論文

査読有り
2017年3月13日

Reproducibility of findings from educational big data: A preliminary study

ACM International Conference Proceeding Series
  • Misato Oi
  • ,
  • Masanori Yamada
  • ,
  • Fumiya Okubo
  • ,
  • Atsushi Shimada
  • ,
  • Hiroaki Ogata

開始ページ
536
終了ページ
537
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1145/3027385.3029445
出版者・発行元
Association for Computing Machinery

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.

リンク情報
DOI
https://doi.org/10.1145/3027385.3029445
DBLP
https://dblp.uni-trier.de/rec/conf/lak/OiYOSO17
URL
http://dl.acm.org/citation.cfm?id=3029445
URL
http://dblp.uni-trier.de/db/conf/lak/lak2017.html#conf/lak/OiYOSO17
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85016477103&origin=inward
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85016477103&origin=inward
ID情報
  • DOI : 10.1145/3027385.3029445
  • DBLP ID : conf/lak/OiYOSO17
  • SCOPUS ID : 85016477103

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