Funded Grants

Researcher: Nathan   Kornell, Ph.D.

Grantee: Williams College, Williamstown, MA, USA

Researcher: Nathan Kornell, Ph.D.

Grant Title: Improving self-regulated learning

Program Area: Understanding Human Cognition

Grant Type: Scholar Award

Amount: $600,000

Year Awarded: 2013

Duration: 6 years

Improving self-regulated learning

A century ago, athletes decided how to train based on intuition. Today they rely on evidence. Athletes get faster, stronger, and more skilled, decade after decade, in virtually all sports that allow objective measurement. Studying, which is the academic equivalent of training, has not changed significantly in the last century. Students (and learners of all ages) still make decisions based on intuition, not evidence. Only a fraction of students decide how to study based on advice they have received, and only a fraction of that advice is probably based on evidence [1], [2].

It is time for students to study more effectively. My research is dedicated to two goals: understanding the basic principles of learning, and understanding the judgments and decisions people make when they study. I pursue these goals by doing research that applies to everyday studying, but my main focus is basic research on principles of learning and self-regulated study.

Understanding the basic principles of learning

My research has focused on two principles of learning: retrieval and spacing. Teachers and students do not realize that retrieving a memory is a powerful way to learn [3], [4]. Our research aims to discover why retrieval enhances learning. We have shown, for example, that even retrieval failures enhance subsequent learning. This finding has practical implications but it also constrains theories of retrieval [5], [6].

Distributing study events across time (e.g., studying biology daily instead of once a week) is another counterintuitive, but effective, technique [7–9]. Even when people learn complex concepts (such as finch or sparrow), we found that interleaving concepts was more effective than studying one concept at a time [8], [10]. In addition its practical implications, understanding how interleaving affects concept learning has consequences for theories of concept learning and spacing [11], [12].

Understanding the judgments and decisions people make when they study

How, when, and how much a student decides to study is ultimately up to him or her. People make study decisions based on judgments of learning (JOLs)—predictions of their ability to remember in the future. Understanding the heuristics and biases that control JOLs is an important theoretical goal [13]. It is also central to helping students study more effectively [14–16], especially because people generally prefer study strategies that maximize immediate performance, rather than more challenging, and effective, strategies like testing and spacing [17].

It was once assumed that memory strength is the cue underlying JOLs [18]. Our research revealed a double dissociation between JOLs and memory strength [19]. JOLs are sensitive to observable cues, but unobservable processes, such as future studying and forgetting, tend to be ignored, which makes JOLs inaccurate [20–22]. Many theoretical puzzles remain.

One way of understanding metacognitive processes is to examine their roots in non-human animals [23–25]. We found that animals can make domain-general confidence judgments that transfer across tasks [26], [27]. Progress in research on metacognition in animals—and young children—stands to benefit from investigating the cues, heuristics, and possibly beliefs that guide judgments.


[1] M. K. Hartwig and J. Dunlosky, “Study strategies of college students: are self-testing and scheduling related to achievement?, “ Psychonomic Bulletin & Review, vol. 19, no. 1, pp. 126–34, Feb. 2012.
[2] N. Kornell and R. A. Bjork, “The promise and perils of self-regulated study, “ Psychonomic Bulletin & Review, vol. 14, no. 2, pp. 219–224, Apr. 2007.
[3] J. D. Karpicke, “Metacognitive control and strategy selection: Deciding to practice retrieval during learning, “ Journal of Experimental Psychology: General, vol. 138, no. 4, pp. 469–486, Nov. 2009.
[4] N. Kornell and L. K. Son, “Learners’ choices and beliefs about self-testing, “ Memory, vol. 17, no. 5, pp. 493–501, Jul. 2009.
[5] N. Kornell, M. J. Hays, and R. A. Bjork, “Unsuccessful retrieval attempts enhance subsequent learning, “ Journal of Experimental Psychology: Learning, Memory, and Cognition, vol. 35, no. 4, pp. 989–998, Jul. 2009.
[6] L. E. Richland, N. Kornell, and L. S. Kao, “The pretesting effect: do unsuccessful retrieval attempts enhance learning?, “ Journal of Experimental Psychology: Applied, vol. 15, no. 3, pp. 243–257, Sep. 2009.
[7] N. Kornell, “Optimizing learning using flashcards: Spacing is more effective than cramming, “ Applied Cognitive Psychology, vol. 23, no. 9, pp. 1297–1317, Dec. 2009.
[8] N. Kornell and R. A. Bjork, “Learning concepts and categories: is spacing the ‘enemy of induction’?, “ Psychological Science, vol. 19, no. 6, pp. 585–592, Jun. 2008.
[9] D. A. Simon and R. A. Bjork, “Metacognition in motor learning, “ Journal of Experimental Psychology: Learning, Memory, and Cognition, vol. 27, no. 4, pp. 907–912, 2001.
[10] N. Kornell, A. D. Castel, T. S. Eich, and R. A. Bjork, “Spacing as the friend of both memory and induction in young and older adults, “ Psychology and Aging, vol. 25, no. 2, pp. 498–503, Jun. 2010.
[11] M. S. Birnbaum, N. Kornell, E. L. Bjork, and R. a Bjork, “Why interleaving enhances inductive learning: The roles of discrimination and retrieval., “ Psychonomic Bulletin & Review, pp. 392–402, Nov. 2012.
[12] S. H. K. Kang and H. Pashler, “Learning Painting Styles: Spacing is Advantageous when it Promotes Discriminative Contrast, “ Applied Cognitive Psychology, vol. 26, no. 1, pp. 97–103, Jan. 2012.
[13] R. A. Bjork, J. Dunlosky, and N. Kornell, “Self-Regulated Learning: Beliefs, Techniques, and Illusions, “ Annual Review of Psychology, vol. 64, pp. 417–444, Sep. 2012.
[14] N. Kornell and J. Metcalfe, “Study efficacy and the region of proximal learning framework, “ Journal of Experimental Psychology: Learning, Memory, and Cognition, vol. 32, no. 3, pp. 609–622, May 2006.
[15] J. Metcalfe and N. Kornell, “Principles of cognitive science in education: The effects of generation, errors and feedback, “ Psychonomic Bulletin & Review, vol. 14, no. 2, pp. 225– 229, Apr. 2007.
[16] K. W. Thiede, M. C. M. Anderson, and D. Therriault, “Accuracy of metacognitive monitoring affects learning of texts, “ Journal of Educational Psychology, vol. 95, no. 1, pp. 66–73, 2003.
[17] E. L. Bjork and R. A. Bjork, “Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning., “ in Psychology and the real world: Essays illustrating fundamental contributions to society, M. A. Gernsbacher, R. W. Pew, L. M. Hough, and J. R. Pomerantz, Eds. New York: Worth Publishers, 2011, pp. 56–64.
[18] J. T. Hart, “Memory and the memory-monitoring process, “ Journal of Verbal Learning and Verbal Behavior, vol. 6, no. 5, pp. 685–691, Oct. 1967.
and Verbal Behavior
, vol. 6, no. 5, pp. 685–691, Oct. 1967.
[19] N. Kornell, M. G. Rhodes, A. D. Castel, and S. K. Tauber, “The ease of processing heuristic and the stability bias: Dissociating memory, memory beliefs, and memory judgments, “ Psychological Science, vol. 22, no. 6, pp. 787–794, Jun. 2011.
[20] A. Koriat, R. A. Bjork, L. Sheffer, and S. K. Bar, “Predicting one’s own forgetting: The role of experience-based and theory-based processes, “ Journal of Experimental Psychology: General, vol. 133, no. 4, pp. 643–656, Dec. 2004.
[21] N. Kornell and R. A. Bjork, “A stability bias in human memory: Overestimating remembering and underestimating learning, “ Journal of Experimental Psychology: General, vol. 138, no. 4, pp. 449–468, Nov. 2009.
[22] N. Kornell, “Failing to Predict Future Changes in Memory: A Stability Bias Yields Long- Term Overconfidence, “ in Successful remembering and successful forgetting: a Festschrift in honor of Robert A. Bjork. , A. S. Benjamin, Ed. New York: Psychology Press, 2011, pp. 365–386.
[23] J. D. Smith, “The study of animal metacognition, “ Trends in Cognitive Sciences, vol. 13, no. 9, pp. 389–96, Sep. 2009.
[24] H. S. Terrace and L. K. Son, “Comparative metacognition., “ Current opinion in neurobiology, vol. 19, no. 1, pp. 67–74, Feb. 2009.
[25] N. Kornell, “Metacognition in Humans and Animals, “ Current Directions in Psychological Science, vol. 18, no. 1, pp. 11–15, Feb. 2009.
[26] L. K. Son and N. Kornell, “Metaconfidence judgments in rhesus macaques: Explicit versus implicit mechanisms, “ in The Missing Link in Cognition: Origins of Self-Reflective Consciousness, H. S. Terrace and J. Metcalfe, Eds. Oxford, UK: Oxford University Press, 2005, pp. 296–320.
[27] N. Kornell, L. K. Son, and H. S. Terrace, “Transfer of metacognitive skills and hint seeking in monkeys, “ Psychological Science, vol. 18, no. 1, pp. 64–71, Jan. 2007.