The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System
Open accessOverview
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 cited source says what the claim attributes to it.
In the citing paper
“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]
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
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)
Cited by
Sorted by citations
Items 101–119 of 119
Chen, J., Shao, D., & Fu, D. (2026) · 教育学文摘 · doi:10.63313/edu.8052
Moustapha, A. K., & Sobreira, P. D. L. (2026) · IEEE World Engineering Education Conference (EDUNINE) · doi:10.1109/edunine62390.2026.11547068
Kong, G. (2026) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-026-00859-4
(2026) · International Research Journal of Modernization in Engineering Technology and Science · doi:10.56726/irjmets98793
ProFeed: Designing Scaffolded Learning in the Age of AI
Münstermann, M. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-29794-5_46
AI-Based Assessment of Revision-Associated Research Writing Development in a Peer-Feedback-Supported
Yahmadi, H. H. N. A. (2026) · Information · doi:10.3390/info17080744
Systematic Review of the Research on the Development of Learner Dashboard for Self-Directed Learning
Park, Y.-S., & Lee, Y.-J. (2026) · Journal of Digital Contents Society · doi:10.9728/dcs.2026.27.7.2023
Münstermann, M., & Chounta, I. (2026) · Mensch und Computer (MuC) · doi:10.1145/3820253.3831394
Intelligent Assessment and Tutoring System Design Based on Large Language Models
Zhang, L., & Jia, J. (2026) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste69562.2026.11649662
VARK-Based Cognitive Tutor Using RAG and Groq Llama 3.3
Bragadeeshwaran, C., Gaurav, D., Miruthula, G., Srivani, M., & Vanitha, V. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-31230-3_19
You, C., Jiang, W., Wei, M., Lu, X., 罗青, Wang, X., Lu, H., & Yao, Y. (2026) · IEEE International Conference on Omni-layer Intelligent Systems (COINS) · doi:10.1109/coins69995.2026.11715609
Eğitimde Yapay Zekâ: İlkokul Öğretmenlerinin Perspektifinden Bir İnceleme
Kaya, E., & Yıldırım, N. (2026) · Temel Eğitim · doi:10.52105/temelegitim.1937771
Rho, J., Guo, R. S., Xing, W., & Li, C. (2026) · Computers & Education · doi:10.1016/j.compedu.2026.105766
GAIOLA: An AI-Assisted Rehearsal Platform for Output-Oriented EFL Oral Presentation Practice
Chen, H.-J., Li, Y.-J., Mansoor, S. A., Chen, H.-C., & Chang, M.-G. (2026) · International Conference on Advanced Learning Technologies · doi:10.1109/icalt68022.2026.00074
Karsli, M. B., Karabey, S. Ç., Guler, M., Arpacık, Ö., Arslan, M. A., Kurşun, E., & Kaba, E. (2026) · Applied Measurement in Education · doi:10.1080/08957347.2026.2738700
Zdyb, W., & Fatahi, S. (2026) · IEEE International Conference on Intelligent Systems · doi:10.1109/is71416.2026.11727424
Or, C. C. P. (2026) · The Open/Technology in Education Society and Scholarship Association Journal · doi:10.18357/otessaj.2025.5.1.90
Vrabie, C. I. (2026) · Teaching Public Administration · doi:10.1177/01447394261502444
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 ›
Are you an author, or do you see a problem with this page? Request a review