Research on Innovative Teaching Model of Data Structure Driven by Generative Artificial Intelligence

Abstract

Aiming at the core dilemmas of the Data Structure course, such as abstract concepts, complex algorithms, disjointed practical application, and the inability of traditional teaching models to meet the needs of high-order competence cultivation in the intelligent era, this paper constructs an GAI-driven collaborative teaching system of "Three Activations, Four Modules, Five Realms" based on the trend of educational digital transformation. Meanwhile, it integrates thinking training empowered by problem mapping. In practice, GAI technology is used to visualize abstract knowledge, refine teaching processes, and contextualize practical scenarios, transforming generative artificial intelligence from a mere knowledge-generation tool into a carrier for thinking training. Ultimately, it achieves the educational goal of building a teacher-student relationship characterized by being both teacher and friend, harmonious and seamless, mutually beneficial, teaching and learning from each other, and wisdom-inspired mutual promotion. Research results show that this teaching path effectively addresses the pain points such as weak recognition of learning value and superficial learning in the course, significantly improving students' algorithmic thinking, innovative capabilities, and intelligent literacy. It provides a theoretical reference and practical paradigm for the intelligent transformation of core computer courses.