Evolving Chatgpt usage in engineering education: insights from a mobile robot control course

The rise of generative AI tools such as ChatGPT presents both opportunities and challenges for engineering education. This study explores how master's students in a mobile robot control course used ChatGPT across two consecutive years (2023–2024). The course combines foundational lectures with programming tasks and hands-on experiments. Using surveys and semi-structured interviews, we examine (1) how students used ChatGPT, (2) how usage varied by learning objective, and (3) how critically students interpreted its responses. Results show that students frequently used ChatGPT for coding support and conceptual clarification—particularly for challenging topics like particle filters—while relying on it less for system integration or report writing. ChatGPT was often used as a "sparring partner" to troubleshoot coding issues, refine ideas, and understand theoretical concepts. Students consistently demonstrated a critical approach to its responses, verifying outputs using simulators, their own knowledge, or external sources. These findings suggest that ChatGPT can support students in their learning process when tasks are well-defined and when validation tools like simulators are available. However, its value is limited for open-ended or integrative assignments requiring creativity or system-level thinking. We recommend providing students with clear guidance on the responsible use of generative AI and highlight ways these tools can be thoughtfully embedded into engineering curricula.