2025 ASEE Annual Conference & Exposition

Dual-submission homework approaches were developed as a way to foster reflectiveness and metacognition in students while discouraging academic dishonesty. However, the rise of large language models (LLMs) challenges this approach. This paper examines whether LLMs can replicate credible reflections and, consequently, compromise the integrity of the dual-submission approach. Experiments were conducted using reflections generated by students and LLMs, analyzed by instructors and teaching assistants, with mixed results. We discuss implications, limitations of current strategies, and potential modifications to maintain academic integrity in an era of LLMs.