TEACHER EFFECTS ON HIGH SCHOOLACADEMIC ACHIEVEMENT SCORES: A CASE STUDY OF BUSIA COUNTY, KENYA

ABSTRACT This study sought to analyze teacher effects on high school academic achievement scores in Busia County, Kenya. The study was based on the education production function theory. A descriptive survey research design was employed. A sample of 236 teachers and 755 students was used. Self administered questionnaires were used to collect data and test re-test was used to ascertain reliability of the instrument. Descriptive statistics namely; percentages, frequencies, mean, and standard deviations were used to carry out preliminary data analysis. Inferential statistics specifically correlation and regression coefficients were then used to test hypotheses. Hierarchical linear modeling was used to model effect of selected teacher variables on school academic achievement scores. Findings of the study were presented in tables and figures. Findings of the study suggested that the number of teachers, teacher commitment and teachers covering missed lessons had statistically significant effects on school academic achievement scores. Key words: Teacher Variables, Academic Achievement Scores, Kenya

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

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 R2) 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.