Fostering Critical Generative AI Use and Systems Thinking Through Project-Based Engineering Education

This work-in-progress report presents a modular, project-based framework for developing generative AI (GAI) literacy and systems thinking in undergraduate thermal-fluids engineering courses. GAI is operationalized through three dimensions of assessment: articulation of intended GAI use context, critical evaluation of output accuracy and limitations, and integration of GAI within problem-solving strategies. Preliminary results from 42 students in a senior level course during the Fall semester of 2025 show clear stratification of GAI literacy: 47.6% demonstrated low, 35.7% moderate, 16.7% high. Qualitative analysis revealed that technical engineering competence did not correlate with GAI literacy. Among students with low literacy, 90% could not identify gaps in GAI outputs and 69% of all students framed GAI as an information source rather than a reasoning partner. These findings informed immediate design iterations for the Spring 2026 semester implementation including computational platform standardization and enhanced system thinking reflection prompts. Future work focuses on checkpoint-based formative assessment, systems thinking rubric development, and the expansion of the project-based resource to introductory thermal-fluid courses.