Enhancing student success by developing hybrid NNRW-LSTM predictive multi-task performance prediction in higher education institutions

Student success in college is influenced by both academic and behavioral wellbeing. In this paper, a novel hybrid architecture called NNRW-LSTM (Neural Network Random Weights. Long Short-Term Memory) is proposed for multi-task predicting academic and behavioral risk among co...

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Bibliographic Details

Main Authors:	Nazir, M., Noraziah, Ahmad, Rahmah, Mokhtar, Fakherldin, Mohammed, Khawaji, Ahmad
Format:	Article
Language:	en
Published:	Academic Publications Ltd. 2025
Subjects:	LB Theory and practice of education QA75 Electronic computers. Computer science
Online Access:	https://umpir.ump.edu.my/id/eprint/46792/1/Enhancing%20student%20success%20by%20developing%20hybrid%20NNRW-LSTM.pdf https://doi.org/10.12732/ijam.v38i11s.1265 https://umpir.ump.edu.my/id/eprint/46792/
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