2026 ASEE Annual Conference & Exposition

Generative artificial intelligence (GenAI) is increasingly integrated into engineering education, yet limited empirical research examines how students use these tools across different contexts in engineering courses. Understanding how engineering students use GenAI is crucial for shaping academic integrity policies, ensuring fundamental skill development, and preparing students for an AI-driven industry. The objective of this mixed-methods study is to investigate how first-year engineering students use GenAI in an open-ended engineering design lab project and a MATLAB-based computational programming project, two distinct instructional settings within the same course. Survey responses and open-ended reflections from 118 students were analyzed using descriptive statistics and inductive thematic coding. Results indicate that students preferred to maintain cognitive and creative ownership of their design ideas in the design project; hence, GenAI use was less frequent and more selective. However, the moderate to high use of GenAI in conducting background research suggests that students viewed it as an acceptable support tool for information gathering. In MATLAB programming, students used GenAI more frequently, primarily for debugging and syntax clarification. Across both contexts, GenAI functioned as a scaffold supporting conceptual understanding and verification. These findings demonstrate that students' use of GenAI is shaped by task structure and cognitive demands, suggesting the need for context-sensitive guidance on GenAI use in engineering courses rather than uniform course policies.