Achmad Hamdan, Hakkun Elmunsyah, Putrinda Inayatul Maula, Heni Vidia Sari, Mohd Firdaus Abdullah, Devi Septianingsih
This study aims to evaluate the implementation of adaptive assessment in e-learning for vocational education through a Systematic Literature Review (SLR). The findings indicate that adaptive assessment enhances student motivation, engagement, and learning outcomes by tailoring materials to individual needs. Algorithms such as K-NN and dynamic scaffolding prove effective in classifying learning styles and providing personalized feedback. However, key challenges include technological limitations, lack of educator training, and the absence of standardized evaluation metrics. This study recommends the development of more dynamic AI-based systems and collaboration with industries to improve the relevance of vocational learning. © 2025 IEEE.
Universitas Negeri Malang, Electronic Syst. Eng. Tech. Study Prog., Malang, Indonesia; Universitas Negeri Malang, Dept. Electrical Eng. and Informatics, Malang, Indonesia; Universiti Teknologi Mara, Centre for Electrical Engineering Studies, Pulau Pinang, Malaysia
