Presentation 2017-11-11
Random question and its estimation method using a hierarchical item bank
Shuya Nakamura, Takako Akakura,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, we discuss the method that random questions of class evaluation item and its estimation method.We made the hierarchical item bank that can estimate result of item in class evaluation question.With the hierarchical item bank, it is possible to estimate responses to specific questions by utilizing the responses to abstract questions.However, expected distribution is easy to strongly influenced by the prior probability.Therefore, we propose a "random questions" of the class evaluation item. In this paper, for all of the items in the hierarchical item bank, it can get a few student's answer. Thus, it is possible to estimate that suppressing the influence of the prior probability.Here we report on the "random question" and its method of estimation method using data in the actual class.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Higher education / FD / Class evaluation questionnaire / Bayesian network
Paper # ET2017-54
Date of Issue 2017-11-04 (ET)

Conference Information
Committee ET
Conference Date 2017/11/11(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Sophia Univ.
Topics (in Japanese) (See Japanese page)
Topics (in English) 50th Memory Technical Committee Conference, etc.
Chair Yozo Miyadera(Tokyo Gakugei Univ.)
Vice Chair Shoichi Nakamura(Fukushima Univ.)
Secretary Shoichi Nakamura(Tokyo Polytechnic Univ.)
Assistant Hiroki Nakayama(Waseda Univ.) / Megumi Kurayama(National Inst. of Tech., Hakodate College)

Paper Information
Registration To Technical Committee on Educational Technology
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Random question and its estimation method using a hierarchical item bank
Sub Title (in English)
Keyword(1) Higher education
Keyword(2) FD
Keyword(3) Class evaluation questionnaire
Keyword(4) Bayesian network
1st Author's Name Shuya Nakamura
1st Author's Affiliation Tokyo University of Science(TUS)
2nd Author's Name Takako Akakura
2nd Author's Affiliation Tokyo University of Science(TUS)
Date 2017-11-11
Paper # ET2017-54
Volume (vol) vol.117
Number (no) ET-296
Page pp.pp.9-12(ET),
#Pages 4
Date of Issue 2017-11-04 (ET)