Construction and Implementation of Metaverse Intelligent Classroom Based on Domain-specific Language
- DOI
- 10.2991/978-94-6463-417-4_12How to use a DOI?
- Keywords
- Metaverse; Virtual Reality; Domain-specific Language; Unity; SpringBoot
- Abstract
In this paper, a metaverse intelligent classroom design based on Domain-specific Language is proposed to address the time, space and form constraints of traditional teaching methods, as well as the problems of insufficient interaction and inconspicuous personalised teaching in existing virtual teaching systems. A general framework based on Unity and Spring Boot is built through the collaborative application of tools such as Blender, Unreal, Visual Studio and IntelliJ IDEA. A lightweight compiler was implemented and a generic syntax was designed to make it easy to use for users without programming experience. Future research can expand virtual courses and experiments in more subject areas, combining augmented reality, artificial intelligence and other technologies to further enhance the usefulness and richness of the virtual teaching system, so as to meet the learning needs of different students and to improve learning effectiveness and satisfaction.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yingmei Wei AU - Yu Li AU - Yuxiang Xie PY - 2024 DA - 2024/05/07 TI - Construction and Implementation of Metaverse Intelligent Classroom Based on Domain-specific Language BT - Proceedings of the 2024 5th International Conference on Big Data and Informatization Education (ICBDIE 2024) PB - Atlantis Press SP - 121 EP - 142 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-417-4_12 DO - 10.2991/978-94-6463-417-4_12 ID - Wei2024 ER -