2019 International Conference on Advanced Electronic Materials, Computers and Materials Engineering | |
Research on the Difficulty Points Marking System of Online Learning Process | |
无线电电子学;计算机科学;材料科学 | |
Daxiong, Luo^1 ; Zhujun, Ye^2 ; Yi, Yu^1 ; Xiaoli, Zhao^1 | |
School of Computing, Central China Normal University, Wuhan | |
430000, China^1 | |
School of Science and Engineering, University of Glasgow, University Avenue, Glasgow | |
G128QQ, United Kingdom^2 | |
关键词: Design and implements; Facial Expressions; Learning behavior; Learning process; Marking system; On-machines; Online learning; Prototype system; | |
Others : https://iopscience.iop.org/article/10.1088/1757-899X/563/4/042009/pdf DOI : 10.1088/1757-899X/563/4/042009 |
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来源: IOP | |
【 摘 要 】
There exists a notable problem in MOOCs that teachers can't find the difficulties during the learners' learning process because of their inefficiency of supervising the learners' real learning status. To solve this problem, we model the learning behavior of online learners based on facial expression information and mouse track data, and propose a method for marking learner's difficulties in online learning process based on machine learning. At same time, we design and implement a prototype system for marking difficulties based on our method. Experiments show that our method can improve the efficiency and quality of marking learner's difficulties effectively.
【 预 览 】
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