Semantic representation and management of student models: An approach to adapt lecture sequencing to enhance learning

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Resumen

In this paper an approach oriented to acquire, depict, and administrate knowledge about the student is proposed. Moreover, content is also characterized to describe lectures. In addition, the work focuses on the semantics of the attributes that reveal a profile of the student and the teaching experiences. The meaning of such properties is stated as an ontology. Thus, inheritance and causal inferences are made. According to the semantics of the attributes and the conclusions induced, the sequencing module of a Web-based educational system (WBES) delivers the appropriate option of lecture to students. The underlying hypothesis is: the apprenticeship of students is enhanced when a WBES understands the nature of the content and the student's characteristics. Based on the empirical evidence outcome by a trial, it is concluded that: Successful WBES account the knowledge that describe their students and lectures.

Idioma originalInglés
Título de la publicación alojadaAdvances in Artificial Intelligence - 9th Mexican International Conference on Artificial Intelligence, MICAI 2010, Proceedings
EditorialSpringer Verlag
Páginas175-186
Número de páginas12
EdiciónPART 1
ISBN (versión impresa)3642167608, 9783642167607
DOI
EstadoPublicada - 2010

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NúmeroPART 1
Volumen6437 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

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