Leveraging Artificial Intelligence in Industrial and Mechanical Engineering Education: An Umbrella Mapping Review


Author: Marius Nicolae Baba

Abstract: This comprehensive research examines the impact of Artificial Intelligence (AI) on industrial and mechanical engineering education by synthesizing insights from 12 review papers published between 2023 and 2025. The study employed CiteSpace software for co-citation and keyword co-occurrence analysis to identify key intellectual structures and thematic clusters shaping the field. The co-citation analysis of authors highlights three main research areas: the use of generative AI tools (e.g., ChatGPT) for personalized education; data-driven models for predicting academic success; and, not least, immersive technologies such as robotics and virtual reality for experiential learning. The clustering of co-cited literature reveals two primary domains: (1) practical AI integration aimed at improving curriculum and exam assessments, and (2) the future potential of generative and immersive AI technologies to promote creativity and skill development among next-generation professionals. The co-citation networks of authors emphasize two distinct but overlapping scholarly communities: one focused on system-level educational technologies and the other on ethical, curricular, and institutional reform needs. The keyword co-occurrence patterns indicate convergence around two main themes: on the one hand, AI-powered analytics and simulations, while on the other, learner-centered adaptive systems. Overall, the findings of this umbrella study suggest a paradigm shift toward AI-enhanced, student-centered, and policy-driven engineering education, as this interdisciplinary field rapidly develops and widens its application, with critical societal relevance for the future.

Pages: 33-44

DOI: 10.46300/9109.2026.20.5

International Journal of Education and Information Technologies, E-ISSN: 2074-1316, Volume 20, 2026, Art. #5

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