Generative AI as a Teaching Tool for Social Research Methodology: Addressing Challenges in Higher Education

Laura Arosio ()
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Laura Arosio: Department of Sociology and Social Research, University of Milano Bicocca, 20126 Milan, Italy

Societies, 2025, vol. 15, issue 6, 1-19

Abstract: Teaching social research methodology in university courses, whether qualitative or quantitative, presents significant challenges for both instructors and students. These challenges include the availability of empirical datasets, the illustration of data analysis techniques, the simulation of research report writing, and the facilitation of scenario-based learning. Emerging AI tools, such as ChatGPT-4, offer potential support in higher education, though their effectiveness depends on the context and their integration with traditional didactic methods. This article explores the potential of AI in teaching social research methodology, with a focus on its benefits, limits and ethical considerations. Furthermore, the paper presents a case study of AI application in teaching qualitative research techniques, specifically in the analysis of solicited documents. Generative AI shows the potential to improve the teaching of social research methodology by providing students with opportunities to engage in hands-on learning, interact with realistic datasets and refine their analytical and communication skills. The integration of AI in education should, however, be approached with a critical mindset, ensuring that AI tools serve as a means to sharpen (not replace) traditional methods of learning.

Keywords: AI in education; teaching social research methodology; qualitative and quantitative methods; ChatGPT; didactic practices; scenario-based learning; ethical considerations of AI; AI-assisted qualitative research; documentary analysis; solicited documents (search for similar items in EconPapers)
JEL-codes: A13 A14 P P0 P1 P2 P3 P4 P5 Z1 (search for similar items in EconPapers)
Date: 2025
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