Addressing Diversity and Inclusion through Group Comparisons: A Primer on Measurement Invariance Testing

Autor/inn/en	Rocabado, Guizella A.; Komperda, Regis; Lewis, Jennifer E.; Barbera, Jack
Titel	Addressing Diversity and Inclusion through Group Comparisons: A Primer on Measurement Invariance Testing
Quelle	In: Chemistry Education Research and Practice, 21 (2020) 3, S.969-988 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Komperda, Regis) ORCID (Lewis, Jennifer E.) ORCID (Barbera, Jack)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1756-1108
DOI	10.1039/d0rp00025f
Schlagwörter	Chemistry; Science Education; Inclusion; Equal Education; Student Diversity; Critical Theory; Race; Disproportionate Representation; Measurement Techniques; Computer Software; Statistical Analysis; Visual Aids; Data; Error of Measurement + Suchen Sie Ihr Suchwort? Chemie; Naturwissenschaftliche Bildung; Inklusion; Kritische Theorie; Rasse; Abstammung; Messtechnik; Statistische Analyse; Anschauungsmaterial; Daten; Messfehler
Abstract	As the field of chemistry education moves toward greater inclusion and increased participation by underrepresented minorities, standards for investigating the differential impacts and outcomes of learning environments have to be considered. While quantitative methods may not be capable of generating the in-depth nuances of qualitative methods, they can provide meaningful insights when applied at the group level. Thus, when we conduct quantitative studies in which we aim to learn about the similarities or differences of groups within the same learning environment, we must raise our standards of measurement and safeguard against threats to the validity of inferences that might favor one group over another. One way to provide evidence that group comparisons are supported in a quantitative study is by conducting measurement invariance testing. In this manuscript, we explain the basic concepts of measurement invariance testing within a confirmatory factor analysis framework with examples and a step-by-step tutorial. Each of these steps is an opportunity to safeguard against interpretation of group differences that may be artifacts of the assessment instrument functioning rather than true differences between groups. Reflecting on and safeguarding against threats to the validity of the inferences we can draw from group comparisons will aid in providing more accurate information that can be used to transform our chemistry classrooms into more socially inclusive environments. To catalyze this effort, we provide code in the ESI for two different software packages (R and Mplus) so that interested readers can learn to use these methods with the simulated data provided and then apply the methods to their own data. Finally, we present implications and a summary table for researchers, practitioners, journal editors, and reviewers as a reference when conducting, reading, or reviewing quantitative studies in which group comparisons are performed. (As Provided).
Anmerkungen	Royal Society of Chemistry. Thomas Graham House, Science Park, Milton Road, Cambridge, CB4 0WF, UK. Tel: +44-1223 420066; Fax: +44-1223 423623; e-mail: cerp@rsc.org; Web site: http://www.rsc.org/cerp
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01