In the last years Intelligent Tutoring Systems have been a very successful way for improving learning experience. Many issues must be addressed until this technology can be defined mature. One of the main problems within the Intelligent Tutoring Systems is the process of contents authoring: knowledge acquisition and manipulation process is a difficult task because it requires specialized skills on computer programming and knowledge engineering. In this paper we propose a mechanism based on first order data mining to partially automate the process of knowledge acquisition. The knowledge has to be used in the ITS during the tutoring process for personalized instruction. Such a mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor.

S. Riccucci, A. Carbonaro, G. Casadei (2007). Knowledge acquisition in Intelligent Tutoring System: a data mining approach. SPRINGER BERLIN / HEIDELBERG : Springer LNCS Publisher.

Knowledge acquisition in Intelligent Tutoring System: a data mining approach

CARBONARO, ANTONELLA;CASADEI, GIORGIO
2007

Abstract

In the last years Intelligent Tutoring Systems have been a very successful way for improving learning experience. Many issues must be addressed until this technology can be defined mature. One of the main problems within the Intelligent Tutoring Systems is the process of contents authoring: knowledge acquisition and manipulation process is a difficult task because it requires specialized skills on computer programming and knowledge engineering. In this paper we propose a mechanism based on first order data mining to partially automate the process of knowledge acquisition. The knowledge has to be used in the ITS during the tutoring process for personalized instruction. Such a mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor.
2007
Springer LNCS Publisher Springer Berlin / Heidelberg
1195
1205
S. Riccucci, A. Carbonaro, G. Casadei (2007). Knowledge acquisition in Intelligent Tutoring System: a data mining approach. SPRINGER BERLIN / HEIDELBERG : Springer LNCS Publisher.
S. Riccucci; A. Carbonaro; G. Casadei
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/65384
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