A problem-oriented method for supporting AEH authors through data mining
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Cristobal Romero, Mykola Pechenizkiy, Toon Calders, Silvia R. Viola, Frans Van AsscheDate
2008-01-07Citation
ADML-2007: Proceedings of the International Workshop on Applying Data Mining in e-Learning. Ed. Cristobal Romero, Mykola Pechenizkiy, Toon Calders, Silvia R. Viola, Frans Van Assche. CEUR Workshop Proceedings, Volumen 305, 2008ISSN
1163-0073Funded by
This work has been partially funded by the Spanish Ministry of Science and Education through project TIN2004-03140 and TSI2006-12085. The author C. Vialardi is also funded by Fundacion Carolina.Editor's Version
http://ceur-ws.org/Vol-305/Subjects
Adaptive Educational Hypermedia Systems; InformáticaNote
Also published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073)Proceeding of International Workshop on Applying Data Mining in e-Learning ADML'07. Sissi, Lassithi - Crete Greece, 18 September, 2007.
Rights
© 2007 The author/sAbstract
One of the main problems with Adaptive Educational Hypermedia Systems (AEHS) is that is very difficult to test whether adaptation decisions are beneficial for all the students or some of them would benefit from a different adaptation. Data mining techniques can provide support to overcome, to a certain extent, this problem. This paper proposes the use of these techniques for detecting potential problems of adaptation in AEH systems. The proposed method searches for symptoms of these problems (called anomalies) through log analysis and tries to interpret the findings. Currently, a decision tree technique is being used for the task.
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Google Scholar:Bravo Agapito, Javier
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Vialardi, César
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Ortigosa Juárez, Álvaro Manuel
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