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The Physical Therapy Learning Institute was proud to host the

2025 Disruptive Innovation in Physical Therapist Education Virtual Summit:

​“Transforming Physical Therapy Education: Powered by AI
The Future Waits for No One"

 which was hosted on April 4-5, 2025

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Gold Level Sponsor:

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We would like to extend our sincere appreciation for the Summit Sponsors and their contributions.  If you are interested in learning more about sponsoring the a future Summit download our Sponsorship Overview.

Summit Recordings, Handouts, & Presentation Slides: 

To view the recordings or download handouts and presentation slides for the keynote and topic sessions, scroll down or select the session you are interested in:

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Summit Description: 

This summit was an insightful and forward-looking virtual summit around a truly disruptive topic, AI in Physical Therapy Teaching and Learning, where leading educators and innovators explored the transformative impact of artificial intelligence on the education of future physical therapists. This event was designed to facilitate high-level discussions around the integration of AI technologies in physical therapy education, with a focus on content generation, precision education, learner assessment, and learner-centered strategies. Participants discovered how AI is revolutionizing teaching methods, enabling precision education through adaptive learning, personalized content, and predictive analytics. With AI-driven tutoring systems, educators can now offer tailored support to students, while content generation and delivery become more efficient, accurate, and adaptable to individual learning styles. Discussion and presentations were centered around AI in the classroom and student tutoring, AI in clinical education, and administrative uses of AI (e.g., policies/accreditation).

Keynote Presentations:

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Ken Masters, PhD, HDE, FDE

​Ethics and Bias in AI 

Presented by: Ken Masters, PhD, HDE, FDE

The first of two keynotes was delivered by Dr. Ken Masters, an Associate Professor of Medical Informatics in the Medical Education and Informatics Department at Sultan Qaboos University in Oman and a global expert on ethics and bias in AI. He's authored numerous papers and guidelines on the ethical use of AI, the creation of custom GPTs, and how health professional educators must prepare for a future with artificial general intelligence (AGI). Dr. Masters delved into the ethical dimensions of AI in education and how we ensure that AI tools are transparent, unbiased, and equitable in physical therapy training.  This session addressed both the promises and perils of AI, focusing on mitigating biases in data, algorithms, and decision-making systems. Dr. Masters also addressed the need for educators to stay ahead of rapid technological changes. Just as large language models (LLMs) transformed classrooms unexpectedly, AGI holds the potential for even more dramatic shifts.

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Precision Education

Presented by:  Martin Pusic, MD

The second keynote focus on precision education—the application of AI to create personalized learning environments that cater to each student’s unique needs and pace. This keynote was delivered by Dr. Martin Pusic, MD. Dr. Pusic is an Associate Professor of Pediatrics and Emergency Medicine at Harvard Medical School, Director of the American Board of Medical Specialties (ABMS) Research and Education Foundation and served as an investigator in more than 100 publications focused on learning analytics and the role and impact of research, data, and informatics on medical education and learning. This session examined how AI enables data-driven insights into student performance, allowing educators to design interventions that maximize individual learning outcomes and prepare students more effectively for the demands of clinical practice.

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Martin Pusic, MD

Keynote: Precision Education

Key Themes & Topics:

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  1. Ethics and Bias in AI (Keynote)​

  2. Precision Education (Keynote)

  3. Integrating AI into the Curriculum: As AI becomes an integral part of healthcare, it is critical for physical therapy students to understand how to leverage AI for patient management and clinical decision-making. This session explored how to teach students to use AI tools effectively, from predictive analytics in patient care to integrating AI into treatment planning. Attendees gained insights on where and how to embed AI instruction into an already packed curriculum, balancing the need for foundational knowledge and skills with the rising importance of AI literacy.

  4. AI for Clinical Education Preparation: AI can enhance clinical education preparation by offering virtual patient simulations, enabling students to practice clinical decision-making in diverse, realistic scenarios. It can provide personalized feedback, track student progress, and adapt learning experiences to individual needs. Additionally, AI tools can analyze clinical case studies, helping students refine critical thinking and treatment planning skills, ultimately better preparing them for real-world patient care.

  5. AI in Learner Assessment: Explore how AI tools are enhancing learner assessment, offering more nuanced and continuous evaluation of student progress. From automated grading to real-time performance feedback in clinical simulations, AI is reshaping how educators measure student competencies and readiness for practice.

  6. AI in Student Tutoring: AI can provide personalized tutoring for physical therapy students, offering real-time feedback, adaptive learning paths, and interactive simulations that enhance clinical decision-making skills.

  7. AI in Faculty Administrative Roles: AI can streamline administrative tasks for faculty, including grading, scheduling, and managing student performance data. It can also assist in maintaining accreditation standards by automating compliance tracking and generating data-driven reports, as well as supporting policy development through analysis of institutional trends and best practices.

Objectives:

This summit was designed to provoke thought and action. Will the early adopters of AI change the future of physical therapy education, leaving those who hesitate behind? The discussions and insights shared demonstrated that AI is not just a passing trend—it is a disruptive force that will shape the future of teaching, learning, and practice in physical therapy. Attendees left equipped with the tools and strategies needed to lead this transformation, ensuring they remain at the forefront of the educational revolution already underway. Participants were encouraged to embrace AI, or risk being left behind in an increasingly AI-driven educational landscape. Upon completion of this event, participants would be able to:

 

  • Understand the Ethical Implications of AI in Education: Participants will explore the ethical considerations of AI in physical therapy education, including strategies to mitigate bias in AI-driven decision-making systems.

  • Leverage AI for Personalized Learning: Attendees will gain insights into how AI can be used to create adaptive learning environments that cater to individual student needs, improving educational outcomes.

  • Integrate AI into the Physical Therapy Curriculum: Educators will learn practical approaches to embedding AI tools in physical therapy education, from clinical decision-making to patient management.

  • Utilize AI for Enhanced Learner Assessment: Participants will explore AI-driven tools that provide real-time feedback and continuous assessment, improving student competency evaluation and readiness for clinical practice.

  • Incorporate AI in Faculty Administrative Tasks: Attendees will discover how AI can streamline administrative duties such as grading and accreditation compliance, allowing educators to focus more on teaching and mentoring.​

Topic Sessions:

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Topic 1: Teaching with AI

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Topic1

​​​Topic 2: Integrating AI into the Curriculum and Learner Competencies

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Topic2

Speaker Presentations/Bios:

​​Topic 3: Administrative Applications of AI

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Topic3

Speaker Presentation/Bio:

Recommended Summit Reading & References

You are encouraged to read or review the following articles prior to the Summit. 

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  • Adler-Milstein, Julia., & Holmgren, A. J. (2021). Next-Generation Artificial Intelligence for Diagnosis: From Predicting Diagnostic Labels to "Wayfinding." JAMA. https://doi.org/10.1001/jama.2021.1205

  • Bowen JA, Watson C.E. (2024) Teaching with AI: A practical guide to a new era of human learning. Johns Hopkins Press, Baltimore MD.

  • Cloud-Biebl, Beth A., Hollman, John H., Krause, David A., & Calley, Darren Q. (2024). Detecting Artificial Intelligence-Generated Personal Statements in Professional Physical Therapist Education Program Applications: A Lexical Analysis. Physical Therapy, 104(1), pzae006. https://doi.org/10.1093/ptj/pzae006

  • Cornwall, Jon., Hildebrandt, Sabine., Champney, Thomas H., & Goodman, Kenneth. (2024). Ethical concerns surrounding artificial intelligence in anatomy education: Should AI human body simulations replace donors in the dissection room? Anatomical Sciences Education, 17, 937-943. https://doi.org/10.1002/ase.2335

  • Cuff, Patricia A., & Forstag, Erin Hammers. (2023). Artificial intelligence in health professions education: Proceedings of a workshop. Washington, DC: The National Academies Press. https://doi.org/10.17226/27174

  • Ferryman, Kadija., Mackintosh, Maxine., & Ghassemi, Marzyeh. (2023). Considering Biased Data as Informative Artifacts in AI-Assisted Health Care. The New England Journal of Medicine, 389(9), 833-838. https://doi.org/10.1056/NEJMra2214964

  • Fortier K., Fagan J., Halle KA. (2024). AI in Clinical Education. Education Leadership Conference (ELC), Oakland CA.

  • Gin, Brian C., O’Sullivan, Patricia S., Hauer, Karen E., Abdulnour, Raja-Elie, Mackenzie, Madelynn, ten Cate, Olle, & Boscardin, Christy K. (2024). Entrustment and EPAs for Artificial Intelligence (AI): A Framework to safeguard the use of AI in health professions education. Academic Medicine. https://doi.org/10.1097/ACM.0000000000005930

  • James, Cornelius A., Wheelock, Kevin M., & Woolliscroft, James O. (2021). Machine Learning: The Next Paradigm Shift in Medical Education. Academic Medicine, 96(7), 954-957. https://doi.org/10.1097/ACM.0000000000003943

  • Lowe, Chan., & Colloton. (2024). Leveraging AI in PT Education Starting Now. ELC 2024.

  • Mangold S, Ream M. Artificial Intelligence in Graduate Medical Education Applications. Journal of Graduate Medical Education, April 2024, 115-118.

  • Masters, Ken., Benjamin, Jennifer., Agrawal, Anoop., MacNeill, Heather., Pillow, M. Tyson., & Mehta, Neil. (2024). Twelve Tips on Creating and Using Custom GPTs to Enhance Health Professions Education. Medical Teacher, 46(6), 752-756. https://doi.org/10.1080/0142159X.2024.2305365

  • Masters, Ken., Herrmann-Werner, Anne., Festl-Wietek, Teresa., & Taylor, David. (2024). Preparing for Artificial General Intelligence (AGI) in health professions education: AMEE Guide No. 172. Medical Teacher, 46(10), 1258-1271. https://doi.org/10.1080/0142159X.2024.2387802

  • Mollick, Ethan., & Mollick, Lilach. (2023). Assigning AI: Seven approaches for students with prompts. SSRN. https://ssrn.com/abstract=4475995

  • Morelli N. A Framework for Integrating Artificial Intelligence and Machine Learning into Physical Therapy, Physical Therapy, 2024, pzae137, https://doi.org/10.1093/ptj/pzae137

  • Savage, Thomas., Nayak, Ashwin., Gallo, Robert., Rangan, Ekanath., & Chen, Jonathan H. (2024). Diagnostic Reasoning Prompts Reveal the Potential for Large Language Model Interpretability in Medicine. npj Digital Medicine, 7(20). https://doi.org/10.1038/s41746-024-01010-1

  • Shen, Mei-di., Chen, Si-bing., & Ding, Xiang-dong. (2024). The Effectiveness of Digital Twins in Promoting Precision Health Across the Entire Population: A Systematic Review. npj Digital Medicine, 7(145). https://doi.org/10.1038/s41746-024-01146-0

  • U.S. Department of Education, Office of Educational Technology, Artificial Intelligence and Future of Teaching and Learning: Insights and Recommendations, Washington, DC, 2023. This report is available at https://tech.ed.gov

  • Watkins, M. Make AI Part of the Assignment. The Chronicle of Higher Education. https://www.chronicle.com/article/make-ai-part-of-the-assignment. AI - Assisted Learning Template.

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Recommended Podcasts on AI:​​

references

Questions?
Please contact Summit Organizers Karen Abraham at kabraham@su.edu.

We Are

MOVERS & SHAKERS

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