Integrative Systematic Review on the Impact of AI-Based Training Programs on Motivation and Performance of Non-Academic Educational Staff
Abstract
This study aims to systematically review how artificial intelligence (AI)-based training affects the motivation and performance of non-academic educational staff in educational institutions. The review employed a Systematic Literature Review (SLR) approach, analyzing 20 selected articles from SCOPUS, Web of Science, and SINTA databases. Findings reveal that AI-based training contributes to improved work efficiency, employee engagement, and adaptive skills. However, its impact on work motivation is highly dependent on digital literacy, training design, and managerial support. The study also highlights a lack of integrative models that link AI training, motivation, and performance in a cohesive framework. The findings offer theoretical contributions to the development of digital HRM in education and practical insights for designing inclusive and adaptive AI-based training. This study’s limitations include the scarcity of longitudinal data, dominance of research from developed countries, and limited contextual insights from Southeast Asia. Future research is encouraged to apply empirical and longitudinal approaches to strengthen causal understanding and contextual applicability
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