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Despite considerable evidence on the links between average classroom quality and children’s learning, the importance of variation in quality is not well understood. We examined whether three measures of variation in observed classroom quality over the school year – overall variation in quality, teacher-specific trends in quality, and instability in quality – were associated with children’s language, literacy, and regulatory outcomes. We also examined whether variation in quality was associated with teachers’ participation in coaching. Overall variation and instability in emotional support and classroom organization over the year were negatively associated with children’s regulatory and literacy outcomes. Participation in coaching was linked to increased variation only in instructional support. We discuss implications for policies focused on improving classroom quality.
How much school students attend is a powerful indicator of their well-being and a strong predictor of their future success in school. Prior research has documented the myriad in-school and out-of-school factors that contribute to high levels of student absenteeism, many emerging from the root causes of poverty and disengagement. The shift to online learning during the COVID-19 pandemic likely disrupted prior barriers to attendance and may have created new ones. This sequential explanatory mixed-methods study examined student absenteeism during the 2020–2021 school year in Detroit. We used administrative data to show whether and how attendance patterns changed, and we linked family survey and interview data to explain those patterns. We found that 70% of students were chronically absent, with 40% of parents reporting that computer problems contributed to absenteeism. While measures of socioeconomic disadvantage and computer/internet issues were associated with lower attendance and higher probability of chronic absenteeism, reported levels of hardship during the pandemic were not. Despite significant investment in technology, the district’s strategies for engaging students were not sufficient in overcoming economic hardships and the new challenges of online learning.
This paper identifies which investments in school facilities help students and are valued by homeowners. Using novel data on school district bonds, test scores, and house prices for 29 U.S. states and a research design that exploits close elections with staggered timing, we show that increased school capital spending raises test scores and house prices on average. However, impacts differ vastly across types of funded projects. Spending on basic infrastructure (such as HVAC) or on the removal of pollutants raises test scores but not house prices; conversely, spending on athletic facilities raises house prices but not test scores. Socio-economically disadvantaged districts benefit more from capital outlays, even conditioning on project type and the existing capital stock. Our estimates suggest that closing the spending gap between high- and low-SES districts and targeting spending towards high-impact projects may close as much as 25% of the observed achievement gap between these districts.
The COVID-19 pandemic resulted in significant disruption in schooling worldwide. This paper uses global test score data to estimate learning losses. It models the effect of school closures on achievement by predicting the deviation of the most recent results from a linear trend using data from all rounds of the Programme for International Student Assessment. Scores declined by an average of 14 percent of a standard deviation, roughly equal to seven months of learning. Losses were greater for students in schools that faced relatively longer closures, boys, immigrants, and disadvantaged students. Educational losses may translate into significant national income losses over time.
This study investigates how individual states raise revenue to pay for elementary-secondary education spending after a school finance reform (SFR). We consider 24 states that implemented SFRs between 1989 and 2005. Using a synthetic control approach, we identify six case-study states (Arkansas, Kansas, Maryland, Michigan, New Hampshire, and Vermont) that increased and sustained education expenditures after reform. We then searched for legislative statutes that appropriated funding for increased education spending and identified how policymakers intended to fund the SFR. Five states—AK, KS, MI, NH, and VT—paid for increased education expenditures by altering tax rates and changing tax revenue sources. A common feature among these five states is that they increased their control over the management of property tax revenues.
A growing body of research shows that students benefit when they demographically match their teachers. However, little is known about how matching affects social-emotional development. We use student-fixed effects to exploit changes over time in the proportion of teachers within a school grade who demographically match a student to estimate matching's effect on social-emotional measures, test scores, and behavioral outcomes. We find improvements for students in grit and interpersonal self-management when matched to teachers of their race and gender. Black female students drive these effects. We also find that matching reduces absences, especially for Black students. Our findings add to the emerging teacher diversity literature by showing its benefits for Black and female students during a critical stage of development.
We leverage log data from an educational app and two-way text message records from over 3,500 students during the summers of 2019 and 2020, along with in-depth interviews in Spanish and English, to identify patterns of family engagement with educational technology. Based on the type and timing of technology use, we identify several distinct profiles of engagement, which we group into two categories: Independent Users who engage with technology-based educational software independently, and Interaction-Supported Users who use two-way communications to support their engagement. We also find that as the demands of families from schools increased during the COVID-19 pandemic, Spanish-speaking families were significantly more likely than English-speaking families to engage with educational technology across all categories of families, particularly as Interaction-Supported Users.
Field supervisors are central to clinical teaching, but little is known about how their feedback informs preservice teachers (PSTs) development. This sequential mixed methods study examines over 3,000 supervisor observation evaluations. We qualitatively code supervisor written feedback, which indicates 2 broad pedagogical categories and 9 separate skills. We then quantize these feedback codes to identify the variation in the presence of these codes across PST characteristics, and then use several modeling techniques to indicate that specific feedback codes are negatively associated with evaluation score. Managing student attention was most detrimental to scores in early observations whereas instructional feedback (e.g., lesson delivery) was prioritized later in clinical teaching. Findings inform teacher preparation policy on understanding PST development and improving supervisory feedback.
“Grow Your Own” (GYO) programs have recently emerged as a promising approach to expand teacher supply, address localized teacher shortages, and diversify the profession. However, little is known about the scale and design of GYO programs, which recruit and support individuals from the local community to become teachers. We conduct a quantitative content analysis to describe 94 GYO initiatives. We find that GYO is used broadly as an umbrella term to describe teacher pipeline programs with very different purposes, participants, and program features. Our results suggest that misalignment between some GYOs’ purposes and program features may inhibit their effectiveness. Finally, we propose a new typology to facilitate more precise discussions of GYO programs.
This study examines the experience of demotion from a principalship to an assistant principalship and how race and gender can differentially impact career trajectories. Using administrative state dataset of 10,946 observations at the principal level, we used probit regression to determine the overall probability of demotion and Kaplan Meier survival analysis to estimate the differences in probability over time. Our analysis describes not only who experiences demotions, but includes the characteristics of the sending and receiving schools. Survival analysis illustrates how small differences over time in demotion by race resulted in statistically significant systemic differences. We also find that experience matters: for every additional year of experience in the principal role, the probability of experiencing demotion decreases by 0.34%.