Abstract
The integration of AI into UX design presents both opportunities and challenges for UX education-how to leverage AI’s efficiency while developing students’ human skills. This pilot study examines LLMs as an analytical AI co-pilot in undergraduate user research. Students (N=17) conducted two cycles of user research: one using traditional methods, and another with Claude-assisted analysis. Findings show 14 (82%) of students perceived the Claude-assisted approach as faster in synthesizing data and extracting insights. However, the results also reveal a trade-off: AI's efficiency may reduce empathy-building, with 6 (35%) students reporting diminished user connection. This research illuminates the inherent tension in AI-augmented UX education and suggests a hybrid pedagogical model that requires traditional user research while leveraging AI for efficiency, providing a critical framework for future research. This pilot study underscores the need to balance technological augmentation with fundamental human skills in UX design education for the AI age.
Keywords
UX, AI, User research, Design education
DOI
https://doi.org/10.21606/drs.2026.2494
Citation
Hu, N. (2026) Efficiency and Empathy: Integrating AI into User Research in an Undergraduate UX Design Course, in Simeone, L., Gray, C. M., Verhoeven, A., de Götzen, A., Bakırlıoğlu, Y., Zohar, H., Stead, M., and Buwert, P. (eds.), DRS2026: Edinburgh, 8–12 June, Edinburgh, United Kingdom. https://doi.org/10.21606/drs.2026.2494
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Included in
Efficiency and Empathy: Integrating AI into User Research in an Undergraduate UX Design Course
The integration of AI into UX design presents both opportunities and challenges for UX education-how to leverage AI’s efficiency while developing students’ human skills. This pilot study examines LLMs as an analytical AI co-pilot in undergraduate user research. Students (N=17) conducted two cycles of user research: one using traditional methods, and another with Claude-assisted analysis. Findings show 14 (82%) of students perceived the Claude-assisted approach as faster in synthesizing data and extracting insights. However, the results also reveal a trade-off: AI's efficiency may reduce empathy-building, with 6 (35%) students reporting diminished user connection. This research illuminates the inherent tension in AI-augmented UX education and suggests a hybrid pedagogical model that requires traditional user research while leveraging AI for efficiency, providing a critical framework for future research. This pilot study underscores the need to balance technological augmentation with fundamental human skills in UX design education for the AI age.