Presentation 2019-11-09
Classification of Students by Principal Components Analysis
Yawen Li, Shinya Nogami,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, we use dummy data on the scores of first-year students in the Faculty of Business Administration to clarify the relationship between students' grades, favorite subjects, and their types (science or humanities) by principal component analysis. For students' grades, use GPA. For good subjects, use grades converted from exam grades. The purpose of this time is to clarify the characteristics of undergraduate students by clarifying these relationships.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) GPA / Cluster Analysis / favorite subjects / science or humanities / principal component analysis
Paper # ET2019-57
Date of Issue 2019-11-02 (ET)

Conference Information
Committee ET
Conference Date 2019/11/9(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Hiroshima City University
Topics (in Japanese) (See Japanese page)
Topics (in English) Learning Support Using VR-AR, etc.
Chair Hideyuki Suzuki(Ibaraki Univ.)
Vice Chair Ryo Takaoka(Yamaguchi Univ.)
Secretary Ryo Takaoka(Waseda Univ.)
Assistant Megumi Kurayama(National Inst. of Tech., Hakodate College) / Ryo Oonuma(Fukushima Univ.)

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) Classification of Students by Principal Components Analysis
Sub Title (in English)
Keyword(1) GPA
Keyword(2) Cluster Analysis
Keyword(3) favorite subjects
Keyword(4) science or humanities
Keyword(5) principal component analysis
1st Author's Name Yawen Li
1st Author's Affiliation Tokyo University of Science(TUS)
2nd Author's Name Shinya Nogami
2nd Author's Affiliation Tokyo University of Science(TUS)
Date 2019-11-09
Paper # ET2019-57
Volume (vol) vol.119
Number (no) ET-276
Page pp.pp.55-58(ET),
#Pages 4
Date of Issue 2019-11-02 (ET)