An Exploration of Theoretical and Practical Teaching Reform in GNSS Courses Education Empowered by Generative AI

Abstract

With the rapid advancement of artificial intelligence, particularly the increasing sophistication of Generative AI and Large Language Models (LLMs), the field of education is encountering unprecedented opportunities and challenges. This manuscript, taking the course Principles and Applications of Global Navigation Satellite System as a case study, presents an in-depth exploration of integrating Generative AI into both the theoretical and practical components of the curriculum. The objective is to enhance classroom instructional effectiveness, stimulate student engagement, and cultivate innovative capabilities. This manuscript encompasses several key areas: the auxiliary role of Generative AI in theoretical knowledge instruction, including concept elucidation, case-study generation, and automated question-and-answer support; the innovation of practical teaching models facilitated by AI, such as the design of virtual simulation experiments, provision of personalized project guidance, and assistance in data analysis and report composition; and the reform of the course assessment framework based on AI-driven methodologies. Through a critical analysis and reflection on these pedagogical reforms, this study aims to construct a new and effective educational paradigm for GNSS course that is adapted for both highly efficient and intellectually stimulating.

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