The role of artificial intelligence in Physical Therapy education
Open accessAbstract
Abstract Background and purpose Recently, there has been significant discussion about artificial intelligence (AI) and Large-Language Models (LLMs) as they relate to teaching and learning. To date, literature exists about the role of AI in Physical Therapy treatment, but not Physical Therapy education. This review will identify the benefits of adapting AI into Physical Therapy education to better prepare the healthcare providers of tomorrow. Rationale Survey research shows that AI can improve access to information, increase productivity, and reduce errors. However, most also feel ill-informed on the topic. A majority agreed that AI concepts should be included in Physical Therapy education. While valid concerns exist about AI sources giving false information, as well as the potential to use these services to plagiarize work, tools are already in existence to mitigate these issues. Potential benefits of AI in Physical Therapy education include the ability to produce examples, provide different explanations, and assist in assessing student learning while providing immediate feedback on performance. Discussion and conclusion With the scope of AI rapidly expanding, we believe it is imperative for Physical Therapy educators to have access to current information about its potential benefits, uses, and limitations. While many professionals do not currently possess much knowledge on the topic, there is a growing consensus as to the role it will play in our profession in the future. While discussions of AI can raise more questions than answers, preparation now will reduce the need for urgent adaptations in the future.
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Research on the application of AI in physiotherapy education remains scarce.
“AI is among the top 10 priorities for physiotherapy (PT) service improvement [29], and while its role in treatment is documented, research on its application in PT education remains scarce [5].”
From Acceptance of AI-Powered Chatbots Among Physiotherapy Students: International Cross-Sectional Study (2025) · cites this paper as [5]
Adapting GAI in physiotherapy education involves collaborating with other education settings and incorporating GAI in teaching and clinical experiences, such as using LLM in learning tasks.
“Adapting GAI in physiotherapy education involves collaborating with other education settings and incorporating GAI in teaching and clinical experiences, such as using LLM in learning tasks [41].”
From Generative artificial intelligence in physiotherapy education: great potential amidst challenges- a qualitative interview study (2025) · cites this paper as [41]
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References 13 · Cited by 17
- Authors
- Lowe, S. W.
- Affiliations
- Philadelphia College of Osteopathic Medicine (US)
- Corresponding author
- Lowe, Scott William
- ORCID
- Lowe, Scott William
- Venue
- Bulletin of Faculty of Physical Therapy
- Published
- 2024-04-03
- Volume
- 29
- Issue
- 1
- ISSN
- 1110-6611 (ISSN-L)
- 2536-9660
- OpenAlex
- W4395483908
- Cited by
- 17
- References
- 13
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 2
- FWCI
- 1.61
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Bulletin of Faculty of Physical Therapy (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Keywords
- artificial intelligence, large language models, physiotherapy education, AI in teaching and learning, student assessment, immediate feedback, plagiarism, misinformation, teacher readiness, curriculum adaptation
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