This article takes the practical teaching process of “Principles and Applications of Microcontrollers” as the research object, explores a hierarchical practical teaching mode that integrates artificial intelligence. It integrates validation experiments, improvement layer experiments, design layer experiments, and free play layer experiments into one actual product, and educates the secondary development process of semi-finished products, organically combining isolated knowledge points to form systematic knowledge. Students use artificial intelligence technology (chatGPT, ERNIE Bot) to complete the program design of large workload, and solve the problem that students cannot complete the product program design due to short classroom teaching time. This teaching model can effectively solve various problems in the traditional practical teaching process, such as insufficient personalized teaching space, insufficient teaching hierarchy, and detachment between teaching and production practice. At the same time, it can stimulate students’ interest in learning, improve their initiative in learning, and cultivate their skills and abilities in dialogue with AI.

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Construction and Implementation of a Hierarchical Practical Teaching Model Integrating AI Technology

  • Ying Zhang,
  • Haoliang Zhu

摘要

This article takes the practical teaching process of “Principles and Applications of Microcontrollers” as the research object, explores a hierarchical practical teaching mode that integrates artificial intelligence. It integrates validation experiments, improvement layer experiments, design layer experiments, and free play layer experiments into one actual product, and educates the secondary development process of semi-finished products, organically combining isolated knowledge points to form systematic knowledge. Students use artificial intelligence technology (chatGPT, ERNIE Bot) to complete the program design of large workload, and solve the problem that students cannot complete the product program design due to short classroom teaching time. This teaching model can effectively solve various problems in the traditional practical teaching process, such as insufficient personalized teaching space, insufficient teaching hierarchy, and detachment between teaching and production practice. At the same time, it can stimulate students’ interest in learning, improve their initiative in learning, and cultivate their skills and abilities in dialogue with AI.