Improving Nursing Simulation Design to Support Learning Transfer to Clinical Settings: Metasynthesis

University essay from Malmö universitet/Centrum för akademiskt lärarskap (CAKL)

Abstract: Introduction  In contemporary higher education systems, interactive learning tool such as simulation, has been widely adopted in clinical studies as an effective learning tool to help students to gain both near and far transferable learning skills in a controlled setting, where parameters are defined, and an alternate reality generated. There is a dearth of knowledge on how simulation designers can support learners to transfer learning from simulation settings to clinical settings, by focusing on improving the design of simulation sessions.  Aim of the Study The aim of conducting this qualitative metasynthesis was to identify significant elements of simulation design that are necessary to support learning transfer to clinical settings.   Methodology A qualitative metasynthesis was adopted as a rigorous method to examine the findings of the original 15 qualitative studies to offer new interpretations and insights on the concept of learning transfer. Inductive thematic analysis was used to synthesize the data  Results  Six key findings we identified that include authentic setup, immersive learners’ role, learner’s cognitive boost, positive formative feedback, timing, and learner’s confidence. The findings represent elements of simulation design that can be improved by simulation session designers to support learning transfer from simulation to the clinical setting. Conclusion The result suggests that learning transfer from simulation sessions cannot be assumed to occur spontaneously in clinical settings but as a product of various factors. Therefore, the designers of simulation settings need to focus on replicating reality while provoking learners’ deeper thinking skills in the actual clinical setup, lay efforts in all aspects of the design to achieve higher levels of authenticity and transferability, consider incorporating observers actively and  eliminate categorization bias. This with a view to learners to transfer near and far learning from simulation settings to clinical settings. 

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