Advancing Adaptive and Personalized E-Learning Systems: A Systematic Literature Review

With the rise of Information and Communication Technologies (ICTs), adaptive e-learning has become a promising method for enhancing educational practices. This study reviews current research on personalized adaptive e-learning systems and proposes a mobile-based design to addressing the requirements toward Industry 4.0 and Society 5.0. Using a systematic literature review methodology by Kitchenham and Charters, 28 studies were analyzed further. The findings suggest a necessity for clearer definitions of "personalized" and "adaptive" learning and categorize adaptive e-learning designs into four models: learning materials, learner characteristics, pedagogical approaches, and learning structure systems. The findings show there is still a lack of clarity in the definitions of "personalised" and "adaptive" learning, emphasizing the importance of more standardized terminology. The proposed system dynamically customized learning content material based on user preferences, cognitive abilities, and performance metrics, demonstrating the potential for increased students’ engagement and their learning outcomes. This study focusses on the possibilities of blockchain-based open educational resources, artificial intelligence, and gamification as for more engaging personalized student test to improve adaptive learning environments. Future study should confirm the suggested paradigm using empirical investigations and assess its usefulness in promoting lifelong learning.