Introduction:
Healthcare education faces ongoing challenges, particularly in bridging the gap between theoretical knowledge and practical skill development. Active learning methodologies, such as self-modelling —where students record and reflect on their own performance— and video modelling —using expert demonstrations— have proven effective in enhancing learner autonomy, critical thinking, and practical skill acquisition. The ClinicalModelling project, funded by the European Union and involving nine partners across four countries, aims to transform nursing and surgical training through these methodologies. Its primary objective is to strengthen both technical and socio-emotional competencies in healthcare students, ensuring they are better equipped to meet the evolving demands of clinical environments.

Methodology:
A pilot study was carried out at the University of Santiago de Compostela to explore the impact of self-modelling on nursing students' perceived self-efficacy. Fourteen second-year nursing students were randomly assigned to either a control group (traditional instruction) or an experimental group (self-modelling with smart glasses). Both groups completed six sessions over three weeks (two per week), focusing on two core procedures: surgical handwashing and donning sterile gloves. While all students received identical theoretical instruction, the experimental group used wearable smart glasses to record their clinical performance, which they then reviewed for self-assessment and improvement. Self-efficacy was measured using the General Self-Efficacy Scale (Baessler & Schwarzer, 1996), administered prior to the intervention (Session 1) and following its completion (Session 6), three weeks later . Observational checklists and student feedback were also collected to provide qualitative insights into learning experiences and procedural confidence.

Results:
The experimental group (n=7) showed an increase in post-intervention self-efficacy scores compared to the control group (n=7). Participants also reported enhanced confidence, greater procedural awareness, and improved ability to self-correct errors. Qualitative data indicated that students appreciated the opportunity to visualize their own performance and found the feedback loop empowering and motivating. In contrast, the control group expressed a desire for more personalized, hands-on feedback and struggled more with procedural consistency.

Conclusions:
These preliminary findings suggest that self-modelling can significantly improve nursing students’ confidence, autonomy, and clinical performance. By enabling reflective practice and experiential learning, ClinicalModelling presents a scalable and adaptable model for modern healthcare education. This approach aligns with the EU’s goals for digital transformation in education and addresses key pedagogical challenges in clinical training by fostering active, self-regulated, and competence-based learning.

Keywords: Self-modelling, Smart glasses, Nursing training, Clinical competence, Self-efficacy.