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  1. 神戸常盤大学紀要 Online ISSN:2188-4781
  2. 第14号(2021)

教学IRにおける機械学習の意義と可能性

https://doi.org/10.20608/00001134
https://doi.org/10.20608/00001134
fd7d9f31-6b0a-494f-ae05-92dcb47aa0e2
名前 / ファイル ライセンス アクション
Bulletin14_06.pdf Bulletin14_06.pdf (493.6 kB)
Item type 紀要論文 / Departmental Bulletin Paper(1)
公開日 2021-03-31
タイトル
タイトル 教学IRにおける機械学習の意義と可能性
タイトル
言語 en
タイトル Significance and possibility of artificial intelligence in institutional research for education
言語
言語 jpn
キーワード
主題 教学IR
キーワード
主題 機械学習
キーワード
主題 予測モデル
キーワード
主題 説明モデル
キーワード
主題 Artificial intelligence/machine learning
キーワード
主題 institutional research for education
キーワード
主題 predictive model
キーワード
主題 explanatory model
資源タイプ
資源タイプ departmental bulletin paper
ID登録
ID登録 10.20608/00001134
ID登録タイプ JaLC
著者 高松, 邦彦

× 高松, 邦彦

WEKO 6025
CiNii ID 9000365071650

高松, 邦彦

ja-Kana タカマツ, クニヒコ

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村上, 勝彦

× 村上, 勝彦

WEKO 6042
CiNii ID 9000347506032

村上, 勝彦

ja-Kana ムラカミ, カツヒコ

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伴仲, 謙欣

× 伴仲, 謙欣

WEKO 6026
CiNii ID 9000365072494

伴仲, 謙欣

ja-Kana バンナカ, ケンヤ

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野田, 育宏

× 野田, 育宏

WEKO 6035
CiNii ID 9000365072495

野田, 育宏

ja-Kana ノダ, イクヒロ

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光成, 研一郎

× 光成, 研一郎

WEKO 6021
CiNii ID 9000356936014

光成, 研一郎

ja-Kana ミツナリ, ケンイチロウ

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大森, 雅人

× 大森, 雅人

WEKO 7009
CiNii ID 9000365072511

大森, 雅人

ja-Kana オオモリ, マサト

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中田, 康夫

× 中田, 康夫

WEKO 6027
CiNii ID 9000365072058

中田, 康夫

ja-Kana ナカタ, ヤスオ

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TAKAMATSU, Kunihiko

× TAKAMATSU, Kunihiko

WEKO 7196

en TAKAMATSU, Kunihiko

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MURAKAMI, Katsuhiko

× MURAKAMI, Katsuhiko

WEKO 7197

en MURAKAMI, Katsuhiko

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BANNAKA, Kenya

× BANNAKA, Kenya

WEKO 7198

en BANNAKA, Kenya

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NODA, Ikuhiro

× NODA, Ikuhiro

WEKO 7199

en NODA, Ikuhiro

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MITSUNARI, Kenichiro

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WEKO 7200

en MITSUNARI, Kenichiro

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OMORI, Masato

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en OMORI, Masato

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NAKATA, Yasuo

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WEKO 7202

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抄録
内容記述タイプ Abstract
内容記述 教学IRにおいては、従来は説明モデルによる解析や可視化にもとづく意思決定支援が主要な機能であったが、近年では予測モデルにもとづく種々の予測に関してその重要性が高まっているといわれている。そこで本稿では、教学IRにおける機械学習の意義と可能性について、われわれの経験を題材として検討した。われわれの経験では、機械学習を用いることで、大学における中途退学や学力進捗を予測できる可能性があることが明らかになっている。このことから、いわゆる教学データを用いた機械学習により、今までなし得なかった教学上の種々の予測が可能となり、今後のわが国の教学IRが飛躍的に進展する可能性が示唆された。
抄録(英)
内容記述タイプ Other
内容記述 In institutional research (IR) for education, the decision-making support based on the analysis and visualization by the explanation model was the main function in the past. However, the importance of various predictions based on predictive models is currently increasing in IR for education. Therefore, this paper examined the significance and possibility of artificial intelligence/machine learning (AI/ML) in IR for education using our experience as subjects. Our experience reveals that using AI/ML can predict dropouts and academic progress in university and college. Thus, it is suggested that using students' educational data, AI/ML could make various predictions in higher education that were not possible earlier, leading to dramatic progress in Japan's IR for education.
書誌情報 神戸常盤大学紀要
en : Bulletin of Kobe Tokiwa University

号 14, p. 22-29, 発行日 2021-03-31
出版者
出版者 神戸常盤大学・神戸常盤大学短期大学部
ISSN
収録物識別子タイプ ISSN
収録物識別子 18845487
著者版フラグ
出版タイプ VoR
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