Short Project Description

Communication and patient history-taking are core competencies for physiotherapists, yet access to high-quality clinical training opportunities remains limited for students. This interdisciplinary project, involving the Department of Rehabilitation Science and Health Technology (RHT), the Faculty of Technology, Art and Design (TKD), and the CIM research group at Oslo Metropolitan University, aims to develop an AI-driven patient avatar to strengthen physiotherapy students’ communication and patient history-taking skills. By creating a custom-made learning tool, the avatar will be tailored to align with the specific course content and learning objectives of the physiotherapy program. In addition, the AI-driven patient avatar will provide realistic and interactive training, supporting government recommendations for digitalization and student-centered, interactive learning methods.

This project has two main objectives: 1) To develop, in collaboration with physiotherapy students, educators, and patient representatives, an AI-driven patient avatar, based on a large language model, tailored for first-year physiotherapy students to enhance their communication and patient history-taking skills. 2) To develop, in collaboration with physiotherapy students and educators, an implementation strategy for integrating the AI-driven patient avatar into a first-year physiotherapy functional assessment course. Combining expertise in physiotherapy, data science, and health technology, this project represents is a collaborative effort involving multiple stakeholders. By creating tailored learning tools, the project aims to equip physiotherapy students with essential skills and better prepare them for clinical practice. The project will result in two scientific papers documenting its development and findings.