TECHNOLOGICAL EVOLUTION AND PEDAGOGICAL SHIFTS IN PREGNANCY SIMULATION TOOLS
A SCOPING REVIEW
DOI:
https://doi.org/10.31983/jahmt.v8i1.14727Keywords:
Pregnancy Simulator; Midwifery Education; Artificial Intelligence; Virtual Reality; Person-Centered Care.Abstract
Technological advancements have fundamentally reshaped midwifery and maternity nursing education. While traditional simulation has been long established, the emergence of digital innovations such as Virtual Reality (VR) and Artificial Intelligence (AI) necessitates necessitates a clearer understanding of evolving technological trends and their associated pedagogical shifts. This study aims to map contemporary pregnancy simulation tools and identify the targeted learning objectives within these modalities. A scoping review was conducted utilizing the Arksey and O’Malley framework and adhering to the PRISMA-ScR guidelines. A systematic search was performed across six databases (Scopus, PubMed, Springer Nature, ScienceDirect, ERIC, and Google Scholar) for literature published between 2015 and 2026. From the 663 records initially identified, 9 selected studies were thematically analyzed to extract data regarding technological classification and pedagogical orientation. The findings identified four major categories of pregnancy simulation technologies: analog and physical (wearable) simulators (n = 1); high-fidelity and hybrid simulators (n = 2); immersive technologies, including VR and AR (n = 2); and AI-based simulations integrating generative AI and telehealth (n = 2). Across these categories, all studies utilized interactive simulation approaches, with most demonstrating high-fidelity characteristics. Four dominant pedagogical orientations were identified: empathy and attitudinal development (n = 1); self-confidence and anxiety reduction (n = 1); psychomotor and clinical skill acquisition (n = 2); and critical incident competence and cultural responsiveness (n = 2). A clear shift was observed from empathy-focused learning toward the development of complex clinical competencies, psychological readiness, and adaptive communication skills. This evolution reflects a transition in simulation fidelity from predominantly physical realism to interpersonal fidelity, enabling integrated development of technical and relational competencies. Pregnancy simulation technologies have evolved from physical wearable devices to high-fidelity manikins, immersive VR/AR systems, and AI-driven telehealth simulations, forming increasingly intelligent and interactive learning ecosystems. Concurrently, pedagogical orientation has shifted from affective learning toward performance readiness, clinical decision-making, and person-centered, culturally responsive care. Despite these advancements, the role of educators particularly in facilitating reflective debriefing remains critical to ensuring meaningful learning. Future research should focus on the ethical standardization of AI integration and the evaluation of long-term impacts on clinical performance and patient safety.
References
1. Musie, M. R., Tagutanazvo, O. B., Sepeng, N. V., Mulaudzi, F. M. & Hlongwane, T. A scoping review on continuing professional development programs for midwives: optimising management of obstetric emergencies and complications. BMC Med Educ 25, 296 (2025).
2. Aryuwat, P., Holmgren, J., Asp, M., Radabutr, M. & Lövenmark, A. Experiences of Nursing Students Regarding Challenges and Support for Resilience during Clinical Education: A Qualitative Study. Nursing Reports 14, 1604–1620 (2024).
3. Daneshfar, M. & Moonaghi, H. K. The impact of clinical simulation on bridging the theory–practice gap in nursing education: a systematic review. BMC Med Educ 25, 1216 (2025).
4. Mannella, P. et al. Simulation of childbirth improves clinical management capacity and self-confidence in medical students. BMJ Simul Technol Enhanc Learn 4, 184–189 (2018).
5. Damioli, G., Van Roy, V., Vertesy, D. & Vivarelli, M. Is artificial intelligence leading to a new technological paradigm? Structural Change and Economic Dynamics 72, 347–359 (2025).
6. McGrew, H. C. et al. Telehealth Simulations with Generative Artificial Intelligence in Midwifery Education: Practice for Person-Centered and Culturally Responsive Care. J Midwifery Womens Health 70, 932–938 (2025).
7. ÖZER, E. & DÖNER, Ş. İ. Cultural clashes in maternity care: midwifery students’ struggles with communication and cultural differences — a qualitative study from Turkey. BMC Med Educ 26, 124 (2025).
8. Mutch, J. et al. Equity, diversity and inclusion in simulation-based education: constructing a developmental framework for medical educators. Adv Simul (Lond) 9, 20 (2024).
9. Aitken, J. A. et al. Influence of simulation-based training on reflective practice. BMJ Simul Technol Enhanc Learn 7, 638–640 (2021).
10. Gamel, W. Effect of Pregnancy Simulator on Midwifery Nursing Students’ Experience of Physical Difficulties and Attitude toward pregnant women. Tanta Scientific Nursing Journal vol. 24 54–74 (2022).
11. Vogel, K. et al. Augmented reality simulation-based training for midwifery students and its impact on perceived knowledge, confidence and skills for managing critical incidents. Midwifery 136, 104064 (2024).
12. Chang, C.-Y., Panjaburee, P. & Chang, S.-C. Effects of Integrating Maternity VR-Based Situated Learning into Professional Training on Students’ Learning Performances. Interactive Learning Environments 32, 2121–2135 (2024).
13. Silmi, H. & Susanti, A. I. Revolutionizing Midwifery Education : A Scoping Review of Artificial Intelligence Methods. j. paedagog. penelit. pengemb. pendidik. 12, 501 (2025).
14. Arksey, H. & O’Malley, L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology 8, 19–32 (2005).
15. Levac, D., Colquhoun, H. & O’Brien, K. K. Scoping studies: advancing the methodology. Implementation Sci 5, 69 (2010).
16. Tricco, A. C. et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med 169, 467–473 (2018).
17. Hall, S. W. High-Fidelity Simulation for Senior Maternity Nursing Students. Nurs Educ Perspect 36, 124–127 (2015).
18. Hernon, O., McSharry, E., MacLaren, I. & Carr, P. J. The use of educational technology in teaching and assessing clinical psychomotor skills in nursing and midwifery education: A state-of-the-art literature review. J Prof Nurs 45, 35–50 (2023).
19. Cobbett, S. & Snelgrove-Clarke, E. Virtual versus face-to-face clinical simulation in relation to student knowledge, anxiety, and self-confidence in maternal-newborn nursing: A randomized controlled trial. Nurse Educ Today 45, 179–184 (2016).
20. Brown, W. & Tortorella, R. Hybrid medical simulation–a systematic literature review. Smart Learning Environments https://doi.org/10.1186/s40561-020-00127-6 (2020) doi:10.1186/s40561-020-00127-6.
21. Fegran, L. et al. Simulation debriefing as part of simulation for clinical teaching and learning in nursing education: A scoping review. Nurs Open 10, 1217–1233 (2022).
