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An overview of realist evaluation for simulation-based education
This article describes the key features of realist (realistic) evaluation and illustrates their application using, as an example, a simulation-based course for final year medical students. The use of simulation-based education (SBE) is increasing and so too is the evidence supporting its value as a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050705/ https://www.ncbi.nlm.nih.gov/pubmed/30026966 http://dx.doi.org/10.1186/s41077-018-0073-6 |
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author | Graham, Alastair C McAleer, Sean |
author_facet | Graham, Alastair C McAleer, Sean |
author_sort | Graham, Alastair C |
collection | PubMed |
description | This article describes the key features of realist (realistic) evaluation and illustrates their application using, as an example, a simulation-based course for final year medical students. The use of simulation-based education (SBE) is increasing and so too is the evidence supporting its value as a powerful technique which can lead to substantial educational benefits. Accompanying these changes is a call for research into its use to be more theory-driven and to investigate both ‘Did it work?’ and as importantly ‘Why did it work (or not)?’ An evaluation methodology that is capable of answering both questions is realist evaluation. Realist evaluation is an emerging methodology that is suited to evaluating complex interventions such as SBE. The realist philosophy positions itself between positivist and constructivist paradigms and seeks to answer the question ‘What works for whom, in what circumstances and why?’ In seeking to answer this question, realist evaluation sets out to identify three fundamental components of an intervention, namely context, mechanism and outcome. Educational programmes work (successful outcomes) when theory-driven interventions (mechanisms) are applied to groups under appropriate conditions (context). Realist research uses a mixed methods (qualitative and quantitative) approach to gathering data in order to test the proposed context-mechanism-outcome (CMO) configurations of the intervention under investigation. Realist evaluation offers a valuable methodology for researchers investigating interventions utilising simulation-based education. By investigating and understanding the context, mechanisms and outcomes of SBE interventions, realist evaluation can provide the deeper level of understanding being called for. |
format | Online Article Text |
id | pubmed-6050705 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60507052018-07-19 An overview of realist evaluation for simulation-based education Graham, Alastair C McAleer, Sean Adv Simul (Lond) Innovation This article describes the key features of realist (realistic) evaluation and illustrates their application using, as an example, a simulation-based course for final year medical students. The use of simulation-based education (SBE) is increasing and so too is the evidence supporting its value as a powerful technique which can lead to substantial educational benefits. Accompanying these changes is a call for research into its use to be more theory-driven and to investigate both ‘Did it work?’ and as importantly ‘Why did it work (or not)?’ An evaluation methodology that is capable of answering both questions is realist evaluation. Realist evaluation is an emerging methodology that is suited to evaluating complex interventions such as SBE. The realist philosophy positions itself between positivist and constructivist paradigms and seeks to answer the question ‘What works for whom, in what circumstances and why?’ In seeking to answer this question, realist evaluation sets out to identify three fundamental components of an intervention, namely context, mechanism and outcome. Educational programmes work (successful outcomes) when theory-driven interventions (mechanisms) are applied to groups under appropriate conditions (context). Realist research uses a mixed methods (qualitative and quantitative) approach to gathering data in order to test the proposed context-mechanism-outcome (CMO) configurations of the intervention under investigation. Realist evaluation offers a valuable methodology for researchers investigating interventions utilising simulation-based education. By investigating and understanding the context, mechanisms and outcomes of SBE interventions, realist evaluation can provide the deeper level of understanding being called for. BioMed Central 2018-07-17 /pmc/articles/PMC6050705/ /pubmed/30026966 http://dx.doi.org/10.1186/s41077-018-0073-6 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Innovation Graham, Alastair C McAleer, Sean An overview of realist evaluation for simulation-based education |
title | An overview of realist evaluation for simulation-based education |
title_full | An overview of realist evaluation for simulation-based education |
title_fullStr | An overview of realist evaluation for simulation-based education |
title_full_unstemmed | An overview of realist evaluation for simulation-based education |
title_short | An overview of realist evaluation for simulation-based education |
title_sort | overview of realist evaluation for simulation-based education |
topic | Innovation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050705/ https://www.ncbi.nlm.nih.gov/pubmed/30026966 http://dx.doi.org/10.1186/s41077-018-0073-6 |
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