AIR is examining the impact of attending a deeper learning network school on students’ civic engagement, college completion, and workforce outcomes and the differences in their college experiences versus those who attend comparison schools. The aim of this study is to measure the longer term impacts of attending a deeper learning network high school not yet captured in previous research.
AIR conducted a randomized controlled trial to determine the effects of Early College High Schools, which allow students to take a mixture of high school and college-level courses. The study examined the impacts of Early College High Schools on college enrollment and degree completion up to 6 years after expected high school graduation, in addition to a cost-benefit analysis of Early College High Schools. The goals of the study were to estimate the longer-term impacts of Early College High Schools on student postsecondary outcomes and compare the financial costs and benefits of these schools.
AIR is evaluating the implementation and impact of the New Tech Network’s (NTN) partnership with 10 high schools in Texas, which is intended to improve student advising during the transition to college. The goals of this evaluation are to help NTN address any implementation issues and determine the effectiveness of their revised advising practices.
The Regional Educational Laboratory Midwest, operated by AIR, is conducting a study to better understand career and technical education (CTE) course offerings in Indiana and Minnesota and identify gaps in access to high-quality CTE programming in these states.
AIR’s NAEP researchers are conducting statistical and psychometric research, evaluation, and data analysis in support of the National Center for Education Statistics (NCES). The goals of the research studies conducted by AIR under this task include (a) developing the psychometric soundness and precision of NAEP assessments, (b) adapting NAEP assessments to changing situations and populations, (c) enhancing understanding of NAEP results, and (d) exploring new ways of modeling NAEP data.