The impact of schools on young people's transition to university

The Longitudinal Surveys of Australian Youth (LSAY), in addition to the characteristics of the individual students making up the sample, collect data on a range of school characteristics. This, and the fact that the sample is clustered with the selected schools as the first stage, provides the opportunity to disentangle the impact of the school from the characteristics of students. This report exploits this feature of LSAY to investigate the impact of schools on tertiary entrance rank (TER) and the probability of going to university. While secondary education is about more than these academic goals, there is no doubt that these are of high importance, both from the point of view of the schools and the individual students and their parents.

The school characteristics covered in this report are: simple characteristics, such as school sector and location; structural characteristics, such as whether the school is single-sex or coeducational; resource base, such as class size and student—teacher ratio; and average demographics, such as the average socioeconomic status of students at the school and the extent to which parents put pressure on the school to achieve high academic results.

Key messages

• The attributes of schools do matter. Although young people’s individual characteristics are the main drivers of success, school attributes are responsible for almost 20% of the variation in TER.
• Of the variation in TER attributed to schools, the measured characteristics account for a little over a third. The remainder captures ‘idiosyncratic’ school factors that cannot be explained by the data to hand and that can be thought of as a school’s overall ‘ethos’; no doubt teacher quality and educational leadership are important here.
• The three most important school attributes for TER are sector (that is, Catholic and independent vs government), gender mix (that is, single-sex vs coeducational), and the extent to which a school is ‘academic’. For TER, the average socioeconomic status of students at a school does not emerge as a significant factor, after controlling for individual characteristics including academic achievement from the PISA test.
• However, the characteristics of schools do matter for the probability of going to university, even after controlling for TER. Here, the three most important school attributes are the proportion of students from non-English speaking backgrounds, sector, and the school’s socioeconomic make-up.

The authors also construct distributions of school performance (in relation to TER and the probability of going to university), which control for individual characteristics. The differences between high performing and low-performing schools are sizeable. There is also considerable variation within school sectors, with the government sector having more than its share of low-performing schools.

Tom Karmel
Managing Director, NCVER
 

This report uses data from the 2006 cohort of the Longitudinal Surveys of Australian Youth (LSAY) to investigate how schools influence tertiary entrance rank¹ (TER) and university enrolment over and above young people’s individual background characteristics. A particular focus is on prominent school-level factors such as sector, school demographic make-up, resources and autonomy, academic orientation, and competition with other schools.

The analysis finds that, while the impact of individual student characteristics is dominant with respect to TER and the transition to university, the way in which schools are organised and operated also matters. And it matters for the probability of going to university, even after controlling for individual TER and other relevant background factors. Of the 25 school characteristics included in the analysis, ten attributes significantly influence either TER or university enrolment, or both. The three most important attributes for TER include school sector (Catholic and independent schools have higher predicted TERs than government schools), gender mix (single-sex schools have higher predicted TERs than coeducational schools), and the extent to which a school is academically oriented.

The role of a school’s overall socioeconomic status with respect to TER is interesting. Previous studies have found that a school’s overall socioeconomic status affects academic achievement outcomes in NAPLAN and PISA. The present study finds that a school’s overall socioeconomic status does not influence students’ TER outcomes, after controlling for individual characteristics including academic achievement from the PISA test. However, the socioeconomic make-up of the student body does influence the probability of going on to university for a given TER. Two other school attributes also affect university enrolment after controlling for individual TER: a high proportion of students from non-English speaking backgrounds and school sector.

After isolating influential school attributes, cluster analysis is used to identify three groups of schools: high-performance schools, where a school’s attributes contribute to a high TER and a high probability of going to university (after controlling for TER); low-performance schools at the other end of the spectrum; and average-performance schools that show middling performance.² Although after controlling for relevant characteristics, the high-performance cluster includes schools from all three sectors, the low-performing schools are almost all from the government sector. Academic orientation, as measured through parental pressure for the school to perform well academically is important, as are the limitations imposed by the timetable of work-related programs. Schools that deviate from the norm (single-sex schools, the small number of schools that do not see themselves as competing with other schools and the few which stream either all or no subjects) perform better than average, as do those with high proportions of students from language backgrounds other than English. The analysis further shows that resources do have some impact. On average, schools with lower student—teacher ratios obtain slightly better TERs, and student fees contribute more to school funds among schools in the high-performing cluster.

Many high-performing schools also have positive ‘idiosyncratic’ factors that contribute to high TERs. This term is used throughout the paper to denote aspects of an individual school’s performance that can be identified statistically but which cannot be explained further using the LSAY data. Idiosyncratic effects reflect a given school’s overall ‘ethos’, which has an important influence on individual student achievement.

Schools in the low-performance group have measured attributes that are not conducive to high TERs, as well as negative idiosyncratic traits. This picture is complicated by the fact that some low-performing schools have students who are likely to do well regardless of the school’s particular characteristics, just as some high-performing schools will have students who get low TERs. Overall, the magnitudes of the differences are sizeable, in that the measured school attributes of high-performing schools add ten to 15 points to the average TER compared with the low-performing schools. While school idiosyncratic effects have a small positive effect on most high-performing schools, their impact on low-performing schools can be quite detrimental.

With respect to university enrolment, measured school characteristics in high-performing schools generally have a positive impact on university enrolment, and an increasingly negative impact as school performance diminishes. Compared with the effect realised through TER, however, young people’s individual characteristics play a much stronger role with respect to university enrolment than the characteristics of their schools, regardless of the performance cluster.

1 At present, the Australian Tertiary Admission Rank (ATAR) is used as a nationwide university entrance score. However, at the time of data collection respondents reported state-based tertiary entrance rank (TER) or equivalent scores. The term ‘TER’ is used throughout this report to denote respondents’ university entrance scores.
2 The performance measure used controls for individual student characteristics.