Document Type
Conference Proceeding
Publication Date
7-7-2026
Abstract
Teaching qualitative research methods to Computer Science and Engineering students could be challenging due to their limited exposure to this research approach. However, using qualitative methods to understand user experiences is essential for designing and evaluating ubiquitous computing and ambient intelligence technology. With the rise of large language models (LLMs), exploring their impact on students’ learning experiences, their role in qualitative research, and their integration in AI-supported classrooms is crucial. This paper presents the learning experience of a four-month qualitative research methods course where students learn qualitative analysis in both traditional and LLM-assisted manners. Our findings highlight the opportunities and challenges of integrating LLMs into qualitative research education and provide recommendations to include them as part of an AI-supported classroom to interpretive inquiry in computing education.
Recommended Citation
Escobedo, L., Cibrian, F.L., Beltran, J.A. (2026). The Learning Experience of Using LLM for Qualitative Research Methods Courses in HCI. In: Kurosu, M., Hashizume, A. (eds) Human-Computer Interaction. HCII 2026. Lecture Notes in Computer Science, vol 16703. Springer, Cham. https://doi.org/10.1007/978-3-032-29596-5_5
Copyright
Springer
Included in
Artificial Intelligence and Robotics Commons, Other Computer Engineering Commons, Other Computer Sciences Commons, Other Electrical and Computer Engineering Commons, Science and Mathematics Education Commons
Comments
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Human-Computer Interaction. HCII 2026. Lecture Notes in Computer Science, volume 16703, in 2026. This article may not exactly replicate the final published version. The definitive publisher-authenticated version is available online at https://doi.org/10.1007/978-3-032-29596-5_5.