Concepts and models from psychometrics

Robert Mislevy*, Maria Bolsinova

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterScientific

Abstract

The concepts and methods of psychometrics originated under trait and behavioral psychology, with relatively simple data, used mainly for purposes of prediction and selection. Ideas emerged over that nevertheless hold value for the new psychological perspectives, contexts of use, and forms of data and analytic tools we are now seeing. In this chapter we review some fundamental models and ideas from psychometrics that are be profitably reconceived, extended, and augmented in in the new world of assessment. Methods we address include classical test theory, generalizability theory, item response theory, latent class models, cognitive diagnosis models, factor analysis, hierarchical models, and Bayesian networks. Key concepts are these: (1) The essential nature of psychometric models (observations, constructs, latent variables, and probability-based reasoning). (2) The interplay of design and discovery in assessment. (3) Understanding the measurement issues of validity, reliability, comparability, generalizability, and fairness as social values that pertain even as forms of data, analysis, context, and purpose evolve.
Original languageEnglish
Title of host publicationComputational psychometrics
Subtitle of host publicationNew methodologies for a new generation of digital learning and assessment
EditorsA.A. von Davier, R.J. Mislevy, J. Hao
PublisherSpringer
Pages81-107
ISBN (Print)978-3-030-74394-9
DOIs
Publication statusPublished - 2021

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