psychology, 17, 387–397.
Masson, M. E. J., & Rotello, C. M. (2009). Sources of bias in the Goodman-Kruskal gamma coefficient measure of association: Implications for studies of metacognitive processes. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 509–527.
Mazzoni, G., Cornoldi, C., & Marchitelli, G. (1990). Do memorability ratings affect study-time allocation? Memory & Cognition, 18, 196–204.
McElreath, R. (2016). Statistical rethinking: A Bayesian course with examples in R and Stan. Boca Raton: CRC Press.
McGillivray, S., & Castel, A. D. (2011). Betting on memory leads to metacognitive improvement in younger and older adults. Psychology and Aging, 26, 137–142.
McNeish, D. (2017). Small sample methods for multilevel modeling: A colloquial elucidation of REML and the Kenward-Roger correction. Multivariate Behavioral Research, 52, 661–670.
Metcalfe, J., & Finn, B. (2008). Evidence that judgments of learning are causally related to study choice. Psychonomic Bulletin & Review, 15, 174–179.
Middlebrooks, C. D., & Castel, A. D. (2017). Self-regulated learning of important information under sequential and simultaneous encoding conditions. Journal of Experimental Psychology: Learning, Memory, and Cognition, 44, 779–792.
Mitchum, A. L., Kelley, C. M., & Fox, M. C. (2016). When asking the question changes the ultimate answer: Metamemory judgments change memory. Journal of Experimental Psychology: General, 145, 200–219.
Murayama, K., Sakaki, M., Yan, V. X., & Smith, G. (2014). Type-1 error inflation in the traditional by-participant analysis to metamemory accuracy: A generalized mixed effects model perspective. Journal of Experimental Psychology: Learning, Memory & Cognition, 40, 1287–1306.
Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and some new findings. In G. H. Bower (Ed.), (p. 80) The psychology of learning and motivation (pp. 125–173). New York: Academic Press.
Nisbett, R. E., Aronson, J., Blair, C., Dickens, W., Flynn, J., Halpern, D. F., & Turkheimer, E. (2012). Intelligence: New findings and theoretical developments. American Psychologist, 67, 130–159.
Ohtani, K., & Hisasaka, T. (2018). Beyond intelligence: A meta-analytic review of the relationship among metacognition, intelligence, and academic performance. Metacognition and Learning, 13, 179–212.
Raven, J., & Raven, J. (2003). Raven progressive matrices. In R. Steve & R. S. McCallum (Eds.), Handbook of nonverbal assessment (pp. 223–237). New York: Kluwer.
Raven, J. C. (1938). Progressive matrices: A perceptual test of intelligence. London: H. K. Lewis.
Rhodes, M. G. (2016). Judgments of learning. In J. Dunlosky & S. K. Tauber (Eds.), The Oxford handbook of metamemory (pp. 65–80). New York: Oxford University Press.
Rhodes, M. G., & Castel, A. D. (2008). Memory predictions are influenced by perceptual information: Evidence for metacognitive illusions. Journal of Experimental Psychology: General, 137, 615–625.
Rhodes, M. G., & Castel, A. D. (2009). Metacognitive illusions for auditory information: Effects on monitoring and control. Psychonomic Bulletin & Review, 16, 550–554.
Richardson, J. T. E. (1998). The availability and effectiveness of reported mediators in associative learning: A historical review and an experimental investigation. Psychonomic Bulletin & Review, 5, 597–614.
Rivers, M. L., Dunlosky, J., & Persky, A. M. (2020). Measuring metacognitive knowledge, monitoring, and control in the pharmacy classroom and experiential settings. American Journal of Pharmaceutical Education, 84, 7730.
Robison, M. K., & Unsworth, N. (2017). Working memory capacity, strategic allocation of study time, and value-directed remembering. Journal of Memory and Language, 93, 231–244.
Rozencwajg, P. (2003). Metacognitive factors in scientific problem-solving strategies. European Journal of Psychology of Education, 18, 281–294.
Ryu, E. (2015). The role of centering for interaction of level 1 variables in multilevel structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 22, 617–630.
Sanna, L. J., & Pusecker, P. A. (1994). Self-efficacy, valence of self-evaluation, and performance. Personality and Social Psychology Bulletin, 20, 82–92.
Saraç, S., Önder, A., & Karakelle, S. (2014). The relations among general intelligence, metacognition and text learning performance. Education and Science, 39, 40–53.
Smouse, A. D., & Munz, D. C. (1968). The effects of anxiety and item difficulty sequence on achievement testing scores. The Journal of Psychology, 68, 181–184.
Soderstrom, N. C., Clark, C. T., Halamish, V., & Bjork, E. L. (2015). Judgments of learning as memory modifiers. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41, 553–558.
Soderstrom, N. C., & McCabe, D. P. (2011). The interplay between value and relatedness as bases for metacognitive monitoring and control: Evidence for agenda-based monitoring. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 1236–1242.
Son, L. K., & Metcalfe, J. (2000). Metacognitive and control strategies in study-time allocation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 204–221.
Spellman, B. A., & Bjork, R. A. (1992). When predictions create reality: Judgments of learning may alter what they are intended to assess. Psychological Science, 5, 315–316.
Staff, R. T., Hogan, M. J., & Whalley, L. J. (2014). Aging trajectories of fluid intelligence in late life: The influence of age, practice and childhood IQ on Raven’s progressive matrices. Intelligence, 47, 194–201.
Sternberg, R. J. (1981). Intelligence and nonentrenchment. Journal of Educational Psychology, 73, 1–16.
Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. New York: Cambridge University Press.
Thiede, K. W., & Dunlosky, J. (1999). Toward a general model of self-paced study: An analysis of selection of items for study and self-paced study time. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25, 1024–1037.
Thorndike, E. L., & Lorge, I. (1944). The Teacher's work book of 30000 words. New York: Bureau of Publications.
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 & Cognition, 35, 822–828.
Unsworth, N. (2016). Working memory capacity and recall from long-term memory: Examining the influence of encoding strategies, study time allocation, search efficiency, and monitoring abilities. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42, 50–61.
Van der Stel, M., & Veenman, M. V. J. (2014). Metacognitive skills and intellectual ability of young adolescents: A longitudinal study from a developmental perspective. European Journal of Psychology of Education, 29, 117–137.
Vuorre, M. (2017). Bmlm: Bayesian multilevel mediation. R package version 1.3.4. https://cran.r-project.org/package=bmlm.
Vuorre, M., & Bolger, N. (2018). Within-subject mediation analysis for experimental data in cognitive psychology and neuroscience. Behavior Research Methods, 50, 2125–2143.
Weinstein, Y., & Roediger III, H. L. (2010). Retrospective bias in test performance: Providing easy items at the beginning of a test makes students believe they did better on it. Memory & Cognition, 38, 366–376.
Yu, Y., Jiang, Y., & Li, F. (2020). The effect of value on judgment of learning in tradeoff learning condition: The mediating role of study time. Metacognition and Learning., 15, 435–454.
This research was supported in part by the National Institutes of Health (National Institute on Aging; Award Number R01 AG044335 to Alan D. Castel).
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Murphy, D.H., Agadzhanyan, K., Whatley, M.C. et al. Metacognition and fluid intelligence in value-directed remembering. Metacognition Learning (2021). https://doi.org/10.1007/s11409-021-09265-9
- Judgments of learning
- Fluid intelligence