This study based on the Hedonic Motivation System Adoption Model (HMSAM), the Expectation Confirmation Model (ECM), and Task Technology Fit (TTF), explores the factors influencing users' continuance intention in gamified learning within metaversity. A total of 286 valid questionnaires were collected using random sampling. The data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM), this research analyzes the key factors affecting users' continuance intention from both hedonic and utilitarian perspectives. The results indicate that hedonic motivations (control, curiosity, and joy) positively influence users' sense of immersion and continuance intention, while utilitarian motivations (task-technology fit and expectation confirmation) also have a positive impact on continuance intention. Additionally, TTF serves as a positive moderator between joy and behavioral intention to use. Furthermore, a multi-group analysis reveals that hedonic motivations have a stronger impact on novice users, whereas utilitarian motivations exert a greater influence on expert users. This study provides theoretical support and practical recommendations for the design of metaversity platforms and the development of educational content. It also offers empirical evidence for policymakers aiming to advance metaversity education and technological innovation.