Reproducibility of findings from educational big data: A preliminary study

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

6 被引用数 (Scopus)

抄録

In this paper, we examined whether previous findings on educational big data consisting of e-book logs from a given academic course can be reproduced with different data from other academic courses. The previous findings showed that (1) students who attained consistently good achievement more frequently browsed different e-books and their pages than low achievers and that (2) this difference was found only for logs of preparation for course sessions (preview), not for reviewing material (review). Preliminarily, we analyzed e-book logs from four courses. The results were reproduced in only one course and only partially, that is, (1) high achievers more frequently changed e-books than low achievers (2) for preview. This finding suggests that to allow effective usage of learning and teaching analyses, we need to carefully construct an educational environment to ensure reproducibility.

本文言語英語
ホスト出版物のタイトルLAK 2017 Conference Proceedings - 7th International Learning Analytics and Knowledge Conference
ホスト出版物のサブタイトルUnderstanding, Informing and Improving Learning with Data
出版社Association for Computing Machinery
ページ536-537
ページ数2
ISBN(電子版)9781450348706
DOI
出版ステータス出版済み - 3 13 2017
イベント7th International Conference on Learning Analytics and Knowledge, LAK 2017 - Vancouver, カナダ
継続期間: 3 13 20173 17 2017

出版物シリーズ

名前ACM International Conference Proceeding Series

その他

その他7th International Conference on Learning Analytics and Knowledge, LAK 2017
国/地域カナダ
CityVancouver
Period3/13/173/17/17

All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ ネットワークおよび通信

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