Understanding Student Experiences with Generative AI
As generative AI tools reshape academic work, critical questions emerge: How are students really using these tools? What motivates their choices? How do they navigate varying policies across courses? Rather than relying on research from other contexts, we're investigating these questions directly with our own UO students.
Our Research Program
This CAIT (Communities Accelerating the Impact of Teaching) group educational research project combines quantitative and qualitative approaches to build a comprehensive understanding of student experiences with generative AI at UO.
Navigating GenAI Policies Across Courses (Spring 2026)
Method: Qualitative Interviews | Timing: Spring 2026
Please consider sharing this with your students — we'd love to hear about their experiences with GenAI policies.
Students can share their experiences in a brief screening survey (7 min) and an optional 45-minute Zoom interview.
- Survey: Drawing for 5 × $10 DuckStore gift cards
- Interview: $20 DuckStore gift card
What We're Investigating
This study explores the lived reality of how students experience and navigate GenAI policies as they move across different courses.
Policy Experiences
- How students encounter and interpret GenAI policies in different courses
- How policies are communicated through syllabi, verbal statements, and assignment instructions
- What happens when policies are unclear, absent, or appear to conflict
Student Decision-Making
- How students decide what's appropriate when expectations aren't clear
- What factors influence their choices: policy clarity, peer behavior, perceived risk, and educational value
- How navigating policy differences shapes their broader perceptions of GenAI
Understanding Student Motivation (Winter 2026)
Method: Quantitative Survey | Timing: Winter-Spring 2026
What We're Investigating
This study examines the psychological factors that influence students' decisions about using — or not using — generative AI tools in their academic work.
GenAI-Specific Motivations
- Students' confidence in using GenAI (expectancy beliefs)
- Perceived value of GenAI tools for learning and assignments
- Perceived costs and concerns
- Intentions to use GenAI for academic work
Course-Specific Factors
- How motivation for a specific course relates to GenAI use intentions in that course
- Whether course-level motivation moderates the relationship between general GenAI beliefs and use intentions
Why This Research Matters
These studies provide both quantitative evidence of what motivates student choices and qualitative depth about real-world navigation challenges. Together, they will help UO educators:
- Understand what's happening in students' academic lives
- Communicate GenAI policies more effectively
- Support student success in evolving academic contexts
- Make informed, evidence-based decisions about GenAI in teaching
Research Showcase
TEP - GenAI: What UO Students Are Experiencing — June 5, 2026
Everyone is welcome. Join us for a presentation of findings, including:
- Initial research findings on student motivations and themes from policy navigation experiences
- Student panel discussion
- Implications for UO policy and practice
- Q&A and open discussion
Our Research Team
This work brings together expertise from across campus.
- Ali SökenTeaching Engagement Program
- Jenefer HusmanCollege of Education
- Isabel Garcia ValdiviaSociology
- Nicole DudukovicPsychology & Neuroscience
- Emily SimnittDigital Humanities & English
- Jon JaramilloRomance Languages
- Christabelle DragooMcNair Scholars Program
- Matt GrahamCollege of Education
- Val SawickyHuman Physiology
Get Involved & Learn More
Ali Söken
Teaching Engagement Program
alisoken@uoregon.edu
541-346-1182
This research has been reviewed and approved by the UO Institutional Review Board. IRB Protocol #STUDY00002187.