Examining Design and Statistical Power for Planning Cluster Randomized Trials Aimed at Improving Student Science Achievement and Science Teacher Outcomes

Autor/inn/en	Zhang, Qi; Spybrook, Jessaca; Unlu, Fatih
Titel	Examining Design and Statistical Power for Planning Cluster Randomized Trials Aimed at Improving Student Science Achievement and Science Teacher Outcomes
Quelle	In: AERA Open, 6 (2020) 3, (12 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	Weitere Informationen
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2332-8584
Schlagwörter	Randomized Controlled Trials; Research Design; Statistical Analysis; Science Achievement; Faculty Development; Teacher Effectiveness; Science Teachers; Educational Research; Outcome Measures; Elementary School Students; Secondary School Students; Secondary School Teachers; Elementary School Teachers; Michigan; Wisconsin; Texas + Suchen Sie Ihr Suchwort? Forschungsdesign; Statistische Analyse; Effectiveness of teaching; Instructional effectiveness; Lehrerleistung; Unterrichtserfolg; Science; Teacher; Teachers; Science teacher; Wissenschaft; Lehrer; Lehrerin; Lehrende; Bildungsforschung; Pädagogische Forschung; Sekundarschüler; Elementary school; Grundschule; Volksschule
Abstract	With the increasing demand for evidence-based research on teacher effectiveness and improving student achievement, more impact studies are being conducted to examine the effectiveness of professional development (PD) interventions. Cluster randomized trials (CRTs) are often carried out to assess PD interventions that aim to improve both teacher and student outcomes. Due to the different design parameters (i.e., intraclass correlation and R[superscript 2]) and benchmark effect sizes associated with the student and teacher outcomes, two power analyses are necessary for planning CRTs that aim to detect both teacher and student effects in one study. These two power analyses are often conducted separately without considering how design choices to power the study to detect student effects may affect design choices to power the study to detect teacher effects and vice versa. In this study, we consider strategies to maximize the efficiency of the study design when both student and teacher effects are of primary interest. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01