Artificial intelligence, robotics, and person-centered care in nursing and midwifery education: qualitative study to develop an augmented caring pedagogy model

Abstract

The rapid growth of AI and robotics is reshaping nursing and midwifery education, offering personalised and data-informed learning while raising ethical and relational challenges. These changes require educators to reassess their readiness and teaching approaches, highlighting the need to understand how faculty integrate AI into person-centred care. This study aimed to explore how nursing and midwifery educators perceive the role of artificial intelligence and robotics in person-centred care education and to generate empirical insights to inform the development of the Augmented Caring Pedagogy Model (ACPM). This qualitative descriptive study was guided by the Normalization Process Theory. Four online semi-structured focus groups were conducted with 20 nursing and midwifery academics recruited from nine universities across Türkiye. Purposive sampling was used, and the data were analyzed using an integrated inductive–deductive thematic approach supported by MAXQDA 24. Four themes were identified: (1) Coherence: Making Sense of AI-and Robotics-Supported Person-Centred Care, (2) Cognitive Participation: Engaging with Technological Transformation, (3) Collective Action: Operationalizing and Sustaining AI Integration, and (4) Reflexive Monitoring: Learning Outcomes, Equity, and Ethical Responsibility in AI-Enhanced Education. Educators viewed artificial intelligence and robotics as enhancing learning and professional growth, while also raising concerns related to empathy, ethics, inequality, and technological dependence. These findings collectively informed the development of the ACPM. Integrating AI and robotics into nursing and midwifery education offers substantial potential to advance person-centred, evidence-based teaching, but it also introduces ethical, emotional, and structural complexities. The ACPM offers a novel pedagogical framework centred on human–technology synergy and a reflective adaptation cycle to support ethically grounded and sustainable integration of emerging technologies. Findings should be interpreted in light of the single-country context and the early stage of AI and robotics integration within educational practice.

Ähnliche Arbeiten