Research and Application of Adaboost Based Prediction of Student’s Academic Achievement
Authors
Shuang Zhang, Ming-Wen Gao, Qing-He Hu
Corresponding Author
Shuang Zhang
Available Online November 2018.
- DOI
- 10.2991/iced-18.2018.35How to use a DOI?
- Keywords
- Teaching quality, Learning effect, Prediction of academic achievement, AdaBoost
- Abstract
Student’s academic achievement is a major indicator of teacher’s teaching quality and student’s learning effect. But exam result is not enough to evaluate and predict student’s academic achievement. The factors of prediction should be scientifically selected from the whole teaching process. Based on analyzing the shortcomings of current research, the author proposes an AdaBoost based, multiple-indicator prediction model of student’s academic achievement. Experiment results show that the prediction model has good predictive performance.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Shuang Zhang AU - Ming-Wen Gao AU - Qing-He Hu PY - 2018/11 DA - 2018/11 TI - Research and Application of Adaboost Based Prediction of Student’s Academic Achievement BT - Proceedings of the 3rd Annual International Conference on Education and Development (ICED 2018) PB - Atlantis Press SP - 218 EP - 223 SN - 2352-5398 UR - https://doi.org/10.2991/iced-18.2018.35 DO - 10.2991/iced-18.2018.35 ID - Zhang2018/11 ER -