Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

creased by 0.47 SDs under active learning (n = 158 studies), and that the odds ratio for failing was 1.95 under traditional lecturing (n = 67 studies). These results indicate that average examination scores improved by about 6% in active learning sections, and that students in classes with traditional lecturing were 1.5 times more likely to fail than were students in classes with active learning. Heterogeneity analyses indicated that both results hold across the STEM disciplines, that active learning increases scores on concept inventories more than on course examinations, and that active learning appears effective across all class sizes—although the greatest effects are in small (n ≤ 50) classes. Trim and fill analyses and fail-safe n calculations suggest that the results are not due to publication bias. The results also appear robust to variation in the methodological rigor of the included studies, based on the quality of controls over student quality and instructor identity. This is the largest and most comprehensive metaanalysis of undergraduate STEM education published to date. The results raise questions about the continued use of traditional lecturing as a control in research studies, and support active learning as the preferred, empirically validated teaching practice in regular classrooms.

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Active learning increases student performance in science, engineering, and mathematics

The power of feedback.

Self-regulated learning (SRL) is a pivot upon which students’ achievement turns. We explain how feedback is inherent in and a prime determiner of processes that constitute SRL, and review areas of research that elaborate contemporary models of how feedback functions in learning. Specifically, we begin by synthesizing a model of self-regulation based on contemporary educational and psychological literatures. Then we use that model as a structure for analyzing the cognitive processes involved in self-regulation, and for interpreting and integrating findings from disparate research traditions. We propose an elaborated model of SRL that can embrace these research findings and that spotlights the cognitive operation of monitoring as the hub of self-regulated cognitive engagement. The model is then used to reexamine (a) recent research on how feedback affects cognitive engagement with tasks and (b) the relation among forms of engagement and achievement. We conclude with a proposal that research on feedback and ...

Feedback and Self-Regulated Learning: A Theoretical Synthesis

I. the origin of species by means of natural selection

Many students are being left behind by an educational system that some people believe is in crisis. Improving educational outcomes will require efforts on many fronts, but a central premise of this monograph is that one part of a solution involves helping students to better regulate their learning through the use of effective learning techniques. Fortunately, cognitive and educational psychologists have been developing and evaluating easy-to-use learning techniques that could help students achieve their learning goals. In this monograph, we discuss 10 learning techniques in detail and offer recommendations about their relative utility. We selected techniques that were expected to be relatively easy to use and hence could be adopted by many students. Also, some techniques (e.g., highlighting and rereading) were selected because students report relying heavily on them, which makes it especially important to examine how well they work. The techniques include elaborative interrogation, self-explanation, summarization, highlighting (or underlining), the keyword mnemonic, imagery use for text learning, rereading, practice testing, distributed practice, and interleaved practice. To offer recommendations about the relative utility of these techniques, we evaluated whether their benefits generalize across four categories of variables: learning conditions, student characteristics, materials, and criterion tasks. Learning conditions include aspects of the learning environment in which the technique is implemented, such as whether a student studies alone or with a group. Student characteristics include variables such as age, ability, and level of prior knowledge. Materials vary from simple concepts to mathematical problems to complicated science texts. Criterion tasks include different outcome measures that are relevant to student achievement, such as those tapping memory, problem solving, and comprehension. We attempted to provide thorough reviews for each technique, so this monograph is rather lengthy. However, we also wrote the monograph in a modular fashion, so it is easy to use. In particular, each review is divided into the following sections: General description of the technique and why it should work How general are the effects of this technique? 2a. Learning conditions 2b. Student characteristics 2c. Materials 2d. Criterion tasks Effects in representative educational contexts Issues for implementation Overall assessment The review for each technique can be read independently of the others, and particular variables of interest can be easily compared across techniques. To foreshadow our final recommendations, the techniques vary widely with respect to their generalizability and promise for improving student learning. Practice testing and distributed practice received high utility assessments because they benefit learners of different ages and abilities and have been shown to boost students' performance across many criterion tasks and even in educational contexts. Elaborative interrogation, self-explanation, and interleaved practice received moderate utility assessments. The benefits of these techniques do generalize across some variables, yet despite their promise, they fell short of a high utility assessment because the evidence for their efficacy is limited. For instance, elaborative interrogation and self-explanation have not been adequately evaluated in educational contexts, and the benefits of interleaving have just begun to be systematically explored, so the ultimate effectiveness of these techniques is currently unknown. Nevertheless, the techniques that received moderate-utility ratings show enough promise for us to recommend their use in appropriate situations, which we describe in detail within the review of each technique. Five techniques received a low utility assessment: summarization, highlighting, the keyword mnemonic, imagery use for text learning, and rereading. These techniques were rated as low utility for numerous reasons. Summarization and imagery use for text learning have been shown to help some students on some criterion tasks, yet the conditions under which these techniques produce benefits are limited, and much research is still needed to fully explore their overall effectiveness. The keyword mnemonic is difficult to implement in some contexts, and it appears to benefit students for a limited number of materials and for short retention intervals. Most students report rereading and highlighting, yet these techniques do not consistently boost students' performance, so other techniques should be used in their place (e.g., practice testing instead of rereading). Our hope is that this monograph will foster improvements in student learning, not only by showcasing which learning techniques are likely to have the most generalizable effects but also by encouraging researchers to continue investigating the most promising techniques. Accordingly, in our closing remarks, we discuss some issues for how these techniques could be implemented by teachers and students, and we highlight directions for future research.

https://www.wku.edu/senate/documents/improving_student_learning_dunlosky_2013.pdf

Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology

Contents: T.O. Nelson, Metacognitive Food for Thought in Educational Theory and Practice. Preface. D.J. Hacker, Definitions and Empirical Foundations. R.L. Dominowski, Verbalization and Problem Solving. J.E. Davidson, R.J. Sternberg, Smart Problem Solving: How Metacognition Helps. M. Carr, B. Biddlecomb, Metacognition in Mathematics From a Constructivist Perspective. B.M. Sitko, Knowing How to Write: Metacognition and Writing Instruction. R.H. Maki, Test Predictions Over Text Material. J. Otero, Influence of Knowledge Activation and Context on Comprehension Monitoring of Science Texts. D.J. Hacker, Self-Regulated Comprehension During Normal Reading. G.E. Garcia, R.T. Jimenez, P.D. Pearson, Metacognition, Childhood Bilingualism, and Reading. S.M. McGlynn, Impaired Awareness of Deficits in a Psychiatric Context: Implications of Rehabilitation. J. Dunlosky, C. Hertzog, Training Programs to Improve Learning in Later Adulthood: Helping Older Adults Educate Themselves. P.H. Winne, A.F. Hadwin, Studying as Self-Regulated Learning. N.J. Vye, D.L. Schwartz, J.D. Bransford, B.J. Barron, L. Zech, The Cognition and Technology Group at Vanderbilt, SMART Environments That Support Monitoring, Reflection, and Revision. M. Pressley, S. Van Etten, L. Yokoi, G. Freebern, P. Van Meter, The Metacognition of College Studentship: A Grounded Theory Approach. J. Dunlosky, Epilogue. Linking Metacognitive Theory to Education.

Metacognition in Educational Theory and Practice

Knowing how to manage one's own learning has become increasingly important in recent years, as both the need and the opportunities for individuals to learn on their own outside of formal classroom settings have grown. During that same period, however, research on learning, memory, and metacognitive processes has provided evidence that people often have a faulty mental model of how they learn and remember, making them prone to both misassessing and mismanaging their own learning. After a discussion of what learners need to understand in order to become effective stewards of their own learning, we first review research on what people believe about how they learn and then review research on how people's ongoing assessments of their own learning are influenced by current performance and the subjective sense of fluency. We conclude with a discussion of societal assumptions and attitudes that can be counterproductive in terms of individuals becoming maximally effective learners.

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Self-regulated learning: beliefs, techniques, and illusions.

Foreword, Robert J. Sternberg Chapter 1. A Growing Sense of "Agency," Douglas J. Hacker, John Dunlosky, and Arthur C. Graesser Part I: Comprehension Strategies Chapter 2. The Role of Metacognition in Understanding and Supporting Reading Comprehension, Margaret G. McKeown and Isabel L. Beck Chapter 3. The Role of Metacognition in Teaching Reading Comprehension to Primary Students, Joanna P. Williams and J. Grant Atkins Part II: Metacognitive Strategies Chapter 4. Question Generation and Anomaly Detection in Texts, Jose Otero Chapter 5. Self-Explanation and Metacognition: The Dynamics of Reading, Danielle S. McNamara and Joseph P. Magliano Part III: Metacomprehension Chapter 6. Metacognitive Monitoring During and After Reading, Keith W. Thiede, Thomas D. Griffin, Jennifer Wiley, and Joshua Redford Chapter 7. The Importance of Knowing What You Know: A Knowledge Monitoring Framework for Studying Metacognition in Education, Sigmund Tobias and Howard T. Everson Part IV: Writing Chapter 8. Metacognition and Children's Writing, Karen R. Harris, Steve Graham, Mary Brindle, and Karin Sandmel Chapter 9. Writing is Applied Metacognition , Douglas J. Hacker, Matt C. Keener, and John C. Kircher Part V: Science and Mathematics Chapter 10. The Interplay of Scientific Inquiry and Metacognition: More than a Marriage of Convenience, Barbara White, John Frederiksen, and Allan Collins Chapter 11. The Enigma of Mathematical Learning Disabilities: Metacognition or STICORDI, That's the Question, Annemie Desoete Part VI: Individual Differences Chapter 12. Context Matters: Gender and Cross-Cultural Differences in Confidence, Mary Lundeberg and Lindsey Mohan Chapter 13. Teachers as Metacognitive Professionals, Gerald G. Duffy, Samuel Miller, Seth Parsons, and Michael Meloth Part VII: Self-Regulated Learning Chapter 14. Supporting Self-Regulated Learning with Cognitive Tools, Philip H. Winne and John C. Nesbit Chapter 15. Effective Implementation of Metacognition, Michael J. Serra and Janet Metcalfe Chapter 16. Self-Regulation: Where Metacognition and Motivation Intersect, Barry J. Zimmerman and Adam R. Moylan Part VIII: Technology Chapter 17. Self-Regulated Learning with Hypermedia, Roger Azevedo and Amy M. Witherspoon Chapter 18. Interactive Metacognition: Monitoring and Regulating a Teachable Agent, Daniel L. Schwartz, Catherine Chase, Doris B. Chin, Marily Oppezzo, Henry Kwong, Sandra Okita, Gautam Biswas, Rod Roscoe, Hogyeong Jeong, and John Wagster Part IX: Tutoring Chapter 19. Meta-Knowledge in Tutoring, Arthur C. Graesser, Sidney D'Mello, and Natalie Person Chapter 20. In Vivo Experiments on Whether Supporting Metacognition in Intelligent Tutoring Systems Yields Robust Learning, Ken Koedinger, Vincent Aleven, Ido Roll, and Ryan Baker Part X: Measurement Chapter 21. Measuring Metacognitive Judgments, Gregory Schraw Chapter 22. Sins Committed in the Name of Ecological Validity: A Call for Representative Design in Education Science, John Dunlosky, Sara Bottiroli, and Marissa Hartwig

Handbook of Metacognition in Education

Judgments of learning (JOLs), which pertain to knowing what one knows and which help to guide self-paced study during acquisition, have almost never been very accurate at predicting subsequent recall. We recently discovered a situation in which the JOLs can be made to be extremely accurate. Here we report the conditions under which such high accuracy occurs, namely, when the JOL made on the stimulus cue is delayed until shortly after study rather than being made immediately after study. Discussion is focused both on theoretical explanations (to be explored in future research) and on potential applications of the delayed-JOL effect.

John Dunlosky

Papers

Improving Students’ Learning With Effective Learning Techniques: Promising Directions From Cognitive and Educational Psychology

Metacognition in Educational Theory and Practice

Self-regulated learning: beliefs, techniques, and illusions.

Handbook of Metacognition in Education

When People's Judgments of Learning (JOLs) are Extremely Accurate at Predicting Subsequent Recall: The “Delayed-JOL Effect”