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At schools with low grading standards, students receive higher school-awarded grades across multiple courses than students with the same skills receive at schools with high grading standards. A new methodology shows grading standards vary substantially, certainly enough to affect post-secondary opportunities, across high schools in Alberta. Schools with low grading standards are more likely to be private, rural, offer courses for students returning to high school, have smaller course cohorts, have a smaller percentage of lone parent households and a larger percentage of well-educated parents. Variation in grading standards changes post-secondary opportunities in systematic ways.
Four-year public colleges may play an important role in supporting intergenerational mobility by providing an accessible path to a bachelor’s degree and increasing students' earnings. Leveraging a midsize state’s GPA- and SAT-based admissions thresholds for the four-year public sector, I use a regression discontinuity design to estimate the effect of four-year public college admissions on earnings and college costs. For low-income students and Black, Hispanic, or Native American students, admission to four-year public colleges increases mean annual earnings by almost $8,000 eight to fourteen years after applying without increasing the private costs of college. The state recovers the cost of an additional four-year public college admission through increased lifetime tax revenue. Expanding access to four-year public colleges may be a particularly effective way to improve the economic outcomes of low-income students and Black, Hispanic, or Native American students.
Teachers’ sense-making of student behavior determines whether students get in trouble and are formally disciplined. Status categories, such as race, can influence perceptions of student culpability, but the degree to which teachers’ initial identification of student misbehavior exacerbates racial disproportionality in discipline receipt is unknown.This study provides the first systematic documentation of teachers’ use of office discipline Referrals (ODRs) in a large, diverse urban school district in California that specifies the identity of both the referred and referring individuals in all ODRs. We identify teachers exhibiting extensive referring behavior, or the top 5 percent referrers based on the number of ODRs they make in a given year and evaluate their contributions to disciplinary disparities. We find that “top referrers” effectively double the racial gaps in ODRs for both Black-White and Hispanic-White comparisons. These gaps are mainly driven by higher numbers of ODRs issued for Black and Hispanic students due to interpersonal offences and defiance, and also partially convert to racial gaps in suspensions. Both the level and racial compositions of the school sites where “top referrers” serve and their personal traits seem to explain some of their frequent referring behavior. Targeting supports and interventions to “top referrers” might afford an important opportunity to reduce racial disciplinary gaps
Lottery-based identification strategies offer potential for generating the next generation of evidence on U.S. early education programs. Our collaborative network of five research teams applying this design in early education and methods experts has identified six challenges that need to be carefully considered in this next context: 1) available baseline covariates may not be very rich; 2) limited data on the counterfactual; 3) limited and inconsistent outcome data; 4) weakened internal validity due to attrition; 5) constrained external validity due to who competes for oversubscribed programs; and 6) difficulties answering site-level questions with child-level randomization. We offer potential solutions to these six challenges and concrete recommendations for the design of future lottery-based early education studies.
We study the effects of increased school spending in rural American school districts by leveraging the introduction and subsequent expansion of Wisconsin’s Sparsity Aid Program. We find that the program, which provides additional state funding to small and isolated school districts, increased spending in eligible districts by 2% annually and that districts primarily allocated funds to areas with low baseline budget shares. This increased spending has little effect on standardized test scores, but modestly increases college enrollment and completion for students with a low likelihood of attending or completing college.
The Revista del Centro de Estudios Educativos, numero 3, 1971 included an early Carnoy article on the economics of education: “Un enfoque de sistemas para evaluar la educación, ilustrado con datos de Puerto Rico.” The article used a unique data set that had student test scores, students’ family background characteristics, and information about teachers and other school inputs for about one-third of all students in Puerto Rican schools to estimate relations between teacher characteristics and student test scores controlling for students’ social class, gender, and whether the school was urban or rural. Such data sets were rare in the late 1960s, and so were attempts to understand how education systems worked to produce student learning outcomes—that is, to improve the quality of education.
There is a lot to criticize in the empirical analysis in that early article, but it does show that there was considerable concern about the quality of education in Latin America even back in 1971. That concern has grown greatly in the past fifty years as countries in the region have expanded their educational systems to provide an increasing proportion of youth with secondary schooling and higher education. With that expansion, there has been a shift in focus from policies concerned with access to schooling to policies concerned with improving the quality of schooling (UNESCO, 2005).
Two factors have contributed to this shift. The first is research claiming that quality of education, as measured by international test scores, is a better predictor of economic growth than the number of years of schooling in the labor force (Hanushek and Kimko, 2000; Hanushek and Woessman, 2008). The second is the increase in testing itself, both at the national and international levels. Student test results are being used increasingly to pressure national and local educational systems, schools, and individual teachers to have their students do better on the tests (OECD, 2013). League tables comparing schools, local school districts, regions, and nations against others are now a regular feature of educational politics in many countries of the world. To some extent, international test scores are becoming important enough to affect government legitimacy.
The effect of school closures in the spring of 2020 on the math, science, and reading skills of secondary school students in Poland is estimated. The COVID-19-induced school closures lasted 26 weeks in Poland, one of Europe's longest periods of shutdown. Comparison of the learning outcomes with pre- and post-COVID-19 samples shows that the learning loss was equal to more than one year of study. Assuming a 45-year working life of the total affected population, the economic loss in future student earnings may amount to 7.2 percent of Poland’s gross domestic product.
Does relaxing strict school discipline improve student achievement, or lead to classroom disorder? We study a 2012 reform in New York City public middle schools that eliminated suspensions for non-violent, disorderly behavior, replacing them with less disruptive interventions. Using a difference-in-differences framework, we exploit the sharp timing of the reform and natural variation in its impact to measure the effect of reducing suspensions on student achievement. Math scores of students in more-affected schools rose by 0.05 standard deviations relative to other schools over the three years after the policy change. Reading scores rose by 0.03 standard deviations. Only a small portion of these aggregate benefits can be explained by the direct impact of eliminating suspensions on students who would have been suspended under the old policy. Instead, test score gains are associated with improvements in school culture, as measured by the quality of student-teacher relationships and perceptions of safety at school. We find no evidence of trade-offs between students, with students benefiting even if they were unlikely to be suspended themselves.
Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models -- one predicting course completion, the second predicting degree completion. Our results show that algorithmic bias in both models could result in at-risk Black students receiving fewer success resources than White students at comparatively lower-risk of failure. We also find the magnitude of algorithmic bias to vary within the distribution of predicted success. With the degree completion model, the amount of bias is nearly four times higher when we define at-risk using the bottom decile than when we focus on students in the bottom half of predicted scores. Between the two models, the magnitude and pattern of bias and the efficacy of basic bias mitigation strategies differ meaningfully, emphasizing the contextual nature of algorithmic bias and attempts to mitigate it. Our results moreover suggest that algorithmic bias is due in part to currently-available administrative data being less useful at predicting Black student success compared with White student success, particularly for new students; this suggests that additional data collection efforts have the potential to mitigate bias.