A Study on Forecasting Post-enrollment Grades of Students Using Gradient Boosting Decision Tree

Author:

Arasawa Komei,Matsukawa Shun,Sugio Nobuyuki,Sanada Hirofumi,Takahara Madoka,Hattori Shun

Publisher

Springer Nature Switzerland

Reference20 articles.

1. Konda, H.: Current status and issues of support measures related to withdrawal from school: from the university practices described in the self-evaluation and inspection report. In: Fukuoka University Annual Review of the Development of Higher Education, vol. 4, pp. 40–49 (2022)

2. Morsy, S., Karypis, G.: Sparse neural attentive knowledge-based models for grade prediction. In: Proceedings of the 12th International Conference on Educational Data Mining, pp. 366–371 (2019)

3. Hu, Q., Rangwala, H.: Reliable deep grade prediction with uncertainty estimation. In: Proceedings of the 9th International Conference on Learning Analytics and Knowledge, pp. 76–85 (2019)

4. Nishioka, K., Mochizuki, H.: Examination of learning log and features analysing grade in the information subject. In: Proceedings of the 84th National Convention of IPSJ, 22H-09 (2022)

5. Matuso, R., Ito, K.: Prediction of score by machine learning in programming class using LMS. In: Proceedings of the 37th JSSST Annual Conference (2020)

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