Research and Reform of Functional Experiment Teaching Based on Generative Artificial Intelligence

Xiulan Yang; Xiaoguang Chen; Ya Hu; Zhenzhen Liu; Jiawei Guo

doi:10.63313/IJSSEH.2002

Authors

Xiulan Yang Experimental Teaching Center, Medical Department, Yangtze University, Jingzhou, Hubei, 421003, China Author
Xiaoguang Chen Experimental Teaching Center, Medical Department, Yangtze University, Jingzhou, Hubei, 421003, China Author
Ya Hu Experimental Teaching Center, Medical Department, Yangtze University, Jingzhou, Hubei, 421003, China Author
Zhenzhen Liu Experimental Teaching Center, Medical Department, Yangtze University, Jingzhou, Hubei, 421003, China Author
Jiawei Guo Experimental Teaching Center, Medical Department, Yangtze University, Jingzhou, Hubei, 421003, China Author

DOI:

https://doi.org/10.63313/IJSSEH.2002

Keywords:

Generative artificial intelligence, Functional experiment, Teaching reform, Innovative ability, Practical ability

Abstract

With the rapid advancement of technology, generative artificial intelligence is gradually permeating the field of education. Functional experiment teaching constitutes a vital component of medical education. However, traditional models struggle to meet the demands of personalized learning and innovation capacity cultivation due to limitations in experimental equipment and resources, rigid teaching methodologies, and untimely resource updates. This paper delves into the reformative concepts and practical pathways for applying generative artificial intelligence in functional experiment teaching, analyzing its notable advantages in enhancing teaching effectiveness and fostering students' innovative abilities. Simultaneously, it reflects on potential challenges during implementation, aiming to provide valuable insights for the innovative development of functional experiment teaching.

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