Single-sex schools
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ResultsOne of the perennial problems affecting attempts to assess the impact of single-sex schooling on science engagement is the difficulty of disentangling the effect of school sector (private versus government) from the effect of gender composition of student populations within schools. Fortunately, in LSAY09 not all single-sex schools belong either in the Catholic or the independent sectors. Therefore, there is some scope for dealing with this problem, even though a mere 2% of students in the government sector are in boys-only settings, and only 3% of students in this sector attend girls-only schools (table 1). The largest degree of sex segregation is present in the Catholic sector, where 17% of 15-year-olds attend boys-only schools and nearly a quarter of students, that is, 24%, receive education in girls-only environments. The comparison of the data in table 1 to the estimates reported by Ainley and Daly (2002) for 1998 reveals that at both points of time 40% of students in upper secondary education attended non-government schools. However, 55% of students in the Catholic sector and 45% students in independent schools were in single-sex environments in 1998 (Ainley & Daly 2002, p.244), but by 2009 the corresponding proportions were only 41% in the former and 17% in the latter (table 1). Thus it appears that the independent sector halved its share of students in sex-segregated settings in the decade between 1998 and 2009. Table 1 Student characteristics, by type of school
Source: LSAY09, weighted estimates. As expected, single-sex schools are concentrated in metropolitan locations (table 1) and provide education to students who score significantly higher on science tests (table 2). On a science performance scale with the mean of 500 and the standard deviation of 100, the average score of a student from a single-sex school exceeded by about 30 points, or close to one-third of a standard deviation, the scores typical for coeducational schools (table 2). Students in single-sex schools come from more advantageous family backgrounds, just as was the case a decade ago. Ainley and Daly reported the advantage of about 0.4 of a standard deviation (2002, p.244), which is comparable with that found in LSAY09. The difference between the economic and socio-cultural background of students in boys-only and coeducational schools is 0.42 of a standard deviation, while the typical socioeconomic status of students in girls-only schools is 0.57, which is significantly higher than the average of 0.29 for their peers in coeducational settings. Comparisons of gender-segregated and coeducational schools often point out that the former tend to be small in size. However, in LSAY09 the mean size (as well as the median, not shown here) of boys-only schools exceeds the average number of students attending coeducational settings, which is contrary to such expectations (table 2). Table 2 Student characteristics, by type of school and gender of students
Source: LSAY09, weighted estimates. Before examining the average differences in subject choice and career plans between single-sex and coeducational schools, it is worth considering whether the individual tendency for boys and girls to select different science subjects changed between 2009 and earlier points of time. For illustration, table 3 contrasts the relevant estimates between LSAY03 and LSAY09. Table 3 Uptake of science subjects in Year 11 and science-related career plans by gender: comparison between LSAY03 and LSAY09
Source: LSAY03 and LSAY09, weighted estimates. There are striking similarities in the proportions of boys and girls in these cohorts who studied science in Year 11. Moreover, the size of the gender gaps in the uptake of life and physical sizes is comparable for Australian adolescents who turned 15 years of age in 2003 and those who were aged 15 in 2009. By analogy, the proportions of students interested generally in science careers and specifically in life and physical science occupations are almost the same in both groups of adolescents. Physical science careers attract relatively few girls (24% of boys versus 6% of girls in 2003 and 22% boys versus 6% of girls in 2009), while life science is less popular among boys (9% of boys versus 24% of girls in 2003 and 11% of boys versus 23% of girls in 2009). These patterns also resemble the proportions reported in the 1990s (Ainley & Daly 2002; Ainley, Kos & Nicholas 2008). They clearly indicate, with respect to the first research question posed in this paper, that the tendency for boys and girls to cluster in different science courses persists over time, with no sign of decreasing, even though the actual titles of science courses and their curricula change. Do single-sex schools make much difference to these self-sorting tendencies? Figure 3 compares males and females in sex-segregated and coeducational settings. Boys in single-sex schools are more likely (17%) than their counterparts in coeducational schools (10%) to plan a life science career. However, their interest in physical science jobs and their uptake of physics courses in either Year 11 or 12 are comparable across coeducational and single-sex schools. By the same token, the proportions of boys taking life science subjects are similar in different types of schools in Years 11 and 12. So, segregated environments make no difference to boys’ inclination to study science, although they seem to encourage more boys to think of life science careers, which are reputed to attract more girls. The patterns for girls shown in the lower panel of figure 3 reveal little differentiation by school type with respect to life science subjects or careers. However, girls in girls-only schools seem to be more likely to consider a career in physical science (8%) than girls in coeducational settings (5%). Moreover, more girls in segregated schools study physical sciences (38% versus 25% in Year 11) and this tendency persists into Year 12 (30% versus 20%), even though the proportion of girls taking science subjects falls between Years 11 and 12. This decreased interest in science in Year 12 is apparent in all groups of students considered here, with the single exception of boys studying physical science in single-sex schools, for whom the estimates are 39% in both Years 11 and 12. The key question that arises, however, is whether these differences persist once a host of other characteristics of students and schools have been taken into account. Many previous studies, including the Ainley and Daly analysis (2002), found that what appeared as the benefits of single-sex schooling were really attributable to the specific features of the student populations or school settings. To provide a strong test of this hypothesis, the multivariate analyses presented in tables 4 and 5 include not only all the variables previously taken into account (Ainley & Daly 2002) but also a large number of other characteristics named in the literature as the potential real causes of the apparent benefits that single-sex schools bestow on science engagement. (The details of the model estimation and independent variables are in appendix A.) Apart from the variables shown in tables 4 and 5, earlier estimations controlled also for the size of school, the average economic, social and cultural status of families within each school, and the school average of students’ science self-confidence, but as these variables made no difference to the results they were omitted to conserve space. In contrast to the analysis of science subject uptake conducted for the 1998 data (Ainley & Daly 2002), this paper finds that single-sex schools encourage a higher level of engagement in physical science among girls (0.49** in table 4). However, an apparently stronger commitment to physical science careers among these girls is explained by other variables, so single-sex schools do not, in their own right, succeed in encouraging adolescent girls to target physical science occupations any more than coeducational schools. Figure 3 Boys’ and girls’ science engagement, by type of school Source: LSAY09, weighted estimates. Table 4 Studying a Year 11 subject in life science and in physical science, unstandardised coefficients from multilevel random intercept models
Notes: * Statistically different from zero at p = 0.05. ** Statistically different from zero at p = 0.01. - - a reference category. Table 5 Planning a career related to life science or physical science, unstandardised coefficients from multilevel random intercept models
Notes: * Statistically different from zero at p = 0.05. ** Statistically different from zero at p = 0.01. - - reference category. Another important aspect of this finding and one which is not evident in the examination of logit coefficients is that the benefit of single-sex schooling for girls’ uptake of physical science is moderate. In predictions informed by a model analogous to the one found in table 4 but run only for female students it was ascertained that, if all the girls in LSAY09 switched schools to girls-only institutions, their average level of physical science uptake in Year 11 would rise from 28% to 34.5%, all else being equal. While this is not a negligible difference, it is by no means staggering. With respect to boys, single-sex schooling makes no difference in the uptake of science subjects in Year 11, once a range of school and student characteristics is taken into account. However, boys in boys-only schools are more likely, all else being equal, to target careers in physiotherapy or medicine than boys in coeducational schools. While not all effects of single-sex schooling are explained away by control variables, single-sex schools are not particularly powerful factors in encouraging enrolments in science courses or science-oriented career plans. With respect to science subjects, students’ gender, science performance and science self-confidence levels have a consistent positive influence on both life and physical science engagement (table 4). These latter two variables are more salient for taking up physical science subjects. There is also some indication that science subjects are taken more frequently by students from higher socioeconomic backgrounds. The socio-cultural status of a student’s family in this analysis includes both material and cultural resources, including parental education and cultural possessions (OECD 2007b). Furthermore, physical sciences appeal more to ethnic minority students, as shown by the positive coefficients associated with students’ place of birth and a negative one for English spoken at home. The controls for the school sector and state or student residence, while essential, are less informative in this analysis. As these variables were used as sampling strata and because science subject titles vary between particular states and territories, these controls are necessary. It is interesting to note the apparent higher uptake of science subjects in Victoria than in New South Wales, but this may be partially an artefact of subject coding, even though this difference appears also in students’ career expectations in table 5. Multilevel models in tables 4 and 5 control for a wide range of indicators of students’ abilities, background and opportunities (Ainley & Daly 2002). As was the case in previous studies, it is impossible to control for ‘constrained curriculum’ effects, which denote the availability of subjects, but a number of variables, including school location (metropolitan versus other), students’ prior academic achievement and school sector, are used as proxy variables to address this issue (Ainley & Daly 2002). At the school level (table 4) students in both independent and Catholic schools are more likely to take life science subjects, although only independent schools foster a higher likelihood of enrolment into physical science in Year 11. Arguably, the benefits of science engagement in high school may be short-lived if students do not plan further study or careers in science-related fields. This is why, in assessing the potential benefits of single-sex schooling, it is worth considering the career expectations of students in both types of schools. Plans for careers in physical science are not significantly related to sector or the gender composition of schools. The only effect at school level is the propensity of boys in sex-segregated schools to opt a little more frequently for life science professions (0.55**, in bold type in table 5). Students in Catholic and independent schools are more likely than government-sector students to plan life science careers, but overall it is more individual than school-level factors that make a significant difference to the vocational plans of students. Ethnic minority students are not only more likely to take physical science courses in Year 11 (-0.78** for English spoken at home in table 4) but also to plan a career in science-related fields (-0.44** and -0.31** in table 5). Foreign-born students are more interested in physical science compared with their Australian-born peers. There are a number of state differences, of which Victorian students, who were also more likely than students in New South Wales to take science courses in Year 11, stand out as more keen on science-related employment. Academic success in science is conducive to science subject uptake and the forming of science-oriented vocational plans, although more so for physical (0.87** in table 4 and 0.41** in table 5) than life science occupations (0.11** in table 4 and 0.25** in table 5). Higher levels of science confidence boost all forms of science engagement, while the time devoted to studying science is a significant predictor of science-related occupational expectations. The latter demonstrates an extra commitment to science study on the part of those students who are intent on future careers in this area. Yüklə 269,74 Kb. Dostları ilə paylaş:
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