Analysis of students' learning activities through quantifying time-series comments

Kazumasa Goda, Tsunenori Mine

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

23 被引用数 (Scopus)

抄録

These days, many university teachers are concerned about the increasing number of students whose motivation is declining. Some of them fall into a situation that they cannot recover from by themselves, and require assistance, but they hesitate to call for help. In order to recognize such students quickly and give guidance to them in class, we have collected time-series comments in the classroom and analyzed them. In the analysis, we divided the comments into the three time slots: P (Previous), C (Current), and N (Next), and quantify them so that we can infer the learning behaviors between the previous and the current classes. We call this analysis method the PCN method. The PCN method is useful for grasping students' learning status in the class. Some of our case studies illustrate the validity of the PCN method.

本文言語英語
ホスト出版物のタイトルKnowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Proceedings
ページ154-164
ページ数11
PART 2
DOI
出版ステータス出版済み - 9 29 2011
イベント15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011 - Kaiserslautern, ドイツ
継続期間: 9 12 20119 14 2011

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 2
6882 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011
Countryドイツ
CityKaiserslautern
Period9/12/119/14/11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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