Creating a syllabus or preparing lecture slides is familiar work for faculty. For Hua Wei, those time-consuming tasks also raised a research question: how could AI help give educators more time to work directly with students?

Hua Wei, an assistant professor in Arizona State University’s School of Computing and AI, is exploring that question through Instructional Agents, a platform designed to support course planning and content creation. In summer 2026, his team joined I-Corps Aspire to better understand the needs and experiences of the educators who might eventually use it.

“As researchers, we often think first about technical capability, but we wanted to learn more about who the real users would be, what problems they care about most, and what barriers might affect adoption,” Hua said.

Understanding the Work Behind Teaching

Customer discovery brought the team closer to the everyday considerations that shape whether an educator will adopt a new tool. Technical capabilities mattered, but so did the time, effort, and confidence required to use them.

“One important insight from customer discovery was that instructors and educational organizations are not simply looking for ‘more AI,’” Hua said. “They care about whether AI tools can reduce real workload, fit naturally into existing teaching workflows, and support responsible, high-quality instructional design.”

Through those conversations, the team began thinking differently about the problem they were trying to solve. Understanding educators’ workloads, existing teaching practices, and concerns about AI helped them consider where Instructional Agents could be useful and what might stand in the way of adoption.

Making Time to Test Assumptions

For Hua’s team, a central benefit of I-Corps was having a structured reason to seek those perspectives early.

“The most valuable part of I-Corps Aspire was the structured push to talk with potential users and stakeholders early,” Hua said. “Those conversations helped us test our assumptions, refine our language, and better understand how different audiences perceive AI tools in education.”

The process helped the team think more intentionally about potential applications, how the technology might be used in educational settings, and the needs of the people involved.

Since the course, they have continued exploring course material generation, instructional design, and AI-enhanced concept explanation videos. Their research has also continued to grow, with collaborations including Mayo Clinic on medical education and Conservation International Kenya on AI literacy.

“The experience also helped us think more clearly about how to communicate the broader impact of our work beyond the research community,” Hua said.

An Opportunity Before Everything Is Figured Out

For faculty and staff considering I-Corps, Hua’s experience offers a useful perspective: the program can help while researchers are still determining where their work could lead.

His team entered with a technology and questions about its potential use. They came away with a clearer understanding of what educators valued, what might affect adoption, and which questions to explore next.

“I would say that it is a very worthwhile experience, even if you are still early in the research process,” Hua said. “It helps you step outside your technical framing and listen carefully to the people who may eventually use, adopt, or benefit from your work.”

For Instructional Agents, those conversations gave the team a more informed starting point for future decisions. Educators’ workloads, teaching practices, and expectations became central to how they considered the technology’s next steps.

What could you learn by talking with the people who might use your research? Explore an upcoming I-Corps course through the NSF I-Corps Hub: Desert and Pacific Region. Learn more and apply today.