Self-Explanation in a Data Normalization Tutor

dc.contributor.authorMitrovic, Antonija
dc.date.accessioned2007-08-07T21:21:48Z
dc.date.available2007-08-07T21:21:48Z
dc.date.issued2003en
dc.description.abstractSelf-explanation is one of the most effective learning strategies, resulting in deep knowledge. In this paper, we discuss how self-explanation is scaffolded in NORMIT, a data normalization tutor. We present the system first, and then discuss how it supports self-explanation. We hypothesized the self-explanation support in NORMIT will affect students problem solving skills, and also result in better conceptual knowledge. A preliminary evaluation study of the system was performed in October 2002, the results of which show that both problem-solving performance and the understanding of the domain of students who selfexplained increased. We also discuss our plans for future research.en
dc.identifier.citationMitrovic, A. (2003) Self-Explanation in a Data Normalization Tutor. Sydney: Supplementary Proceedings, AIEd 2003 Artificial Intelligence in Education, 20-24 Jul 2003. 565-577.en
dc.identifier.isbn978-1-58603-356-9
dc.identifier.urihttp://hdl.handle.net/10092/337
dc.language.isoen
dc.publisherUniversity of Canterbury. Computer Science and Software Engineering.en
dc.rights.urihttps://hdl.handle.net/10092/17651en
dc.subject.marsdenFields of Research::280000 Information, Computing and Communication Sciences::280100 Information Systems::280104 Computer-human interactionen
dc.subject.marsdenFields of Research::280000 Information, Computing and Communication Sciences::280100 Information Systems::280112 Information systems development methodologiesen
dc.titleSelf-Explanation in a Data Normalization Tutoren
dc.typeConference Contributions - Published
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