|
Vol.14, No.3, August 2025. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Machine Learning Algorithm for Real-Time Feedback on Mobile Learning Platforms for Students in High School
Sumarlin Sumarlin, Remerta Noni Naatonis, Edwin Ariesto Umbu Malahina
© 2025 Sumarlin Sumarlin, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 14, Issue 3, Pages 2799-2811, ISSN 2217-8309, DOI: 10.18421/TEM143-80, August 2025.
Received: 14 October 2024. Revised: 05 May 2025.
Abstract:
This study explores the application of machine learning algorithms to deliver real-time feedback in mobile learning platforms for high school students. Previous research has shown that real-time feedback can significantly improve student engagement and academic performance, particularly when supported by predictive models such as Neural Networks (NNs) and Decision Trees (DTs). This study addresses the following research question: Can machine learning models accurately predict student engagement levels to provide timely and personalized feedback in mobile learning environments. It is hypothesized that NNs will outperform DTs in predictive accuracy due to their ability to model complex, non-linear relationships. Using an experimental field study design, the research involved 150 high school students aged 16–18, who interacted with an AI-integrated mobile learning platform. The collected data included demographic attributes, platform usage, quiz performance, and engagement levels. Results showed that the NN model achieved 85% accuracy, outperforming the DT model (82%), with higher precision, recall, and F1-score values. These findings suggest that machine learning can effectively support personalized learning through adaptive feedback systems.
Keywords – Machine learning algorithms, mobile learning, real-time feedback. |
|
----------------------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------------------- |