Using Bayesian Networks to Manage Uncertainty in Student Modeling
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As early as the 1970s, AI-based systems were first implemented in support of personalized and adaptive instruction, giving rise to the field of Intelligent Tutoring Systems.
“As early as the 1970s, AI-based systems were first implemented in support of personalized and adaptive instruction, giving rise to the field of ITS [17][18][19].”
From Artificial Intelligence in Higher Education: A State-of-the-Art Overview of Pedagogical Integrity, Artificial Intelligence Literacy, and Policy Integration (2025) · cites this paper as [17]
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- Authors
- Conati, C., Gertner, A., & VanLehn, K.
- Affiliations
- University of British Columbia (CA)
- Mitre (United States) (US)
- University of Pittsburgh (US)
- Corresponding author
- Conati, Cristina
- Gertner, Abigail
- VanLehn, Kurt
- Venue
- User Modeling and User-Adapted Interaction
- Published
- 2002-11
- Volume
- 12
- Issue
- 4
- Pages
- 371-417
- ISSN
- 0924-1868 (ISSN-L)
- 1573-1391
- OpenAlex
- W1529098247
- Cited by
- 493
- References
- 65
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 10 · 2023: 8 · 2022: 12 · 2021: 9 · 2020: 15 · 2019: 14 · 2018: 20 · 2017: 26 · 2016: 19 · 2015: 21 · 2014: 26 · 2013: 31 · 2012: 27
- FWCI
- 18.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- User Modeling and User-Adapted Interaction (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
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Keywords
- Bayesian networks, student modeling, uncertainty management, adaptive tutoring systems, knowledge assessment, plan recognition, model scalability
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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.
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