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A Bayesian student model for ERST - an External Representation Tutor
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posted on 2023-06-08, 04:59 authored by Beate Grawemeyer, Richard CoxThis paper describes the process by which we are constructing an intelligent tutoring system (ERST) designed to improve learners' external representation (ER) selection accuracy on a range of database query tasks. This paper describes how ERST's student model is being constructed - it is a Bayesian network with values seeded from data derived from two experimental studies. The studies examined the effects of students' background knowledge-of-external representations (KER) upon performance and their preferences for particular information display forms across a range of database query types.
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Publication status
- Published
Publisher
IOS PressPages
3.0Presentation Type
- paper
Event name
Proceedings of the 12th International Conference on Artificial Intelligence in Education (AIED05)Event location
AmsterdamEvent type
conferenceISBN
978-1-58603-530-3Department affiliated with
- Informatics Publications
Full text available
- No
Peer reviewed?
- Yes
Editors
B Bredeweg, C.-K. Looi, J Breuker, G McCallaLegacy Posted Date
2012-02-06Usage metrics
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