No abstract

Novice teachers’ professional contexts may have important implications for their effectiveness, development, and retention. However, due to data limitations, descriptions of these contexts are often unidimensional or vague. Using 10 years of administrative data from the Los Angeles Unified School District, we describe patterns of new teacher sorting using 24 context measures organized along three dimensions—intensity of instructional responsibilities, homophily, and colleagues’ qualifications—and use school-level survey data to measure a fourth dimension. professional culture. Relative to more experienced teachers, novice teachers have placements that are more challenging along the first three dimensions, and composite measures of the dimensions are differentially predictive of teachers’ outcomes. This suggests that policymakers should carefully consider placements to better support novice teachers.

While the effect of teachers’ unions on school districts continues to be debated, the research literature provides few definitive conclusions to guide these discussions. In this article, we examine the relationship between teachers’ union contracts and school district efficiency. We define efficiency as the ratio of short-run productivity (student performance on standardized exams) to expenditures. We estimate a series of school district fixed effect models using measures of district collective bargaining agreement (CBA) restrictiveness tied to longitudinal outcomes. We find that CBA restrictiveness is positively associated with expenditures on students, instruction, instruction support services, and teacher and administrator salaries over time. We find no significant relationship between CBA restrictiveness and student achievement. Finally, we find a negative relationship between CBA restrictiveness and district efficiency. Given the small magnitude of our effect sizes, we conclude that weakening union rights may not produce large gains in efficiency and may come at substantial political costs.

Little is known about the extent to which expansions of K-12 computer science (CS) have been equitable for students of different racial backgrounds and gender identities. Using longitudinal course-level data from all high schools in California between the 2003–2004 and 2018–2019 school years we find that 79% of high school students in California, including majorities of all racial groups, are enrolled in schools that offer CS, up from 45% in 2003. However, while male and female students are equally likely to attend schools that offer CS courses, CS courses represent a much smaller share of course enrollments for female students than for male students. Non-Asian students enroll in relatively few CS courses, and this is particularly true for Black, Hispanic, and Native American students. Race gaps in CS participation are to a substantial degree explicable in terms of access gaps, but gender gaps in CS participation are not. Different groups of students have access to CS teachers with similar observable qualifications, but CS teachers remain predominantly white and male. Consequently, white and male CS students are much more likely than other students to have same-race or same-gender instructors. Our findings and the implications we draw for practice will be of interest to administrators and policymakers who, over and above needing to ensure equitable access to CS courses for students, need to attend carefully to equity-related course participation and staffing considerations.

Many schools and districts have considerable discretion when hiring teachers, yet little is known about how that discretion should be used. Using data from a new teacher screening system in the Los Angeles Unified School District (LAUSD), we find that performance during screening, and especially performance on specific screening assessments, is significantly and meaningfully predictive of hired teachers’ evaluation outcomes, contributions to student achievement, attendance, and mobility. However, applicants’ performance on individual components of the screening process are differentially predictive of different teacher outcomes, highlighting challenges and potential trade-offs faced by districts during screening.

We analyze a natural experiment in which policymakers in Pennsylvania first implemented, and later removed, reimbursements to districts for students exiting to brick and mortar and cyber charter schools. Generalized difference-in-difference models show that larger shares of students enrolling in charter schools predict decrements in spending, financial health, and achievement in sending districts; however, these relationships attenuate in years when districts receive reimbursements. After receiving reimbursements, districts with increased competition spent more on instruction and instructional support services, but not on facilities or non-instructional operations. Perhaps due to higher instructional expenditures, the relationship between competition and student achievement in reimbursement years is significantly less negative, and at times even positive, compared to non-reimbursement years. Cyber charter schools induce fewer instructional expenditures in districts than brick and mortar charter schools. The findings show clear policy choices can support traditional public systems experiencing competition.

In the 2013–2014 school year, the state of California implemented a new equity-minded funding system, the Local Control Funding Formula (LCFF). LCFF increased minimum per-pupil funding for educationally underserved students and provided greater autonomy in allocating resources. We use the implementation of LCFF to enrich our understanding of rural school finance and explore the implications of equity-based school finance reform across urbanicity (i.e., between rural, town, suburban, and urban districts) and between rural areas of different remoteness. Drawing on 15 years of financial data from California school districts, we find variation in the funding levels of rural districts but few differences in the ways resources are allocated and only modest evidence of constrained spending in rural areas. Our results suggest that spending progressivity (i.e., spending advantage of higher-poverty districts) has increased since LCFF, although progressivity is lowest in rural districts by the end of the data panel.

Purpose: We aim to better understand the curricular, staffing, and achievement trade-offs entailed by expansions of high-school computer science (CS) for students, schools, and school leaders. Methods: We use descriptive, correlational, and quasi-experimental methods to analyze statewide longitudinal course-, school-, and staff-level data from California, where CS course taking has expanded rapidly. Findings: We find that these rapid CS course expansions have not come at the expense of CS teachers’ observable qualifications (namely certification, education, or experience). Within-school course taking patterns over time suggest that CS enrollment growth has come at the expense of social studies, English/language arts (ELA), and arts courses, as well as from other miscellaneous electives. However, we find no evidence that increased enrollment of students in CS courses at a school has a significant effect on students’ math or ELA test scores. Implications: Flexible authorization requirements for CS teachers appear to have allowed school leaders to staff new CS courses with teachers whose observable qualifications are strong, though we do not observe teachers’ CS teaching skill. Increasing CS participation is unlikely to noticeably improve school-level student test scores, but administrators also do not need to be overly concerned that test scores will suffer. However, school leaders and policymakers should think carefully about what courses new CS courses will replace and whether such replacements are worthwhile.