2026 ASEE Annual Conference & Exposition

Artificial Intelligence (AI) has been progressing rapidly and impacting society tangibly. Engineering and technology students are expected to master AI tools at work, and graduates may join teams developing such tools in the future. Although educators in higher education have not reached a consensus on how AI education should be carried out or even if AI should be included in education, such different opinions promote critical thinking and are intrinsically helpful in developing the pedagogy for AI education. As a step in exploring effective methods for AI education, the authors incorporated AI LLM (large language model) tools, together with other classic library tools, to guide first-year engineering and technology students on proper AI usage, in the scope of literature survey, patent search, and information verification. The students in the first-year seminar course at Western Carolina University are from all engineering disciplines in the school (electrical, mechanical, technology, etc.). During the class module on library resources, students were introduced to both traditional venues with reputable resources and the AI tool currently institutionally approved. The students were then randomly grouped to do research on each tool and present their findings on each tool’s pros and cons during class. After the class, the students were tasked to do an assignment individually to choose at least three out of six questions to answer on a discussion board at the online learning management system. They could not see others’ responses until they had posted their own answers. They were also tasked to read other students’ answers and make comments on those. Students were allowed to use both AI and traditional tools to develop their answers, and they were expected to verify the information from multiple sources. The research questions covered an array of disciplinary topics on math, statistics, quantum computing, case studies in engineering practices, and environmental issues. This exercise allowed students to apply what they had learned in class and served as an assessment of how the teaching module impacted their usage of AI tools. Findings indicated that the students were most excited to answer unfamiliar questions and that the AI tools enabled them to take on these topics easily, although a few answers and student comments were incorrect, inaccurate or irrelevant. The recommended next step is investigating how to use AI tools to correct incorrect or inaccurate statements, however, this is complicated by the students’ lack of recognition of mistakes. Students need to be aware of such mistakes to follow up. A solution proposed in this paper is for the students to research any new keyword in the conversation with AI, no matter how plausible a statement may seem, until all statements are understood and verified. This framework is expected to be applicable in more senior disciplinary courses, as future work.