Game-based personalized learning in the metaverse computer virtual laboratory: Improving user experience with a learning material recommender system

Arif, Yunifa Miftachul ORCID: https://orcid.org/0000-0002-2183-0762, Nurhayati, Hani, Karami, Ahmad Fahmi, Ayunda, Nisa, Subiyakto, A'ang, Samala, Agariadne Dwinggo and Criollo-C, Santiago (2025) Game-based personalized learning in the metaverse computer virtual laboratory: Improving user experience with a learning material recommender system. International Journal of Human–Computer Interaction, 41 (4). pp. 1-18. ISSN 1044-7318

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Abstract

Assembly learning is an important component in computer education in terms of emphasizing the understanding of computer components and their functions. This study explores the evolving learning methodologies and media to convey this knowledge, especially in today’s era of advanced technology characterized by online interactions. However, the real difficulty in the learning process is guiding students to relevant learning resources. Therefore, this study proposes the integration of Multi-Criteria Recommender System (MCRS) in metaverse, so that we can use the pretest as a reference and make appropriate learning material recommendations. The purpose of integrating the recommendation system into the virtual learning environment is to improve the computer assembly learning process so that students get the right materials and the best learning outcomes. The test results show that the recommender system can generate appropriate learning material recommendations for players, and the Metaverse-based Computer Virtual Laboratory (MCVL) also received a good usability rating.

Item Type:	Journal Article
Keywords:	Computer assembly; metaverse; learning material; recommender system
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080110 Simulation and Modelling 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080111 Virtual Reality and Related Simulation
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Yunifa Miftachul Arif
Date Deposited:	18 Feb 2025 13:56

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