Cognitive diagnostic modelling in healthcare professions education: an eye-opener

Carlos Collares*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Criticisms about psychometric paradigms currently used in healthcare professions education include claims of reductionism, objectification, and poor compliance with assumptions. Nevertheless, perhaps the most crucial criticism comes from learners' difficulty in interpreting and making meaningful use of summative scores and the potentially detrimental impact these scores have on learners. The term "post-psychometric era" has become popular, despite persisting calls for the sensible use of modern psychometrics. In recent years, cognitive diagnostic modelling has emerged as a new psychometric paradigm capable of providing meaningful diagnostic feedback. Cognitive diagnostic modelling allows the classification of examinees in multiple cognitive attributes. This measurement is obtained by modelling these attributes as categorical, discrete latent variables. Furthermore, items can reflect more than one latent variable simultaneously. The interactions between latent variables can be modelled with flexibility, allowing a unique perspective on complex cognitive processes. These characteristic features of cognitive diagnostic modelling enable diagnostic classification over a large number of constructs of interest, preventing the necessity of providing numerical scores as feedback to test takers. This paper provides an overview of cognitive diagnostic modelling, including an introduction to its foundations and illustrating potential applications, to help teachers be involved in developing and evaluating assessment tools used in healthcare professions education. Cognitive diagnosis may represent a revolutionary new psychometric paradigm, overcoming the known limitations found in frequently used psychometric approaches, offering the possibility of robust qualitative feedback and better alignment with competency-based curricula and modern programmatic assessment frameworks.

Original languageEnglish
Pages (from-to)427-440
Number of pages14
JournalAdvances in Health Sciences Education
Issue number2
Early online date24 Feb 2022
Publication statusPublished - May 2022

JEL classifications

  • i23 - Higher Education and Research Institutions


  • Assessment
  • Clinical reasoning
  • Cognitive diagnostic modelling
  • Patient safety
  • Psychometrics
  • Standard setting


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