Students' Choice of Post-Compulsory Science: In search of schools that compensate for the socio-economic background of their students

It is commonly argued that socio-economic inequalities can explain many of the differences in achievement and participation in science education that have been reported among countries and among schools within a country. We addressed this issue by examining (a) the relationship between variables associated with socio-economic background and application frequencies to the Swedish Natural Science Programme (NSP) in upper secondary school and (b) whether there are lower secondary schools in Sweden that seem to compensate for these variables. Data from Statistics Sweden (SCB) covering the whole population of 106,483 ninth-grade students were used to calculate the probability for each student to apply to the NSP. Our results indicate that the variables, such as parental educational level and grades, have explanatory power, but with varying effect for different subpopulations of students. For example, grades in mathematics have a greater impact than grades in science for females' choice of the NSP. The opposite holds for male students. Out of 1,342 schools, 158 deviated significantly from predicted, that is, the students in these schools applied to the NSP in greater or lesser extent than expected. The number of deviating schools is greater than predicted by pure random variation. This suggests that variables of socio-economic background are only a partial explanation of the application frequencies, and that the deviation needs to be investigated further. Our findings suggest that in order to understand why schools deviate positively and so compensate for the socio-economic background of their students, we need to study their practices more closely. Keywords: Post-compulsoryScienceInterestSocio-economicSchool effect Acknowledgement We want to thank Jan-Olov Persson, Department of Mathematics, Stockholm University for statistical assistance in analysing the data. Per-Olof Wickman was funded by the Knut and Alice Wallenberg Foundation, The Bank of Sweden Tercentenary Foundation and the Swedish Research Council during this study. Notes Other explanations are differences in immigrant population, the status and competence of the teachers and allocation of resources for schools (IFAU, Citation2010; The Swedish National Agency for Education, Citation2009b). We could have used a more complex model, for example, a smoothing spline function for parental income and final grades. However, the small number of students in a much greater number of classes would affect the potential to generalize the findings between the four groups and also to other populations. The logistic model has the form: By taking the inverse of the natural logarithm of the logistic model, one derives an equation to predict the probability of a certain outcome: , where p is the probability of the outcome of interest, α is the constant or Y intercept, β is the regression coefficient and e is the base of the system of natural logarithms. As the reader may notice, outliers lying below the line seem to be clustered at the lower end of the probability scale whereas outliers above the line seem more evenly distributed. On closer inspection in the data matrix, however, this difference turns out to be less marked than what Figure 4 implies. From the 158 schools deviating significantly, 18 negative and 12 positive outliers are in the predicted probability range 0–0.9, 50 negative and 49 positive are in the range 0.1–0.19; 3 negative and 21 positive are in the range 0.2–0.29, and finally, 2 negative and 3 positive are in the range 0.3–0.39. Hence, except for 0.2–0.29, negative and positive outliers display a similar distribution in predicted probability. The differences in the range 0.2–0.29 may imply that at a certain level of likelihood of choosing the NSP, schools will deviate positively than negatively to a greater extent. Although we cannot rule out the possibility that there is a real difference between negative and positive outliers, the present analysis cannot shed any further light on this matter.