Abstract
The technological transformation of the digital era has significantly reshaped the educational landscape, driving a shift toward more personalized learning approaches. This study explores the integration of deep learning technologies in tailoring curriculum to meet the individual needs of students. Using a qualitative literature review, it examines how deep learning can identify learning behavior patterns, assess students' strengths and weaknesses, and deliver timely and relevant instructional interventions. The findings suggest that personalized learning powered by artificial intelligence (AI) and adaptive curricula can enhance student motivation, learning effectiveness, and inclusivity. However, the implementation also poses challenges, including concerns over data privacy, algorithmic bias, and infrastructure readiness. Therefore, achieving sustainable personalized education requires a synergistic alignment between technology, educational policy, and educator preparedness.
First Page
404
Last Page
411
Recommended Citation
Khalik, M.,
&
Nampira, A.
(2025).
Deep Learning for Personalized Learning: Tailoring Curriculum to Student Needs.
Journal of ICSAR, 9(2), 404-411.
DOI: https://doi.org/https://doi.org/10.17977/um005v9i22025p404-411
Available at:
https://citeus.um.ac.id/icsar/vol9/iss2/16