Articles
Vol. 4 No. 1 (2025): Generative AI and education
Generative AI in higher education: A cross-institutional study on faculty preparation and resources
Center for Teaching Excellence, Texas A&M University, College Station, TX, USA
Department of Educational Psychology, Texas A&M University, College Station, TX, USA
Center for Teaching Excellence, Texas A&M University, College Station, TX, USA
Abstract
The release of ChatGPT in 2022 sparked widespread adoption of generative AI (GAI) in higher education, leading to significant shifts in teaching and learning practices. This study examines how universities are supporting faculty in integrating GAI, focusing on available guidelines, institutional positions on GAI adoption, and resources to aid faculty in teaching with GAI. There is limited research analyzing and comparing approaches across multiple institutions. Using qualitative thematic analysis followed by quantitative review, resources from fifteen research-intensive universities in North America were analyzed to identify the extent and variety of institutional support for the implementation of GAI in higher education. Findings reveal a strong emphasis on ethical guidelines and teaching resources, primarily provided through central offices such as those of the Provost and the Center for Teaching and Learning. Most institutions offer informational articles and professional development opportunities, though there is limited access to interactive resources like open forums or research-focused support. These results highlight a cautious yet supportive stance from institutions, balancing regulatory guidance with encouragement for responsible GAI use. This study provides insights for higher education leaders seeking to enhance faculty support in the age of GAI, offering a framework for more comprehensive, adaptable, and collaborative GAI integration.
References
- Alqahtani, N., & Wafula, Z. (2024). Artificial intelligence Integration: pedagogical strategies and policies at leading universities. Innovative Higher Education. https://doi.org/10.1007/s10755-024-09749-x
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa
- Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00391-8
- 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(1), 43. https://doi.org/10.1186/s41239-023-00396-3
- Chhina, S., Antony, B., & Firmin, S. (2023). Navigating the terrain of large language models in higher education: A systematic literature review. ACIS 2023 Proceedings. https://aisel.aisnet.org/acis2023/106
- Chiu, T. K. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6, 100197. https://doi.org/10.1016/j.caeai.2023.100197
- Corbin, J. M., & Strauss, A. L. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory (4th ed.). Thousand Oaks, CA: SAGE.
- Javaid, M., Haleem, A., Singh, R. P., Khan, S., & Khan, I. H. (2023). Unlocking the opportunities through ChatGPT Tool towards ameliorating the education system. Bench Council Transactions on Benchmarks, Standards and Evaluations, 3(2), 100115. https://doi.org/10.1016/j.tbench.2023.100115
- Krause, S., Panchal, B. H., & Ubhe, N. (2024). The Evolution of Learning: Assessing the Transformative Impact of Generative AI on Higher Education. https://doi.org/10.48550/arXiv.2404.10551
- Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., ... & Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives. Computers and Education: Artificial Intelligence, 6, 100221. https://doi.org/10.1016/j.caeai.2024.100221
- Peláez-Sánchez, I. C., Velarde-Camaqui, D., & Glasserman-Morales, L. D. (2024). The impact of large language models on higher education: Exploring the connection between AI and Education 4.0. Frontiers in Education, 9, 1392091. https://doi.org/10.3389/feduc.2024.1392091
- Rogers, E. M. (2003). Diffusion of innovations (5th ed). Tampa, FL: Free Press.
- Thornberg, R. (2012). Informed grounded theory. Scandinavian Journal of Educational Research, 56(3), 243-259. https://doi.org/10.1080/00313831.2011.581686
- Walczak, K., & Cellary, W. (2023). Challenges for higher education in the era of widespread access to Generative AI. Economics and Business Review, 9(2), 71-100. https://doi.org/ http://dx.doi.org/10.18559/ebr.2023.2.743
- Wang, H., Dang, A., Wu, Z., & Mac, S. (2024). Generative AI in Higher Education: Seeing CHATGPT through universities’ policies, resources, and guidelines. Computers and Education: Artificial Intelligence, 100326. https://doi.org/10.1016/j.caeai.2024.100326
- Xiao, P., Chen, Y., & Bao, W. (2023). Waiting, banning, and embracing: An empirical analysis of adapting policies for generative AI in higher education. https://doi.org/10.2139/ssrn.4458269
- Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), 21. https://doi.org/10.1186/s41239-024-00453-6
- Zawacki-Richter, O., Marín, V., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16. https://doi.org/10.1186/s41239-019-0171-0