Literature DB >> 30140098

Retrofitting Diagnostic Classification Models to Responses From IRT-Based Assessment Forms.

Ren Liu1, Anne Corinne Huggins-Manley1, Okan Bulut2.   

Abstract

Developing a diagnostic tool within the diagnostic measurement framework is the optimal approach to obtain multidimensional and classification-based feedback on examinees. However, end users may seek to obtain diagnostic feedback from existing item responses to assessments that have been designed under either the classical test theory or item response theory frameworks. Retrofitting diagnostic classification models to existing assessments designed under other psychometric frameworks could be a plausible approach to obtain more actionable scores or understand more about the constructs themselves. This study (a) discusses the possibility and problems of retrofitting, (b) proposes a step-by-step retrofitting framework, and (c) explores the information one can gain from retrofitting through an empirical application example. While retrofitting may not always be an ideal approach to diagnostic measurement, this article aims to invite discussions through presenting the possibility, challenges, process, and product of retrofitting.

Keywords:  diagnostic classification modeling; diagnostic measurement; dimensionality; item response theory; retrofit; test development

Year:  2017        PMID: 30140098      PMCID: PMC6096460          DOI: 10.1177/0013164416685599

Source DB:  PubMed          Journal:  Educ Psychol Meas        ISSN: 0013-1644            Impact factor:   2.821


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8.  The Effects of Q-Matrix Design on Classification Accuracy in the Log-Linear Cognitive Diagnosis Model.

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9.  On the Relationship Between Classical Test Theory and Item Response Theory: From One to the Other and Back.

Authors:  Tenko Raykov; George A Marcoulides
Journal:  Educ Psychol Meas       Date:  2015-04-01       Impact factor: 2.821

10.  A multicomponent latent trait model for diagnosis.

Authors:  Susan E Embretson; Xiangdong Yang
Journal:  Psychometrika       Date:  2012-12-06       Impact factor: 2.500

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