This paper uses data from the My School website to explore some indicators of change in the equity of schools since the evidence on which the Gonski panel based its findings about school funding and inequality was obtained. At the time of writing there is a bare three years since the release of the Gonski Report. Nevertheless there have been several significant developments in the state of education funding, in student outcomes and in the political landscape around education funding that make it timely to address these changes

Bernie Shepherd

English

Analysis and Policy Observatory (APO)

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Equity in Australian Schooling 
 
An Update 
 
 
 
Prepared for the "Need to Succeed" Symposium 
23 October, 2014 
 
 
<Revision 2> 
 
 
 
 
 
 
Bernie Shepherd AM FACE 
Chris Bonnor AM FACE FACEL 
  
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Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
What can the My School website data tell us about whether equity in schools has 
drifted in one direction or the other since the Review of Funding for Schooling 
(‘Gonski Review’) produced its report? 
 
The Review Panel's report had a great deal to say on the question of equity and its 
recommendations are framed around the concern that any system of funding should 
have equity of opportunity for Australian students as one of its central goals.  In 
Chapter 4 of the report, the panel lists a number of principles, including: 
 
• Public funding should be allocated in a fair, logical and practical way so 
that schools with similar characteristics and student populations have similar 
access to public funding, taking into account, in the non-government sector, 
the capacity for a contribution from private resources. 
• Funding should be allocated to schools and students on the basis of need, in 
particular to ensure that differences in educational outcomes are not the result 
of differences in wealth, income, power or possessions. 
• Funding from all sources should be sufficient to ensure that all Australian 
students have the opportunity to receive a high standard of schooling.1 
 
This paper uses data from the My School website to explore some indicators of change 
in the equity of schools since the evidence on which the panel based their findings 
was obtained. At the time of writing there is a bare three years since the release of the 
Gonski Report. Nevertheless there have been several significant developments in the 
state of education funding, in student outcomes and in the political landscape around 
education funding that make it timely to address these changes. 
 
Although not primarily intended for that purpose, the data published on the My School 
website could potentially have a good deal to say on equity matters, since it carries 
comprehensive information about school demographics, outcomes and finances over 
several years. The architects of the website had aspects of equity in mind with their 
development of the Index of Community Socio-Educational Advantage (ICSEA) 
which assesses a number of non-school variables that are known to have an impact on 
school outcomes.  The index is designed to establish the “statistical similarity” of the 
socio-educational setting of schools in order to provide a basis for fairly comparing 
outcomes. 
 
The ICSEA has been something of a work in progress since 2009. In 2009, the 
ICSEAs were based on readily available, but quite coarse-grained, census data. Since 
that time, the calculation has been based more and more upon individual student 
family information: a more reliable source, although collecting it has problems of its 
own. Still, each succeeding edition has inspired increased levels of confidence. 
 
  
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Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
Equity according to the Funding Review 
The Gonski panel defined equity as an aspiration that: 
 
"differences in educational outcomes are not the result of differences in 
wealth, income, power or possessions."2 
 
Early in their discussion of equity they quoted this graph of social gradients in PISA 
reading literacy from a 2011 COAG report. 
 
 
Figure 1  Social Gradients in PISA reading literacy 2009 quoted in the report of the funding review 
It shows trendlines for the PISA reading literacy results of a number of countries that 
we often compare ourselves with, along with the OECD average. The horizontal scale 
is the socio-economic status of the students and the vertical scale is their reading 
scores. For all of the countries shown, the higher the SES of the students, the better 
their reading scores. The slope of that kind of graph is referred to as a "social 
gradient", since the slope is determined by social factors. 
 
The reality that the graph is reflecting is that the students' socio-economic status is 
having a large say in determining how well the students learn to read and that's an 
equity issue.  It is not unimportant that the steepest line shown here – indicating the 
greatest impact of SES on reading in 2009 – is the one belonging to Australia. 
 
Since the My School data includes NAPLAN test averages and ICSEA measures, the 
ingredients exist for a similar presentation of outcomes against, in this case, the  
socio-educational factors measured by ICSEA.  We could do this for each NAPLAN 
domain and each cohort, but to obtain a more generalised picture, it is useful to 
combine them in a statistically appropriate way that reflects the overall efficacy of 
each school’s performance. The NAPIndex used in this analysis is such a measure, 
combining the results of different cohorts equally and weighting literacy-based 
domains equally with numeracy results.  The overall average for the NAPIndex is 
500: numerically similar to NAPLAN scores … but quite different from them. 
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Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
Then and now 
 
To apply this idea, figure 2 shows trendlines3 for 2010 (blue) and 2013 (red), with the 
actual data points obscured for clarity and privacy.  Since the ICSEA is the 
determining variable, we can call the slope of the trendlines we get here a Socio-
Educational Gradient (SEG). 
 
We see at once that the slopes of the plots are different, with the data for 2013 
indicating a steeper result than that for 2010.  Some caution is needed at this point.  In 
order that student progress can be tracked from Year 3 through to Year 9, NAPLAN 
results are carefully crafted to be comparable from year to year.  However, as noted 
earlier, the ICSEA measure has evolved somewhat over the years and we have to 
allow that - certainly in the earlier years - there is variability in the index that might 
not reliably reflect the socio-educational situation of each school’s community. 
 
 
Figure 2  SEG of NAPLAN Indices for all school types; 2010, 2013 
With that caveat clearly in mind, we nonetheless note that the socio-educational 
gradient of NAPLAN performance appears to have increased over the years from 
2010 to 2013.  If this is an accurate representation of the situation, then school-to-
school equity has declined measurably over the period, with high-ICSEA schools 
improving and low-ICSEA schools declining in performance. 
 
It would be unsafe on the basis of these results alone to draw anything other than a 
suspicion, albeit a fairly strong one, of declining equity; we should look to other 
evidence as well.  Perhaps the most unsettling feature of this result is that it does not 
give us any reason to think that equity has actually improved over the period. 
 
2010:  32% 
2013:  37% 
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School ICSEA 
Socio-Educational Gradient of Aggregated  School NAPLAN Indices 
2010, 2013 
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Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
SEG in other contexts 
 
If we confine ourselves to just the most recent (i.e. 2013) data, we find some 
intriguing results in comparing the SEGs for particular subsets of schools.  
City and Country 
A division that is of particular interest relates to schools in metropolitan and 
provincial areas. Figure 3 shows how schools in those categories line up against their 
ICSEA.  
 
 
Figure 3  SEG for provincial and metropolitan schools; 2013 
The most striking observation about this view of the data is that the performance of 
metropolitan schools is much more strongly affected by ICSEA than that of provincial 
schools.  We tend to think of more remote schools when we think of inequity, but in 
terms of school-to-school differences, it seems to be in metropolitan areas that the 
differences related to advantage are greatest.  We may wonder why this is the case. 
A Comparison of School Types 
 
What differences exist among the different levels of schooling recognised in the My 
School data: primary, secondary and combined?  Figure 4 shows us that secondary 
schools are considerably more differentiated by socio-educational advantage than 
primary schools, with combined schools in between.  Again, this raises questions: 
firstly about what the data is saying, but also about why it is the case. 
 
That's a lot of questions lined up already, but before we have a look in directions that 
might provide clues, we should examine the situation of the secondary years more 
closely, with NSW as a case in point (figure 5).  
 
Metropolitan: 42% 
Provincial: 33% 
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Socio-Educational Gradient by Location 
2013 NAPLAN Indices 
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Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
 
Figure 4  Socio-educational gradient by school type; all schools, all sectors; 2013 
Figure 5  SEG of NSW secondary and combined schools by geo-location 
Our remote secondary schools in NSW have definitely been struggling: the fact that 
they are only modestly differentiated at 27% pales alongside the fact that they need 
far better outcome performance overall (recall that the average NAPIndex is 500). 
Our provincial schools do a little better performance-wise, but they are more 
influenced by socio-educational advantage. The NSW metropolitan schools, at an 
SEG of 50%, represent the most highly differentiated group of its kind in the country. 
Primary: 35% 
Combined: 37% 
Secondary: 43% 
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Socio-Educational Gradient by School Type 
2013 NAPLAN Indices 
Metropolitan = 50% 
Provincial = 34% 
Remote = 27% 
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Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
What is going on? 
 
Coming to the "why is it so?" questions, the My School data holds some clues. Figure 
6 shows five graphs superimposed, one for each year from 2009 to 2013. Each graph 
shows the total full-time-equivalent enrolments in schools of all types, in all sectors, 
at points along the ICSEA scale. The median values for each year are labelled.  These 
are the points on the ICSEA scale where exactly 50% of students sit either side1.  
 
Perhaps the first thing we note is that the median points have been shifting to the right 
(i.e. high-ICSEA end) by close to one ICSEA unit per year.  While this may not seem 
much, one unit around the middle of the scale is the population equivalent of around 
35 schools, or something like 15,000 students. 
 
 
Figure 6  Student enrolment (EFT) distribution by ICSEA 2009-13 
The second thing to notice is that the graphs overlap almost perfectly, but the areas 
where they don't overlap (i.e. the 'colour-fringed' zones) give us important 
information. The schools that have grown most over recent years have been the 
schools above the ICSEA average of 1000. 
 
What this is telling us is that over the period since Gonski reported, schools of 1000 
ICSEA or more have taken an increasing share of the student population. The detail of 
the data says that the shift is not just at the middle, but there is a drift towards the right 
of the graph across most of the range (see table 1, table 2).  Some of the growth will 
be due to natural increase in Australia's student population which, in the absence of 
other data, we might assume would impact evenly across the ICSEA range.  From the 
                                                 
1 In interpreting the data here (as elsewhere in this paper) it should be recalled that the methodology 
and data sources for socio-educational advantage calculations have changed over the years, however 
the final index itself continues to be distributed around a mean of 1000 and SD of 100. 
2009: 1022 
2010: 1023 
2011: 1024 
2012: 1024 
2013: 1025 
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2013 ICSEA 
Student EFT distribution by ICSEA; 2009-2013 
2009 2010 2011 2012 2013
8 
Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
pattern of the shifting percentiles, we actually see that there is a rightwards "drift" 
superimposed on the natural growth. 
 
Percentile\Year 2009 2010 2011 2012 2013 
10th 929 930 931 932 932 
20th 957 959 959 960 961 
30th 982 983 983 984 985 
40th 1003 1004 1005 1006 1006 
50th 1022 1023 1024 1024 1025 
60th 1042 1042 1043 1044 1044 
70th 1066 1067 1069 1069 1070 
80th 1097 1098 1099 1100 1101 
90th 1138 1138 1139 1139 1140 
Table 1  School ICSEA values by population percentile; 2009-2013 
ICSEA \ Year 2009 2010 2011 2012 2013 
700 0.43% 0.43% 0.42% 0.42% 0.40% 
800 0.82% 0.82% 0.80% 0.77% 0.78% 
900 4.16% 4.16% 4.10% 3.99% 3.94% 
950 16.85% 16.49% 16.21% 16.89% 16.70% 
1000 38.55% 38.02% 37.57% 37.11% 36.79% 
1050 63.59% 63.27% 62.92% 62.61% 62.36% 
1100 80.50% 80.35% 80.13% 79.98% 79.83% 
1150 91.87% 91.84% 91.78% 91.76% 91.70% 
1200 98.81% 98.81% 98.80% 98.80% 98.81% 
Table 2 Cumulative school population percentage at ICSEA points; 2009-2013 
If, as seems probable, most of that drift is due to the physical transfer or diversion of 
students to higher ICSEA schools in their locality or elsewhere, then it would likely 
be a direct consequence of school choice policies put in place by successive 
governments and supported via their funding measures. 
 
Figure 7  Student EFT distribution by ICSEA for metropolitan and provincial schools 
1025 
1044 
981 
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ICSEA 
Student EFT vs ICSEA; 2013 
All Schools Metropolitan Provincial
9 
Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
Figure 7 gives us an insight into how city-country SEG differences arise. Detail in the 
data shows that 73% of metropolitan students are in schools with above-average 
ICSEA ratings.  Some will see great merit in that statistic, since more students will be 
situated in more advantaged schools, however we must also consider what it means in 
equity terms for those students in the remainder of the schools. 
 
In particular, we might examine the equity implications when we have a sizeable 
minority (27%) of metropolitan students and a small majority of non-metropolitan 
students (~63%) in schools with ICSEAs below 1000 and showing, on earlier 
indications, relatively modest to poor NAPLAN performance. 
 
If we would be correct in speculating that the students moving to the higher-ICSEA 
schools would include a preponderance of the students from relatively advantaged 
families, then we are describing a situation of concentrating disadvantage among the 
other schools.  Research shows that the concentration of disadvantage brings its own 
impost on outcomes in addition to that of the disadvantage itself4. 
 
What is clear is that socio-educational advantage, which is what ICSEA measures: (i) 
is quite strongly associated with performance, by definition and (ii) is not evenly 
spread through our schools. In fact, the indications are that separation is increasing. 
 
Although other countries – including some more educationally successful ones – have 
made different decisions, we have declared as a society that the free choice of 
schooling is a virtue to be supported by public policy and funding on the implicit 
assumption that it is available to all. 
 
What we are seeing here is arguably one consequence of that decision. Unless we are 
prepared as a society to say that the families and students who do not or cannot 
choose a "more advantaged" school are of no importance, then our system must 
ensure that their school – and their educational outcomes – are the best they can be. 
How are we responding to this situation? 
 
I will finish by updating another graph from the Gonski report. It's the one that 
compares the distribution of socio-educational advantage across our schooling sectors 
in terms of the "Quarter" divisions, where Quarter 1 is the lowest and 4 is the highest. 
 
With blocks of data the size of these, there are few differences and some that exist in 
figure 8 may relate to differences in the methods of calculating SEA referred to 
earlier. Looking across the 50% line, we see that the middle student in the government 
system is still near the top of Quarter 2 as was the case in 2010. The middle student in 
the Catholic system is still a Quarter 3 student. We see that nearly half of the students 
in the Independent sector were and still are from Quarter 4. 
 
One of the most tangible and relevant manifestations of our national approach to 
equity since the Gonski Review has been the continued distribution of government 
funding to these sectors.  
 
10 
Equity in Australian Schools – an Update 
Bernie Shepherd  26 October 2014 
 
Figure 8  SEA Quarters distribution; 2010 and 2013 
As My School data shows, government schools, with 56% of their students in the Q1 
and Q2 groups received per-student funding increases over the period averaging 3.6% 
per annum, which is close to the inflation figure. Catholic schools, with fewer (41%) 
of their students in Q1/Q2 received government-sourced increases of 5.0% per-
student, per annum over the same time. Independent schools with even fewer Q1/Q2 
students (26%) had their per-student government funding raised by 5.5% per annum. 
To conclude … 
 
In examining the entrails of My School since 2010 for signs, it would seem that the 
indicators of educational need have been pointing one way, while public funding for 
schools has been continuing in the other. This needs to change. The New South Wales 
government is to be congratulated for being the earliest and most enthusiastic adopter 
of the Gonski funding principles outlined at the start of this paper. It is imperative that 
other jurisdictions follow their lead. 
 
Bernie Shepherd AM FACE 
beshep@optusnet.com.au 
October, 2014 
 
                                                 
1 Review of the Funding of Schooling Report, p 149 
2 Review of Funding for Schooling Final Report; Dec, 2011, p 105 
3   Throughout this paper, the trendlines are derived from Ordinary Least-Squares Regression. 
4 NSW submission to Gonski: NSW Government, Review of Funding for Schooling New South Wales 
Government Submission to the Australian Government, September 2011; 
https://www.det.nsw.edu.au/media/downloads/about-us/news-at-
det/announcements/yr2011/schoolfundingreview/submission.pdf 
Also Richard Teese; From opportunity to outcomes. The changing role of public schooling in Australia 
and national funding arrangements.  http://resources.news.com.au/files/2012/01/31/1226258/621517-
aus-news-file-public-schools-in-australia-report.pdf 
35% 
22% 
13% 
30% 
15% 9% 
20% 
22% 
15% 
26% 
26% 
17% 
22% 
28% 
26% 
23% 
30% 
27% 
22% 28% 
47% 
21% 29% 
47% 
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50%
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100%
Government Catholic Independent Government Catholic Independent
2010 2010 2010 2013 2013 2013
SEA Quarter Distribution by School Sector; 2010, 2013 
Q1 Q2 Q3 Q4


Equity in Australian schooling: an update

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Equity in Australian schooling: an update

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