Exploring the influence of the learning Metaverse on student satisfaction: an integrated framework of dual-congruity theory and interactive learning environment features

Abstract

ABSTRACT Employing Metaverse platforms for teaching is an emerging form of computer-assisted education, and such courses often require students to first learn how to operate relevant platforms. Learning to use the platform is a course itself. In this context, this study develops a predictive model to explore students’ satisfaction with learning to operate the Metaverse platforms. We used the dual-congruity theory as the basis for the study, focusing on the features of Metaverse interactive learning environment as the causative factors. A total of 486 respondents who have learned the Metaverse were collected, and partial least squares method was adopted to evaluate the model and test the hypothesis. The study findings reveal that visual appeal, escapism, and perceived Metaverse quality are predictors of self-congruity and perceived diagnosticity, which positively influence students’ learning satisfaction. The study provides recommendations for both education establishments and professionals who develop Metaverse platforms. This study contributes to the academic development of Metaverse education and serves as a guide for better learning effectiveness and satisfaction in information education.