Online college courses are a rapidly growing feature of higher education. One out of three students now takes at least one course online during their college career, and that share has increased threefold over the past decade (Allen and Seaman 2013). The promise of cost savings, partly through economies of scale, fuels ongoing investments in online education by both public and private institutions (Deming et al. 2015). Nonselective and for-profit institutions, in particular, have aggressively used online courses.In this paper we estimate the effects of taking a college course online, instead of in a traditional in-person classroom setting, on student achievement and progress in college. We examine both mean effects and how online courses change the distribution of student outcomes. While online course-taking is both prevalent and growing, there remains relatively little evidence about how taking a course online, instead

Residential segregation, by definition, leads to racial and socioeconomic disparities in neighborhood conditions. These disparities may in turn produce inequality in social and economic opportunities and outcomes. Because racial and socioeconomic segregation are not independent of each other, however, any analysis of their causes, patterns, and effects must rest on an understanding of the joint distribution of race/ethnicity and income among neighborhoods. In this article, we use a new technique to describe the average racial composition and income distributions in the neighborhoods of households with different income levels and race/ethnicity. Using data from the decennial censuses and the American Community Survey, we investigate how patterns of neighborhood context in the United States over the past two decades vary by household race/ethnicity, income, and metropolitan area. We find large and persistent racial differences in neighborhood context, even among households with the same annual income.

Districts, states, and researchers are using value-added models with increasing frequency to evaluate educational policies and programs, as well as teachers and other educators individually. Despite their prevalence, little research assesses whether value-added measures (VAM) are consistent across student subgroups. Are teachers who are effective with one group of students also effective with others? If they are not, then it may be worthwhile to develop separate measures of teacher effectiveness for different student groups; if they are, a single average measure will likely suffice. Our article uses data from a large urban district with a considerable English learner (EL) population to compare teachers' VAM with ELs to the same teachers' VAM with non-ELs. We find that teachers who are effective with ELs also tend to be effective with their non-ELs and vice versa. We also, however, find evidence that some teachers are relatively more effective with ELs than with non-ELs, and that this increased efficacy is predicted by a teacher's fluency in students' home language and whether he or she possesses a bilingual teaching certification.

Ear acupuncture may be a promising modality to be used for pain reduction within 48 hours, with a low side effect profile. Rigorous research is needed to establish definitive evidence of a clinically significant difference from controls or from other pain treatments.