On the prediction of students’ quiz score by recurrent neural network

Fumiya Okubo, Takayoshi Yamashita, Atsushi Shimada, Yuta Taniguchi, Shinichi Konomi

研究成果: ジャーナルへの寄稿Conference article

抄録

In this paper, we explore the factor for improving the performance of prediction of students’ quiz scores by using a Recurrent Neural Network. The proposed method is applied to the log data of 2693 students in 15 courses that were conducted with following the common syllabus by 10 teachers. The experimental results show that in the case where the same teacher is not included in both training and test data, the accuracy of prediction slightly lower. We also show that at the beginning of a course, it is better to construct a prediction model including various items of learning logs, however, in the latter half, it is better to update the model by using selected information only.

元の言語英語
ジャーナルCEUR Workshop Proceedings
2163
出版物ステータス出版済み - 1 1 2018
イベント2nd Multimodal Learning Analytics Across (Physical and Digital) Spaces, CrossMMLA 2018 - Sydney, オーストラリア
継続期間: 3 6 2018 → …

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Recurrent neural networks
Students

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

これを引用

On the prediction of students’ quiz score by recurrent neural network. / Okubo, Fumiya; Yamashita, Takayoshi; Shimada, Atsushi; Taniguchi, Yuta; Konomi, Shinichi.

:: CEUR Workshop Proceedings, 巻 2163, 01.01.2018.

研究成果: ジャーナルへの寄稿Conference article

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