The aim of this study is to investigate the determinants that affect undergraduate students' behavioral intentions to continue learning computer hardware concepts utilizing a Metaverse-based system. The current study examined the factors influencing students' adoption of Metaverse technology at the tertiary level using a model based on the Technology Acceptance Model (TAM) and the General Extended Technology Acceptance Model for E-Learning (GETAMEL). The data was collected from 210 undergraduate students and Structural Equation Modeling (SEM) was adopted to analyze the responses. The findings show that Perceived Usefulness and Hedonic Motivation have significant positive effect on Behavioral Intention. Additionally, Natural Interaction and Perceived Usefulness significantly affect Hedonic Motivation, while Computer Anxiety negatively affects Hedonic Motivation. Furthermore, Natural Interaction was found to be the strongest predictor of Perceived Usefulness, whereas Experience was the strongest predictor of Perceived Ease of Use. The findings also indicate that Subjective Norms and Self-Efficacy have a significant effect on Experience, while Subjective Norms significantly influence Self-Efficacy. The research results also showed that neither gender nor the department had any effect. The results of this study provide major practical outcomes for higher education institutions and teachers in terms of designing Metaverse-based teaching environments.