Edu-Metaverse: concept, architecture, and applications

ABSTRACT

As an important form of education in the future, Edu-Metaverse cannot only innovate the existing teaching mode, provide diversified teaching resources and environments, realize intelligent teaching evaluation and certification methods, etc., but also realize the real integration of people’s physical world and virtual world. Therefore, how to deepen the concept of metaverse into the field of education and creating an innovative education model has become the challenge of this research. To this end, this paper develops a comprehensive Edu-Metaverse ecosystem architecture which provides an effective implementation reference for the development of the Edu-Metaverse. In addition, the Edu-Metaverse teaching mode is constructed, and the feasibility of the Edu-Metaverse teaching mode and its breakthrough significance to the existing offline and online education are demonstrated through questionnaires. Through the case study of Edu-Metaverse teaching, the implementation scheme and effective ways of Edu-Metaverse are verified. The research shows that Edu-Metaverse can not only broaden and deepen the educational content, but also reduce the educational cost and improve the quality and efficiency of education, but it also has potential risks.

KEYWORDS:

• Edu-Metaverse
• gamified interactive teaching
• digital twin campus
• virtual digital human

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was funded in part by the Ministry of Education Humanities and Social Sciences Research Youth Fund Project [grant number 22YJCZH046], the Science and Technology Research Project of Hubei Provincial Department of Education [grant number B2022274], the Natural Science Basic Research Plan in Shaanxi Province of China [grant number 2022JM-371] and the comprehensive research program on teaching reform of Shaanxi Normal University [grant number 22JG04].

Notes on contributors

Ting Wu

Ting Wu received her M.Sc. degree in Visual Design from Dongseo University in South Korea in 2014, and received her Ph.D. in Visual Contents from the same university in 2019. Currently, she is an assistant professor at the School of Zhongnan University of Economics and Law in Wuhan, China. Her research focuses on the emotional experiences of film audiences, psychological needs of viewers, and film analytics, drawing inspiration from psychology, film theory, and affective computing. Ting Wu has published research work extensively in the fields of film design and film studies, and she is dedicated to creating meaningful film experiences by employing computational research methods and interdisciplinary approaches.

Fei Hao

Fei Hao received the B.Sc. degree in Information and Computing Science and the M.Sc. degree in Computer Software and Theory from Xihua University, China, in 2005 and 2008, respectively, and the Ph.D. degree in Computer Science and Engineering from Soonchunhyang University, South Korea, in 2016. He is currently an associate professor with the School of Computer Science, Shaanxi Normal University, China. From 2020 to 2022, he was a Marie Sklodowska-Curie Fellow with the University of Exeter, Exeter, United Kingdom. He has authored over 100 papers in international journals and conferences. He received 6 best paper awards from KISM 2012, GreenCom 2013, MUE 2015, UCAWSN 2015, CUTE 2016 and CSA 2020. He is a recipient of the IEEE Outstanding Leadership Award at CPSCom 2013, the 2015 Chinese Government Award for Outstanding Self-Financed Students Abroad and the IEEE Outstanding Service Awards at SmartData 2017 and DSS 2018. His research interests include social computing, ubiquitous computing, big data analysis and processing and mobile cloud computing. He is a member of ACM and KIPS.