2026 ASEE Annual Conference & Exposition

Artificial Intelligence (AI) is increasingly framing aerospace engineering, however undergraduate exposure to AI applications in early coursework remains very limited. In MAE 2 (Introduction to Aerospace Engineering), a freshman-level course at UC San Diego, we explored students’ perceptions of AI and their strategies for maintaining added value in a future with AI-driven engineering tools. To provide hands-on experience without requiring programming, we implemented a conceptual AI group activity using Google Teachable Machine. Students trained a simple image classifier to categorize a topic of interest in aerospace engineering and observe how AI models learn from visual patterns. The activity emphasized pattern recognition, model limitations, and the role of human supervision in engineering applications. Preliminary results from student reflections and post-activity surveys indicate increased awareness of AI’s potential and limitations. This Work-in-Progress paper presents the design and implementation of the activity, summarizes early findings, and suggests plans for integrating longitudinal AI experiences and collaborative projects in future course offerings.