Who Did the Work? Direct Measures and AI-Completed Coursework in Program Assessment
Dr. Stavros Hadjisolomou
October 21, 2026
3:00pm ET / 2:00pm CT / 1:00pm MT / 12:00pm PT
Description: Program assessment reports often rely on graded, course-embedded work as direct measures, because students are motivated to do well when the work affects their course grade. AI tools can now complete much of that coursework. Report rubrics, even those that ask about testing conditions, rarely ask whether students produced the work themselves. When the report's data collection section says nothing about this, reviewers cannot tell how far the results reflect what students can do on their own.
In this hands-on session, participants will review excerpts from sample program reports using a worksheet they can reuse at their own institution. For each learning outcome, they will note how students completed each direct measure (for example, supervised in class, online with identity or process checks, or unsupervised) and mark the measures where the report says nothing about these conditions. Participants will leave with conversation prompts they can adapt for asking programs and colleagues how students completed the work. They will also leave with a question for the data collection section of next cycle's report template, so programs record these conditions and reviewers can judge how far the results support conclusions about students' learning.
For assessment and institutional effectiveness staff who review program reports or write institutional summaries, coordinators in assessment offices, and faculty who write their program's assessment report. No AI expertise required.
Speaker Bio: Stavros Hadjisolomou, PhD, is Associate Professor of Psychology and Accreditation Liaison Officer at the American University of Kuwait, where he previously served as Associate Dean for Assessment and Accreditation. His research on AI browser agents that complete learning management system coursework with no student at the keyboard was featured in Forbes and The Verge and presented at AALHE 2026. He has published two articles on AI in assessment in Intersection: A Journal at the Intersection of Assessment and Learning, one on AI agents in the LMS and one on how generative AI chatbots support and complicate programmatic assessment principles. He also advises the AMICAL consortium on the responsible use of generative AI. He holds a PhD in Psychology from the City University of New York.
Non-Member Cost: $50
Member Cost: FREE
