Strategies for Improving Power in School-Randomized Studies of Professional Development

Autor/inn/en	Kelcey, Ben; Phelps, Geoffrey
Titel	Strategies for Improving Power in School-Randomized Studies of Professional Development
Quelle	In: Evaluation Review, 37 (2013) 6, S.520-554 (35 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0193-841X
DOI	10.1177/0193841X14528906
Schlagwörter	Statistical Analysis; Research Design; Faculty Development; Sample Size; Hierarchical Linear Modeling; Teachers; Teacher Characteristics; Mathematics; Pretests Posttests; Effect Size; Teacher Certification; Elementary School Mathematics; Number Concepts; Algebra; Geometry; Middle Schools; Grade 4; Grade 5; Grade 6; Grade 7; Grade 8 + Suchen Sie Ihr Suchwort? Statistische Analyse; Forschungsdesign; Lehrer; Lehrerin; Lehrende; Mathematik; Elementare Mathematik; Schulmathematik; Number concept; Zahlbegriff; Geometrie; Middle school; Mittelschule; Mittelstufenschule; School year 04; 4. Schuljahr; Schuljahr 04; School year 05; 5. Schuljahr; Schuljahr 05; School year 06; 6. Schuljahr; Schuljahr 06; School year 07; 7. Schuljahr; Schuljahr 07; School year 08; 8. Schuljahr; Schuljahr 08
Abstract	Objectives: Group-randomized designs are well suited for studies of professional development because they can accommodate programs that are delivered to intact groups (e.g., schools), the collaborative nature of professional development, and extant teacher/school assignments. Though group designs may be theoretically favorable, prior evidence has suggested that they may be challenging to conduct in professional development studies because well-powered designs will typically require large sample sizes or expect large effect sizes. Using teacher knowledge outcomes in mathematics, we investigated when and the extent to which there is evidence that covariance adjustment on a pretest, teacher certification, or demographic covariates can reduce the sample size necessary to achieve reasonable power. Method: Our analyses drew on multilevel models and outcomes in five different content areas for over 4,000 teachers and 2,000 schools. Using these estimates, we assessed the minimum detectable effect sizes for several school-randomized designs with and without covariance adjustment. Results: The analyses suggested that teachers' knowledge is substantially clustered within schools in each of the five content areas and that covariance adjustment for a pretest or, to a lesser extent, teacher certification, has the potential to transform designs that are unreasonably large for professional development studies into viable studies. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10