Measuring student ability, classifying schools, and detecting item bias at school level, based on student-level dichotomous items

Margot Bennink, Marcel A. Croon, Jos Keuning, Jeroen K. Vermunt

Research output: Contribution to journalArticleScientificpeer-review

Abstract

In educational measurement, responses of students on items are used not only to measure the ability of students, but also to evaluate and compare the performance of schools. Analysis should ideally account for the multilevel structure of the data, and school-level processes not related to ability, such as working climate and administration conditions, need to be separated from student and school ability. However, in educational studies such as Programme for International Student Assessment, Trends in International Mathematics and Science Study, and COOL5–18, this is hardly ever done. This study presents a model that simultaneously accounts for the nested structure, controls student ability for processes at school level, classifies schools to monitor and compare schools, and tests for school-level item bias.
Original languageEnglish
Pages (from-to)180-202
JournalJournal of Educational and Behavioral Statistics
Volume39
Issue number3
DOIs
Publication statusPublished - Jun 2014

Keywords

  • dichotomous items
  • educational tests
  • item bias
  • latent variable framework
  • multilevel analysis
  • school-level processes

Cite this

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title = "Measuring student ability, classifying schools, and detecting item bias at school level, based on student-level dichotomous items",
abstract = "In educational measurement, responses of students on items are used not only to measure the ability of students, but also to evaluate and compare the performance of schools. Analysis should ideally account for the multilevel structure of the data, and school-level processes not related to ability, such as working climate and administration conditions, need to be separated from student and school ability. However, in educational studies such as Programme for International Student Assessment, Trends in International Mathematics and Science Study, and COOL5–18, this is hardly ever done. This study presents a model that simultaneously accounts for the nested structure, controls student ability for processes at school level, classifies schools to monitor and compare schools, and tests for school-level item bias.",
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Measuring student ability, classifying schools, and detecting item bias at school level, based on student-level dichotomous items. / Bennink, Margot; Croon, Marcel A.; Keuning, Jos; Vermunt, Jeroen K.

In: Journal of Educational and Behavioral Statistics, Vol. 39, No. 3, 06.2014, p. 180-202.

Research output: Contribution to journalArticleScientificpeer-review

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