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LMSのログから見える学生の学習行動分析
https://doi.org/10.34356/00000782
https://doi.org/10.34356/00000782a70d5af2-94e7-495c-90ed-c3f34ba11e18
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
LMSのログから見える学生の学習行動分析 (936.7 kB)
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| Item type | 紀要論文 / Departmental Bulletin Paper(1) | |||||||
|---|---|---|---|---|---|---|---|---|
| 公開日 | 2021-10-19 | |||||||
| タイトル | ||||||||
| タイトル | LMSのログから見える学生の学習行動分析 | |||||||
| タイトル | ||||||||
| タイトル | Analysis of Students’ Learning Behavior from LMS Logs | |||||||
| 言語 | en | |||||||
| 言語 | ||||||||
| 言語 | jpn | |||||||
| キーワード | ||||||||
| 言語 | en | |||||||
| 主題Scheme | Other | |||||||
| 主題 | Cluster Analysis | |||||||
| キーワード | ||||||||
| 言語 | en | |||||||
| 主題Scheme | Other | |||||||
| 主題 | Data Analytics | |||||||
| キーワード | ||||||||
| 言語 | en | |||||||
| 主題Scheme | Other | |||||||
| 主題 | Evidence-Based Education | |||||||
| キーワード | ||||||||
| 言語 | en | |||||||
| 主題Scheme | Other | |||||||
| 主題 | LMS | |||||||
| 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 | departmental bulletin paper | |||||||
| ID登録 | ||||||||
| ID登録 | 10.34356/00000782 | |||||||
| ID登録タイプ | JaLC | |||||||
| 著者 |
吉岡, 卓
× 吉岡, 卓
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| 著者別名 | ||||||||
| 識別子Scheme | WEKO | |||||||
| 識別子 | 10871 | |||||||
| 姓名 | YOSHIOKA, Suguru | |||||||
| 抄録 | ||||||||
| 内容記述タイプ | Abstract | |||||||
| 内容記述 | 概要 In recent years, the importance of evidence-based education has increased, and efforts to use data analysis as well as teachers’ experience and practical knowledge for education have been widely implemented. In this paper, I present a method to dynamically analyze students’ learning progress by focusing on the log data on the LMS. By analyzing the learning process rather than the results of learning, we aim to predict dropouts in advance, change the flow of the class, and verify the content of homework and assignments in advance. By using this method, I found that changes in the number of accesses to the LMS affect the learning progress. In particular, I show that the use of a quadratic approximation curve for the analysis of the number of accesses enables us to analyze the learning process in detail. As a result, it was found that in distance education, there were more than a certain number of accesses during the course hours, not late at night, and that students who changed the number of accesses according to the contents of the course materials performed better. Finally, a comparison with clustering analysis shows the usefulness of the analysis method presented in this paper. |
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| 出版者 | ||||||||
| 出版者 | 都留文科大学 | |||||||
| 書誌情報 |
都留文科大学研究紀要 en : 都留文科大学研究紀要 号 94, p. 37-49, 発行日 2021-10-19 |
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| ISSN | ||||||||
| 収録物識別子タイプ | ISSN | |||||||
| 収録物識別子 | 0286-3774 | |||||||
| NCID | ||||||||
| 収録物識別子タイプ | NCID | |||||||
| 収録物識別子 | AN00149431 | |||||||
| 著者版フラグ | ||||||||
| 出版タイプ | VoR | |||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||
