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We investigate the determinants of high school completion and college attendance, the likelihood of taking science, technology, engineering or math (STEM) courses in the first year of college and the probability of earning a degree in a STEM field. The focus is on women, who tend to be under-represented in STEM fields. Tracking four cohorts of students throughout Florida, women perform nearly as well as men on math achievement tests through high school and are more likely to finish high school and attend college than males. Among college students, however, women are less likely than are men to take courses in the physical sciences in their first year and are less likely to earn a degree in physics or engineering, even after adjusting for pre-college test scores. Gender matching of students and math/science teachers in middle and high school tends to increase the likelihood that female college freshman will take at least one STEM course. However, conditional on first-year coursework, neither gender matching at the secondary or college levels appears to have any effect on the likelihood of completing a major in a STEM field. For all students, having high school math and physics teachers with a degree in math or physics, respectively, (as opposed to education) is associated with a higher likelihood of taking STEM courses as college freshmen.
We demonstrate that heat inhibits learning and that school air-conditioning may mitigate this effect. Student fixed effects models using 10 million PSAT-retakers show hotter school days in years before the test reduce scores, with extreme heat being particularly damaging. Weekend and summer temperature has little impact, suggesting heat directly disrupts learning time. New nationwide, school-level measures of air-conditioning penetration suggest patterns consistent with such infrastructure largely offsetting heat’s effects. Without air-conditioning, a 1°F hotter school year reduces that year’s learning by one percent. Hot school days disproportionately impact minority students, accounting for roughly five percent of the racial achievement gap.
Teachers’ impact on student long-run success is only partially explained by their contributions to students’ short-run academic performance. For this study, we explore a second dimension of teacher effectiveness by creating measures of teachers’ contributions to student class-attendance. We find systematic variation in teacher effectiveness at reducing unexcused class absences at the middle and high school level. These differences across teachers are as stable as those for student achievement, but teacher effectiveness on attendance only weakly correlates with their effects on achievement. We link these measures of teacher effectiveness to students’ long-run outcomes. A high value-added to attendance teacher has a stronger impact on students’ likelihood of finishing high school than does a high value-added to achievement teacher. Moreover, high value-added to attendance teachers can motivate students to pursue higher academic goals as measured by Advanced Placement course taking. These positive effects are particularly salient for low-achieving and low-attendance students.
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.