The DOI matches its Crossref record; 22 of the 24 references it cites were found in a registry or an index.
Locus of feedback control in computer-based tutoring: impact on learning rate, achievement and attitudes
Abstract
The advent of second-generation intelligent computer tutors raises an important instructional design question: when should tutorial advice be presented in problem solving? This paper examines four feedback conditions in the ACT Programming Tutor. Three versions offer the student different levels of control over error feedback and correction: (a) immediate feedback and immediate error correction; (b) immediate error flagging and student control of error correction; (c) feedback on demand and student control of error correction. A fourth, No-tutor condition offers no stepby-step problem solving support. The immediate feedback group with greatest tutor control of problem solving yielded the most efficient learning. These students completed the tutor problems fastest, and the three tutor-supported groups performed equivalently on tests. Questionnaires revealed little student preference among the four conditions. These results suggest that students will need explicit guidance to benefit from learning opportunities that arise when they have greater control over tutorial assistance.
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“Providing an evaluative response (e.g., correct or incorrect) soon after a students' attempt at task or step”
From The Knowledge‐Learning‐Instruction Framework: Bridging the Science‐Practice Chasm to Enhance Robust Student Learning (2012) · cites this paper as Corbett & Anderson (2001)
Citations
Cites
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“Overall, feedback timing has little consistent impact on learning, although delayed feedback can facilitate retention [5,11,12].”
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Shute, V. J. (2008) · Review of Educational Research · doi:10.3102/0034654307313795 · Cited by 4,631
VanLEHN, K. (2011) · Educational Psychologist · doi:10.1080/00461520.2011.611369 · Cited by 2,323
Current practice in measuring usability: Challenges to usability studies and research
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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
Koedinger, K. R., Corbett, A. T., & Perfetti, C. (2012) · Cognitive Science · doi:10.1111/j.1551-6709.2012.01245.x · Cited by 772
“…KCs (e.g., perceptual categories, simple concepts and skills) may imply instructional approaches that emphasize recall (Roediger & Karpicke, 2006), spacing of practice (Cepeda et al., 2006), tutored practice (e.g., Corbett & Anderson, 2001), and optimized scheduling of practice (Pavlik, 2007).”
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Metadata
- Authors
- Corbett, A. T., & Anderson, J. R.
- Affiliations
- Carnegie Mellon University (US)
- ORCID
- Anderson, John R.
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2001-03
- Pages
- 245-252
- OpenAlex
- W2105543722
- Cited by
- 280
- References
- 24
- Citations by year
- 2026: 7 · 2025: 13 · 2024: 5 · 2023: 12 · 2022: 15 · 2021: 14 · 2020: 13 · 2019: 15 · 2018: 14 · 2017: 14 · 2016: 20 · 2015: 10 · 2014: 15 · 2013: 10 · 2012: 17
- FWCI
- 2.67
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- computer-based tutoring, intelligent tutoring systems, feedback control, error feedback, error correction, programming education, student control, immediate feedback, learning efficiency, student preferences
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