Immersive learning in virtual worlds: A two-step analysis SEM and NCA for assessing the impact of Metaverse education on knowledge retention and student collaboration

Fazeelat Aziz, Cai Li and Asad Ullah Khan

Technology in Society, 2025, vol. 81, issue C

Abstract: The Metaverse is transforming education by providing immersive and interactive learning environments that engage students in ways traditional education cannot. Educational platforms within the Metaverse are increasingly popular among educators due to their potential to enhance student experiences and outcomes. This study examines how immersive learning experiences in the Metaverse (ILE) focusing on Knowledge Retention (KR), Collaborative Engagement (CE), Perceived Enjoyment (PE), and New Learning Models (NLM) contribute to improved educational outcomes. In particular, it aims to address these factors in Chinese students. Social Learning Theory (SLT) focuses on social interaction, modelling, and reinforcement. This study examines how the Metaverse develops those processes in the environment. The current research employs two statistical techniques: Partial Least Squares Structural Equation Modeling (PLS-SEM) and Necessary Condition Analysis (NCA) on data collected via an online survey from 453 Chinese university students. This implies that collaborative engagement (CE), in particular, and new learning models (NLM) influence knowledge retention (KR) positively. This can only demonstrate the need always to be met of integrating innovative techniques supported by technology with conventional approaches to learning. The quantitative analysis shows only the overall results based on the educators’ views on the Metaverse platforms. The present study adds to existing metaverse literature, although the topical area is relatively under-researched in education.

Keywords: Collaborative learning; Pedagogical issues; Learning strategies; Knowledge retention; Necessary condition analysis (NCA) (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:81:y:2025:i:c:s0160791x25000612

DOI: 10.1016/j.techsoc.2025.102871

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