Towards the exploitation of multimodal data to measure students' mental effort

被引:0
|
作者
Moissa, Barbara [1 ]
Bonnin, Geoffray [1 ]
Boyer, Anne [1 ]
机构
[1] Univ Lorraine, CNRS, LORIA, F-54000 Nancy, France
来源
2020 IEEE 20TH INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT 2020) | 2020年
关键词
Students' effort; cognitive load; COGNITIVE LOAD; COLLEGE; REWARD;
D O I
10.1109/ICALT49669.2020.00118
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we rely on the Cognitive Load Theory and explore how multimodal data can be used to measure students' effort at the task level. Different from what we expected, the subjective effort ratings have a higher correlation with the students' scores, while the behavioral and physiological data have higher correlations with the scores than with the effort ratings. Moreover, we found that, in the context of our study, ability had a stronger influence on students' success than the prior knowledge, while none of these variables had an influence on the effort ratings. Finally, we propose a new effort model based on students' activity.
引用
收藏
页码:373 / 375
页数:3
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