Teaching Skills Cultivation of Information Technology Normal University Students from the Perspective of Group Intelligence: Research on the Training and Application Optimization of GPT Dialogue Model


  • Haixi Guo
  • Shasha Liu




Generative Artificial Intelligence, Teaching Skills Training for Normal University Students, Large Model, Perspective of Group Intelligence


With the wide application of information technology in education, the cultivation of teaching skills for information technology normal university students is particularly important. However, the traditional teaching model faces challenges, and new methods are needed to improve the teaching ability of normal university students. The purpose of this study is to explore the teaching skills training mode of information technology normal students based on the perspective of group intelligence, and to use GPT dialogue model for training and application optimization, so as to improve the teaching effect and the professional level of normal students. Through the teaching mode from the perspective of group wisdom, normal university students can have more in-depth interaction and cooperation with classmates, teachers and teaching resources, and promote the innovation and improvement of information technology teaching. Using GPT dialogue model for training and application optimization can realize personalized and intelligent teaching assistance, and provide teaching content and methods more close to the needs of students. The results show that the teaching mode based on the perspective of group intelligence and the GPT dialogue model can effectively improve the teaching skills of information technology normal university students, and provide new ideas and methods for the innovation and development in the field of education.


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How to Cite

Guo, H., & Liu, S. (2024). Teaching Skills Cultivation of Information Technology Normal University Students from the Perspective of Group Intelligence: Research on the Training and Application Optimization of GPT Dialogue Model. Frontiers in Computing and Intelligent Systems, 8(3), 28-32. https://doi.org/10.54097/6wb9xf11