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 processes are difficult tasks because they
require a specialised skills on computer programming and knowledge engineering. In this thesis we
discuss a general framework for knowledge management in an Intelligent Tutoring System and
propose a mechanism based on first order data mining to partially automate the process of
knowledge acquisition that have to be used in the ITS during the tutoring process. Such a
mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor.
We design and implement a part of the proposed architecture, mainly the module of knowledge
acquisition from examples based on first order data mining. We then show that the algorithm can be
applied at least two different domains: first order algebra equation and some topics of C
programming language. Finally we discuss the limitation of current approach and the possible
improvements of the whole framework.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:916 |
| Date | 28 April 2008 |
| Creators | Riccucci, Simone <1978> |
| Contributors | Carbonaro, Antonella |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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