A multidisciplinary approach is crucial for developing a user-adaptive gamified learning system, starting with pedagogy and continuing through psychology, user experience (UX) design, and artificial intelligence (AI). This study inspects different layers of knowledge, starting from foundational pedagogical theories such as constructivism, behaviourism, and Bloom's taxonomy. Moving to individual learner needs with all related complexities, which include cognitive traits, learning styles, personality types, motivational drivers, and player types, is important. Thus, the gamified learning experience can be tailored for optimal engagement and effectiveness. The gamified learning experience is influenced by a set of factors, including learners evolving traits and experiences. A user system must track and interpret these changes in real time to maintain interaction and effectiveness. Modern Technological tools like AI and machine learning (ML) can be used to design personalized predictive models. Human-computer interaction (HCI) through UX and interaction design is crucial for maintaining learners’ engagement throughout the learning process. The complexity of user-adaptive processes requires the use of HCI via UX design. This study proposes a framework that integrates andragogy, psychology, and intelligent technologies, such as AI and ML, to create a personalized learning system. This approach optimizes the learning process, allowing learners to develop their knowledge and skills and enhance productivity, efficiency, and work quality. It focuses on professional retraining for longer-tenured workers who have been away from formal education for several years and require customized learning paths to close the digital skill gap essential for operating in smart, sustainable manufacturing environments.
Elkady et al. (Fri,) studied this question.