2026-05-31T00:05:21Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/100122026-02-03T11:27:04Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Millán-Valldeperas, Eva
author
Belmonte-Martínez, María Victoria
author
Jiménez, Guiomar
author
Pérez-de-la-Cruz-Molina, José Luis
2015-07-03T09:55:41Z
2015-07-03T09:55:41Z
2015-07-03
http://hdl.handle.net/10630/10012
http://orcid.org/0000-0001-9178-7600
In the last decade, there has been a growing interest in using Bayesian Networks (BN) in the student modelling problem. This increased interest is probably due to the fact that BNs provide a sound methodology for this difficult task. In order to develop a Bayesian student model, it is necessary to define the structure (nodes and links) and the parameters. Usually the structure can be elicited with the help of human experts (teachers), but the difficulty of the problem of parameter specification is widely recognized in this and other domains. In the work presented here we have performed a set of experiments to compare the performance of two Bayesian Student Models, whose parameters have been specified by experts and learnt from data respectively. Results show that both models are able to provide reasonable estimations for knowledge variables in the student model, in spite of the small size of the dataset available for learning the parameters
eng
by-nc-nd
Enseñanza asistida por ordenador
Learning Bayesian Networks for Student Modeling
journal article
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URL
https://riuma.uma.es/bitstreams/4965fd5b-85b4-4610-a527-8463c0baeba1/download
File
MD5
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submission.pdf
URL
https://riuma.uma.es/bitstreams/abe33dc6-a688-41a4-87a1-69a09ffe09d9/download
File
MD5
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text/plain
submission.pdf.txt