2026 ASEE Annual Conference & Exposition

Artificial intelligence (AI) tools are rapidly becoming central to academic and professional work. While these tools offer efficiency and enhanced recall, growing reliance on them raises concerns about reduced independent thinking and shifts in cognitive effort. Drawing on insights from 15 prior studies on trust, cognition, and human–AI interaction, this research investigates how individuals form trust in AI and how such reliance reshapes decision-making.

The study involves 50 senior computer science and computer engineering majors at a large land-grant university in the US and adopts a two-phase experimental design. Participants’ AI usage rates, performance outcomes on technical problem-solving tasks, and cognitive effort (measured via self-report and time-on-task) are measured to evaluate how trust influences use. The governing hypothesis is that higher reliance on AI improves short-term performance but reduces cognitive independence over time. By integrating theoretical frameworks from human–computer interaction and cognitive psychology, this project aims to clarify the trade-offs between efficiency and autonomy in an AI-mediated world. This research nuances previous findings that trust in AI is directly correlational to measurable increases in efficiency and accuracy on technical tasks, but inversely correlational to engagement in higher-order cognitive processes. This research aims to provide evidence of both the benefits and costs of AI reliance, offering guidance for educators, designers, and policymakers seeking to balance AI integration with the cultivation of human critical thinking in engineering education.