Presentation 2014-09-27
An algorithm for generating personalized learning processes based on the relation between learning items and its improvement
Hiyori YOSHIKAWA, Hiroshi HIRAI,
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Abstract(in English) In e-Learning, a learning system must recommend a learner the learning item which he/she is ready to learn. Thus the learning system needs to know in advance the whole structure of all possible knowledge states of learners. Knowledge space and learning space, introduced by Doignon and Falmagne, are mathematical models which represent such structure. The previous algorithm to construct knowledge spaces, QUERY routine, is to update the knowledge space according to the answers of queries to an expert. This algorithm requires a huge number of queries, and in the middle does not necessarily output a learning space, which is desirable for a practical use. In this article, we show the existence of the unique maximal learning space inside a knowledge space. We also characterize a binary relation which represents learning spaces. Finally we give a naive algorithm to obtain the maximal learning space inside a knowledge space.
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Keyword(in English) e-Learning / active learning / expert system / knowledge space / Horn function / algorithm
Paper # ET2014-34
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Committee ET
Conference Date 2014/9/20(1days)
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Registration To Educational Technology (ET)
Language JPN
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Title (in English) An algorithm for generating personalized learning processes based on the relation between learning items and its improvement
Sub Title (in English)
Keyword(1) e-Learning
Keyword(2) active learning
Keyword(3) expert system
Keyword(4) knowledge space
Keyword(5) Horn function
Keyword(6) algorithm
1st Author's Name Hiyori YOSHIKAWA
1st Author's Affiliation Graduate School of Information Science and Technology, The University of Tokyo()
2nd Author's Name Hiroshi HIRAI
2nd Author's Affiliation Graduate School of Information Science and Technology, The University of Tokyo
Date 2014-09-27
Paper # ET2014-34
Volume (vol) vol.114
Number (no) 228
Page pp.pp.-
#Pages 6
Date of Issue