Learning Performance Prediction with Imbalanced Virtual Learning Environment Students’ Interactions Data

Learning Performance Prediction with Imbalanced Virtual Learning Environment Students’ Interactions Data

One of the critical aspects in completing study in a virtual learning environment (VLE) is the student behavior when interacting with the system. However, in real cases, most of the student behavior data have imbalanced label distribution. This imbalanced dataset affects the model performance of mac...

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Bibliographic Details
Main Authors: Chen, Hsing-Chung, Prasetyo, Eko, Prayitno, Prayitno, Kusumawardani, Sri Suning, Tseng, Shian-Shyong, Kung, Tzu-Liang, Wang, Kuei-Yuan
Format: Article
Language:English
Published: 2022
Subjects:
Electrical and Electronic Engineering not elsewhere classified
Electrical and Electronic Engineering
Online Access:https://repository.ugm.ac.id/282249/1/Chung%20Chen%20et%20al%20-%202022%20-%20Learning%20Performance%20Prediction.pdf

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https://repository.ugm.ac.id/282249/1/Chung%20Chen%20et%20al%20-%202022%20-%20Learning%20Performance%20Prediction.pdf

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