Forecasting Students¡¯ Future Academic Records Using Past Attendance Recording Data and Grade Data

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• 作者：Hirotaka Itoh ; Yuma Itoh ; Kenji Funahashi ; Daisuke Yamamoto ; Shoichi Saito ; Ichi Takumi ; Hiroshi Matsuo
• 关键词：Bayesian network ; Information gain
• 刊名：Procedia Computer Science
• 出版年：2013
• 出版时间：2013
• 年：2013
• 卷：22
• 期：Complete
• 页码：921-927
• 全文大小：265 K

文摘

In this study, the authors forecast students¡¯ future academic records using past attendance recording data and grade data. We use a Bayesian network as forecasting method. During construction of the Bayesian network forecasting model, unnecessary variables become noise and so lower the forecasting accuracy. Therefore, to improve the forecasting accuracy, we used information gain to reduce the number of variables in the model. As a result, accuracy improved.