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Concept mapping internal validity: A case of misconceived mapping?

Normand Péladeau1, Christian Dagenais2, Valéry Ridde3

  • 1Provalis Research, 1255 Robert Bourassa Blvd Suite 1604, Montréal, QC H3B 3X3, Canada.

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|March 7, 2017
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Summary

This study proposes an improved statistical analysis for concept mapping, a program evaluation tool. Reversing the order of hierarchical cluster analysis and multidimensional scaling enhances map accuracy and interpretability.

Keywords:
Concept mappingEvaluation methodsHierarchical cluster analysisInternal validityMultidimensional scaling

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Area of Science:

  • Program evaluation
  • Qualitative and statistical analysis
  • Social sciences research methodology

Background:

  • Concept mapping, developed by William M. K. Trochim, is a widely used technique for program development and evaluation.
  • The technique integrates qualitative and statistical methods to identify and prioritize key components of a given reality.
  • Current statistical analysis in concept mapping may lead to suboptimal representations of participants' viewpoints.

Purpose of the Study:

  • To propose an alternative statistical analysis for concept mapping to improve utility and interpretability.
  • To address perceived methodological limitations in the current application of multidimensional scaling (MDS) and hierarchical cluster analysis (HCA).
  • To enhance the accuracy of concept maps as representations of participants' realities.

Main Methods:

  • Critique of the conventional statistical approach involving MDS followed by HCA on Euclidean distances.
  • Proposal of an alternative methodology: performing HCA first, followed by MDS.
  • Validation through logical arguments, expert opinions, statistical evidence, and a social validation experiment.

Main Results:

  • The proposed HCA-first approach is statistically superior to the conventional MDS-first method.
  • The alternative method yields more optimal and interpretable concept maps.
  • Social validation experiment supports the enhanced representational accuracy of the proposed technique.

Conclusions:

  • Reversing the order of HCA and MDS in concept mapping statistical analysis improves results.
  • The proposed methodological adjustment offers a more accurate and interpretable representation of participants' viewpoints.
  • This enhanced technique provides evaluators and program planners with a more valuable tool.