– School-based hiring is associated with a larger gap in the distribution of teacher quality between advantaged and disadvantaged schools.
– There is an association between school-based hiring and inequality of achievement based on socioeconomic status of students.
– School-based hiring may contribute to exacerbating inequality in learning opportunities and increasing family background’s positive effect on achievement.
– ESCS (a proxy of family SES) is positively associated with student performance in mathematics and science.
– School-based hiring is not associated with student performance on average, but school-based hiring is associated with the larger achievement gap between high- and low-SES students.
– More school autonomy in hiring was associated with a larger gap in the distribution of teacher quality across schools as well as larger socioeconomic achievement inequality.
– School-level mean SES has a positive and significant relationship with math and science achievement.
Current Selections
ClearSchool-based Teacher Hiring and Achievement Inequality: A Comparative Perspective
Is There Systemic Meaningful Evidence of School Poverty Thresholds?
-The author review of the literature about the relationships among SES and educational outcomes revealed surprisingly few SES threshold studies relative to the enormous corpus of research on SES composition effects.
– With few exceptions, the very small number of U.S. studies that report thresholds effects typically were conducted by a school district’s internal staff using cross-sectional data (only one year) for a subpopulation of district’s students.
-Conclusions reached in these studies arguably apply only to the students in the district who took part in the study, in the year in which the data were collected.
-The studies described in this report are not an empirical foundation upon which general educational policy regarding SES thresholds can be reliably or validly based.
– Educational decision makers should focus on reducing concentrations of school-level poverty to as low a level as is feasible given the available demographic mix, and avoid policies based on the unsupported notion that there are poverty thresholds above and below which student achievement levels can be predicted.
– There is not yet a body of systematic, reliable, and valid evidence that school poverty thresholds exist, and that they influence student achievement outcomes.
Socio-economic Status and Subject Choice at 14: Do They Interact to Affect University Access
– There are substantial socioeconomic differences in the subjects that young people study from age 14 to 16.
– Young people from advantaged households take more selective subjects, have higher odds of doing three or more facilitating subjects, higher odds of studying a full set of EBacc-eligible subjects (including English, Maths, History or Geography, two sciences and a modern or ancient language), but lower odds of taking Applied GCSEs (e.g. Applied Hospitality, Applied Health or Applied Manufacturing) than less advantaged young people.
– There were important differences by school characteristics, which may be a result of differential opportunities, subjects offered and within school policies.
– Even holding other factors constant, pupils in non-selective schools within selective local authorities study a less academically selective set of subjects.
– When considering university entry, and admission to high-status universities in particular, there are large raw differences associated with studying more academic combinations of subjects.
However, once differences in young people’s backgrounds and prior attainment associated with these differences in subjects studied are taken into account, these differences are, at most,
small.
– The results for studying the full set of EBacc subjects and for studying any applied subjects do show residual associations with university attendance.
– If young people from different socioeconomic backgrounds were studying a more similar curriculum between ages 14 and 16 it would be unlikely to make much of difference to the inequality in university entry highlighted by previous studies.
– Household income, home ownership and higher parental education increase the odds of taking three STEM subjects
– Socio-economic differentials in access to STEM are largely driven by prior attainment.
– Participation in STEM subjects does not vary by school characteristics, with the exception of the proportion of Free School Meals (FSM) in the school which is negatively associated with doing three or more STEM subjects.
Student and School SES, Gender, Strategy Use, and Achievement
– Schools, as opposed to families, may be the primary vehicle for developing effective strategy use practices for students and thus,
targeted interventions may be particularly useful for male students
attending low SES schools.
– One learning strategy (i.e., control strategies) was found to relate significantly and positively to achievement.
– These strategies were used more by females and students attending higher SES schools.
– Males and students attending lower SES schools tended to use a greater number of learning strategies that did not relate to achievement, including memorization and elaboration.
– Strategies that did not relate to achievement were used more
frequently by students from higher SES families.
Academic Performance of African American High School Students Related to Socioeconomic Status and School Size
– There was a negative correlation between school level SES and reading at -.50, -.44 for mathematics, and -.35 for science performance.
– There was a positive correlation between school size and reading at .10, .01 for mathematics, and .07 for science performance.
– School level SES and school size had significant impact on school
performance in reading.
– School level SES had significant impact on school performance in mathematics.
– School level SES and school size had significant impact on school performance in science.
The Impact of School SES on Student Achievement: Evidence From U.S. Statewide Achievement Data
-This study finds significant school SES effects when cross-sectional models are estimated.
-These effects largely disappear when longitudinal models are applied, namely, value-added and student fixed effect models.
– There are some statistically significant effects remaining for school racial composition in two of the states and for various subgroups, but the magnitudes of the effects are small.
-Peer SES has no effects or only very small effects on academic achievement
-Large school SES effects often found in cross-sectional studies are artifacts of aggregation and are not a sound basis for SES-based school integration policies.
– The commonly used cross-sectional models for student achievement produce sizable estimates for school SES effects which are often comparable with the effect for student SES. However, in properly specified models using longitudinal data that either (a) control for students’ prior achievement or (b) control for stable differences between students, the effects of school SES are very small.
– The analyses presented in this article do not support the widely held view that school SES and school racial composition have strong effects on student achievement.