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Misconceptions mining and visualizations for Chinese-based MOOCs forum based on NLP
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Misconceptions mining and visualizations for Chinese-based MOOCs forum based on NLP

Hao-Hsuan Hsu, Nen-Fu Huang, So-Chen Chen, Chia-An Lee and Jian-Wei Tzeng
2017 IEEE 2nd International Conference on Big Data Analysis, ICBDA 2017, pp.634-639
10/2017

Abstract

Chinese-based forum misconceptions mining MOOCs NLP social network graph word cloud Signal Processing Computer Networks and Communications Information Systems Information Systems and Management
With the popularity of MOOCs (Massive Open Online Courses), massive structured, semi-structured and unstructured data about learning is recorded for further analysis and applications. Forum is the direct way for learners to ask questions and clarify their misconceptions. Therefore, we utilize the plain text of posts and responses in MOOCs forum to extract keywords of misconceptions for instructors based on Natural Language Processing (NLP) technique. In this study, the researchers mining these misconceptions from over 120 thousands of single Chinese words and 15 thousands of English words in a course. Moreover, we visualize them by word clouds and social network graphs for quickly and better understanding of misconceptions and their correlation.

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