Presentation Schedule
Research Coach Framework: AI-Integrated Pedagogy for UX Design Research Education (105456)
Session Chair: Min Kang
Wednesday, 25 March 2026 10:45
Session: Session 1
Room: Room 603 (6F)
Presentation Type: Oral Presentation
This course-based study presents a pedagogical framework integrating AI tools into a 15-week Introduction to UX Design course with 16 students (14 undergraduates, 2 graduates). Addressing the persistent challenge of teaching effective research question development, this study introduces a "Research Coach package" that strategically pairs AI tools with specific research phases while preserving students' research intent.
The framework emphasizes intentional tool selection: students first develop 500-word project proposals without AI assistance, establishing authentic research intent around self-selected topics addressing real user needs. For secondary research, students employ ChatGPT and Claude for literature reviews and market analysis. For primary research, NotebookLM serves as the cornerstone tool, chosen specifically because it operates exclusively on student-provided content, preventing generic AI-generated insights from overshadowing student agency. Students input their proposals and secondary research into NotebookLM to generate initial survey and interview questions, which they critically review before conducting interviews with three participants. NotebookLM then analyzes recorded interviews to extract core problems, unmet needs, and improvement opportunities, informing REFRAME MAP development. Analysis of student reflections collected at each assignment stage and comparative assessment with the previous cohort (n=18, no AI tools) revealed three key findings: improved research question specificity and appropriateness (evidenced through reflection narratives and final artifacts), enhanced metacognitive awareness of qualitative versus quantitative research distinctions, and reported time reallocation from research mechanics toward iterative design refinement. This scalable framework offers educators a replicable model for integrating discipline-specific AI tools while maintaining pedagogical integrity, with potential extension to Ideation and Validation Coach packages.
Authors:
Min Kang, University of Houston, United States
About the Presenter(s)
Professor Min Kang is a University Assistant Professor/Lecturer at University of Houston in United States
See this presentation on the full schedule – Wednesday Schedule
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