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More than half of U.S. children fail to meet proficiency standards in mathematics and science in fourth grade. Teacher professional development and curriculum improvement are two of the primary levers that school leaders and policymakers use to improve children’s science, technology, engineering and mathematics (STEM) learning, yet until recently, the evidence base for understanding their effectiveness was relatively thin. In recent years, a wealth of rigorous new studies using experimental designs have investigated whether and how STEM instructional improvement programs work. This article highlights contemporary research on how to improve classroom instruction and subsequent student learning in STEM. Instructional improvement programs that feature curriculum integration, teacher collaboration, content knowledge, pedagogical content knowledge, and how students learn all link to stronger student achievement outcomes. We discuss implications for policy and practice.
Despite substantial evidence that resources and outcomes are transmitted across generations, there has been limited inquiry into the extent to which anti-poverty programs actually disrupt the cycle of bad outcomes. We explore how the effects of the United States’ largest early childhood program, Head Start, transfer across generations. We leverage the rollout of this federally funded, means-tested preschool program to estimate the effect of early childhood exposure among mothers on their children’s long-term outcomes. We find evidence of intergenerational transmission of effects in the form of increased educational attainment, reduced teen pregnancy, and reduced criminal engagement in the second generation.
In an effort to reduce the STEM gender gap, policymakers often propose providing women with close mentoring by female scientists. This is based on the idea that female scientists might act as role models and counteract negative gender stereotypes that are pervasive in science fields. However, as of yet, there is still no clear evidence on the role of mentor or advisor gender in reducing the STEM gender gap. We use rich administrative data from a private 4-year college to provide some of the first causal evidence on the impact of advisor gender on women's STEM degree attainment. We exploit a unique setting where students are randomly assigned to academic advisors--who are also faculty members--in their freshman year of college. We find that being matched to a female rather than a male science advisor substantially narrows the gender gaps in STEM enrollment and graduation, with the strongest effects occurring among students who are highly skilled in math. In contrast, the gender of an advisor from a non-science department has no impact on students' major choice. Our results indicate that providing close mentoring or advising by female scientists can play an important role in promoting women's participation and persistence in STEM fields.
Existing research on self-management skills shows that measures of self-management predict student success. However, these conclusions are based on small samples or narrowly defined self-management measures. Using a rich longitudinal dataset of 221,840 fourth through seventh grade students, this paper describes self-management gaps across student groups, and confirms, at a large scale, the predictive power of self-management for achievement gains, even with unusually rich controls for students’ background, previous achievement, and measures of other social-emotional skills. Self-management is a better predictor of student learning than are other measures of socioemotional skills. Average growth in English language arts due to changing from a low to a high level of self-management is between 0.091 and 0.112 standard deviations, equivalent to almost 80 days of learning.
This paper reports improvements in teacher job performance, as measured by student test scores, resulting from a program of (zero-) low-stakes peer evaluation. Teachers working at the same school observed and scored each other’s teaching. Students in randomly-assigned treatment schools scored 0.07σ higher on math and English exams (0.09σ lower-bound on TOT). Within each treatment school, teachers were further randomly assigned to roles: observer and observee. Teachers in both roles improved, perhaps slightly more for observers. The typical treatment school completed 2-3 observations per observee teacher. Variation in observations was generated partly by randomly assigning a low and high (2*low) dose of suggested number of observations. Benefits were quite similar across dose conditions.
Using statewide data from Tennessee over more than a decade, this paper estimates the job performance returns to principal experience as measured by student, teacher, and principal outcomes. I find that principals improve substantially over time, evidenced by higher student achievement, higher ratings from supervisors, and lower rates of teacher turnover. However, improvement in student achievement as principals gain experience does not carry over when principals change schools. The returns to school-specific experience are largest for principals in high-poverty schools, highlighting the potential benefits of policies to improve the recruitment and retention of high-quality leaders in hard-to-staff environments.
Students’ level of academic skills at school entry are a strong predictor of later academic success, and focusing on improving these skills during the preschool years has been a priority during the past ten years. Evidence from two prior nationally representative studies indicated that incoming kindergarteners’ math and literacy skills were higher in 2010 than 1998, but no national studies have examined trends since 2010. This study examines academic skills at kindergarten entry from 2010 and 2017 using data from over 2 million kindergarten students. Results indicated kindergarteners in 2017 have slightly lower math and reading skills than in 2010, but that inequalities at school entry by race/ethnicity and school poverty level have decreased during this period.
How should teachers spend their STEM-focused professional learning time? To answer this question, we analyzed a recent wave of rigorous new studies of STEM instructional improvement programs. We found that programs work best when focused on building knowledge teachers can use during instruction: knowledge of the curriculum materials they will use, knowledge of content and how content can be represented for learners, and knowledge of how students learn that content. We argue that such learning opportunities improve teachers’ professional knowledge and skill, potentially by supporting teachers in making more informed in-the-moment instructional decisions.
Conceptualizing and measuring levels of segregation in higher education is difficult as both vertical and horizontal sorting is prevalent and patterns vary across racial groups. In this paper, we measure various trends in racial segregation in California for 20 years. We find that the most selective four-year campuses are the least segregated and that the community college sector is the most segregated. This fact has remained relatively stable over time. We also find that observed levels of Latinx-White segregation are lower than the hypothetical levels we would see if college choice were determined exclusively by geography. However, observed Asian-White segregation is higher than it would be if college attendance were determined exclusively by geography.
The sustaining environments hypothesis refers to the popular idea, stemming from theories in developmental, cognitive, and educational psychology, that the long-term success of early educational interventions is contingent on the quality of the subsequent learning environment. Several studies have investigated whether specific kindergarten classroom and other elementary school factors account for patterns of persistence and fadeout of early educational interventions. These analyses focus on the statistical interaction between an early educational intervention – usually whether the child attended preschool – and several measures of the quality of the subsequent educational environment. The key prediction of the sustaining environments hypothesis is a positive interaction between these two variables. To quantify the strength of the evidence for such effects, we meta-analyze existing studies that have attempted to estimate interactions between preschool and later educational quality in the United States. We then attempt to establish the consistency of the direction and a plausible range of estimates of the interaction between preschool attendance and subsequent educational quality by using a specification curve analysis in a large, nationally representative dataset that has been used in several recent studies of the sustaining environments hypothesis. The meta-analysis yields small positive interaction estimates ranging from approximately .00 to .04, depending on the specification. The specification curve analyses yield interaction estimates of approximately 0. Results suggest that the current mix of methods used to test the sustaining environments hypothesis cannot reliably detect realistically sized effects. Our recommendations are to combine large sample sizes with strong causal identification strategies, and to study combinations of interventions that have a strong probability of showing large main effects.