Factors influencing faculty decision-making on student use of generative AI in higher education

J.M.Shalani Dilinika

doi:10.32674/ksb6gv95

Authors

J.M.Shalani Dilinika University of Pittsburgh, University of Kelaniya https://orcid.org/0000-0002-4695-4307

DOI:

https://doi.org/10.32674/ksb6gv95

Keywords:

AI-supported learning, faculty decision-making, student learning, generative AI, sociotechnical systems theory, , higher education , sensemaking

Abstract

As generative AI (GenAI) becomes increasingly integrated into higher education, faculty encounter growing uncertainty and complexity in responding to student use of these tools. This study examines how faculty make sense of and navigate decisions about student use of GenAI in graduate-level courses, with particular attention to student learning processes. Drawing on sociotechnical systems theory and sensemaking theory, this study employed reflexive thematic analysis of open-ended interviews with 15 full-time faculty in graduate-level Library and Information Science (LIS) programs in the United States. The findings revealed the nuanced nature of faculty decision-making when navigating students’ AI use, highlighting how they engage in ongoing sensemaking as they interpret ambiguous situations, weigh competing pedagogical and professional priorities, and adapt to evolving academic expectations.

Author Biography

J.M.Shalani Dilinika, University of Pittsburgh, University of Kelaniya

J.M.Shalani Dilinika is a PhD candidate in the School of Computing and Information at the University of Pittsburgh, USA. She also serves as a Lecturer in Library and Information Science at the University of Kelaniya, Sri Lanka. Her research focuses on generative artificial intelligence in higher education, student learning assessment, and emerging competencies for the future workforce.

References

Alcántar, M. R.C., Macías González, G. G., Gómez Rodríguez, H., Jiménez Padilla, A. A., & Jacobo Montes, F. M. (2024). Percepciones docentes sobre la integración de aplicaciones de IA generativa en el proceso de enseñanza universitario. REDU. Revista de Docencia Universitaria, 22(2), 158–176. https://doi.org/10.4995/redu.2024.22027

Almisad, B., & Aleidan, A. (2025). Faculty perspectives on generative artificial intelligence: Insights into awareness, benefits, concerns, and uses. Frontiers in Education, 10, Article 1632742. https://doi.org/10.3389/feduc.2025.1632742

American Association of University Professors. (2025). Artificial intelligence and academic professions. Retrieved January 10, 2026, from https://www.aaup.org/reports-publications/aaup-policies-reports/topical-reports/artificial-intelligence-and-academic

American Library Association. (2025). ALA-accredited programs: Directory of ALA-accredited and candidate programs in library and information studies. Retrieved May 16, 2026, from https://www.ala.org/educationcareers/accreditedprograms/directory

An, Y., Yu, J. H., & James, S. (2025). Investigating the higher education institutions’ guidelines and policies regarding the use of generative AI in teaching, learning, research, and administration. International Journal of Educational Technology in Higher Education, 22(1). https://doi.org/10.1186/s41239-025-00507-3

Athanassopoulos, S., Tzavara, A., Aravantinos, S., Lavidas, K., Komis, V., & Papadakis, S. (2026). Teacher Education Students’ Practices, Benefits, and Challenges in the Use of Generative AI Tools in Higher Education. Education Sciences, 16(2), 228. https://doi.org/10.3390/educsci16020228

Azevedo, L., Robles, P., Best, E., & Mallinson, D. J. (2025). Institutional policies on artificial intelligence in higher education: Frameworks and best practices for faculty. New Directions for Adult and Continuing Education, 2025(188), 70–78. https://doi.org/10.1002/ace.70013

Baker, M. J. (2000). The Roles of Models in Artificial Intelligence and Education Research: A Prospective View. Journal of Artificial Intelligence and Education, 11, 122-143.

Bamasoud, D. M., Mohammad, R., & Bilal, S. (2025). Adopting Generative AI in Higher Education: A Dual-Perspective Study of Students and Lecturers in Saudi Universities. Big Data and Cognitive Computing, 9(10), 264. https://doi.org/10.3390/bdcc9100264

Baytas, C., & Ruediger, D. (2025). Making AI Generative for Higher Education: Adoption and Challenges Among Instructors and Researchers. Ithaka S+R. https://doi.org/10.18665/sr.322677

Beale, R. (2025, June 27). Adapting University Policies for Generative AI: Opportunities, challenges, and policy solutions in Higher education. arXiv. https://arxiv.org/abs/2506.22231

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa

Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589-597. https://doi.org/10.1080/2159676X.2019.1628806

Braun, V., & Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. https://doi.org/10.1080/14780887.2020.1769238

Bridges, L., Lopezosa, C., Velilla, M. C., & Ferran-Ferrer, N. (2025). Moving toward critical AI literacy in LIS education: a scoping review and syllabi analysis. The Electronic Library, 43(5), 798–817. https://doi.org/10.1108/el-06-2025-0224

Chan, C. K. Y., & Hu, W. (2023). Students’ Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education. International Journal of Educational Technology in Higher Education, 20, Article No. 43. https://doi.org/10.1186/s41239-023-00411-8

Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2253861

Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229-1245. https://doi.org/10.1080/00131857.2020.1728732

Crawford, J., Allen, K.-A., Pani, B., & Cowling, M. (2024). When artificial intelligence substitutes humans in higher education: The cost of loneliness, student success, and retention. Studies in Higher Education, 49(5), 883–897. https://doi.org/10.1080/03075079.2024.2326956

Crompton, H., & Burke, D. (2024). The educational affordances and challenges of ChatGPT: State of the field. TechTrends, 68(2), 380-392. https://doi.org/10.1007/s11528-024-00939-0

Dilinika, J. (2026). Teaching Students to Think Critically About AI: Practical Approaches for Academic Librarians in Designing Literacy Instruction. College & Research Libraries News, 87(5), 201. https://doi.org/10.5860/crln.87.5.201

Ding, L., Li, T., Jiang, S., & Gapud, A. (2023). Students’ perceptions of using ChatGPT in a physics class as a virtual tutor. International Journal of Educational Technology in Higher Education, 20(1), 63. https://doi.org/10.1186/s41239-023-00434-1

Emery, F. E. (1980). Designing sociotechnical systems for “greenfield” sites. Journal of Occupational Behavior, 1(1), 19–27. http://www.jstor.org/stable/3004061

Essien, A., Bukoye, O. T., O’Dea, X., & Kremantzis, M. (2024). The influence of AI text generators on critical thinking skills in UK business schools. Studies in Higher Education, 49(5), 865–882. https://doi.org/10.1080/03075079.2024.2316881

Farazouli, A., Cerratto-Pargman, T., Bolander-Laksov, K., & McGrath, C. (2023). Hello GPT! Goodbye home examination? An exploratory study of AI chatbots impact on university teachers' assessment practices. Assessment & Evaluation in Higher Education, 49(4), 1–13. https://doi.org/10.1080/02602938.2023.2241676

Hamzah, H. A., Abu Seman, M. S., & Ahmed, M. (2025). The impact of artificial intelligence in enhancing online learning platform effectiveness in higher education. Information Development, 41(3), 794-810. https://doi.org/10.1177/02666669251315842

Harrer, S. (2023). Attention is not all you need: The complicated case of ethically using large language models in healthcare and medicine. eBioMedicine, 90, 104512. https://doi.org/10.1016/j.ebiom.2023.104512

Hashmi, N., & Bal, A. S. (2024). Generative AI in higher education and beyond. Business Horizons, 67(5), 607–614. https://doi.org/10.1016/j.bushor.2024.05.005

Hu, K. (2023, February 2). ChatGPT sets record for fastest-growing user base. Reuters. Retrieved May 29, 2026, from https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/

Humble, N., & Mozelius, P. (2022). The threat, hype, and promise of artificial intelligence in education. Discover Artificial Intelligence, 2, Article 22. https://doi.org/10.1007/s44163-022-00039-z

IBM. (n.d.). What is generative AI? Retrieved May 27, 2026, from https://research.ibm.com/blog/what-is-generative-AI

Jiang, Y., L.Xie, & X.Cao. (2025). Exploring the Effectiveness of Institutional Policies and Regulations for Generative AI Usage in Higher Education. Higher Education Quarterly, 79(4) e70054. https://doi.org/10.1111/hequ.70054

Jonassen, D.H. (1999). Designing constructivist learning environments. In C. Reigeluth, (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (pp. 215-239). University Park: Pennsylvania State University.

Jose, B., Cherian, J., Verghis, A. M., Varghise, S. M., M., S., & Joseph, S. (2025). The cognitive paradox of AI in education: Between enhancement and erosion. Frontiers in Psychology, 16, Article 1550621. https://doi.org/10.3389/fpsyg.2025.1550621

Kofinas, A. K., Tsay, C. H., & Pike, D. (2025). The impact of generative AI on academic integrity of authentic assessments within a higher education context. British Journal of Educational Technology, 56, 2522–2549. https://doi.org/10.1111/bjet.13585

Kong, E., Dilinika, J. M. S., Nie, X., Gautam, A. & Huang, K.T. (2025). Measuring Socio-Ethical Engagement with Generative AI: Scale Development via Exploratory Factor Analysis. Proceedings of the Association for Information Science and Technology, 62: 978-983. https://doi.org/10.1002/pra2.1325

Li, M., Enkhtur, A., Cheng, F., & Yamamoto, B. A. (2024). Ethical implications of ChatGPT in higher education: A scoping review. Journal of Interdisciplinary Studies in Education, 13(1), 55-68. https://doi.org/10.32674/jise.v13i1.6072

Liang J., Stephens, J. M., & Brown, G.T.L. (2025). A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment. Frontiers in Education, 10:1522841. https://doi.org/10.3389/feduc.2025.1522841

Lee, H. P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3706598.3713778

Mah, D. K., Groß, N. (2024). Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs. Int J Educ Technol High Educ, 21, Article 58. https://doi.org/10.1186/s41239-024-00490-1

Maitlis, S., & Christianson, M. (2014). Sensemaking in organizations: Taking stock and moving forward. Academy of Management Annals, 8(1), 57–125. https://doi.org/10.5465/19416520.2014.873177

Malterud, K., Siersma, V. D., & Guassora, A. D. (2016). Sample size in qualitative interview studies: Guided by information power. Qualitative Health Research, 26(13), 1753-1760. https://doi.org/10.1177/1049732315617444

Mumford, E. (2006). The story of sociotechnical design: Reflections on its successes, failures, and potential. Information Systems Journal, 16(4), 317–342. https://doi.org/10.1111/j.1365-2575.2006.00221.x

Nadler, M. D. (2024). Faculty perceptions of generative artificial intelligence in the social sciences and humanities: A phenomenological study [Doctoral dissertation, Saint Louis University]. ProQuest Dissertations & Theses Global. https://eric.ed.gov/?id=ED663109

Nguyen, A., Hong, Y., Dang, B., & Huang, X. (2024). Human-AI collaboration patterns in AI-assisted academic writing. Studies in Higher Education, 1–18. https://doi.org/10.1080/03075079.2024.2323593

Paustian, T., & Slinger, B. (2024). Students are using large language models and AI detectors can often detect their use. Front. Educ. 9:1374889. doi: 10.3389/feduc.2024.1374889

Pensky, A.E.C, Usdan, J. H., & Chang, H. (2025). Generative AI's impact on graduate student professional writing productivity and quality. International Journal of Artificial Intelligence in Education, 35, 4057–4082. https://doi.org/10.1007/s40593-025-00528-z

Peres, R., Shreier, M., Schweidel, D., & Sorescu, A. (2023). On ChatGPT and beyond: How generative artificial intelligence may affect research, teaching, and practice. International Journal of Research in Marketing, 40(2). https://doi.org/10.1016/j.ijresmar.2023.03.001

Pesovski, I., Santos, R., Henriques, R., & Trajkovik, V. (2024). Generative AI for customizable Learning Experiences. Sustainability, 16(7), 3034. https://doi.org/10.3390/su16073034

Rana, N. K. (2024). Generative AI and Academic Research: A Review of the Policies from Selected HEIs. Higher Education for the Future, 12(1), 97-113. http://dx.doi.org/10.1177/23476311241303800

Saito, K., Tajika, R., Shibuya, S., & Kanno, H. (2026). Generative AI use in professional graduate thesis writing: Adoption, perceived outcomes, and the role of a research-specialized agent. arXiv. https://doi.org/10.48550/arXiv.2604.02792

Sampah, S. N. A., Nabang, M., Krampa, E. K., Issah, M., Koduah, F., Essel, H. B., & Adu-Agyem, J.J. (2026). Generative AI Competence and Student Engagement in Higher Education: Mediating Roles of Utilization, Autonomy, and Formal Learning. Journal of Interdisciplinary Studies in Education, 15(2), 109-146. https://doi.org/10.32674/3s3cx241

Shata, A., & Hartley, K. (2025). Artificial intelligence and communication technologies in academia: faculty perceptions and the adoption of generative AI. International Journal of Educational Technology in Higher Education, 22(1). https://doi.org/10.1186/s41239-025-00511-7

Silvola, A., Kajamaa, A., Merikko, J., & Muukkonen, H. (2025). AI-mediated sensemaking in higher education students' learning processes: Tensions, sensemaking practices, and AI-assigned purposes. British Journal of Educational Technology, 56, 2001-2018. https://doi.org/10.1111/bjet.13606

Simelane, P. M., & Kittur, J. (2024). Use of Generative Artificial intelligence in teaching and learning: engineering Instructors’ perspectives. Computer Applications in Engineering Education, 33(1). https://doi.org/10.1002/cae.22813

Siraj, M., Duke, J., & Plötz, T. (2026). The GenAI generation: Student views of awareness, preparedness, and concern. In Proceedings of IEEE SoutheastCon 2026 (pp. 1–8). IEEE. https://doi.org/10.1109/SoutheastCon63549.2026.11476077

Strike, V. M., & Rerup, C. (2016). Mediated sensemaking. Academy of Management Journal, 59(3), 880–905. https://www.jstor.org/stable/24758245

Sutedjo, A., Liu, S. P., & Chowdhury, M. (2025). Generative AI in higher education: A cross-institutional study on faculty preparation and resources. Studies in Technology Enhanced Learning, 4(1). https://doi.org/10.21428/8c225f6e.955a547e

Tan, S. C., Lee, A. V. Y., & Lee, M. (2022). A systematic review of artificial intelligence techniques for collaborative learning over the past two decades. Computers and Education: Artificial Intelligence, 3, 100097. https://doi.org/10.1016/j.caeai.2022.100097

Tarisayi, K. S. (2024). ChatGPT use in universities in South Africa through a sociotechnical lens. Cogent Education, 11(1). https://doi.org/10.1080/2331186X.2023.2295654

Tlili, A., Saqer, K., Salha, S.S., & Huang, R. (2025). Investigating the effect of artificial intelligence in education (AIEd) on learning achievement: A meta-analysis and research synthesis. Information Development, 41, 825-842. https://doi.org/10.1177/02666669241304407

Trist, E. L., & Bamforth, K. (1951). Some social and psychological consequences of the Longwall Method of coal-getting: An examination of the psychological situation and defenses of a work group in relation to the social structure and technological content of the work system. Human Relations, 4, 3-38.

U.S. Bureau of Labor Statistics. (2024). Employed persons by detailed occupation, sex, race, and Hispanic or Latino ethnicity. U.S. Department of Labor. https://www.bls.gov/cps/cpsaat11.htm

Weaver, J. (2025). Digital Education Council: Global AI Meets Academia Faculty Survey 2025. ibl.ai. Retrieved May 27, 2026, from https://ibl.ai/blog/digital-education-council-global-ai-meets-academia-faculty-survey-2025

Weick, K. E. (1995). Sensemaking in organizations. Sage Publications.

Wu, C., Moorhouse, B. L., Wan, Y., & Wu, M. (2026). Exploring PhD students’ utilization of generative AI in academic writing for publication purposes: Insights for EAP. Journal of English for Academic Purposes, 79, Article 101612. https://doi.org/10.1016/j.jeap.2025.101612

Xia, Q., Weng, X., Ouyang, F., Fan, Ouyang., Tzung, Jin Lin., & Chiu, T.K.F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. Int J Educ Technol High Educ 21, 40. https://doi.org/10.1186/s41239-024-00468-z

Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of overreliance on AI dialog systems on students' cognitive abilities: A systematic review. Smart Learning Environments, 11, Article 28. https://doi.org/10.1186/s40561-024-00316-7

Zhai, X. (2022). ChatGPT user experience: Implications for education. SSRN. https://doi.org/10.2139/ssrn.4312418

Zhou, G. (2025). ChatGPT in the classroom: Exploring student attitudes and ethical concerns around AI-assisted learning. Edelweiss Applied Science and Technology, 9(7), 448–458. https://doi.org/10.55214/25768484.v9i7.8592