The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Detecting Student Misuse of Intelligent Tutoring Systems
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Claims the paper makes
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
High frequency of submissions may indicate 'gaming the system' rather than constructive iteration.
“aligning with some studies in the context of ITS that a high frequency of submissions may indicate 'gaming the system' rather than constructive iteration (Baker et al., 2004).”
From Assessing the Impact and Underlying Pathways of Sequenced AI feedback on Student Learning (2026) · cites this paper as Baker et al., 2004
Citations
Cites
Knowledge 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
Self-citation
Flagged first, then by citations
Research works printed but not linked: 16
- Aleven, V., Koedinger, K.R.: Investigations into Help Seeking and Learning with a Cognitive Tutor. In: Luckin, R. (ed.) Papers of the AIED-2001 Workshop on Help Provision and Help Seeking in Interactive Learning Environments, pp. 47–58 (2001)
- Aleven, V., McLaren, B., Roll, I., Koedinger, K.: Toward Tutoring Help Seeking: Applying Cognitive Modeling to Meta-Cognitive Skills. To appear at Intelligent Tutoring Systems Conference (2004) · DOI
- Arbreton, A.: Student Goal Orientation and Help-Seeking Strategy Use. In: Karabenick, S.A. (ed.) Strategic Help Seeking: Implications For Learning And Teaching, pp. 95–116. Lawrence Erlbaum Associates, Mahwah (1998)
- Baker, R.S., Corbett, A.T., Koedinger, K.R.: Learning to Distinguish Between Representations of Data: a Cognitive Tutor That Uses Contrasting Cases. To appear at International Conference of the Learning Sciences (2004)
- Baker, R.S., Corbett, A.T., Koedinger, K.R., Wagner, A.Z.: Off-Task Behavior in the Cognitive Tutor Classroom: When Students “Game the System”. In: Proceedings of ACM CHI 2004: Computer-Human Interaction, pp. 383–390 (2004) · DOI
- Corbett, A.T., Koedinger, K.R., Hadley, W.S.: Cognitive Tutors: From the Research Classroom to All Classrooms. In: Goodman, P. (ed.) Technology Enhanced Learning: Opportunities For Change, pp. 235–263. Lawrence Erlbaum Associates, Mahwah (2001)
- de Vicente, A., Pain, H.: Informing the Detection of the Students’ Motivational State: an Empirical Study. In: Cerri, S.A., Gouarderes, G., Paraguacu, F. (eds.) Proceedings of the Sixth International Conference on Intelligent Tutoring Systems, pp. 933–943 (2002) · DOI
- del Soldato, T., du Boulay, B.: Implementation of Motivational Tactics in Tutoring Systems. Journal of Artificial Intelligence in Education 6(4), 337–376 (1995)
- Donaldson, W.: Accuracy of d’ and A’ as Estimates of Sensitivity. Bulletin of the Psychonomic Society 31(4), 271–274 (1993) · DOI
- Lloyd, J.W., Loper, A.B.: Measurement and Evaluation of Task-Related Learning Behavior: Attention to Task and Metacognition. School Psychology Review 15(3), 336–345 (1986) · DOI
- Maris, E.: Psychometric Latent Response Models. Psychometrika 60(4), 523–547 (1995) · DOI
- Martin, J., vanLehn, K.: Student Assessment Using Bayesian Nets. International Journal of Human-Computer Studies 42, 575–591 (1995) · DOI
- Mostow, J., Aist, G., Beck, J., Chalasani, R., Cuneo, A., Jia, P., Kadaru, K.: A La Recherche du Temps Perdu, or As Time Goes By: Where Does the Time Go in a Reading Tutor that Listens? In: Sixth International Conference on Intelligent Tutoring Systems, pp. 320–329 (2002) · DOI
- Ramsey, F.L., Schafer, D.W.: The Statistical Sleuth: A Course in Methods of Data Analysis. Duxbury Press, Belmont (1997) Section 12.3
- Schofield, J.W.: Computers and Classroom Culture. Cambridge University Press, Cambridge (1995) · DOI
- Wood, H., Wood, D.: Help Seeking, Learning, and Contingent Tutoring. Computers and Education 33, 153–159 (1999) · DOI
Cited by
Sorted by citations
Educational Data Mining: A review of the state of the art
Romero, C., & Ventura, S. (2010) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2010.2053532 · Cited by 2,251
Affect-aware tutors: recognising and responding to student affect
Woolf, B., Burleson, W., Arroyo, I., Dragon, T., Cooper, D., & Picard, R. (2009) · International Journal of Learning Technology · doi:10.1504/ijlt.2009.028804 · Cited by 371
New Potentials for Data‐Driven Intelligent Tutoring System Development and Optimization
Koedinger, K. R., Brunskill, E., Baker, R. S. J. D., McLaughlin, E. A., & Stamper, J. (2013) · AI Magazine · doi:10.1609/aimag.v34i3.2484 · Cited by 178
Self-citationAnalysing adaptive scaffolds that help students develop self‐regulated learning behaviours
Munshi, A., Biswas, G., Baker, R., Ocumpaugh, J., Hutt, S., & Paquette, L. (2023) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12761 · Cited by 88
Self-citationA meta-analysis of the effectiveness of ALEKS on learning
Fang, Y., Ren, Z., Hu, X., & Graesser, A. C. (2019) · Educational Psychology · doi:10.1080/01443410.2018.1495829 · Cited by 79
Assessing the Impact and Underlying Pathways of Sequenced AI feedback on Student Learning
Cao, J., Zhao, C. Q., Schunn, C., McLaughlin, E. A., Lin, J., & Koedinger, K. R. (2026) · arXiv · doi:10.48550/arxiv.2604.07469
Self-citation
Metadata
- Authors
- Baker, R. S., Corbett, A. T., & Koedinger, K. R.
- Affiliations
- Carnegie Mellon University (US)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2004
- Pages
- 531-540
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1589525026
- Cited by
- 353
- References
- 1
- Citations by year
- 2026: 14 · 2025: 6 · 2024: 10 · 2023: 15 · 2022: 10 · 2021: 11 · 2020: 19 · 2019: 17 · 2018: 16 · 2017: 21 · 2016: 23 · 2015: 18 · 2014: 21 · 2013: 21 · 2012: 18
- FWCI
- 8.93
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- intelligent tutoring systems, gaming the system, machine learning, learning outcomes, tutor feedback, student behavior detection
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