Topic Analysis of Syllabus for Faculty of Engineering in the Japanese National University

被引：0

作者：

Nakamura, Shuya ^{[1
]}

Akakura, Takako ^{[2
]}

机构：

[1] Tokyo Univ Sci, Grad Sch Engn, Tokyo, Japan

[2] Tokyo Univ Sci, Fac Engn, Tokyo, Japan

来源：

PROCEEDINGS OF 2018 IEEE INTERNATIONAL CONFERENCE ON TEACHING, ASSESSMENT, AND LEARNING FOR ENGINEERING (TALE) | 2018年

基金：

日本学术振兴会;

关键词：

syllabus; LDA; text mining; class evaluation;

D O I：

暂无

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

We discuss the topic analysis of syllabi of Faculties of Engineering in Japanese national universities. To extract the important information (the course content, methods, etc.) from the syllabus document, we used the latent Dirichlet allocation (LDA). This work-in-progress paper describes that the topics of the syllabi of Faculties of Engineering from an analysis of actual data.

引用

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页码：1138 / 1141

页数：4

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