The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Self‐Explanations: How Students Study and Use Examples in Learning to Solve Problems
Open accessAbstract
The present paper analyzes the self‐generated explanations (from talk‐aloud protocols) that “Good” and “Poor” students produce while studying worked‐out examples of mechanics problems, and their subsequent reliance on examples during problem solving. We find that “Good” students learn with understanding: They generate many explanations which refine and expand the conditions for the action parts of the example solutions, and relate these actions to principles in the text. These self‐explanations are guided by accurate monitoring of their own understanding and misunderstanding. Such learning results in example‐independent knowledge and in a better understanding of the principles presented in the text. “Poor” students do not generate sufficient self‐explanations, monitor their learning inaccurately, and subsequently rely heavily on examples. We then discuss the role of self‐explanations in facilitating problem solving, as well as the adequacy of current AI models of explanation‐based learning to account for these psychological findings.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This mechanism resembles prompted self-explanation, an instructional technique that encourages learners to articulate their reasoning and has been shown to support monitoring of understanding, identification of knowledge gaps, and integration of new information with prior knowledge (Bisra et al., 2018;Chi et al., 1989).”
From Think Before You Accept: Can Written Justification Reduce Uncritical Uptake of AI Writing Suggestions? (2026) · cites this paper as Chi et al., 1989
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The self-explanation effect was demonstrated independently of cognitive load theory (Chi et al. 1989) but can be explained by the theory.”
From Cognitive Architecture and Instructional Design: 20 Years Later (2019) · cites this paper as Chi et al. 1989
In the citing paper
“Moreover, researchers have advocated active learning because it enables learners to connect new information with the knowledge they already possess (Chi et al. 1989;Mayer 2001;Wittrock 1974).”
From Interactivity in Video-based Models (2007) · cites this paper as Chi et al. 1989
In the citing paper
“Asking learners to explain to themselves aloud what they have understood from a learning task has proved to be an effective instructional method (Chi et al. 1989;Renkl 1997;Renkl and Atkinson 2002).”
From Interactivity in Video-based Models (2007) · cites this paper as Chi et al. 1989
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Axten, N., Newell, A., & Simon, H. A. (1973) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2063712 · Cited by 6,886
Categorization and Representation of Physics Problems by Experts and Novices*
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981) · Cognitive Science · doi:10.1207/s15516709cog0502_2 · Cited by 5,248
Why a Diagram is (Sometimes) Worth Ten Thousand Words
Larkin, J. H., & Simon, H. A. (1987) · Cognitive Science · doi:10.1111/j.1551-6708.1987.tb00863.x · Cited by 3,855
The role of theories in conceptual coherence.
Murphy, G. L., & Medin, D. L. (1985) · Psychological Review · doi:10.1037/0033-295x.92.3.289 · Cited by 2,805
Advances in Instructional Psychology
(2019) · Routledge eBooks · doi:10.4324/9781315864341 · Cited by 2,538
(2014) · doi:10.4324/9781315799681 · Cited by 2,174
Advances in the Psychology of Human Intelligence
Sternberg, R. J. (2014) · Psychology Press eBooks · doi:10.4324/9781315808246 · Cited by 1,771
Eye fixations and cognitive processes
Just, M. A., & Carpenter, P. A. (1976) · Cognitive Psychology · doi:10.1016/0010-0285(76)90015-3 · Cited by 1,730
Advances in the psychology of human intelligence
Eysenck, H. J. (1983) · Behaviour Research and Therapy · doi:10.1016/0005-7967(83)90111-0 · Cited by 1,590
Michelene, T. H., Glaser, R. A., & Rees, E. T. (1981) · Defense Technical Information Center (DTIC) · Cited by 1,529
Research works printed but not linked: 4
- Brown A.L., 1983, Cognitive development (Vol. III of P.H. Mussen, Ed., Handbook of child psychology, 77
- Halliday D., 1981, Fundamentals of physics.
- Lewis C.H., 1982, Proceedings of the conference of human factors in computer systems
- 10.1007/BF00116250 · DOI · Paper page
Cited by
Sorted by citations
Items 601–700 of 1,022
Ge, X., Planas, L. G., & Er, N. (2010) · Interdisciplinary Journal of Problem-based Learning · doi:10.7771/1541-5015.1093 · Cited by 59
Argumentative Interactions, Discursive Operations, and Learning to Model in Science
Brna, P., Baker, M. J., Stenning, K., & Tiberghien, A. (2014) · Psychology Press eBooks · doi:10.4324/9781410606280-20 · Cited by 59
Wu, S. P. W., & Rau, M. A. (2017) · Learning and Instruction · doi:10.1016/j.learninstruc.2017.09.010 · Cited by 61
Clark, D. B., & Martinez-Garza, M. M. (2012) · Cambridge University Press eBooks · doi:10.1017/cbo9781139031127.023 · Cited by 59
Automated advice-giving strategies for scientific inquiry
Paolucci, M., Suthers, D. D., & Weiner, A. W. (1996) · Lecture notes in computer science · doi:10.1007/3-540-61327-7_135 · Cited by 59
Using heuristic worked examples to promote inquiry-based learning
Mulder, Y. G., Lazonder, A. W., & de Jong, T. (2013) · Learning and Instruction · doi:10.1016/j.learninstruc.2013.08.001 · Cited by 58
Chen, Y. L., Pan, P. R., Sung, Y., & Chang, K.-E. (2013) · Educational Technology & Society · Cited by 58
GRAESSER, S. D. A. C. (2011) · Routledge eBooks · doi:10.4324/9780203839089-29 · Cited by 58
Hester, S. D., Nadler, M., Katcher, J., Elfring, L. K., Dykstra, E. A., Rezende, L. F., & Bolger, M. S. (2018) · CBE—Life Sciences Education · doi:10.1187/cbe.18-06-0090 · Cited by 58
Towards a framework for effective instructional explanations in science teaching
Kulgemeyer, C. (2018) · Studies in Science Education · doi:10.1080/03057267.2018.1598054 · Cited by 68
A Comparison of Self-Explanation and Elaborative Interrogation
O’Reilly, T., Symons, S., & MacLatchy-Gaudet, H. (1998) · Contemporary Educational Psychology · doi:10.1006/ceps.1997.0977 · Cited by 58
Designing Learning Environments That Support Thinking: The Jasper Series as a Case Study
Duffy, T. M., Lowyck, J., Jonassen, D. H., & Welsh, T. M. (1993) · Springer eBooks · doi:10.1007/978-3-642-78069-1_2 · Cited by 58
Judging the plausibility of arguments in scientific texts: a student–scientist comparison
von der Mühlen, S., Richter, T., Schmid, S., Schmidt, E. M., & Berthold, K. (2015) · Thinking & Reasoning · doi:10.1080/13546783.2015.1127289 · Cited by 56
Development of a mobile learning system based on a collaborative problem-posing strategy
Sung, H., Hwang, G., & Chang, Y.-C. (2013) · Interactive Learning Environments · doi:10.1080/10494820.2013.867889 · Cited by 66
General-Purpose Situational Simulation Environment for Construction Education
Rojas, E. M., & Mukherjee, A. (2005) · Journal of Construction Engineering and Management · doi:10.1061/(asce)0733-9364(2005)131:3(319 · Cited by 57
The Effects of Critical Thinking Instruction on Training Complex Decision Making
Helsdingen, A. S., den Bosch, K. V., van Gog, T., & van Merriënboer, J. J. G. (2010) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720810377069 · Cited by 57
The importance of structural model availability on seismic interpretation
Alcalde, J., Bond, C. E., Johnson, G., Butler, R. W., Cooper, M. A., & Ellis, J. F. (2017) · Journal of Structural Geology · doi:10.1016/j.jsg.2017.03.003 · Cited by 57
How cognitive psychology changed the face of medical education research
Schmidt, H. G., & Mamede, S. (2020) · Advances in Health Sciences Education · doi:10.1007/s10459-020-10011-0 · Cited by 65
Hmelo‐Silver, C. E., Nagarajan, A., & Day, R. (2002) · Science Education · doi:10.1002/sce.10002 · Cited by 55
Hwang, W., Chen, N., & Hsu, R.-L. (2004) · Computers & Education · doi:10.1016/j.compedu.2004.05.005 · Cited by 57
Mediating the mechanisms which make collaborative learning sometimes effective.
Dillenbourg, P., & Schneider, D. (1995) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · Cited by 57
Taraban, R., Anderson, E. E., DeFinis, A., Brown, A. G., Weigold, A., & Sharma, M. P. (2007) · Journal of Engineering Education · doi:10.1002/j.2168-9830.2007.tb00915.x · Cited by 57
Eshuis, E. H., ter Vrugte, J., Anjewierden, A. A., Bollen, L., Sikken, J., & de Jong, T. (2019) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-019-09296-0 · Cited by 58
The Generative Activity Principle in Multimedia Learning
Fiorella, L., & Mayer, R. E. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108894333.036 · Cited by 72
The benefits of collaboration for student programmers
Wilson, J. D., Hoskin, N., & Nosek, J. T. (1993) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/169070.169383 · Cited by 56
Cabrera, A. F., Moore, J. D., & Mellish, C. (2007) · International Journal of Artificial Intelligence in Education · doi:10.3233/irg-2007-17(4)04 · Cited by 56
Assessing the relation between language comprehension and performance in general chemistry
Pyburn, D. T., Pazicni, S., Benassi, V., & Tappin, E. (2013) · Chemistry Education Research and Practice · doi:10.1039/c3rp00014a · Cited by 51
Learning stoichiometry: a comparison of text and multimedia formats
Evans, K. L., Yaron, D., & Leinhardt, G. (2008) · Chemistry Education Research and Practice · doi:10.1039/b812409b · Cited by 56
Tripto, J., Assaraf, O. B., Snapir, Z., & Amit, M. (2016) · International Journal of Science Education · doi:10.1080/09500693.2016.1150620 · Cited by 59
The use of additional information in problem-oriented learning environments
Gräsel, C., Fischer, F., & Mandl, H. (2000) · Learning Environments Research · doi:10.1023/a:1011421732004 · Cited by 61
Learning by Solved Example Problems: Instructional Explanations Reduce Self-Explanation Activity
Schworm, S., & Renkl, A. (2019) · Routledge eBooks · doi:10.4324/9781315782379-175 · Cited by 60
Pre-service and in-service teachers' metacognitive knowledge about problem-solving strategies
Metallidou, P. (2008) · Teaching and Teacher Education · doi:10.1016/j.tate.2008.07.002 · Cited by 56
Training team problem solving skills: an event-based approach
Oser, R. L., Gualtieri, J. W., Cannon‐Bowers, J. A., & Eduardo Salas, A. (1999) · Computers in Human Behavior · doi:10.1016/s0747-5632(99)00031-x · Cited by 55
Effects of Variation and Prior Knowledge on Abstract Concept Learning
Braithwaite, D. W., & Goldstone, R. L. (2015) · Cognition and Instruction · doi:10.1080/07370008.2015.1067215 · Cited by 60
Chung, K. K. H., & Tam, Y. H. (2005) · Journal of Intellectual & Developmental Disability · doi:10.1080/13668250500349409 · Cited by 55
Chan, J. Y. K., & Bauer, C. F. (2016) · Chemistry Education Research and Practice · doi:10.1039/c5rp00205b · Cited by 61
Schmitz, F., Schnabel, K., Stricker, D., Fischer, M. R., & Guttormsen, S. (2017) · Patient Education and Counseling · doi:10.1016/j.pec.2017.01.016 · Cited by 55
The Role of Surprise in Learning: Different Surprising Outcomes Affect Memorability Differentially
Foster, M. I., & Keane, M. T. (2018) · Topics in Cognitive Science · doi:10.1111/tops.12392 · Cited by 55
Roelle, J., & Renkl, A. (2019) · Journal of Educational Psychology · doi:10.1037/edu0000365 · Cited by 60
J. Evaluation on an assessment system based on Bayesian student modeling
VanLehn, K. A., & Martin, J. J. (1997) · NPARC · Cited by 55
Learning about noticing, by, and through, noticing
Mason, J. H. (2020) · ZDM · doi:10.1007/s11858-020-01192-4 · Cited by 54
How do contrasting cases and self-explanation promote learning? Evidence from fraction division
Sidney, P. G., Hattikudur, S., & Alibali, M. W. (2015) · Learning and Instruction · doi:10.1016/j.learninstruc.2015.07.006 · Cited by 54
Reading mathematics for understanding—From novice to expert
Shepherd, M. D., & van de Sande, C. C. (2014) · The Journal of Mathematical Behavior · doi:10.1016/j.jmathb.2014.06.003 · Cited by 54
The Moderating Effects of Utilitarian and Hedonic Values on Information Technology Continuance
Xu, L., Lin, J., & Chan, H. C. (2012) · ACM Transactions on Computer-Human Interaction · doi:10.1145/2240156.2240160 · Cited by 55
Explanations and Context in the Emergence of Students' Informal Inferential Reasoning
Gil, E., & Ben‐Zvi, D. (2011) · Mathematical Thinking and Learning · doi:10.1080/10986065.2011.538295 · Cited by 59
Future teachers’ knowledge about learning strategies: Misconcepts and knowledge-in-pieces
Glogger‐Frey, I., Ampatziadis, Y., Ohst, A., & Renkl, A. (2018) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2018.02.001 · Cited by 54
Recasting the feedback debate: benefits of tutoring error detection and correction skills
Mathan, S. A., & Koedinger, K. R. (2003) · Cited by 54
Another source of individual differences: Strategy adaptivity to changing rates of success.
Schunn, C. D., & Reder, L. M. (2001) · Journal of Experimental Psychology: General · doi:10.1037/0096-3445.130.1.59 · Cited by 95
Translating words into equations: a cognitive load theory approach
Pawley, D., Ayres, P., Cooper, M. G., & Sweller, J. (2005) · Educational Psychology · doi:10.1080/0144341042000294903 · Cited by 57
Nielsen, W., & HOBAN, G. F. (2015) · Journal of Research in Science Teaching · doi:10.1002/tea.21242 · Cited by 53
Koedinger, K. R., Aleven, V. A. W. M. M., Roll, I., & Baker, R. S. (2009) · doi:10.4324/9780203876428.ch20 · Cited by 52
Bennell, C., Blaskovits, B., Jenkins, B., Semple, T., Khanizadeh, A., Brown, A. S., & Jones, N. J. (2020) · Policing An International Journal · doi:10.1108/pijpsm-06-2020-0092 · Cited by 65
An Empirical Assessment of Comprehension Fostering Features in an Intelligent Tutoring System
Mathan, S. A., & Koedinger, K. R. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47987-2_37 · Cited by 53
External support and the development of problem-solving routines.
Cary, M., & Carlson, R. A. (1999) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.25.4.1053 · Cited by 54
Littlefield, J., & Rieser, J. J. (1993) · Cognition and Instruction · doi:10.1207/s1532690xci1102_2 · Cited by 53
Nakakoji, Y., & Wilson, R. (2020) · Journal of Intelligence · doi:10.3390/jintelligence8030032 · Cited by 74
2007 Presidential Address—The End(s) of Testing
Baker, E. L. (2007) · Educational Researcher · doi:10.3102/0013189x07307970 · Cited by 54
Coordinating principles and examples through analogy and self-explanation
Nokes‐Malach, T. J., VanLehn, K. A., Belenky, D. M., Lichtenstein, M., & Cox, G. E. (2012) · European Journal of Psychology of Education · doi:10.1007/s10212-012-0164-z · Cited by 57
Acquisition of procedures: The effects of example elaborations and active learning exercises
Catrambone, R., & Yuasa, M. (2006) · Learning and Instruction · doi:10.1016/j.learninstruc.2006.02.002 · Cited by 52
The Role of Self-monitoring in Learning Chemistry with Dynamic Visualizations
Chiu, J. L., & Linn, M. C. (2011) · Contemporary trends and issues in science education · doi:10.1007/978-94-007-2132-6_7 · Cited by 56
Hoskinson, A., Caballero, M. D., & Knight, J. (2013) · CBE—Life Sciences Education · doi:10.1187/cbe.12-09-0149 · Cited by 53
Kautzmann, T. R., & Jaques, P. A. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.10.017 · Cited by 54
Supporting Self-Regulated Learning with Cognitive Tools
Winne, P. H., & Frederiksen, J. R. (2009) · Routledge eBooks · doi:10.4324/9780203876428-21 · Cited by 52
Eliciting Self-Explanations Improves Children's Performance on a Field-Based Map Skills Task
Kastens, K. A., & Liben, L. S. (2007) · Cognition and Instruction · doi:10.1080/07370000709336702 · Cited by 52
The explanatory role of spontaneously generated analogies in reasoning about physiological concepts
Kaufman, D. R., Patel, V. L., & Magder, S. A. (1996) · International Journal of Science Education · doi:10.1080/0950069960180309 · Cited by 52
The Role of Explanations and Plan Recognition in the Learning of Theatrical Scripts
Noice, H. (1991) · Cognitive Science · doi:10.1207/s15516709cog1503_4 · Cited by 52
Schalk, L., Schumacher, R., Barth, A. P., & Stern, E. (2017) · Journal of Educational Psychology · doi:10.1037/edu0000234 · Cited by 56
Computer-based guidance to support students’ revision of their science explanations
Gerard, L. F., Linn, M. C., & Berkeley, U. C. (2021) · Computers & Education · doi:10.1016/j.compedu.2021.104351 · Cited by 51
Allen, L. K., Snow, E. L., & McNamara, D. S. (2015) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2723576.2723617 · Cited by 51
Cook, J. (2002) · Journal of Interactive Media in Education · doi:10.5334/2002-5 · Cited by 51
The Effects of Self-efficacy Beliefs and Metacognition on Academic Performance: A Mixed Method Study
Aurah, C. M. (2013) · American Journal of Educational Research · doi:10.12691/education-1-8-11 · Cited by 51
Kang, H. B., & Guo, P. J. (2017) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3126594.3126632 · Cited by 62
Bywater, J., Chiu, J. L., Hong, J., & Sankaranarayanan, V. (2019) · Comput. Educ. · doi:10.1016/j.compedu.2019.05.004 · Cited by 53
Are instructional explanations more effective in the context of an impasse?
Sánchez, E., García-Rodicio, H., & Acuña, S. R. (2008) · Instructional Science · doi:10.1007/s11251-008-9074-5 · Cited by 63
Cross‐National Comparisons of Complex Problem‐Solving Strategies in Two Microworlds
Güss, C. D., Tuason, M. T., & Gerhard, C. (2010) · Cognitive Science · doi:10.1111/j.1551-6709.2009.01087.x · Cited by 55
Exploring Information about Concepts by asking Questions
Graesser, A. C., Langston, M. C., & Baggett, W. B. (1993) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/s0079-7421(08)60147-4 · Cited by 51
Kneser, C., Pilkington, R. M., & Treasure-Jones, T. (2001) · Cited by 51
Explaining the moral of the story
Walker, C. M., & Lombrozo, T. (2017) · Cognition · doi:10.1016/j.cognition.2016.11.007 · Cited by 71
EXAMINING EXPERTISE USING INTERVIEWS AND VERBAL PROTOCOLS
van de Wiel, M. W. J. (2017) · Frontline Learning Research · doi:10.14786/flr.v5i3.257 · Cited by 78
Even, R., & Schwarz, B. B. (2003) · Educational Studies in Mathematics · doi:10.1023/b:educ.0000006166.50134.7a · Cited by 50
Kim, J., & Loewenstein, J. (2020) · Journal of Business Ethics · doi:10.1007/s10551-020-04457-w · Cited by 50
Bagno, E., Eylon, B., & Ganiel, U. (2000) · American Journal of Physics · doi:10.1119/1.19515 · Cited by 50
Learning From Cases and Questions: The Socratic Case-Based Teaching Architecture
Edelson, D. C. (1996) · Journal of the Learning Sciences · doi:10.1207/s15327809jls0504_3 · Cited by 50
Nelms, A. A., & Segura-Totten, M. (2019) · CBE—Life Sciences Education · doi:10.1187/cbe.18-05-0077 · Cited by 50
Sobel, D. M., & Legare, C. H. (2014) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1291 · Cited by 54
The power of affective pedagogical agent and self-explanation in computer-based learning
Wang, Y., Gong, S., Cao, Y., & Fan, W. (2023) · Computers & Education · doi:10.1016/j.compedu.2022.104723 · Cited by 52
Measuring Discourse-Level Processes With Verbal Protocols and Latent Semantic Analysis
Millis, K., Magliano, J. P., & Todaro, S. A. (2006) · Scientific Studies of Reading · doi:10.1207/s1532799xssr1003_2 · Cited by 49
Language learning experience in school context and metacognitive awareness of multilingual children
Pichon, E. L., de Swart, H., Čeginskas, V. L. A., & van den Bergh, H. (2009) · International Journal of Multilingualism · doi:10.1080/14790710902878692 · Cited by 49
Comparing Four Instructional Techniques for Promoting Robust Knowledge
Richey, J. E., & Nokes‐Malach, T. J. (2014) · Educational Psychology Review · doi:10.1007/s10648-014-9268-0 · Cited by 57
Cognitive load of critical thinking strategies
Shehab, H. M., & Nussbaum, E. M. (2014) · Learning and Instruction · doi:10.1016/j.learninstruc.2014.09.004 · Cited by 54
The relationship between patterns of classroom discourse and mathematics learning
Pierson, J. (2008) · Texas ScholarWorks (Texas Digital Library) · Cited by 48
Understanding behavior makes it more normal
Ahn, W., Novick, L. R., & Kim, N. S. (2003) · Psychonomic Bulletin & Review · doi:10.3758/bf03196541 · Cited by 49
Activation of Learning Strategies in Writing Learning Journals
Glogger‐Frey, I., Holzäpfel, L., Schwonke, R., Nückles, M., & Renkl, A. (2009) · Zeitschrift für Pädagogische Psychologie · doi:10.1024/1010-0652.23.2.95 · Cited by 62
Designing Adaptive Instructional Environments: Insights from Empirical Evidence
Durlach, P. J., & Ray, J. M. (2011) · Defense Technical Information Center (DTIC) · doi:10.21236/ada552677 · Cited by 49
Budé, L. M., Imbos, T., van de Wiel, M. W. J., Broers, N. J., & Berger, M. P. F. (2008) · Higher Education · doi:10.1007/s10734-008-9130-8 · Cited by 48
Improving Engagement in Program Construction Examples for Learning Python Programming
Hosseini, R., Akhüseyinoğlu, K., Brusilovsky, P. L., Malmi, L., Pollari-Malmi, K., Schunn, C. D., & Sirkiä, T. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00197-0 · Cited by 48
The Acquisition of Qualitative Physics Knowledge During Textbook-Based Physics Training
Ploetzner, R., & VanLehn, K. A. (1997) · Cognition and Instruction · doi:10.1207/s1532690xci1502_2 · Cited by 48
Knowledge Connectedness in Geometry Problem Solving
Lawson, M. J., & Chinnappan, M. (2000) · Journal for Research in Mathematics Education · doi:10.2307/749818 · Cited by 48
Feltovich, P. J., Coulson, R. L., Spiro, R. J., & Dawson-Saunders, B. K. (1992) · Springer eBooks · doi:10.1007/978-3-662-02833-9_12 · Cited by 48
de Bruin, A. B. H., Rikers, R. M. J. P., & Schmidt, H. G. (2006) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2006.01.001 · Cited by 47
Metadata
- Authors
- Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R.
- Affiliations
- RAND Corporation (US)
- TU Bergakademie Freiberg (DE)
- Venue
- Cognitive Science
- Publisher
- Wiley
- Published
- 1989-04
- Volume
- 13
- Issue
- 2
- Pages
- 145-182
- ISSN
- 0364-0213 (ISSN-L)
- 1551-6709
- OpenAlex
- W4239816899
- Cited by
- 1,714
- References
- 33
- Citations by year
- 2026: 54 · 2025: 49 · 2024: 41 · 2023: 41 · 2022: 65 · 2021: 80 · 2020: 103 · 2019: 99 · 2018: 58 · 2017: 53 · 2016: 77 · 2015: 69 · 2014: 60 · 2013: 58 · 2012: 59
- FWCI
- 27.12
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cognitive Science (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- self-explanation, worked examples, problem solving, mechanics problems, self-monitoring, understanding-based learning, explanation-based learning, student differences
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
