The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
The Behavior of Tutoring Systems
Abstract
Tutoring systems are described as having two loops. The outer loop executes once for each task, where a task usually consists of solving a complex, multi-step problem. The inner loop executes once for each step taken by the student in the solution of a task. The inner loop can give feedback and hints on each step. The inner loop can also assess the student's evolving competence and update a student model, which is used by the outer loop to select a next task that is appropriate for the student. For those who know little about tutoring systems, this description is meant as a demystifying introduction. For tutoring system experts, this description illustrates that although tutoring systems differ widely in their task domains, user interfaces, software structures, knowledge bases, etc., their behaviors are in fact quite similar.
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Cites
Kluger, A. N., & DeNisi, A. (1996) · Psychological Bulletin · doi:10.1037/0033-2909.119.2.254 · Cited by 5,882
The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring
BLOOM, B. S. (1984) · Educational Researcher · doi:10.3102/0013189x013006004 · Cited by 2,734 · cited 2×
“(3) The outer loop implements a pedagogy called mastery learning (Bloom, 1984).”
BackgroundKnowledge tracing: Modeling the acquisition of procedural knowledge
Corbett, A. T., & Anderson, J. R. (1995) · User Modelling and User-Adapted Interaction · doi:10.1007/bf01099821 · Cited by 2,324
Categorization of action slips
Norman, D. A. (1981) · Psychological Review · doi:10.1037/0033-295x.88.1.1 · Cited by 1,736 · cited 1×
“Students sometimes make careless errors, called "slips" in psychology (Norman, 1981), but fail to notice that they have made them, which can cause them to waste time looking for deep, potential misconceptions.”
BackgroundSelf‐Explanations: How Students Study and Use Examples in Learning to Solve Problems
Chi, M. T. H., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989) · Cognitive Science · doi:10.1207/s15516709cog1302_1 · Cited by 1,714
Cognitive Apprenticeship: Teaching the Craft of Reading, Writing and Mathematics
Collins, A., Brown, J. S., Newman, S. E., & Montclair State University (1988) · Thinking: The Journal of Philosophy for Children · doi:10.5840/thinking19888129 · Cited by 1,299
Worked-out examples: Instructional explanations support learning by self-explanations
Renkl, A. (2002) · Learning and Instruction · doi:10.1016/s0959-4752(01)00030-5 · Cited by 452
Limitations of Student Control: Do Students Know when They Need Help?
Aleven, V., & Koedinger, K. R. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-45108-0_33 · Cited by 236
Cited by
VanLEHN, K. (2011) · Educational Psychologist · doi:10.1080/00461520.2011.611369 · Cited by 2,323
Self-citationEvolution and Revolution in Artificial Intelligence in Education
Roll, I., & Wylie, R. (2016) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-016-0110-3 · Cited by 1,229
Effectiveness of Intelligent Tutoring Systems: A Meta-Analytic Review
Kulik, J. A., & Fletcher, J. D. (2016) · Review of Educational Research · doi:10.3102/0034654315581420 · Cited by 930
Exploring the Assistance Dilemma in Experiments with Cognitive Tutors
Koedinger, K. R., & Aleven, V. (2007) · Educational Psychology Review · doi:10.1007/s10648-007-9049-0 · Cited by 632
A systematic literature review of automated feedback generation for programming exercises
Keuning, H., Jeuring, J., & Heeren, B. (2019) · ACM Transactions on Computing Education · doi:10.1145/3231711 · Cited by 370
Metadata
- Authors
- VanLehn, K.
- Venue
- International Journal of Artificial Intelligence in Education
- Publisher
- IOS Press
- Published
- 2006-08
- Volume
- 16
- Issue
- 3
- Pages
- 227-265
- ISSN
- 1560-4292 (ISSN-L)
- 1560-4306
- OpenAlex
- W1765030997
- Cited by
- 749
- References
- 8
- FWCI
- 19.90
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
