Use of a group concept mapping approach to define learning outcomes for an interdisciplinary module in medicine

Learning outcomes are typically developed using standard group-based consensus methods. Two main constraints with standard techniques such as the Delphi method or expert working group processes are: (1) the ability to generate a comprehensive set of outcomes and (2) the capacity to reach agreement o...

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Published in:Perspectives on medical education Vol. 3; no. 3; pp. 245 - 253
Main Authors: Stoyanov, Slavi, Spoelstra, Howard, Bennett, Deirdre, Sweeney, Catherine, Van Huffel, Sabine, Shorten, George, O’Flynn, Siun, Cantillon-Murphy, Padraig, O’Tuathaigh, Colm, Burgoyne, Louise
Format: Journal Article
Language:English
Published: Houten Bohn Stafleu van Loghum 01.06.2014
Ubiquity Press
Subjects:
Concept mapping
Data Analysis
Delphi Technique
Education
Educational objectives
Engineering Education
Group Dynamics
Interdisciplinary aspects
Medical Education
Multidimensional Scaling
Multivariate Analysis
Problem solving
Short Communication
Work Environment
Medicine
Group concept mapping
Interdisciplinary learning
ISSN:2212-2761, 2212-277X, 2212-277X
Online Access:Get full text
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Summary:Learning outcomes are typically developed using standard group-based consensus methods. Two main constraints with standard techniques such as the Delphi method or expert working group processes are: (1) the ability to generate a comprehensive set of outcomes and (2) the capacity to reach agreement on them. We describe the first application of Group Concept Mapping (GCM) to the development of learning outcomes for an interdisciplinary module in medicine and engineering. The biomedical design module facilitates undergraduate participation in clinician-mentored team-based projects that prepare students for a multidisciplinary work environment. GCM attempts to mitigate the weaknesses of other consensus methods by excluding pre-determined classification schemes and inter-coder discussion, and by requiring just one round of data structuring. Academic members from medicine and engineering schools at three EU higher education institutions participated in this study. Data analysis, which included multidimensional scaling and hierarchical cluster analysis, identified two main categories of outcomes: technical skills (new advancement in design process with special attention to users, commercialization and standardization) and transversal skills such as working effectively in teams and creative problem solving. The study emphasizes the need to address the highest order of learning taxonomy (analysis, synthesis, problem solving, creativity) when defining learning outcomes.
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ISSN:2212-2761
2212-277X
2212-277X
DOI:10.1007/s40037-013-0095-7