Abstract
The high-fidelity simulation is a teaching method based on the use of technologically enhanced manikins that faithfully reproduce real clinical conditions allowing students to learn by doing clinical activities in a controlled and safe learning environment. Currently, there is evidence that single exposures to high-fidelity simulation can improve the learning outcomes of undergraduate nursing students. However, as regard the postgraduate critical care nursing courses, there is a paucity of evidence related to the effects of high-fidelity simulation on students’ learning outcomes and about its best application modality to guarantee acceptable learning gains and their retention over time. Therefore, the aim of this study was to explore any difference in learning outcomes of nurses enrolled in an intensive care nursing course exposed to three different teaching models based on high-fidelity simulation. A retrospective comparative analysis was conducted merging and analyzing datasets related to three homogeneous cohorts of students participating in previous research experiences at the University of L’Aquila. Multiple exposures to high-fidelity simulation guaranteed better levels of satisfaction, self-confidence, self-efficacy, and performance than those achieved participating to traditional high-fidelity simulation experiences. However, multiple exposures characterized by longer duration produced better performance levels. Educational models based on multiple exposure to high-fidelity simulation can be considered potential teaching tools to complement the traditional education in postgraduate critical care nursing courses. Further experimental studies are needed to confirm the effectiveness of multiple exposure to high-fidelity simulation on learning outcomes.
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Marcotullio, A. et al. (2023). A Comparative Analysis of High-Fidelity Simulation Models Utilized in an Intensive Critical Care Nursing Course. In: Kubincová, Z., Melonio, A., Durães, D., Rua Carneiro, D., Rizvi, M., Lancia, L. (eds) Methodologies and Intelligent Systems for Technology Enhanced Learning, Workshops, 12th International Conference. MIS4TEL 2022. Lecture Notes in Networks and Systems, vol 538. Springer, Cham. https://doi.org/10.1007/978-3-031-20257-5_15
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