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Time- and Learner-Dependent Hidden Markov Model for Writing Process Analysis Using Keystroke Log Data
https://uec.repo.nii.ac.jp/records/9675
https://uec.repo.nii.ac.jp/records/967520a8f8a8-13a5-4e9c-bc7e-d3cfb8339c24
名前 / ファイル | ライセンス | アクション |
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IJAIED_Springer (1.5 MB)
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Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2020-11-18 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Time- and Learner-Dependent Hidden Markov Model for Writing Process Analysis Using Keystroke Log Data | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Writing skills | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Writing process | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Keystroke log | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Hidden Markov model | |||||
キーワード | ||||||
言語 | en | |||||
主題 | Markov chain Monte Carlo method | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者 |
Uto, Masaki
× Uto, Masaki× Miyazawa, Yoshimitsu× Kato, Yoshihiro× Nakajima, Koji× Kuwata, Hajime |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Teaching writing strategies based on writing processes has attracted wide attention as a method for developing writing skills. The writing process can be generally defined as a sequence of subtasks, such as planning, formulation, and revision. Therefore, instructor feedback is often given based on sequence patterns of those subtasks. For such feedback, instructors need to analyze sequence patterns for all learners, which becomes problematic as the number of learners increases. To resolve this problem, this study proposes a new machine-learning method that estimates sequence patterns from keystroke log data. Specifically, we propose an extension of the Gaussian hidden Markov model that incorporates parameters representing temporal change in a subtask appearance distribution for each learner. Furthermore, we propose a collapsed Gibbs sampling algorithm as the parameter estimation method for the proposed model. We demonstrate effectiveness of the proposed model by applying it to actual keystroke log datasets. | |||||
書誌情報 |
en : International Journal of Artificial Intelligence in Education 巻 30, 号 2, p. 271-298, 発行日 2020-06 |
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出版者 | ||||||
出版者 | Springer | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 15604306 | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1007/s40593-019-00189-9 | |||||
権利 | ||||||
権利情報 | (c) 2020 Springer | |||||
関連サイト | ||||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1007/s40593-019-00189-9 | |||||
著者版フラグ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa |