– 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.
Current Selections
ClearSocio-economic Status and Subject Choice at 14: Do They Interact to Affect University Access
Quantitative Analysis of an Urban Community College S-STEM Program
– There were higher rates in student success, progress, and cumulative GPA in the group of students who received the program as an intervention than a comparison group of students, matched on previously reported measures of success, who did not receive the intervention.
– The evidence presented supports the efficacy of the UC S-STEM program in increasing student progress rate for credits earned, cumulative GPA, and success.
– Progress rates for Cohort students were lower prior to program entry than after program entry, by an average of almost three credit hours per semester. This observed difference in rate means was statistically and represented a large effect size.
Science Engagement and Science Achievement in the Context of Science Instruction: A Multilevel Analysis of U.S. Students and Schools
– All aspects of science engagement were statistically significantly and positively related to science achievement, and nearly all showed medium or large effect sizes.
– Each aspect was positively associated with one of the four practices (strategies) of science teaching.
– Focus on applications or models was positively related to the most aspects of science engagement (science self-concept, enjoyment of science, instrumental motivation for science, general value of science, and personal value of science).
– Hands-on activities were positively related to additional aspects of science engagement (science self-efficacy and general interest in learning science) and also showed a positive relationship with science achievement.
– School mean SES has a positive and significant effect on students’ future motivation in science and on science achievement.
Laying the Tracks for Successful Science, Technology, Engineering and Mathematics Education: What Can We Learn from Comparisons of Immigrant-Native Achievement in the USA?
This paper examines the immigrant-native achievement gap in science, technology,
engineering, and mathematics (STEM) fields in college in the USA.
Family Socioeconomic Status and Choice of STEM Major in College: An Analysis of a National Sample
Does students’ decision of STEM enrollment in college differ systematically by family SES?
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.
Understanding the Relationship Between Parental Education and STEM Course Taking Through Identity-Based and Expectancy-Value Theories of Motivation
This study investigates the relationships between expectancy-value and identity-based motivational variables by examining how these motivational variables predict STEM preparation (i.e., course taking) in high school and college.
Disadvantage and the ‘Capacity to Aspire' to Medical School
This study was designed to elucidate
why students from backgrounds of
lower socio-economic status (SES) and who
may be first in their family (FIF) to enter
university continue to be under-represented in
medical schools.
Does it Matter Who Your Schoolmates Are? An Investigation of the Association between School Composition, School Processes and Mathematics Achievement in the Early Years of Primary Education
(1) What are the effects of school composition with regard to prior math achievement, SES, ethnicity and sex on mathematics achievement at the end of the second grade? (2) Are there differential school composition effects? In other words: are all students affected equally by their school composition or are some specific subgroups more sensitive to their school composition than others? (3) Do certain school processes mediate the association between school composition and mathematics achievement at the end of the second grade?
Characteristics of Schools Successful in STEM: Evidence from Two States' Longitudinal Data
This report estimates school effectiveness in science and mathematics to identify and describe both successful and un-successful schools in STEM fields.
Experimental Evidence on the Effect of Childhood Investments on Postsecondary Attainment and Degree Completion
Does having a small class size in K through 3rd have an impact on postsecondary outcomes?
The Effects of Single-Sex Compared With Coeducational Schooling on Mathematics and Science Achievement: Data From Korea
– Results for eighth graders indicated no differences between students in single-sex and coeducational schools in mathematics and science achievement.
– Results from the 2003 TIMSS data replicated the finding: students’ mathematics and science achievement was unrelated to the gender composition of their school.
– For both the 2007 and the 2003 data sets, students’ performance was consistently significantly predicted by factors related to socioeconomic status; students (both boys and girls) performed better on the mathematics and science exams when their fathers had more education, their families had more resources, and a lower proportion of their schoolmates came from economically disadvantaged families.
– Both boys’ and girls’ mathematics performance was predicted by the amount of time spent on homework; students do worse when they spend relatively more time on mathematics homework (or students spend more time on homework when they are performing poorly).
School Composition and Contextual Effects on Student Outcomes
Examine the relationships among school composition, several aspects of school and classroom context, and students’ literacy skills in science.