| Title |
Multidimensional pedagogical framework for interprofessional education: blending classroom, high fidelity and extended reality simulation |
| Authors |
Kristina, Mikkonen ; Ying, Liaw Sok ; Spirgienė, Lina ; Subočius, Andrėjus ; Ignatavičius, Povilas ; Blažauskas, Tomas ; Riklikienė, Olga |
| DOI |
10.1016/j.nedt.2025.106838 |
| Full Text |
|
| Is Part of |
Nurse education today.. Edinburgh : Elsevier. 2025, vol. 154, art. no. 106838, p. 1-6.. ISSN 0260-6917. eISSN 1532-2793 |
| Keywords [eng] |
Artificial intelligence ; Extended reality ; Interprofessional ; Learning ; Pedagogical framework ; Simulation |
| Abstract [eng] |
The growing complexity of healthcare systems and the imperative for collaborative practice underscore the pressing need to innovate interprofessional education. This paper presents a multidimensional pedagogical framework that integrates blended classroom-based learning, high-fidelity simulation (HFS), and AI-enhanced extended reality (XR) technologies to develop interprofessional competences and improve preparedness for emergency care. Grounded in socio-constructivist and student-centred educational theories, the approach combines theoretical knowledge acquisition with immersive and experiential learning environments that reflect the realities of clinical practice. HFS provides a controlled setting to cultivate critical thinking, decision-making, and collaborative skills. In parallel, AI-enhanced XR introduces adaptive, gamified scenarios that foster digital competence, emotional resilience, and situated cognition. Together, these elements form a cohesive educational strategy that prepares nursing, midwifery, and medical students for high-stakes clinical situations such as anaphylaxis and trauma care. The framework contributes to enhanced patient safety, learner engagement, and the cultivation of future-ready professionals. It also responds to international calls for digital transformation and innovation in healthcare education. By harmonising traditional teaching methods with emerging technologies, this framework offers a globally relevant, scalable solution for advancing interprofessional learning across diverse healthcare contexts. |
| Published |
Edinburgh : Elsevier |
| Type |
Journal article |
| Language |
English |
| Publication date |
2025 |
| CC license |
|
