Differential school effects among low, middle, and high social class composition schools: a multiple group, multilevel latent growth curve analysis

Do some schools narrow the gap? Differential school effectiveness by ethnicity, gender, poverty, and prior achievement

“…Smith and Tomlinson (1989) also report significant differential effects in relation to ethnicity, but conclude they are 'trivial compared with the very large school differences across all ethnic groups" (p305). Palardy (2008), analysing student progress between ages 14 and 18 using the US National Education Longitudinal Study, did not directly model differential effects at the school level but broadly categorised schools into three groups based on the mean socioeconomic status (SES) of the students attending the schools. Only one student characteristic (Asian ethnicity) provided strong evidence of a differential effects across the three school types, with Asian students in high SES schools making more progress relative to White students, but not in middle or low SES schools.…”

School Sector, School Poverty, and the Catholic School Advantage

“…In a recent study, Rumberger and Palardy (2005) found that the SES of a school has at least as much impact on achievement gains as the student's individual economic background. Palardy (2008) also reported that students attending high-poverty schools learn at signifi cantly slower rates than those in wealthier schools, even when extensive individual background characteristics are controlled. Orfi eld and Eaton (1996) claim that the effect of school poverty on student outcomes is among the most consistent fi nding in educational research.…”

Predictors of the Drop in School Marks in Secondary School: Evidence for Effects of Students’ Socio-Demographic Background

“…In this analysis we first estimated the model simultaneously for the academic track and the vocational track for each school subject, with no constraints on the parameters slope and intercept. We then tested whether the slopes and the intercepts in both tracks were significantly different by re-estimating the models while keeping either the slopes or the intercepts invariant (Palardy, 2008;Duncan and Duncan, 2009). If there were significant differences in the slopes or in the intercepts between school tracks, models that allow for freely varying slopes or intercepts should yield a better fit than models where the slope or the intercept were fixed.…”