Research on Key Technologies of AI-Assisted Virtual Simulation Training System for Vocational Education

Now vocational education is transitioning to digital, but there are still many problems with the traditional practical teaching mode, such as insufficient space, equipment can't keep up, and security risks. This paper has come up with a way to help with AI technology, mainly to solve the problem that the virtual simulation training system is not intelligent enough, especially in terms of teaching guidance and evaluation capabilities.We tried reinforcement learning so that the system could adjust the training content on its own so that it could better adapt to the needs of different students. From the experimental results, the effect was indeed good, the accuracy of skill evaluation was improved, the speed of scene generation became faster, and the students felt more satisfied. Specifically, the accuracy of skills assessment reached 93.5%, an increase of 15.3% over the old method, which is still quite obvious.

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Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1145/3744367.3744407
Primary Topic
Innovative Educational Techniques
Type
article
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article

Research on Key Technologies of AI-Assisted Virtual Simulation Training System for Vocational Education

Y. Yin, Qian Liu, Xingwang Pi
Innovative Educational Techniques
article

Research on Key Technologies of AI-Assisted Virtual Simulation Training System for Vocational Education

Y. Yin, Qian Liu, Xingwang Pi
article en

Abstract

Now vocational education is transitioning to digital, but there are still many problems with the traditional practical teaching mode, such as insufficient space, equipment can't keep up, and security risks. This paper has come up with a way to help with AI technology, mainly to solve the problem that the virtual simulation training system is not intelligent enough, especially in terms of teaching guidance and evaluation capabilities.We tried reinforcement learning so that the system could adjust the training content on its own so that it could better adapt to the needs of different students. From the experimental results, the effect was indeed good, the accuracy of skill evaluation was improved, the speed of scene generation became faster, and the students felt more satisfied. Specifically, the accuracy of skills assessment reached 93.5%, an increase of 15.3% over the old method, which is still quite obvious.

Openalex Percentile: Top 79%
Innovative Educational Techniques
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