Mining Precedence Relations among Lecture Videos in MOOCs via Concept Prerequisite Learning

In recent years, MOOC has gradually become an important way for people to learn knowledge. But the knowledge background of different people is quite different. Moreover, the precedence relations between lecture videos in a MOOC are often not clearly explained. As a result, some people may encounter...

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Bibliographic Details
Published in:Mathematical problems in engineering 2021-08, Vol.2021, p.1-10
Main Authors: Xiao, Kui, Bai, Youheng, Wang, Shihui
Format: Article
Language:English
Subjects:
Algorithms
Curricula
Deep learning
Encyclopedias
Knowledge
Learning
Neural networks
Online instruction
Video
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Summary:In recent years, MOOC has gradually become an important way for people to learn knowledge. But the knowledge background of different people is quite different. Moreover, the precedence relations between lecture videos in a MOOC are often not clearly explained. As a result, some people may encounter obstacles due to lack of background knowledge when learning a MOOC. In this paper, we proposed an approach for mining precedence relations between lecture videos in a MOOC automatically. First, we extracted main concepts from video captions automatically. And then, an LSTM-based neural network model was used to measure prerequisite relations among the main concepts. Finally, the precedence relations between lecture videos were identified based on concept prerequisite relations. Experiments showed that our concept prerequisite learning method outperforms the existing methods and helps accurately identify the precedence relations between lecture videos in a MOOC.
ISSN:1024-123X
1563-5147
DOI:10.1155/2021/7655462