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Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System
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“Meanwhile, ITS's offering personalised automated hints and explanations have been shown to improve learning outcomes and receive positive evaluation from students [76, 130].”
From AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities (2026) · cites this paper as [76]
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AutoTutor: an intelligent tutoring system with mixed-initiative dialogue.
Graesser, A. C., Chipman, P., Haynes, B. C., & Olney, A. (2005) · IEEE Transactions on Education · doi:10.1109/te.2005.856149 · Cited by 750
Anderson, J. R., Boyle, C., & Reiser, B. (1985) · Science · doi:10.1126/science.228.4698.456 · Cited by 699
(2001) · doi:10.1609/aimag.v22i4.1591 · Cited by 381
AutoTutor and Family: A Review of 17 Years of Natural Language Tutoring
Nye, B. D., Graesser, A. C., & Hu, X. (2014) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-014-0029-5 · Cited by 326
Designing Learning by Teaching Agents: The Betty's Brain System
Leelawong, K., & Biswas, G. (2008) · International Journal of Artificial Intelligence in Education · doi:10.3233/irg-2008-18(3)02 · Cited by 311
Lin, C. F., Yeh, Y., Hung, Y. H., & Chang, R.-I. (2013) · Computers & Education · doi:10.1016/j.compedu.2013.05.009 · Cited by 250
Peekaboo as an Instructional Model: Discourse Development at Home and at School
Cazden, C. B. (1983) · Springer eBooks · doi:10.1007/978-1-4899-1525-2_3 · Cited by 143
ActiveMath: An Intelligent Tutoring System for Mathematics
Melis⋆, E., & Siekmann, J. H. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-24844-6_12 · Cited by 110
Instructional Factors Analysis: A Cognitive Model For Multiple Instructional Interventions
Chi, M., Koedinger, K. R., Gordon, G. J., Jordon, P., & VanLahn, K. (2018) · PubMed · doi:10.1184/r1/6475808.v1 · Cited by 69
Assessment with computer agents that engage in conversational dialogues and trialogues with learners
Graesser, A. C., Cai, Z., Morgan, B., & Wang, L. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.03.041 · Cited by 63
Research works printed but not linked: 2
- Agha, M., Jarghon, A., Abu-Naser, S.: An intelligent tutoring system for teaching SQL. Int. J. Acad. Inf. Syst. Res. (IJAISR) 2(2), 1–7 (2018)
- Al Rekhawi, H., Abu-Naser, S.: Android applications UI development intelligent tutoring system. Int. J. Eng. Inf. Syst. (IJEAIS) 2(1), 1–14 (2018)
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Metadata
- Authors
- Kochmar, E., Vu, D. D., Belfer, R., Gupta, V., Serban, I. V., & Pineau, J.
- Affiliations
- University of Cambridge (GB)
- École de Technologie Supérieure (CA)
- Corresponding author
- Kochmar, Ekaterina
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 140-146
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- PMC
- PMC7334734
- OpenAlex
- W3023718816
- Cited by
- 103
- References
- 24
- Citations by year
- 2026: 31 · 2025: 30 · 2024: 17 · 2023: 10 · 2022: 11 · 2021: 4
- FWCI
- 2.39
- Type
- conference paper
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Lecture notes in computer science (publishedVersion)
- PubMed Central (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- intelligent tutoring systems, personalized feedback, automated feedback, natural language generation, learning outcomes
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 ›
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