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ID 48748
本文ファイル
別タイトル
A Multiple Hurdle Model for Students’ Conversions in Online English Learning Materials
著者
草薙 邦広 外国語教育研究センター 広大研究者総覧
抄録(英)
The present study provides a multiple hurdle model which computationally explains complex patterns of students’ engagement levels in online learning materials. It has been empirically known that online learning log data such as login counts and the number of learning contents studied by students quite often deviate from ordinary discrete probabilistic distributions such as a Poisson distribution and a negative binomial distribution. As an underlying mechanism of this empirical fact, the present study posits that there are latent sub-processes to obtain learning outcomes, which we call micro conversions, and between them, the model also assumes hurdles that students clear and fail. This modeling framework was statistically implemented as a finite mixture distribution model that mixes a hurdle negative binomial distribution and an ordinary negative binomial distribution. Using Bayesian modeling with the Hamiltonian Monte Carlo method, the model was fitted to the real login data of 899 students in Hiroshima university and achieved a relatively good fit.
掲載誌名
広島外国語教育研究
23号
開始ページ
45
終了ページ
61
出版年月日
2020-03-01
出版者
広島大学外国語教育研究センター
ISSN
1347-0892
NCID
言語
日本語
NII資源タイプ
紀要論文
広大資料タイプ
学内刊行物(紀要等)
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
publisher
権利情報
Copyright (c) 2020 広島大学外国語教育研究センター
部局名
外国語教育研究センター
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