Improving Online Teaching Based on Knowledge Tracing Model

被引:0
|
作者
Wan, Han [1 ]
Tang, Lina [1 ]
Zhong, Zihao [1 ]
Liu, Kangxu [1 ]
机构
[1] Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China
来源
IEEE TALE2021: IEEE INTERNATIONAL CONFERENCE ON ENGINEERING, TECHNOLOGY AND EDUCATION | 2021年
基金
中国国家自然科学基金;
关键词
knowledge tracing; online teaching; visualization;
D O I
10.1109/TALE52509.2021.9678661
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
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.
引用
收藏
页码:1062 / 1066
页数:5
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