基于大模型的教学反思与持续改进  

Teaching Reflection and Continuous Improvement Based on Large Models

作　　者：舒畅 Shu Chang(College of Computer Science and Technology,Civil Aviation Flight University of China,Guanghan 618307,Sichuan Province,China)

机构地区：[1]中国民用航空飞行学院计算机学院,四川广汉618307

出　　处：《科学与信息化》2024年第21期192-194,198,共4页Technology and Information

基　　金：中央高校基本科研业务费专项资金资助,项目名称:服务于智慧飞行的卫星边缘计算系统,项目编号:24CAFUC04014。

摘　　要：在现代教育中,随着大数据和AI技术的应用,教育数字化转型正迅速发展。本项创新实践引入了大模型技术和聚类算法,旨在精确识别和解决教学过程中的关键问题。通过使用生成式预训练变换器(GPT),能够提出有效的教学改善策略,即通过分析师生反馈快速定位教学问题,利用GPT技术提供针对性的教学内容和策略改进建议。该策略不仅提升了教学效率,还通过实时更新教学方法,有效提高了学生的学习成效。In modern education,with the application of big data and AI technology,the digital transformation of education is developing rapidly.This innovative practice introduces large model technology and clustering algorithms,aiming to accurately identify and solve key problems in the teaching process.By using the Generative Pretrained Transformer(GPT),effective teaching improvement strategies can be proposed,that is,by analyzing the feedback of teachers and students,the teaching problems can be quickly located,and GPT technology is used to provide targeted teaching content and strategy improvement suggestions.This strategy not only improves teaching efficiency,but also effectively improves students'learning effectiveness by updating teaching methods in real time.

关 键 词：课程反思 教学改进 大模型 

分 类 号：G63[文化科学—教育学]