Navigating the Future of Metaverse Education: A Comparative Study of VR and Non-VR Learning Environments

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Bibliographic Details
Title: Navigating the Future of Metaverse Education: A Comparative Study of VR and Non-VR Learning Environments
Language: English
Authors: Ping Geng (ORCID 0000-0002-6248-3867), Daniel Shen (ORCID 0000-0003-0867-3528)
Source: International Society for Technology, Education, and Science. 2024.
Availability: International Society for Technology, Education, and Science. 944 Maysey Drive, San Antonio, TX 78227. Tel: 515-294-1075; Fax: 515-294-1003; email: istesoffice@gmail.com; Web site: http://www.istes.org
Peer Reviewed: Y
Page Count: 13
Publication Date: 2024
Document Type: Speeches/Meeting Papers
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Computer Simulation, Educational Technology, Technology Uses in Education, Technology Integration, Value Judgment, Intention, Game Based Learning, Relevance (Education), Food Processing Occupations, College Students, Educational Games, Student Attitudes
Abstract: Despite the rapid advancement of virtual reality (VR) and its integration into educational settings, the adoption of metaverse learning platforms often encounters challenges. These include technical limitations and a lack of understanding of how these platforms impact learning effectiveness and user engagement. Previous studies have revealed mixed outcomes regarding the effectiveness of VR in education, with many platforms failing to meet user expectations in terms of usability and learning outcomes. This uncertainty hampers the broader adoption of immersive learning technologies. Thus, this study aims to investigate what factors contribute most significantly to the effectiveness and user adoption of metaverse learning platforms. Specifically, it examines how perceived usefulness and efficiency influence learners' intentions to use these platforms. Utilizing a Technology Adoption Model specifically adapted for VR in the metaverse, the study conducted a comprehensive survey assessing various constructs such as immersive quality, intuitiveness of the user interface, and functionality of interactive elements in food science education. Linear regression analysis was employed to analyze the data, revealing that perceived usefulness (USE) and perceived efficiency (PERF2) are significant predictors of learners' intent to use the platform, explaining 62.6% of the variance in intent scores. The findings suggest that enhancing the practical utility and optimizing the efficiency of metaverse learning platforms are crucial for improving their adoption and effectiveness. Based on these insights, recommendations for platform developers include focusing on real-world applicability and connectivity with lecture content, improving technical performance, and enhancing user support mechanisms within the platform. [For the complete proceedings, see ED672804.]
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED673132
Database: ERIC
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