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A Tool to Extract Quantitative and Qualitative Data from Zoom Chat Transcripts from Online Classes
https://doi.org/10.15100/0002000046
https://doi.org/10.15100/0002000046b3525b98-9590-427f-b3ba-ca4283400bc6
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
AA12013209-20230801-0014.pdf
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| Item type | ☆紀要論文 / Departmental Bulletin Paper(1) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2023-08-30 | |||||||||
| タイトル | ||||||||||
| タイトル | A Tool to Extract Quantitative and Qualitative Data from Zoom Chat Transcripts from Online Classes | |||||||||
| 言語 | en | |||||||||
| 著者 |
Pellowe, William
× Pellowe, William
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| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題 | student engagement, online classes, Zoom chat transcripts | |||||||||
| 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 | 10.15100/0002000046 | |||||||||
| ID登録タイプ | JaLC | |||||||||
| 版 | ||||||||||
| 出版タイプ | AM | |||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||
| 出版者 名前 | ||||||||||
| 出版者 | 近畿大学産業理工学部 | |||||||||
| 言語 | ja | |||||||||
| 書誌情報 |
ja : かやのもり：近畿大学産業理工学部研究報告 en : Reports of Faculty of Humanity-Oriented Science and Engineering, Kindai University 号 34, p. 14-20, 発行日 2023-08-01 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | EISSN | |||||||||
| 収録物識別子 | 13495801 | |||||||||
| 内容記述 | ||||||||||
| 内容記述タイプ | Abstract | |||||||||
| 内容記述 | The pandemic caused upheavals in tertiary education, but one positive outcome is that many universities now offer online makeup lessons. However, this convenience comes with the same set of challenges as before: students participating in Zoom classes report a loss of motivation, and some reportedly “ghost” classes, appearing in name only. Given these circumstances, it becomes crucial for teachers to find ways to keep students engaged, attentive, and active, especially in large classes. One way to accomplish this in Zoom classes is to periodically elicit student answers via DM (direct chat messages) in IRT (Initiation-Response-Feedback) question cycles. We can elicit a variety of answer types, including multiple choice and short answers. Yet how can teachers reliably and quickly track the frequency of student responses? In this paper, the author describes the development of a tool designed to analyze student responses through chat-based direct messaging. | |||||||||
| 言語 | en | |||||||||
