A study on prediction of academic performance based on current learning records of a language class using blended learning

Byron Sanchez, Xiumin Zhao, Takashi Mitsuishi, Terumasa Aoki

研究成果: Conference contribution

抄録

In this paper, we describe a classification method that does not rely on historic data to predict changes in student academic performance, and therefore predict if a student will fail a class or not. By classifying students into groups given their grades, and extracting the common features in between them, it is possible to use those common features to predict if other students that share common characteristics will fall into the same classification groups. As well, those same common features can be used to help students improve their academic performance.

本文言語English
ホスト出版物のタイトルProceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings
編集者Ahmad Fauzi Mohd Ayub, Antonija Mitrovic, Jie-Chi Yang, Su Luan Wong, Wenli Chen
出版社Asia-Pacific Society for Computers in Education
ページ493-495
ページ数3
ISBN(印刷版)9789869401265
出版ステータスPublished - 2017
イベント25th International Conference on Computers in Education, ICCE 2017 - Christchurch, New Zealand
継続期間: 2017 12 42017 12 8

出版物シリーズ

名前Proceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings

Other

Other25th International Conference on Computers in Education, ICCE 2017
CountryNew Zealand
CityChristchurch
Period17/12/417/12/8

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science Applications
  • Information Systems
  • Hardware and Architecture
  • Education

フィンガープリント 「A study on prediction of academic performance based on current learning records of a language class using blended learning」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル