An experience applying reinforcement learning in a web-based adaptive and intelligent educational system

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Show simple item record Iglesias, Ana Martínez, Paloma Fernández, Fernando 2013-02-12T12:05:17Z 2013-02-12T12:05:17Z 2003-03
dc.identifier.bibliographicCitation Informatics in education, vol. 2, n. 2 (2003), pp. 223-240
dc.identifier.issn 1648-5831
dc.identifier.issn 0868-4952
dc.description.abstract The definition of effective pedagogical strategies for coaching and tutoring students according to their needs is one of the most important issues in Adaptive and Intelligent Educational Systems (AIES). The use of a Reinforcement Learning (RL) model allows the system to learn automatically how to teach to each student individually, only based on the acquired experience with other learners with similar characteristics, like a human tutor does. The application of this artificial intelligence technique, RL, avoids to define the teaching strategies by learning action policies that define what, when and how to teach. In this paper we study the performance of the RL model in a DataBase Design (DBD) AIES, where this performance is measured on number of students required to acquire efficient teaching strategies.
dc.format.extent 18
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Institute of Mathematics and Informatics, Vilnius
dc.rights © Institute of Mathematics and Informatics, Vilnius
dc.subject.other Web-based adaptive and intelligent educational systems
dc.subject.other Intelligent tutoring system
dc.subject.other Reinforcement learning
dc.subject.other Curriculum sequencing
dc.title An experience applying reinforcement learning in a web-based adaptive and intelligent educational system
dc.type article
dc.subject.eciencia Informática
dc.rights.accessRights openAccess
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 223
dc.identifier.publicationissue 2
dc.identifier.publicationlastpage 240
dc.identifier.publicationtitle Informatics in education
dc.identifier.publicationvolume 2
dc.identifier.uxxi AR/0000011369
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