Article

Introducing prerequisite relations in a multi-layered bayesian student model

Authors:

C. Carmona,

E. Millán,

J. L. Pérez-de-la-Cruz,

M. Trella,

R. ConejoAuthors Info & Claims

UM'05: Proceedings of the 10th international conference on User Modeling

Pages 347 - 356

https://doi.org/10.1007/11527886_46

Published: 24 July 2005 Publication History

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Abstract

In this paper we present an extension of a previously developed generic student model based on Bayesian Networks. A new layer has been added to the model to include prerequisite relationships. The need of this new layer is motivated from different points of view: in practice, this kind of relationships are very common in any educational setting, but also their use allows for improving efficiency of both adaptation mechanisms and the inference process. The new prerequisite layer has been evaluated using two different experiments: the first experiment uses a small toy example to show how the BN can emulate human reasoning in this context, while the second experiment with simulated students suggests that prerequisite relationships can improve the efficiency of the diagnosis process by allowing increased accuracy or reductions in the test length.

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Lu YChen PPian YZheng V(2022)CMKT: Concept Map Driven Knowledge TracingIEEE Transactions on Learning Technologies10.1109/TLT.2022.319635515:4(467-480)Online publication date: 1-Aug-2022
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Huang YGuerra-Hollstein JBarria-Pineda JBrusilovsky PBielikova MHerder ECena FDesmarais M(2017)Learner Modeling for Integration SkillsProceedings of the 25th Conference on User Modeling, Adaptation and Personalization10.1145/3079628.3079677(85-93)Online publication date: 9-Jul-2017
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Huang YVassileva JBlustein JAroyo LD'Mello S(2016)Deeper Knowledge Tracing by Modeling Skill Application Context for Better Personalized LearningProceedings of the 2016 Conference on User Modeling Adaptation and Personalization10.1145/2930238.2930373(325-328)Online publication date: 13-Jul-2016
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Published In

UM'05: Proceedings of the 10th international conference on User Modeling

July 2005

529 pages

ISBN:3540278850

Editors:
Liliana Ardissono
Dipartimento di Informatica, Università di Torino, Corso Svizzera 185, Torino, Italy
,
Paul Brna
The SCRE Centre, University of Glasgow, 11 Eldon Street, Glasgow, United Kingdom
,
Antonija Mitrovic
Intelligent Computer Tutoring Group, Department of Computer Science and Software Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand

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Springer-Verlag

Berlin, Heidelberg

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Published: 24 July 2005

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Lu YChen PPian YZheng V(2022)CMKT: Concept Map Driven Knowledge TracingIEEE Transactions on Learning Technologies10.1109/TLT.2022.319635515:4(467-480)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1109/TLT.2022.3196355
Huang YGuerra-Hollstein JBarria-Pineda JBrusilovsky PBielikova MHerder ECena FDesmarais M(2017)Learner Modeling for Integration SkillsProceedings of the 25th Conference on User Modeling, Adaptation and Personalization10.1145/3079628.3079677(85-93)Online publication date: 9-Jul-2017
https://dl.acm.org/doi/10.1145/3079628.3079677
Huang YVassileva JBlustein JAroyo LD'Mello S(2016)Deeper Knowledge Tracing by Modeling Skill Application Context for Better Personalized LearningProceedings of the 2016 Conference on User Modeling Adaptation and Personalization10.1145/2930238.2930373(325-328)Online publication date: 13-Jul-2016
https://dl.acm.org/doi/10.1145/2930238.2930373
Seffrin HRubi GJaques PCho YShin SKim SHung CHong J(2014)A dynamic bayesian network for inference of learners' algebraic knowledgeProceedings of the 29th Annual ACM Symposium on Applied Computing10.1145/2554850.2555062(235-240)Online publication date: 24-Mar-2014
https://dl.acm.org/doi/10.1145/2554850.2555062
Chen YWuillemin PLabat J(2014)Bayesian Student Modeling Improved by Diagnostic Items12th International Conference on Intelligent Tutoring Systems - Volume 847410.1007/978-3-319-07221-0_17(144-149)Online publication date: 5-Jun-2014
https://dl.acm.org/doi/10.1007/978-3-319-07221-0_17
Nguyen VPham V(2011)Bayesian network to manage learner model in context-aware adaptive system in mobile learningProceedings of the 6th international conference on E-learning and games, edutainment technologies10.5555/2040452.2040468(63-70)Online publication date: 7-Sep-2011
https://dl.acm.org/doi/10.5555/2040452.2040468
Desmarais M(2011)Performance comparison of item-to-item skills models with the IRT single latent trait modelProceedings of the 19th international conference on User modeling, adaption, and personalization10.5555/2021855.2021863(75-86)Online publication date: 11-Jul-2011
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Castillo GDescalço LDiogo SMillán EOliveira PAnjo B(2010)Computerized evaluation and diagnosis of student's knowledge based on Bayesian networksProceedings of the 5th European conference on Technology enhanced learning conference on Sustaining TEL: from innovation to learning and practice10.5555/1889250.1889297(494-499)Online publication date: 28-Sep-2010
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Liu C(2008)A Simulation-Based Experience in Learning Structures of Bayesian Networks to Represent How Students Learn Composite ConceptsInternational Journal of Artificial Intelligence in Education10.5555/1454278.145428218:3(237-285)Online publication date: 1-Aug-2008
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Brusilovsky PMillán E(2007)User models for adaptive hypermedia and adaptive educational systemsThe adaptive web10.5555/1768197.1768199(3-53)Online publication date: 1-Jan-2007
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