Journal article
Contemporary approaches to psychometrics: item response theory and diagnostic classification models / Enfoques contemporáneos sobre psicometría: los modelos de la teoría de respuesta al ítem y los modelos de clasificación de diagnósticos
Cultura y Educación: Analytic Strategies in Education/ Estrategias de análisis avanzadas en educación, Vol.29(3), pp.461-491
07/03/2017
DOI: 10.1080/11356405.2017.1367171
Abstract
Evaluating test scores is an essential process, critical in both educational research and practice. To scientifically understand and utilize test scores, educators and researchers need to choose appropriate psychometric models to analyse and interpret assessment data. In this paper, we discuss two classes of psychometric models that have been widely used in educational measurement: item response theory (IRT) models and diagnostic classification models (DCMs). Specifically, the IRT discussion focuses on producing scores on a numerical continuum using the two-parameter logistic model. We then discuss methods for producing scores based on ordinal classifications with DCMs and compare and contrast such scores with those from IRT models. In addition, through step-by-step examples, we demonstrate how to obtain estimates from and interpret results from each model we present. We conclude the paper with considerations in and suggestions for choosing an appropriate psychometric model.
Details
- Title: Subtitle
- Contemporary approaches to psychometrics: item response theory and diagnostic classification models / Enfoques contemporáneos sobre psicometría: los modelos de la teoría de respuesta al ítem y los modelos de clasificación de diagnósticos
- Creators
- Bo Hu - University of KansasLu Qin - University of KansasMeghan Sullivan - University of KansasJonathan Templin - University of Kansas
- Resource Type
- Journal article
- Publication Details
- Cultura y Educación: Analytic Strategies in Education/ Estrategias de análisis avanzadas en educación, Vol.29(3), pp.461-491
- Publisher
- Routledge
- DOI
- 10.1080/11356405.2017.1367171
- ISSN
- 1135-6405
- eISSN
- 1578-4118
- Language
- English
- Date published
- 07/03/2017
- Academic Unit
- Psychological and Quantitative Foundations
- Record Identifier
- 9983993490602771
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