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The primary goal of job training programs is to improve employment and earning outcomes of participants. However, effective job training programs may have potential secondary benefits, including in the form of reduced arrests. In this paper, we evaluate the impact of a job training program in New Orleans that was implemented using a randomized controlled trial design. We find that among those who had a prior criminal record, those assigned to the treatment group were two-fifths as likely to get arrested as those assigned to the control group at any time point after randomization. We explore several potential mechanisms for why this effect occurs and find suggestive evidence that the training program’s impact on wages, as well as peer effects from other trainees, can partially explain this effect.
In very low-income settings, how much does family demand matter for child learning? In rural Gambia, caregivers with high aspirations for their children’s future education and career, measured before children start school, invest substantially more than other families in their children’s education. Despite this, essentially no children are literate or numerate three years later. In contrast, in villages receiving a highly impactful, teacher-focused supply-side intervention, children of high-aspirations caregivers are 25 percent more likely to achieve literacy and numeracy than other children. In such settings, greater demand can map onto developmentally meaningful learning differences, but only with adequate complementary inputs.
The 2020-2021 academic year was a trying year for teachers. We use a nationally representative sample of teachers from the RAND American Teacher Panel to document that teachers’ stated consideration of leaving the profession increased during the pandemic. We also study factors associated with teachers’ consideration of leaving the profession and high levels of job burnout during the pandemic. Approaching retirement age (being 55 or older), having to change instruction modes, health concerns, and high levels of job burnout all appear to be important predictors of the probability of considering leaving or retiring from teaching. Hybrid teaching increased consideration of leaving the profession because of COVID. Health concerns and switching instruction modes are all associated with higher levels of concern about job burnout. Interestingly, those approaching retirement ages do not present higher levels of concern about job burnout than younger teachers. Although increased consideration of leaving and concern about burnout do not yet appear to have materialized into higher attrition rates so far, higher levels of job dissatisfaction could affect teacher effectiveness and could harm student academic progress.
In this paper, I study the effect of winning the public school choice lottery on public school enrollment. In particular, I look at how different outside options affect how sensitive students are to receiving their first choice in the public school lottery, focusing on three measures of outside options: ability to afford private schools, geographic convenience of private schools, and zoned-school quality. Using rich administrative data from applications submitted through a centralized enrollment system in Tulsa Public Schools (TPS), I find that overall, students who do not get assigned to their top choice school in a public school choice program are 15 percentage points more likely to leave the public school system entirely than those who do get an offer at their top choice. This effect is driven by higher-income students: these students, who are more likely to be able to afford private schools, are 33 percentage points more likely to leave the public school system if they do not get an offer at the public school they rank first than those who do get a spot. Geographic convenience of private schools and zoned-school quality do not differentially affect students’ enrollment decisions once they receive a school assignment. These effects are important to understand as districts undergo efforts to increase participation in school choice programs, while seeking to maintain district enrollment. They also provide useful insights about how attrition may affect estimates of the impact of choice schools on student outcomes.
In this paper, we show that the election of a new school board member causes home values in their neighborhood to rise. This increase is identified using narrowly-decided contests and is driven by non-Democratic members, whose neighborhoods appreciate about 4% on average relative to those of losing candidates. We find that student test scores in the neighborhood public schools of non-Democratic winners also relatively increase, but this effect is driven by changing student composition, including via the manipulation of attendance zones, rather than improvements in school quality (as measured by test score value-added). Notably, we detect no differential changes when comparing neighborhood or scholastic outcomes between winning and losing Democratic school board candidates. These results suggest that partisan affiliation is correlated with private motivations for seeking public office.
Many studies rely on public sector employees’ reported career intentions instead of measuring actual turnover, but research does not clearly document how these variables relate to one another. We develop and test three ways in which measures of employee intentions and turnover might relate to one another: (a) intention may measure the same underlying construct as turnover; (b) intention may be distinct from but strongly related to turnover; or (c) intentions may be distinct from turnover. Using nationally representative data on 102,970 public school teachers, we conduct a descriptive and regression analysis to probe how teachers’ turnover intentions are and are not associated with attrition. While there is some variation across measures of intent, we find evidence most consistent with the second scenario; intention is distinct from, but strongly related to, turnover. We offer recommendations for how researchers should use public sector employee intentions in research.
An important subgroup of English learner-classified (EL) students immigrate to the U.S., entering U.S. schools upon their arrival. Using growth models and statewide data, this study asks first, how newcomers’ English proficiency status and growth compare to those of non-newcomer EL students; and second, what characteristics are associated with differences in English language growth patterns among newcomers. We find that newcomers enter school at earlier stages of English proficiency compared to their non-newcomer peers, but grow faster, especially in their first two years. We also find variation in growth patterns suggestive that schools play an important role in fostering growth.
The COVID-19 pandemic initially resulted in an unanticipated and near-universal shift from in-person to virtual instruction in spring 2020. During the 2020-21 school year, schools began to re-open and families were faced with decisions regarding the instructional mode for their children. We leverage administrative, survey, and virtual-learning data to examine the determinants of family learning-mode choice and the effects of virtual education on student engagement and academic achievement. Family preference for virtual (versus face-to-face) instruction was most highly associated with school-level infection rates and appeared relatively uniform within schools. We find that students who were assigned a higher proportion of instructional days in virtual mode experienced higher rates of attendance, but also negative student achievement growth compared to students who were assigned a higher proportion of instructional days in face-to-face mode. Students belonging to marginalized groups experienced more positive associations with attendance but were also more likely to experience lower student achievement growth when assigned a greater proportion of instructional days in virtual mode. Insights from this study can be used to better understand family preference as well as to target and refine virtual learning in a post-COVID-19 society.
Educators must balance the needs of students who start the school year behind grade level with their obligation to teach grade-appropriate content to all students. Educational software could help educators strike this balance by targeting content to students’ differing levels of mastery. Using a regression discontinuity design and detailed software log and administrative data, we compare two versions of an online mathematics program used by students in three education agencies. We find that although students assigned the modified curriculum did progress through content objectives more quickly than students assigned the default curriculum, they did not perform better on pre- and post-objective quizzes embedded in the software, and most never progressed far enough to reach the grade-level content. Furthermore, there was no statistically significant effect of the modified curriculum on formative test scores. These findings suggest policymakers and practitioners should exercise caution when assigning exclusively remedial content to students who start the school year behind grade level, even though this is a common feature of many math educational software programs.
A growing body of research shows that students benefit when they are demographically similar to their teachers. However, less is known about how matching affects social-emotional development. We investigate the effect of teacher-student race and gender matching for middle school students in six charter management organizations. Using a student fixed effects strategy exploiting changes over time in the proportion of demographic matching in a school-grade, we estimate matching’s effect on self-reports of interpersonal and intrapersonal social-emotional skills, test scores, and behavioral outcomes. We find improvements for Black and female students in interpersonal self-management and grit when they are matched to demographically similar teachers. We also find demographic matching leads to reductions in absences for Black students and improved math test scores for females. Our findings add to the emerging teacher diversity literature by showing its benefits for Black and female students during a critical stage of social-emotional development in their lives.