Hostname: page-component-745bb68f8f-cphqk Total loading time: 0 Render date: 2025-01-07T22:05:45.975Z Has data issue: false hasContentIssue false
  • English
  • Français

A Review of “Sociocognitive Foundations of Educational Measurement” by Robert Mislevy

Published online by Cambridge University Press:  01 January 2025

Anthony Clairmont  and
Andrew Maul Open the ORCID record for Andrew Maul [Opens in a new window]
Anthony Clairmont
Affiliation:
University of California, Santa Barbara
Andrew Maul
Affiliation:
University of California, Santa Barbara
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Book Review
Information
Psychometrika , Volume 84 , Issue 4 , December 2019 , pp. 1097 - 1100
Copyright
Copyright © 2019 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Boring, E. G.. (1920). The logic of the normal law of error in mental measurement. American Journal of Psychology, 31 1– 33. CrossRefGoogle Scholar
Borsboom, D..(2006). The attack of the psychometricians. Psychometrika, 71 (3) 425– 440. CrossRefGoogle ScholarPubMed
Messick, S.Linn, R. L.(1989). Validity. Educational measurement, 3 New York: American Council on Education/Macmillian. 13– 103. Google Scholar
Michell, J.(2008). Is psychometrics pathological science?. Measurement: Interdisciplinary Research & Perspectives, 6 (1) 7– 24. Google Scholar
Mislevy, R. J..(2018). Sociocognitive foundations of educational measurement, New York: Routledge. CrossRefGoogle Scholar
Quine, W.V.O.. (1948). On what there is. The Review of Metaphysics, 2 (1) 21– 38. Google Scholar
Shepard, L. A..(1991). Psychometricians’ beliefs about learning. Educational Researcher, 20 (7) 2– 16. 10.3102/0013189X020007002 CrossRefGoogle Scholar
Taylor, C..(2005). The "weak ontology" thesis. Hedgehog Review, 7 (2) 35– 41. Google Scholar
Wilson, M..(2013). Seeking a balance between the statistical and scientific elements in psychometrics. Psychometrika, 78 (2) 211– 236. 10.1007/s11336-013-9327-3 CrossRefGoogle ScholarPubMed