Skip to main content Accessibility help
×
Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-29T03:38:29.890Z Has data issue: false hasContentIssue false

5 - Metacognition and Self-Regulated Learning

from Part I - Foundations

Published online by Cambridge University Press:  14 March 2022

R. Keith Sawyer
Affiliation:
University of North Carolina, Chapel Hill
Get access

Summary

Metacognition is thinking about the contents and processes of one’s own cognition. Research shows that metacognition plays important roles in most cognitive tasks, from everyday behaviors to problem-solving to expert performance. This chapter focuses on metacognition’s centrality in learning and in self-regulated learning. When learning, people monitor what they know and whether it is aligned with their intended learning outcome. A learner’s ability to monitor effectively is known as calibration. Learners then control their next actions based on their monitoring, and finally they self-regulate the process of monitoring and controlling their learning by shaping and adapting cognition or behavior by reaching forward by planning for future tasks. Research shows that people learn better when they have strong metacognitive abilities and when they can self-regulate their learning effectively.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ainley, M., & Ainley, J. (2020). Motivation and learning. In Renninger, K. A. & Hidi, S. E. (Eds.), The Cambridge handbook of motivation and learning (pp. 665688). Cambridge, England: Cambridge University Press.Google Scholar
Azevedo, R. (2014). Metacognition and multimedia learning. In Mayer, R. E. (Ed.), The Cambridge handbook of multimedia (2nd ed., pp. 647672). Cambridge, England: Cambridge University Press.Google Scholar
Azevedo, R. (2020). Reflections on the field of metacognition: Issues, challenges, and opportunities. Metacognition and Learning, 15(2), 919998.Google Scholar
Azevedo, R., & Gasević, D. (2019). Analyzing multimodal multichannel data about self-regulated learning with advanced learning technologies: Issues and challenges. Computers in Human Behavior, 96, 207210.Google Scholar
Azevedo, R., Johnson, A., Chauncey, A., & Graesser, A. (2011). Use of hypermedia to convey and assess self-regulated learning. In Zimmerman, B. & Schunk, D. (Eds.), Handbook of self-regulation of learning and performance (pp. 102121). New York, NY: Routledge.Google Scholar
Azevedo, R., Taub, M., & Mudrick, N. V. (2018). Using multi-channel trace data to infer and foster self-regulated learning between humans and advanced learning technologies. In Schunk, D. & Greene, J. A. (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 254270). New York, NY: Routledge.Google Scholar
Baars, M., & Wijnia, L. (2018). The relation between task-specific motivational profiles and training of self-regulated learning skills. Learning and Individual Differences, 64, 125137.Google Scholar
Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 126.CrossRefGoogle ScholarPubMed
Biswas, G., Baker, R., & Paquette, L. (2018). Data mining for assessing self-regulated learning. In Schunk, D. & Greene, J. A. (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 388404). New York, NY: Routledge.Google Scholar
Biswas, G., Segedy, J. R., & Bunchongchit, K. (2016). From design to implementation to practice – a learning by teaching system: Betty’s Brain. International Journal of Artificial Intelligence in Education, 26(1), 350364.Google Scholar
Boekaerts, M. (1995). Self-regulated learning: Bridging the gap between metacognitive and metamotivation theories. Educational Psychologist, 30(4), 195200.CrossRefGoogle Scholar
Bol, L., & Hacker, D. (2012). Calibration research: Where do we go from here? Frontiers in Psychology, 3, 16.Google Scholar
Bol, L., Hacker, D. J., Walck, C. C., & Nunnery, J. (2012). The effects of individual or group guidelines on the calibration accuracy and achievement of high school biology students. Contemporary Educational Psychology, 37(4), 280287.Google Scholar
Bol, L., Riggs, R., Hacker, D. J., & Nunnery, J. (2010). The calibration accuracy of middle school students in math classes. Journal of Research in Education, 21(2), 8196.Google Scholar
Butler, D., & Winne, P. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245281.Google Scholar
Carpenter, S. K. (2020). Distributed practice or spacing effect. In Zhang, L.-F. (Ed.), Oxford research encyclopedia of education. Oxford, England: Oxford University Press. Retrieved from https://664ef278-1723-43c6-bbe1-3bd4e65a87fe.filesusr.com/ugd/f4b9f1_18eca7ddc3bc4783a23bda3ff7e4d1f8.pdfGoogle Scholar
Cromley, J., & Azevedo, R. (2011). Measuring strategy use in context with multiple-choice items. Metacognition and Learning, 6(2), 155177.CrossRefGoogle Scholar
Cromley, J., & Kunze, A. (2020). Metacognition in education: Translational research. Translational Issues in Psychological Science, 6(1), 1520.Google Scholar
Desoete, A. (2008). Multi-method assessment of metacognitive skills in elementary school children: How you test is what you get. Metacognition and Learning, 3, 189206.Google Scholar
Dignath, C., & Buttner, G. (2018). Teachers’ direct and indirect promotion of self-regulated learning in primary and secondary school mathematics classes – insights from video-based classroom observations and teacher interviews. Metacognition and Learning, 13(2), 127157.Google Scholar
Dignath, C., & Veenman, M. (2021). The role of direct strategy instruction and indirect activation of self-regulated learning. Evidence from classroom observation studies. Educational Psychology Review, 33, 489533.Google Scholar
Donker, A. S., de Boer, H., Kostons, D., Dignath van Ewijk, C. C., & van der Werf, M. P. C. (2014). Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Educational Research Review, 11(1), 126.CrossRefGoogle Scholar
Double, K., & Birney, D. (2019). Reactivity to measures of metacognition. Frontiers in Psychology, 10, 112.CrossRefGoogle ScholarPubMed
Dunlosky, J., & Ariel, R. (2011). Self-regulated learning and the allocation of study time. In Ross, B. (Ed.), Psychology of learning and motivation (Vol. 54, pp. 103140). San Diego, CA: Elsevier Academic Press.Google Scholar
Dunlosky, J., & Lipko, A. (2007). Metacomprehension: A brief history and how to improve its accuracy. Current Directions in Psychological Science, 16(4), 228232.Google Scholar
Dunlosky, J., & Rawson, K. A. (2012). Overconfidence produces underachievement: Inaccurate self-evaluations undermine students’ learning and retention. Learning and Instruction, 22(4), 271280.Google Scholar
Dunlosky, J., & Rawson, K. (2019). The Cambridge handbook of cognition and education. Cambridge, England: Cambridge University Press.CrossRefGoogle Scholar
Dunlosky, J., & Tauber, S. K. (2016). The Oxford handbook of metamemory. Oxford, England: Oxford University Press.Google Scholar
Dunn, K. E., & Lo, W.-J. (2015). Understanding the influence of learners’ forethought on their use of science study strategies in postsecondary science learning. International Journal of Science Education, 37(16), 25972618.Google Scholar
Elliot, A. J., & Hulleman, C. S. (2017). Achievement goals. In Elliot, A. J., Dweck, C. S., & Yeager, D. S. (Eds.), Handbook of competence and motivation: Theory and application (pp. 4360). New York, NY: The Guilford Press.Google Scholar
Fiechter, J. L., Benjamin, A. S., & Unsworth, N. (2016). The metacognitive foundations of effective remembering. In Dunlosky, J. & Tauber, S. K. (Eds.), The Oxford handbook of metamemory (pp. 307324). Oxford, England: Oxford University Press.Google Scholar
Flavell, J. H., Friedrichs, A. G., & Hoyt, J. D. (1970). Developmental changes in memorization processes. Cognitive Psychology, 1(4), 324340.Google Scholar
Garner, R. (1990). When children and adults do not use learning strategies: Toward a theory of settings. Review of Educational Research, 60(4), 517529.Google Scholar
Gentner, N., & Seufert, T. (2020). The double-edged interactions of prompts and self-efficacy. Metacognition and Learning, 15, 261289.Google Scholar
Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451482.Google Scholar
Graesser, A. C. (2019). Learning science principles and technologies with agents that promote deep learning. In Feldman, R. S. (Ed.), Learning science: Theory, research, and practice (pp. 233). New York, NY: McGraw-Hill.Google Scholar
Greene, J. A., & Azevedo, R. (2009). A macro-level analysis of SRL processes and their relations to the acquisition of sophisticated mental models. Contemporary Educational Psychology, 34(1), 1829.Google Scholar
Greene, J. A., Deekens, V., Copeland, D., & Yu, S. (2018). Capturing and modeling self-regulated learning using think-aloud protocols. In Schunk, D. & Greene, J. A (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 323337). New York, NY: Routledge.Google Scholar
Greene, J. A., Hutchison, L. A., Costa, L., & Crompton, H. (2012). Investigating how college students’ task definitions and plans relate to self-regulated learning processing and understanding of a complex science topic. Contemporary Educational Psychology, 37(4), 307230.Google Scholar
Griffin, T. D., Mielicki, M. K., & Wiley, J. (2019). Improving students’ metacomprehension accuracy. In Dunlosky, J. and Rawson, K. A. (Eds.), The Cambridge handbook of cognition and education (pp. 619646). Cambridge, England: Cambridge University Press.Google Scholar
Hacker, D., & Bol, L. (2019). Calibration and self-regulated learning. In Dunlosky, J. & Rawson, K. (Eds.), The Cambridge handbook of cognition and education (pp. 647677). Cambridge, England: Cambridge University Press.Google Scholar
Hacker, D. J., Bol, L., & Bahbahani, K. (2008). Explaining calibration in classroom contexts: The effects of incentives, reflection, and attributional style. Metacognition and Learning, 3(2), 101121.CrossRefGoogle Scholar
Hacker, D. J., Bol, L., Horgan, D., & Rakow, E. A. (2000). Test prediction and performance in a classroom context. Journal of Educational Psychology, 92(1), 160170.Google Scholar
Hart, J. T. (1965). Memory and the feeling-of-knowing experience. Journal of Educational Psychology, 56(4), 208216.Google Scholar
Hart, J. T. (1967). Memory and the memory-monitoring process. Journal of Verbal Learning and Verbal Behavior, 6(5), 685691.Google Scholar
Hartman, H. J. (2001). Metacognition in learning and instruction: Theory, research and practice. Amsterdam, The Netherlands: Springer.Google Scholar
Hartwig, M. K., & Dunlosky, J. (2017). Category learning judgments in the classroom: Can students judge how well they know course topics? Contemporary Educational Psychology, 49, 8090.Google Scholar
Ikeda, K., Yue, C. L., Murayama, K., & Castel, A. D. (2016). Achievement goals affect metacognitive judgments. Motivation Science, 2(4), 199219.Google Scholar
Jacobs, J. E., & Paris, S. G. (1987). Children’s metacognition about reading: Issues in definition, measurement, and instruction. Educational Psychologist, 22(3–4), 255278.CrossRefGoogle Scholar
Järvelä, S., Malmberg, J., Haataja, E., Sobosincki, M., & Kirschner, P. (2021). What multimodal data can tell us about the students’ regulation of their learning process? Learning and Instruction, 72. doi:10.1016/j.learninstruc.2019.04.004Google Scholar
Jemstedt, A., Schwartz, B., & Jönsson, F. (2018). Ease-of-learning judgments are based on both processing fluency and beliefs. Memory, 26(6), 807815.Google Scholar
Kirk, E. P., & Ashcraft, M. H. (2001). Telling stories: The perils and promise of using verbal reports to study math strategies. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27(1), 157175.Google Scholar
Kleitman, S., & Narciss, S. (2019). Introduction to the special issue “applied metacognition: Real-world applications beyond learning.” Metacognition & Learning, 14(3), 335342.Google Scholar
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), 349370.Google Scholar
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), 959972.Google Scholar
Koriat, A., Ma’ayan, H., & Nussinson, R. (2006). The intricate relationship between monitoring and control in metacognition: Lessons for the cause-and effect relation between subjective experience and behavior. Journal of Experimental Psychology: General, 135(1), 3669.CrossRefGoogle ScholarPubMed
Kramarski, B. (2018). Teachers as agents in prompting students’ SRL and performance: Applications for teachers’ dual role training program. In Schunk, D. & Greene, J. A. (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 223239). New York, NY: Routledge.Google Scholar
Kramarski, B., & Dudai, V. (2009). Group-metacognitive support for online inquiry in mathematics with differential self-questioning. Journal of Educational Computing Research, 40(4), 377404.Google Scholar
Lippmann, M., Schwartz, N., Jacobson, N., & Narciss, S. (2019). The concreteness of titles affects metacognition and study motivation. Instructional Science, 47(2), 257277.Google Scholar
Maki, R. H., & Serra, M. (1992). The basis of test predictions for text material. Journal of Experimental Psychology: Learning, Memory, and Cognition, 18(1), 116126.Google Scholar
Maki, R. H., Shields, M., Wheeler, A. E., & Zacchilli, T. L. (2005). Individual differences in absolute and relative metacomprehension accuracy. Journal of Educational Psychology, 97(4), 723731.Google Scholar
McDowell, L. D. (2019). The roles of motivation and metacognition in producing self-regulated learners of college physical science: A review of empirical studies. International Journal of Science Education, 41(17), 25242541.CrossRefGoogle Scholar
Metcalfe, J., & Finn, B. (2008). Evidence that judgments of learning are causally related to study choice. Psychonomic Bulletin & Review, 15(1), 174179.Google Scholar
Metcalfe, J., & Kornell, N. (2005). A region of proximal learning model of study time allocation. Journal of Memory and Language, 52(4), 463477.Google Scholar
Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York, NY: Holt, Rinehart & Winston.Google Scholar
Mudrick, N. V., Azevedo, R., & Taub, M. (2019). Integrating metacognitive judgements and eye movements using sequential pattern mining to understand processes underlying successful multimedia learning. Computers in Human Behavior, 96, 223234.Google Scholar
Muis, K., & Duffy, M. (2013). Epistemic climate and epistemic change: Instruction designed to change students’ epistemic beliefs and learning strategies and improve achievement. Journal of Educational Psychology, 105, 213222.Google Scholar
National Academies of Sciences, Engineering, and Medicine. (2018). How people learn II: Learners, contexts, and cultures. Washington, DC: The National Academies Press.Google Scholar
Nelson, T. O. (1996). Gamma is a measure of the accuracy of predicting performance on one item relative to another item, not of the absolute performance on an individual item. Applied Cognitive Psychology, 10(3), 257260.Google Scholar
Nietfeld, J. L., Enders, C. K., & Schraw, G. (2006). A Monte Carlo comparison of two measures of monitoring accuracy. Educational and Psychological Measurement, 66(2), 258271.Google Scholar
Pesout, O., & Nietfeld, J. (2020). The impact of cooperation and competition on metacognitive monitoring in classroom context. The Journal of Experimental Education, 1–22. doi:10.1080/00220973.2020.1751577Google Scholar
Pieschl, S., Stahl, E., Murray, T., & Bromme, R. (2013). Is adaptation to task complexity really beneficial for performance? Learning and Instruction, 22(4), 281289.Google Scholar
Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In Boekaerts, M., Pintrich, P., & Zeidner, M. (Eds.), Handbook of self-regulation (pp. 451502). San Diego, CA: Academic Press.Google Scholar
Pintrich, P. R. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667686.Google Scholar
Pintrich, P. R., Smith, D., Garcia, T., & McKeachie, W. (1993). Predictive validity and reliability of the Motivated Strategies for Learning Questionnaire (MSLQ). Educational and Psychological Measurement, 53, 801813.Google Scholar
Robey, A., Dougherty, M., & Buttaccio, D. (2017). Making retrospective confidence judgements improves learners’ ability to decide what not to study. Psychological Science, 28(11), 16831693.Google Scholar
Roth, A., Ogrin, S., & Schmitz, B. (2015). Assessing self-regulated learning in higher education: A systematic literature review of self-report instruments. Educational Assessment, Evaluation and Accountability, 28(3), 225250. doi:10.1007/s11092-015-9229-2Google Scholar
Schraw, G. (2009a). A conceptual analysis of five measures of metacognitive monitoring. Metacognition and Learning, 4(1), 3345.Google Scholar
Schraw, G. (2009b). Measuring metacognitive judgements. In Hacker, D. J., Dunlosky, J., & Graesser, A. C. (Eds.), Handbook of metacognition in education (pp. 415429). New York, NY: Routledge.Google Scholar
Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460475.Google Scholar
Schraw, G., Potenza, M. T., & Nebelsick-Gullet, L. (1993). Constraints on the calibration of performance. Contemporary Educational Psychology, 18(4), 455463.Google Scholar
Schunk, D., & Greene, J. A. (2018). Handbook self-regulation of learning and performance (2nd ed.). New York, NY: Routledge.Google Scholar
Sitzmann, T., & Ely, K. (2011). A meta-analysis of self-regulated learning in work-related training and educational attainment: What we know and where we need to go. Psychological Bulletin, 137(3), 421444.Google Scholar
Suárez, J. M., & Fernández, A. P. (2011). Evaluación de las estrategias de autorregulación afectivo-motivacional de los estudiantes: Las EEMA-VS. Anales de Psicología, 27(2), 369380.Google Scholar
Taub, M., & Azevedo, R. (2019). How does prior knowledge influence fixations on and sequences of cognitive and metacognitive SRL processes during learning with an ITS? International Journal of Artificial Intelligence in Education, 29(1), 128.Google Scholar
Urdan, Y., & Kaplan, A. (2020). The origins, evolution, and future directions of achievement goal theory. Contemporary Educational Psychology, 61, Article 101862. doi:10.1016/j.cedpsych.2020.101862Google Scholar
Veenman, M. J. (2007). The assessment and instruction of self-regulation in computer-based environments: A discussion. Metacognition and Learning, 2, 177183.Google Scholar
Weber, E. U., & Johnson, E. J. (2009). Mindful judgment and decision making. Annual Review of Psychology, 60(1), 5385.Google Scholar
Wiedbusch, M., & Azevedo, R. (2020). Modeling metacomprehension monitoring accuracy with eye gaze on informational content in a multimedia learning environment. In Symposium on Eye Tracking Research and Applications (ETRA’20 Full Papers), ACM, New York.Google Scholar
Winne, P. H. (2010a). Improving measurements of self-regulated learning. Educational Psychologist, 45(4), 267276.Google Scholar
Winne, P. H. (2010b). Bootstrapping learner’s self-regulated learning. Psychological Test and Assessment Modeling, 52(4), 472490.Google Scholar
Winne, P. H. (2011). A cognitive and metacognitive analysis of self-regulated learning. In Zimmerman, B. J. & Schunk, D. H. (Eds.), Handbook of self-regulation of learning and performance (pp. 1532). New York, NY: Routledge.Google Scholar
Winne, P. H. (2018a). Theorizing and researching levels of processing in self-regulated learning. British Journal of Educational Psychology, 88(4), 920.Google Scholar
Winne, P. H. (2018b). Cognition and metacognition within self-regulated learning. In Schunk, D. & Greene, J. (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 3648). New York, NY: Routledge.Google Scholar
Winne, P. H. (2020a). A proposed remedy for grievances about self-report methodologies. Frontline Learning Research, 8(3), 165174.Google Scholar
Winne, P. H. (2020b). Construct and consequential validity for learning analytics based on trace data. Computers in Human Behavior, 12, Article 106457. doi:10.1016/j.chb.2020.106457Google Scholar
Winne, P. H., Gupta, L., & Nesbit, J. (1994). Exploring individual differences in studying strategies using graph theoretic statistics. Alberta Journal of Educational Research, 40(2), 177193.Google Scholar
Winne, P. H., & Hadwin, A. F. (2008). The weave of motivation and self-regulated learning. In Schunk, D. H. & Zimmerman, B. J. (Eds.), Motivation and self-regulated learning: Theory, research, and applications (pp. 297314). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Winne, P. H., & Marzouk, Z. (2019). Learning strategies and self-regulated learning. In Dunlosky, J. & Rawson, K. (Eds.), Cambridge handbook of cognition and education (pp. 696715). New York, NY: Cambridge University Press.Google Scholar
Winne, P. H., Teng, K., Chang, D., et al. (2019). nStudy: Software for learning analytics about processes for self-regulated learning. Journal of Learning Analytics, 6(2), 95106.Google Scholar
Zepeda, C., Richey, J. E., Ronevich, P., & Nokes-Malach, T. (2015). Direct instruction of metacognition benefits adolescent science learning, transfer, and motivation: An in vivo study. Journal of Educational Psychology, 107(4), 954970.Google Scholar
Zhou, M. (2013). University student’s goal profiles and metacomprehension accuracy. Educational Psychology: An International Journal of Experimental Educational Psychology, 33(1), 113.Google Scholar
Zimmerman, B. (2011). Motivational sources and outcomes of self-regulated learning and performance. In Zimmerman, B. J. & Schunk, D. H. (Eds.), Handbook of self-regulation of learning and performance (pp. 4964). New York, NY: Routledge.Google Scholar
Zimmerman, B. J., & Moylan, A. R. (2009). Self-regulation: Where metacognition and motivation intersect. In Hacker, D., Dunlosky, J., & Graesser, A. (Eds.), Handbook of metacognition in education (pp. 299315). New York, NY: Routledge.Google Scholar
Zimmerman, B. J., & Schunk, D. H. (Eds.). (2011). Handbook of self-regulation of learning and performance. New York, NY: Routledge.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×