@techreport{oai:ipsj.ixsq.nii.ac.jp:00225136,
 author = {伊藤, 泰史 and 五嶋, 研人 and 遠山, 元道 and 金子, 晋丈 and Yasushi, Ito and Kento, Goto and Motomichi, Toyama and Kunitake, Kaneko},
 issue = {28},
 month = {Mar},
 note = {クラス内の議論は最初に発言する親発言と返信を付ける子発言から構成されている．親発言と子発言の関係は木構造で表現できる．この関係をモデル化するにあたって発言を隣接行列に紐づけることができ，発言あるいは発言者をノードとしたグラフ化ができる．クラスごとに発言内容や議論の取り組みが異なり，学習効果も異なったものになる．そこでこのグラフ化したものを定量化し，定量化された指数と発言数や発言量など客観的な値との間に相関関係が見出せるかを検証する．相関関係が見いだせたら，議論の特徴を把握し，学習効果の高いクラスをクラスの受講生同士で自律的に再現する学習支援の仕組みに展開していく．, A discussion in a class consists of a parent utterance, which is the first utterance, and child utterances, to which replies are attached. The relationship between parent and child statements can be represented by a tree structure. In modeling this relationship, it is possible to link the statements to an adjacency matrix, and to graph the statements or speakers as nodes. Each class will have different comments and discussion approaches, and the learning effect will be different. We will then quantify this graphed data and test whether a correlation can be found between the quantified index and objective values such as the number of utterances and the amount of discussion. If a correlation can be found, the characteristics of the discussions will be identified and developed into a learning support system that allows students in a class to autonomously reproduce a class with high learning effectiveness among themselves.},
 title = {onraindaigakutounokurasunaigironnokashikatoteiryouka－学習支援への展開－},
 year = {2023}
}