The purpose of this study employing meta-analysis was to assess the impact that after-school programs have on reading and mathematics outcomes. The participants in the primary studies were students in Grades K through 8; years 200 through 2009. The study utilized the theory of change as its theoretical basis. This meta-analysis used the effect size as the standard measure. It began with an overall Cohen's d of .40 for the impact that after-school programs have on reading and mathematics outcomes, and then proceeded to analyze three moderator variables: subject, time periods, and grade level.The findings of the meta-analysis, both overall and sub analyses, show that the independent variable, after-school programs, has an impact on the dependent variable, reading and mathematics. The overall results indicated that after-school programs are educationally significant in the areas of reading and mathematics combined. As for the moderator variable, the results for the areas of (a) subject (reading and mathematics), (b) time period (2000-2002, 2003-2005 and 2006-2009), and (c) grade (middle, and middle plus elementary combined), all indicated educationally significant results. The notable exception was the grade moderator, elementary.This study provides more information for researchers, practitioners and policy makers upon which to make practical research based …

This study examined the impact of principals' data-driven decision-making practices on student achievement using the theoretical frame of Dervin's sense-making theory. This study is a quantitative cross-sectional research design where principals' perceptions about data were quantitatively captured at a single point in time. The participants for this study were 253 rural school principals currently serving in schools across Texas, and included both males and females across all ethnic groups, including white, African American, Hispanic, Asian, Native American and other. A developed survey instrument was administered to principals. The findings from the quantitative SEM analyses indicated that the Principal Uses Data to Improve Student Achievement latent variable (Factor 1) and the Principal and Staff Ability to Analyze Data to Improve Student Achievement latent variable (Factor 2) were significantly and positively associated with student achievement. Higher scores on these two latent variables were associated with better student achievement. There was no statistical association between the Principal Uses Data to Design Teacher Professional Development latent variable (Factor 3) and this target outcome. In total, the three latent variables accounted for 6% of the variance in student achievement (TAKS). When the campus level outcome was considered, no statistically significant associations between any of the …