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Improving Online Teaching Based on Knowledge Tracing Model

  • Han Wan
  • , Lina Tang
  • , Zihao Zhong
  • , Kangxu Liu
  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

During the hybrid teaching, knowledge tracing plays an important role in constructing adaptive teaching system. This study models the students' knowledge status by mining a large number of exercise records based on the improved dynamic key-value memory network (DKVMN), which is a knowledge tracing model with two external memory modules. Furthermore, the features of students' behavior are extracted to improve the prediction results of DKVMN. Since the model could depict the evolving knowledge state of students, the visualized results are displayed to both students and teachers. It could encourage students to learn the concepts that have not been mastered. On the other hand, it could help teachers to conduct teaching interventions on the high-risk students.

源语言英语
主期刊名TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
1062-1066
页数5
ISBN(电子版)9781665436878
DOI
出版状态已出版 - 2021
活动2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021 - Wuhan, 中国
期限: 5 12月 20218 12月 2021

出版系列

姓名TALE 2021 - IEEE International Conference on Engineering, Technology and Education, Proceedings

会议

会议2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021
国家/地区中国
Wuhan
时期5/12/218/12/21

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