How to obtain knowledge evidences in a student model based on Bayesian Network

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dc.contributor.authorLima S.F.
dc.contributor.authorStump S.M.D.
dc.date.accessioned2024-03-13T01:30:43Z
dc.date.available2024-03-13T01:30:43Z
dc.date.issued2010
dc.description.abstractA considerably proportion of the adaptativity of an Intelligent Tutoring System is due to the Student Model. Bayesian Networks has been used in student modeling in order to provide adaptativity from the tutor system to the student knowledge. However, a Bayesian Network requires evidences in order to make inferences. This article presents a proposal to measure and update knowledge evidences in a Bayesian Network which aims at sequencing the course content in a way adapted to the student knowledge.
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/37140
dc.relation.ispartofProceedings of the 5th Iberian Conference on Information Systems and Technologies, CISTI 2010
dc.rightsAcesso Restrito
dc.subject.otherlanguageBayesian networks
dc.subject.otherlanguageIntelligent tutor system
dc.subject.otherlanguageStudent model
dc.titleHow to obtain knowledge evidences in a student model based on Bayesian Network
dc.typeArtigo de evento
local.scopus.citations3
local.scopus.eid2-s2.0-77957835340
local.scopus.subjectCourse contents
local.scopus.subjectIntelligent tutoring system
local.scopus.subjectIntelligent tutors
local.scopus.subjectStudent knowledge
local.scopus.subjectStudent model
local.scopus.subjectStudent Modeling
local.scopus.subjectStudent Models
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77957835340&origin=inward
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