– 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.
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Socio-economic Status and Subject Choice at 14: Do They Interact to Affect University Access
Science, Technology, Engineering and Math Readiness: Ethno-Linguistic and Gender Differences in High-School Course Selection Patterns
1) What are the ethno-linguistic profiles of high school graduates that entered the ESL program in schools in British Columbia at different ages? 2) What are the determinants and correlates of Grade 12 course selecting patterns (CSP) with respect to student gender, ethno-linguistic group, academic history, grade level at entry and achievement history? 3) What student demographics increase the probability that students will choose classes that prepare them for a STEM major? 4) What are the probabilities of CSP by gender and ethnic group status?