2026 ASEE Annual Conference & Exposition

This Work-in-Progress paper details artificial intelligence (AI) and natural language processing (NLP) technologies become increasingly integrated into first-year education, they enable new modes of student-centered learning driven by reflective, iterative engagement. This study introduces a prompt-led student learning framework aimed at improving metacognition, scientific communication, and creative problem-solving in STEM education. The central research question guiding this investigation is: How do students engage with AI-supported prompts embedded in engineering assignments, and what evidence suggests that these prompts support reflective reasoning and communication? Specifically, the framework examines how structured prompts—embedded throughout project activities and project ideation tasks, which encourage students to monitor, evaluate, and regulate their own understanding while strengthening their ability to think and write scientifically.

In many project-based courses, students often concentrate on completing procedures rather than reflecting on the reasoning behind them. As a result, they may produce technically correct but conceptually shallow reports. The proposed framework reframes the project report as a reflective learning process rather than a final deliverable. Through guided prompts such as “What assumptions underlie your experimental setup?”, “What alternative interpretations could explain this outcome?”, and “How does this finding change your understanding of the concept?”, students actively engage in metacognitive reflection—thinking about how they think and learn. This recursive process encourages them to connect theory with evidence, identify gaps in comprehension, and revise their explanations.

The framework also extends to project idea preparation, where prompts serve as scaffolds for creative and analytical thinking. Students begin by articulating a real-world problem or challenge, explore potential technical solutions, and then develop testable hypotheses. Prompts such as “Which data or tools would you need to validate your idea?” or “What ethical or practical constraints might arise?” help students transition from conceptual exploration to structured project design. This process not only strengthens creativity but also reinforces self-regulation and planning.

To evaluate the impact of prompt-led learning on metacognitive growth, an initial testing plan will be implemented within an undergraduate engineering course. Approximately 40 students will be divided into two groups: a control group using traditional instruction and an experimental group using the prompt-led framework integrated with AI tools. Assessment will focus on three domains: First it is the Metacognitive awareness, measured through a validated Metacognitive Awareness Inventory (MAI). Preliminary results suggest that students exposed to prompt-led activities demonstrate increased self-monitoring, deeper reflection, and improved coherence in their scientific arguments.