Revolutionizing Midwifery Education : A Scoping Review of Artificial Intelligence Methods - Silmi, Harridhil; Susanti, Ari Indra (Jurnal Paedagogy, 2025)
This study aims to explore the application of artificial intelligence (AI) methods in midwifery education and to identify key barriers to their effective implementation. This study employed a systematic literature review method conducted using the Arksey and O’Malley framework and aligned with PRISMA-ScR guidelines. Articles were sourced from PubMed, ScienceDirect, and Google Scholar, limited to publications from 2020 to March 2025. Data were analyzed through qualitative thematic analysis, with contextual analysis applied where relevant to infer missing or ambiguous details in the source articles. Of 182 articles identified, 9 met the inclusion criteria. The review revealed four main AI applications: predictive analytics for risk identification, decision support systems (DSS) for evidence-based practice, AI-powered simulations for clinical training, and generative AI tools like ChatGPT for fostering critical thinking and digital literacy. Despite these advancements, challenges such as ethical concerns (algorithmic bias, privacy issues), poor data quality, limited AI expertise among educators, and resistance to change in traditional learning environments were noted. AI has the potential to transform midwifery education, but overcoming technical, ethical, and pedagogical barriers is essential for its successful integration. Enhancing faculty capacity, ensuring data integrity, and incorporating AI literacy into curricula are vital steps toward sustainable implementation.