University of North Texas 
Artificial Intelligence (AI) Research Methods and Approaches
Studying artificial intelligence and its effects on individuals, institutions, and society draws on a wide range of research traditions, reflecting the fact that AI is simultaneously a technical artifact, a social phenomenon, and a subject of ethical inquiry. A variety of research designs are needed to build and evlauate mdoels for AI literacy scales, algorithmic auditing techniques, and frameworks for evaluating explainability and transparency. Because AI technologies evolve rapidly and cut across disciplinary boundaries, researchers in this space often must navigate methodological questions with limited precedent, balancing rigor with the need to remain responsive to a fast-changing technical and policy landscape.
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AI Research Methods and Approaches Resources
Hirvonen, N., Jylhä, V., Lao, Y., & Larsson, S. (2023). Artificial intelligence in the information ecosystem: Affordances for everyday information seeking. Journal of the Association for Information Science and Technology, 75(10), 1152–1165.
Lund, B. D., Mannuru, N. R., Katta, M., Hota, S. S. L. M., Pamukuntla, A., Uppala, S., Kola, S. M., & Mannuru, A. (2025). Bringing artificial intelligence (AI) into health information seeking behavior: A study of AI and information seeking research. Journal of Health Communication, 30(10–12), 330–335.
Mohammed, Y., Qandil, H., & Lund, B. (2026). Engineering student perceptions of generative AI use in learning trust judgment and information seeking. Discover Artificial Intelligence, 6, Article 1004.
Yen, R., Xie, Y., Sultanum, N., & Zhao, J. (2025, July). To search or to gen? Design dimensions integrating web search and generative AI in programmers' information-seeking process. In Proceedings of the 2025 ACM Designing Interactive Systems Conference (pp. 1084–1106). Association for Computing Machinery.
Zhou, T., & Li, S. (2024). Understanding user switch of information seeking: From search engines to generative AI. Journal of Librarianship and Information Science, Article 09610006241244800.
Følstad, A., & Taylor, C. (2021). Investigating the user experience of customer service chatbot interaction: A framework for qualitative analysis of chatbot dialogues. Quality and User Experience, 6(1), Article 6.
Gilardi, F., Alizadeh, M., & Kubli, M. (2023). ChatGPT outperforms crowd-workers for text annotation tasks. PNAS, 120(30), Article e2305016120.
Ha, T. (2022). An explainable artificial-intelligence-based approach to investigating factors that influence the citation of papers. Technological Forecasting and Social Change, 184, Article 121974.
Haque, M. U., Dharmadasa, I., Sworna, Z. T., Rajapakse, R. N., & Ahmad, H. (2022). "I think this is the most disruptive technology": Exploring sentiments of ChatGPT early adopters using Twitter data. arXiv.
Liu, Y., Mittal, A., Yang, D., & Bruckman, A. (2022). Will AI console me when I lose my pet? Understanding perceptions of AI-mediated email writing. Proceedings of the CHI Conference on Human Factors in Computing Systems, Article 474.
Helal, M. Y. I., Elgendy, I. A., Albashrawi, M. A., Dwivedi, Y. K., Al-Ahmadi, M. S., & Jeon, I. (2025). The impact of generative AI on critical thinking skills: A systematic review, conceptual framework and future research directions. Information Discovery and Delivery.
Medrado, A., & Verdegem, P. (2024). Participatory action research in critical data studies: Interrogating AI from a South–North approach. Big Data & Society, 11(1).
AI Research Methods and Approaches Research Guides
The SALAMANDER project is funded through the generous support of the Institute of
Museum and Library Services, Grant Number RE-259543-OLS-26.
This resource guide was created by Dr. Brady Lund and graduate assistant Bryan Anderson.
Last Updated September 25, 2026.