The Perceptions of Faculty and Students Regarding Artificial Intelligence Usage in Education at an Academic Medical Center

Main Article Content

Xiaoshan Zhu Gordy
https://orcid.org/0000-0002-0533-6684

Abstract

Background: The emergence of generative artificial intelligence (AI), particularly with platforms like OpenAI, has brought about a paradigm shift in problem-solving and decision-making approaches. One sector that has notably embraced AI is education, where its integration has revolutionized traditional teaching and learning methods. While prior reports have highlighted the opportunities AI presents in education, they also emphasize the associated risks. Despite these concerns, proponents argue that incorporating AI into education could potentially better prepare students for evolving industry demands.


Objective: The objective of this study is to explore the perceptions of faculty and students at the University of [blinded] regarding AI usage in education.


Methods: The study, approved by the [blinded] Institutional Review Board, employed a mixed-methods design. Quantitative data were collected through a cross-sectional survey distributed to faculty and students. The survey included questions on demographics and perceptions of AI in education. Participants were also given the option to express interest in follow-up interviews. Interviews were conducted with willing participants to further explore their views on AI in education.


Results: The quantitative data revealed that the majority of the faculty and students were aware of and somewhat familiar with AI tools. They generally perceived AI as a beneficial addition to education. However, concerns about AI included potential dependency and the ethical implications of AI-generated content. The follow-up interviews provided deeper insights, with participants expressing optimism about AI's potential to transform education while emphasizing the need for robust ethical guidelines and training to maximize its benefits.


Conclusion: The findings suggest a positive perception of AI among both faculty and students at [blinded], highlighting its potential to enhance personalized learning and better prepare students for future industry demands. However, there is a clear need for comprehensive ethical guidelines and training to address concerns about dependency and the ethical use of AI. The study emphasizes the importance of balancing the benefits of AI with the associated risks to ensure its effective and responsible integration into educational practices. Continued research and dialogue are essential to navigate the evolving landscape of AI in education, ultimately aiming to enhance the learning experience and outcomes for students in healthcare education.


 


Keywords: Artificial intelligence, perceptions, education, survey, interview

Downloads

Download data is not yet available.

Article Details

How to Cite
Gordy, X. Z. (2026). The Perceptions of Faculty and Students Regarding Artificial Intelligence Usage in Education at an Academic Medical Center. Journal of the Scholarship of Teaching and Learning, 26(2). https://doi.org/10.14434/josotl.v26i2.38849
Author Biography

Xiaoshan Zhu Gordy, University of Mississippi Medical Center

Assistant Professor at School of Health Related Professions, 

University of Mississippi Medical Center. 

References

Birt, L., Scott, S., Cavers, D., Campbell, C., & Walter, F. (2016). Member Checking: A Tool to Enhance Trustworthiness or Merely a Nod to Validation? Qual Health Res, 26(13), 1802-1811. https://doi.org/10.1177/1049732316654870

Cameron, R., Dwyer, T., Richardson, S., Ahmed, E., & Sukumaran, A. (2013). Lessons from the field: Applying the Good Reporting of A Mixed Methods Study (GRAMMS) framework [Article]. Electronic Journal of Business Research Methods, 11(2), 53-64. http://search.ebscohost.com/login.aspx?direct=true&db=bth&AN=93517883&site=ehost-live

Chan, C. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20. https://doi.org/10.1186/s41239-023-00408-3

Creswell, J. W., & Clark, V. L. P. (2017). Designing and conducting mixed methods research. Sage publications.

Gillani, N., Eynon, R., Chiabaut, C., & Finkel, K. (2023). Unpacking the "Black Box" of AI in Education [Article]. Journal of Educational Technology & Society, 26(1), 99-111. https://doi.org/10.30191/ETS.202301_26(1).0008

Glaser, B. G., & Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. Aldine Publishing Co.

Golan, R., Reddy, R., Muthigi, A., & Ramasamy, R. (2023). Artificial intelligence in academic writing: a paradigm-shifting technological advance. Nature Reviews Urology, 20(6), 327-328. https://doi.org/10.1038/s41585-023-00746-x

Henshall, W. (2023). 4 Charts That Show Why AI Progress Is Unlikely to Slow Down. Time. Retrieved June 5 from https://time.com/6300942/ai-progress-charts/

Huang, J., Saleh, S., & Liu, Y. (2021). A Review on Artificial Intelligence in Education. Academic Journal of Interdisciplinary Studies, 10(3), 206. https://doi.org/10.36941/ajis-2021-0077

Intelligent.com. (2023). Nearly 1 in 3 college students have used ChatGPT on written assignments. Intelligent.com. Retrieved June 5 from https://www.intelligent.com/nearly-1-in-3-college-students-have-used-chatgpt-on-written-assignments/

Lucariello, K. (2023a). Key Concepts in Designing AI-Based Learning Strategies. The Journal Transforming Education Through Technology. Retrieved June 7 from https://thejournal.com/articles/2023/06/02/key-concepts-in-designing-ai-based-learning-strategies.aspx

Lucariello, K. (2023b). Report: AI R&D Should Align with ED Recommendations and Focus on Context, Partnership, and Public Policy. The Journal Transforming Education Through Technology. Retrieved June 7 from https://thejournal.com/articles/2023/05/31/report-ai-rd-should-align-with-ed-recommendations.aspx

Lucariello, K. (2023c). The Role of AI in Assisting Teachers and in Formative Assessments of Student. The Journal Transforming Education Through Technology. Retrieved June 7 from https://thejournal.com/articles/2023/06/01/the-role-of-ai-in-assisting-teachers-and-in-formative-assessments-of-students.aspx

Lucariello, K. (2024). New Amazon Study Reveals How AI Will Transform the Workplace in Five Years. Campus Technology. Retrieved February 12 from https://campustechnology.com/Articles/2024/01/02/New-Amazon-Study-Reveals-How-AI-Will-Transform-the-Workplace-in-Five-Years.aspx

Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B.-P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221-4241. https://doi.org/10.1007/s10639-022-11316-w

Novak, K. (2023). AI Is an Ally: Saving Teachers Time with ChatGPT. The Journal. Retrieved June 7 from https://thejournal.com/articles/2023/05/11/ai-is-an-ally-saving-teachers-time-with-chatgpt.aspx?s=the_in_020623&oly_enc_id=0006C8403078G6E

O'Cathain, A., Murphy, E., & Nicholl, J. (2008). The quality of mixed methods studies in health services research. Journal of Health Services Research & Policy, 13(2), 92-98. http://search.ebscohost.com/login.aspx?direct=true&db=cin20&AN=105765605&site=ehost-live

OpenAI. (2023). ChatGTP (June 7 Version) [Large language model]. In OpenAI. https://chat.openai.com/chat

Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121-154. https://doi.org/https://doi.org/10.1016/j.iotcps.2023.04.003

Sallam, M. (2023). ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare (Basel), 11(6). https://doi.org/10.3390/healthcare11060887

Schiff, D. (2022). Education for AI, not AI for education: The role of education and ethics in national AI policy strategies. International Journal of Artificial Intelligence in Education, 32(3), 527-563. https://doi.org/10.1007/s40593-021-00270-2 (Fairness, accountability, transparency and ethics (FATE) in AIED)

Stenfors, T., Kajamaa, A., & Bennett, D. (2020). How to … assess the quality of qualitative research. The Clinical Teacher, 17(6), 596-599. https://doi.org/https://doi.org/10.1111/tct.13242

Taber, K. S. (2018). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48(6), 1273-1296. https://doi.org/10.1007/s11165-016-9602-2

Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. Int J Med Educ, 2, 53-55. https://doi.org/10.5116/ijme.4dfb.8dfd

U.S. Department of Education, O. o. E. T. (2023). Artificial Intelligence and the Future of Teaching and Learning. https://tech.ed.gov/files/2023/05/ai-future-of-teaching-and-learning-report.pdf