Metaverse Technology of Car Vital Damage Detection Based on Virtual Training with PJBL Concept of Automotive Future

Authors

Keywords:

Metaverse, Technology, Car Vital Damage, Virtual Training; PjBL, automotive future

Abstract

This research aims to develop Metaverse Technology for Car Vital Damage Detection Based on Virtual Training with the Concept of Project-based Learning (PjBL) to improve the critical analysis skills of automotive engineering education students. The background of this research focuses on the urgent need to prepare graduates who can face the complexity of modern automotive technology. Using the Research and Development (R&D) method and the ADDIE (Analysis et al., Evaluation) approach, this research successfully identified ten key need elements that became the foundation for the development of innovation. The results showed that the developed metaverse technology can realistically simulate various car damage scenarios, provide an immersive learning experience through an interactive interface, and enable virtual collaboration with industry professionals. The designed simulations assist students in critically analyzing and solving problems, while the adaptive evaluation feature ensures continuous skill development. The conclusion of this study confirms that the integration of metaverse technology with PjBL is a practical, innovative step in supporting automotive education, preparing students with relevant technical and analytical skills to face the challenges of the evolving automotive industry.

 

Downloads

Published

2024-09-21

How to Cite

Andika Bagus Nur Rahma Putra, Sumarli, Poppy Puspitsari, Erwin Komara Mindarta, Tee TzeKiong, & Lee Ming Foong. (2024). Metaverse Technology of Car Vital Damage Detection Based on Virtual Training with PJBL Concept of Automotive Future. Journal of Computational Analysis and Applications (JoCAAA), 33(4), 197–209. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/639

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.