Using deep learning models to predict student performance in introductory computer programming courses

This study used deep learning techniques with Moodle log data to predict student performance in introductory computer programming courses. Particularly, this study would like to use prediction results to identify potential low-performing students who may need assistance from teachers. The results su...

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Bibliographic Details
Main Authors: Chiang, Yueh-Hui Vanessa, Lin, Ying-Ru, Chen, Nian-Shing
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
Computer performance
Data mining
Data models
Deep learning
Educational data mining
Moodle
Predictive models
Programming profession
student performance prediction
time-series data
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Summary:This study used deep learning techniques with Moodle log data to predict student performance in introductory computer programming courses. Particularly, this study would like to use prediction results to identify potential low-performing students who may need assistance from teachers. The results suggested that deep learning models are promising to predict student performance and identify low-performing students in the researched context. What the prediction results provided by the models can inform teachers in learning settings was also further discussed in this paper.
ISSN:2161-377X
DOI:10.1109/ICALT55010.2022.00060