Integrating Generative AI in Engineering Education: Enhancing Learning and Attendance in a Vehicle Theory Course

This paper presents the results of a two-year innovative teaching project in the Vehicle Theory course, a fourth-year Mechanical Engineering subject at Universidad Carlos III de Madrid. The project explored the integration of generative artificial intelligence (GenAI) tools, particularly ChatGPT, to enhance student engagement, support project work, and promote ethical academic use. Key strategies included a flipped classroom approach, where students summarized previous lessons with GenAI assistance, and the use of AI to aid in the design and optimization of a tubular chassis project. Survey results and course observations indicate high student adoption of GenAI, with positive impacts on understanding theoretical concepts, completing exercises, and generating project outputs. Students reported that GenAI facilitated idea generation, technical problem-solving, and the creation of more effective and visually appealing presentations. Limitations included information bias, overreliance on GenAI, and variability in response quality depending on prompt formulation. Overall, the project improved attendance, engagement, and academic performance, highlighting the potential of GenAI as a complementary educational tool. Additionally, by requiring students to critically evaluate the GenAI responses, the project encouraged the development of judgment and decision-making skills, which are essential competences for future engineers.