Affero Ismail

Work place: Department of Engineering Education, Faculty of Technical and Vocational Education, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

E-mail: affero@uthm.edu.my

Website:

Research Interests:

Biography

Affero Ismail is the Head of the UTHM Digital Innovation Centre, the UNEVOC Centre Coordinator, and an associate professor in the Department of Engineering Education, Faculty of Technical and Vocational Education. He formerly served as the Head of Department at the Malaysia Research Institute for Vocational Education and Training (MyRIVET). He has a Ph.D. in TVET, a Master of Science in Human Resource Development, and a Bachelor of Engineering in Computer and Communication Systems. He is a professional member of the Malaysia Board of Technologist and Young Scientist Network, Academy of Science Malaysia. His research interests include curriculum development, digitization, training, teaching and learning, professional development, the sustainable development goals, and green skills.

Author Articles
Deep Learning and Digital Literacy: A Systematic Literature Network and Bibliometric Review

By Rayendra Fikri Aulia Dadi Mulyadi Affero Ismail Jodi Hardika

DOI: https://doi.org/10.5815/ijmecs.2026.03.05, Pub. Date: 8 Jun. 2026

This study examines the integration of computational deep learning and digital literacy from 2011 to June 2025. Employing a hybrid methodology of Systematic Literature Network Analysis and Latent Dirichlet Allocation topic modeling, 141 high impact documents were synthesized following the PRISMA 2020 protocol. Findings reveal a conceptual shift from technical exploration (2011–2018) toward human-centric, pedagogical deep learning frameworks (2019–2025). While publications peaked in 2024, Australia and South Korea emerged as leading centers of excellence in citation impact. Latent Dirichlet Allocation modeling identified ten topics, uncovering a significant research gap in using AI for fundamental research processes compared to its dominance in instructional assessment. This study provides a novel mapping of thematic evolution and offers strategic recommendations for longitudinal empirical studies and inclusive AI-driven pedagogical designs.

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