Revealing Hidden Impression Topics in Students' Journals Based on Nonnegative Matrix Factorization

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

6 被引用数 (Scopus)

抄録

Students' reflective writings are useful not only for students themselves but also teachers. It is important for teachers to know which concepts were understood well by students and which concepts were not, to continuously improve their classes. However, it is difficult for teachers to thoroughly read the journals of more than one hundred students. In this paper, we propose a novel method to extract common topics and students' common impressions against them from students' journals. Weekly keywords are discovered from journals by scoring noun words with a measure based on TF-IDF term weighting scheme, and then we analyze co-occurrence relationships between extracted keywords and adjectives. We employs nonnegative matrix factorization, one of the topic modeling techniques, to discover the hidden impression topics from the co-occurrence relationships. As a case study, we applied our method on students' journals of the course 'Information Science' held in our university. Our experimental results show that conceptual keywords are successfully extracted, and four significant impression topics are identified. We conclude that our analysis method can be used to collectively understand the impressions of students from journal texts.

本文言語英語
ホスト出版物のタイトルProceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017
編集者Ronghuai Huang, Radu Vasiu, Kinshuk, Demetrios G Sampson, Nian-Shing Chen, Maiga Chang
出版社Institute of Electrical and Electronics Engineers Inc.
ページ298-300
ページ数3
ISBN(電子版)9781538638705
DOI
出版ステータス出版済み - 8 3 2017
イベント17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017 - Timisoara
継続期間: 7 3 20177 7 2017

出版物シリーズ

名前Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017

会議

会議17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017
CityTimisoara
Period7/3/177/7/17

All Science Journal Classification (ASJC) codes

  • コンピュータ ネットワークおよび通信
  • コンピュータ サイエンスの応用
  • 教育

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