Purpose This study aims to address the critical need for a systematic and resource-efficient approach to integrating metaverse learning platforms within higher education institutions facing budgetary constraints, specifically in engineering education. Design/methodology/approach A two-phase methodology was used. First, a modified analytic hierarchy process (AHP) surveyed engineering students to prioritize challenging subjects within their extensive curriculum (minimum 132 credit hours). Second, expert instructors leveraged these insights to inform the development of a cost-effective metaverse learning platform focused on the identified high-difficulty subjects. A case study involving mechanical engineering students was then conducted to evaluate the platform’s effectiveness. Findings The case study demonstrated an approximate of 47% relative improvement in average performance in learning outcomes among mechanical engineering students using the AHP-driven, low-cost metaverse platform compared to traditional teaching methods. This highlights the platform’s practical utility in enhancing educational delivery. Practical implications This research provides a validated framework for low-budget institutions to strategically implement metaverse learning environments, optimizing resource allocation while effectively balancing theoretical and practical learning in complex subjects. It offers a tangible solution for improving engineering education in resource-limited settings. Originality/value This study is novel in proposing and validating an AHP-based methodology for systematically designing and deploying a low-cost metaverse learning platform, specifically tailored to prioritize learning difficulties within a vast engineering curriculum in resource-constrained environments. It offers a practical and data-driven approach to addressing a critical gap in educational technology adoption.
Shaban et al. (Thu,) studied this question.