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Autor/inn/enPeralta, Yadira; Moreno, Mario; Harwell, Michael; Guzey, S. Selcen; Moore, Tamara J.
TitelGoing beyond the Mean: Using Variances to Enhance Understanding of the Impact of Educational Interventions for Multilevel Models
QuelleIn: Educational Research Quarterly, 41 (2018) 3, S.39-71 (33 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0196-5042
SchlagwörterEducational Research; Hierarchical Linear Modeling; Engineering; Design; STEM Education; Science Curriculum; Academic Achievement; Equations (Mathematics); Statistical Analysis; Achievement Gap; Evaluation Methods; Predictor Variables
AbstractVariance heterogeneity is a common feature of educational data when treatment differences expressed through means are present, and often reflects a treatment by subject interaction with respect to an outcome variable. Identifying variables that account for this interaction can enhance understanding of whom a treatment does and does not benefit in ways that can inform and improve the treatment. Even in the absence of a treatment effect expressed through means studying variance heterogeneity offers insight into a treatment by identifying subject characteristics related to heterogeneity. This study illustrates four methods of modeling variance heterogeneity for data from a study of the impact of an engineering design-based STEM curriculum on student achievement with a focus on multilevel models. (As Provided).
AnmerkungenBehavioral Research Press. Grambling State University, Math Department, P.O. Box 1191, Grambling, LA 71245. Tel: 318-274-2425; Web site: http://erquarterly.org/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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