As artificial intelligence (AI) tools become embedded in professional engineering practice, developing students’ ability to use these tools critically and responsibly has emerged as a key
pedagogical priority. This paper describes the design and early implementation of a low-stakes reflective assignment intended to promote AI literacy within a first-year engineering design course at a small public campus within a large public university system. The Weekly AI Use Reflection activity invited students to post brief weekly reflections describing how they used AI in their coursework (e.g., brainstorming design concepts, troubleshooting SolidWorks models, or developing research questions) and to evaluate the usefulness, accuracy, and appropriateness of
AI-generated responses.

To encourage peer learning, participating students also responded to classmates’ posts with constructive commentary or follow-up questions, creating an asynchronous dialogue around
effective and responsible AI use in engineering contexts. Over ten instructional weeks, students demonstrated greater sophistication in how they applied AI for ideation, problem-solving, and
technical communication. Preliminary thematic analysis suggests a shift from passive information seeking toward more active, metacognitive engagement, with students increasingly positioning AI
as a collaborative design support rather than an answer-providing shortcut.

This paper presents the assignment structure, grading approach, and implementation considerations for this scalable, IRB-exempt classroom practice, along with preliminary findings
illustrating students’ developing AI literacy and reflective judgment. Across the study period, 42 students contributed 148 reflection posts and 94 peer responses. The paper concludes with plans for continued qualitative analysis and future integration of reflective AI activities into broader engineering curricula.