2026 ASEE Annual Conference & Exposition

Engineering technology education often requires students to master complex concepts that are difficult to address through traditional classroom instruction alone. The integration of emerging technologies offers new opportunities to immerse students in authentic, real-world design challenges, yet barriers such as low confidence, limited prior experience, and the need to balance multiple stakeholder perspectives often make this process challenging. As sustainability and energy efficiency become central themes in modern engineering practice, there is a growing need for pedagogical approaches that foster both technical competence and systems thinking.

This study reports on the implementation of artificial intelligence (AI) to support a project in a first-year engineering technology course, Gateway to Engineering Technology. Students participated in an energy-efficiency design challenge involving a simulated house with solar panels that were affected by shading from surrounding trees. The task required students to make informed design decisions that balanced technical, economic, and social considerations while maintaining environmental responsibility. A large language model (LLM) was integrated as a conversational agent to act as a counterpart during the design process, prompting students to justify their decisions, provide evidence from simulations, and articulate trade-offs. Two versions of the AI agent were used: a scaffolded model, which structured argumentation through targeted prompts, and a non-scaffolded model, which offered open-ended, human-like conversation.

Data were collected from multiple sources, including pre- and post-tests assessing conceptual understanding of energy principles, surveys measuring self-efficacy, decision-making, metacognitive strategies, and open-ended reflections on the learning experience. Quantitative analyses showed a significant increase in students’ self-efficacy and decision-making abilities, while qualitative data revealed that students perceived the AI as an effective tool for deepening reasoning and uncovering design factors they had not previously considered.

Overall, this work demonstrates that integrating AI-driven scaffolding into simulation-based design challenges can enhance both the cognitive and motivational dimensions of engineering learning. By embedding argumentation and sustainability-focused reasoning into early engineering education, the approach encourages students to think critically, justify design decisions, and engage with the broader social and environmental context of technology.