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One Size Doesn’t Fit All: Using Factor Analysis to Gather Validity Evidence When Using Surveys in Your Research
Umeå University, Faculty of Science and Technology, Department of Science and Mathematics Education. Department of Biological Sciences, Florida International University, Miami, FL 33199.ORCID iD: 0000-0002-1861-6589
Department of Educational Psychology, University of Texas at Austin, Austin, TX 78712; National Board of Medical Examiners, Philadelphia, PA 19104.
Department of Biological Sciences, Florida International University, Miami, FL 33199.
2019 (English)In: CBE - Life Sciences Education, ISSN 1931-7913, E-ISSN 1931-7913, Vol. 18, no 1, p. 1-17, article id rm1Article in journal (Refereed) Published
Abstract [en]

Across all sciences, the quality of measurements is important. Survey measurements are only appropriate for use when researchers have validity evidence within their particular context. Yet, this step is frequently skipped or is not reported in educational research. This article briefly reviews the aspects of validity that researchers should consider when using surveys. It then focuses on factor analysis, a statistical method that can be used to collect an important type of validity evidence. Factor analysis helps researchers explore or confirm the relationships between survey items and identify the total number of dimensions represented on the survey. The essential steps to conduct and interpret a factor analysis are described. This use of factor analysis is illustrated throughout by a validation of Diek- man and colleagues’ goal endorsement instrument for use with first-year undergraduate science, technology, engineering, and mathematics students. We provide example data, annotated code, and output for analyses in R, an open-source programming language and software environment for statistical computing. For education researchers using surveys, understanding the theoretical and statistical underpinnings of survey validity is fundamental for implementing rigorous education research.

Place, publisher, year, edition, pages
2019. Vol. 18, no 1, p. 1-17, article id rm1
Keywords [en]
Factor analysis, validity, reliability, R, biology education, educational measurements, survey
National Category
Educational Sciences
Research subject
didactics of educational measurement; didactics of natural science
Identifiers
URN: urn:nbn:se:umu:diva-157009DOI: 10.1187/cbe.18-04-0064ISI: 000465386400005PubMedID: 30821600OAI: oai:DiVA.org:umu-157009DiVA, id: diva2:1293494
Available from: 2019-03-05 Created: 2019-03-05 Last updated: 2019-05-28Bibliographically approved

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fulltext(692 kB)54 downloads
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Knekta, Eva

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