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We present results from a meta-analysis of 95 experimental and quasi-experimental preK-12 science, technology, engineering, and mathematics (STEM) professional development and curriculum programs, seeking to understand what content, activities and formats relate to stronger student outcomes. Across rigorously conducted studies, we found an average weighted impact estimate of +0.21 standard deviations. Programs saw stronger outcomes when they helped teachers learn to use curriculum materials; focused on improving teachers' content knowledge, pedagogical content knowledge and/or understanding of how students learn; incorporated summer workshops; and included teacher meetings to troubleshoot and discuss classroom implementation. We discuss implications for policy and practice.
Text-message based parenting programs have proven successful in improving parental engagement and preschoolers’ literacy development. The tested programs have provided a combination of (a) general information about important literacy skills, (b) actionable advice (i.e., specific examples of such activities), and (c) encouragement. The regularity of the texts – each week throughout the school year – also provided nudges to focus parents’ attention on their children. This study seeks to identify mechanisms of the overall effect of such programs. It investigates whether the actionable advice alone drives previous study’s results and whether additional texts of actionable advice improve program effectiveness. The findings provide evidence that text messaging programs can supply too little or too much information. A single text per week is not as effective at improving parenting practices as a set of three texts that also include information and encouragement, but a set of five texts with additional actionable advice is also not as effective as the three-text approach. The results on children’s literacy development depend strongly on the child’s pre-intervention literacy skills. For children in the lowest quarter of the pre-treatment literacy assessments, only providing one example of an activity decreases literacy scores by 0.15 standard deviations relative to the original intervention. Literacy scores of children in higher quarters are marginally higher with only one tip per week. We find no positive effects of increasing to five texts per week.
We use a natural experiment to evaluate sample selection correction methods' performance. In 2007, Michigan began requiring that all students take a college entrance exam, increasing the exam-taking rate from 64 to 99%. We apply different selection correction methods, using different sets of predictors, to the pre-policy exam score data. We then compare the corrected data to the complete post-policy exam score data as a benchmark. We find that performance is sensitive to the choice of predictors, but not the choice of selection correction method. Using stronger predictors such as lagged test scores yields more accurate results, but simple parametric methods and less restrictive semiparametric methods yield similar results for any set of predictors. We conclude that gains in this setting from less restrictive econometric methods are small relative to gains from richer data. This suggests that empirical researchers using selection correction methods should focus more on the predictive power of covariates than robustness across modeling choices.
School finance reforms caused some of the most dramatic increases in intergovernmental aid from states to local governments in U.S. history. We examine whether teachers’ unions affected the fraction of reform-induced state aid that passed through to local spending and the allocation of these funds. Districts with strong teachers’ unions increased spending nearly dollar-for-dollar with state aid, and spent the funds primarily on teacher compensation. Districts with weak unions used aid primarily for property tax relief, and spent remaining funds on hiring new teachers. The greater expenditure increases in strong union districts led to larger increases in student achievement.