Artificial Intelligence Policy Development in a Hybrid, Accelerated DPT Program: Planning for Academic Integrity

Authors

• Jennifaye V. Brown, Augustana UniversityFollow
• Keiba Shaw, Augustana UniversityFollow
• Otis L. Owens, University of South CarolinaFollow

Abstract

Purpose: Artificial intelligence (AI), particularly generative forms like ChatGPT, has rapidly grown across higher education. Institutions are developing policies for responsible/ethical use to preserve academic integrity, while acknowledging AI’s role in healthcare to confirm diagnoses and create personalized plans based on social determinants. In physical therapy education, AI can serve a valuable purpose despite documented misuse by Doctor of Physical Therapy (DPT) students during admissions and curricular activities. This paper describes the development of an AI policy following identified misuse and demonstrated knowledge gaps from student orientation essays. Methods: An AI task force was convened. Policy development was guided by three core elements of a context specific Logic Model: Inputs (situational context of DPT student and faculty use, evidence of AI knowledge gathered from student essays, and a university plan to develop an AI online resource center); Activities (literature searches supporting the use of AI in healthcare education, particularly DPT programs and attendance to university AI forums); and Output (a policy that promoted AI knowledge attainment and sharing and AI use to enhance student learning as well as faculty teaching and research). Results: The AI policy addressed issues for students and faculty adherence with examples to avoid misunderstanding of inappropriate AI use. The policy was reviewed, edited, and approved by the faculty and thereafter, added to the student handbook. Conclusions: While the Logic Model's outcomes and impact phases were not initially addressed as emphasis was placed on policy dissemination and implementation across two student cohorts; the data collection methods established during development provide a framework for tracking future effectiveness. The task force recommended including specific consequences for AI misuse that aligned with existing Honor Code and Academic Integrity policies. The policy development process created a balanced approach recognizing AI's educational and clinical value while establishing guardrails against academic misconduct. This framework can serve as a model for other health professions programs navigating similar challenges in maintaining academic standards amid evolving technological capabilities.

Author Bio(s)

Jennifaye V. Brown, PT, MSPT, Ph.D., NCS, CAPS is a four-time 10-year board certified clinical specialist in neurologic physical therapy with 28 of 34 years in academia and retired as an Associate Professor. Research interests were in AFOs and diversity-related topics and artificial intelligence in healthcare education. info@jvbneuropt.com

Keiba Shaw, PT, D.P.T., Ed.D., M.A., is a physical therapist, Professor, and former Director of Student Affairs at Augustana University. She is currently the Program Director for South College – Atlanta Doctor of Physical Therapy Program. With 29 years of clinical and 23 years of academic experience, her interests include psychosocial concepts in aging adults, diverse student recruitment, and promoting exercise in special needs populations. kshaw@south.edu

Otis L. Owens, Ph.D., M.P.H., CAPS is a decision scientist, health communications specialist, and Associate Professor with 14 years of experience in qualitative research methods. His research interests are in the community-driven development and evaluation of technologies for supporting cancer decision-making, enabling aging-in-place, and promoting health equity. owenso@mailbox.sc.edu

Acknowledgements

Acknowledgements The authors would like to recognize and thank Jason Bartley, PT, D.P.T., D.Sc., Jessica Fuentes, PT, DPT, NCS, Andrea Mierau, PT, DPT, Ed.D., and Trenton Schoenborn, MPP as members of the AI task force who assisted in securing literature for AI policy development and editing of the policy. Additional members of the AI task force included authors with the exception of Dr. Owens.

Recommended Citation

Brown JV, Shaw K, Owens OL. Artificial Intelligence Policy Development in a Hybrid, Accelerated DPT Program: Planning for Academic Integrity. The Internet Journal of Allied Health Sciences and Practice. 2026 Jun 09;24(2), Article 27.