Comparing the performance of machine learning and deep learning algorithms classifying messages in Facebook learning group

Cheng Yo Huang-Fu, Chen Hsuan Liao, Jiun Yu Wu

研究成果: Conference contribution同行評審

7 引文 斯高帕斯(Scopus)

摘要

The use of computer-mediated communication (CMC) has been ubiquitous in higher education. To better understand students' behaviors and facilitate students' learning through CMC, this study aimed to classify messages in Facebook learning group which was created as an on-line discussion board. Different machine learning and deep learning classification models were proposed, trained and testified with corpuses from PTT, one of the famous on-line forums in Taiwan. Furthermore, the classification of Facebook messages by these well-trained models were compared with human coding. Results revealed that recurrent neural network (RNN) with word to vector (W2V) for feature extraction demonstrated the best performance in accuracy. In addition, the combination of RNN and TF-IDF was proved to have the highest correlation with human work. Implications for artificial intelligence (AI) in education context was discussed.

原文English
主出版物標題Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021
編輯Maiga Chang, Nian-Shing Chen, Demetrios G Sampson, Ahmed Tlili
發行者Institute of Electrical and Electronics Engineers Inc.
頁面347-349
頁數3
ISBN(電子)9781665441063
DOIs
出版狀態Published - 7月 2021
事件21st IEEE International Conference on Advanced Learning Technologies, ICALT 2021 - Virtual, Online, Malaysia
持續時間: 12 7月 202115 7月 2021

出版系列

名字Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021

Conference

Conference21st IEEE International Conference on Advanced Learning Technologies, ICALT 2021
國家/地區Malaysia
城市Virtual, Online
期間12/07/2115/07/21

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