Traditional or modern education with artificial intelligence for physical therapy students

Abstract

Introduction: This article explores the role of artificial intelligence (AI) in physiotherapy education, comparing traditional and modern teaching methods. Traditional education relies on direct lectures, in-person practical training, and immediate supervision. Its strengths include building a strong theoretical foundation, fostering teamwork, and developing interpersonal skills. However, it often fails to address individual learning differences and limits exposure to diverse clinical cases.
Methodology: Modern education is student-centered, using active learning, simulation, and problem-based approaches. It enhances critical thinking, clinical application, and flexibility but can be resource-intensive and may neglect theoretical depth if not carefully implemented.
Results: AI acts as a bridge between these two models. Through virtual patients, real-time feedback, personalized learning platforms, medical image analysis, and AI tutors, AI provides endless clinical simulations, adapts content to individual student needs, and offers objective assessment. It does not replace human teachers but complements them by handling technical instruction while educators focus on guidance and emotional support.
Conclusion: The article concludes that the optimal approach is an integrated hybrid model: classical methods deliver essential theoretical knowledge (anatomy, biomechanics), modern methods enable active application, and AI enhances personalization and safe, repetitive practice. This combination produces physiotherapists who are scientifically competent, clinically skilled, and technologically prepared, while retaining essential human qualities like empathy and communication.