IMPACT OF AI-BASED EDUCATIONAL TECHNOLOGIES ON THE DEVELOPMENT OF DIGITAL COMPETENCIES IN NURSES: A QUASI-EXPERIMENTAL PRETEST–POSTTEST STUDY

Abstract

Background and Aim: The digital transformation of healthcare requires nurses to possess well-developed digital competencies essential for effective and safe clinical practice. Traditional educational approaches often fail to adequately meet these demands. The aim of the present study was to examine the impact of AI-based educational technologies on the development of specific digital competencies in nursing students. Materials and Methods: A quasi-experimental study was conducted involving 80 undergraduate nursing students, divided into an experimental and a control group. The experimental group participated in training using an AI-based simulation platform designed to model the use of electronic health records, telemedicine tools, and clinical decision support systems. The control group received traditional instruction covering the same content. Digital competencies were assessed using a validated instrument administered before and after the intervention (pretest/posttest design). Data were analyzed using t-tests and ANOVA. Results: The experimental group demonstrated a statistically significant greater improvement in digital competencies compared to the control group (p < 0.01). The most pronounced gains were observed in the interpretation of digital data and the operational use of digital health tools. A post-intervention satisfaction survey indicated high levels of acceptance and motivation among participants, with AI-based simulations rated as realistic and practically applicable. Conclusion: AI-based educational technologies represent an effective approach for enhancing digital competencies and should be systematically integrated into nursing education.