Textbooks are a widely used educational intervention that can affect student achievement, and the marginal cost of choosing a more effective textbook is typically small. However, we know little about how textbooks get from the publisher to the classroom. We use a lens of institutional theory and interviews with district leaders in a stratified random sample of 34 California school districts to investigate the ways mathematics textbook adoption practices vary and predict adoption decisions. We find isomorphic, highly formalized adoption processes in most districts. However, we observe some differences along dimensions of district size, technological interest/infrastructure, and English learner concentration. We recommend states produce and update lists of high quality materials early and often, and that they use a highly rigorous evaluation process. We also recommend states experiment with encouraging similar districts to partner on textbook evaluation and adoption to respond to district demands for information and capacity building around curricula.
Free and reduced-price meal (FRM) data are used ubiquitously to proxy for student disadvantage in education research and policy applications. The Community Eligibility Provision (CEP)—a recently-implemented policy change to the federally-administered National School Lunch Program—allows schools serving low-income populations to identify all students as FRM-eligible regardless of individual circumstances. We study the CEP’s effect on FRM eligibility as a proxy for student disadvantage, and relatedly, we examine the viability of direct certification (DC) status as an alternative disadvantage measure. Our findings on whether the CEP degrades the informational content of FRM data are mixed. At the individual level there is essentially no effect, but the CEP does meaningfully change the information conveyed by the FRM-eligible share of students in a school. Our comparison of FRM and DC data in the post-CEP era shows that these measures are similarly informative as proxies for disadvantage, despite the CEP-induced information loss in FRM data. Using both measures together can improve the identification of disadvantaged students, but only marginally.