DISCUSSION PAPER
REVIEW OF THE LOW SOCIO-ECONOMIC STATUS LOADING
Purpose
To outline the current arrangements, issues and key policy questions to guide stakeholder
consultations for the review of the low socio-economic status (SES) loading.
Government’s commitment to review the loadings
On 14 January 2014, the Australian Government Minister wrote to key education
stakeholders confirming the Government’s commitment to needs based funding over the
next four years, including a base per student amount plus loadings to address educational
disadvantage.
Rationale for a low SES loading
The COAG Reform Council Report for 2010 found that, based on 2009 PISA data, the socioeconomic background of Australian students had a greater impact on their reading
performance than for students in five of the six countries that significantly outperformed
Australia.
Australia’s 2009 PISA results show that across all literacy domains, the higher the level of
student socio-economic background, the higher the student performance. The data also
reveals that one in four Australian students from the lowest SES backgrounds performed
below the proficiency baseline across each of the PISA domains. In relation to the reading
literacy domain, the gap between Australian students from the highest and lowest SES
backgrounds was found to be equivalent to almost three years of schooling.
As part of their research for the Review of Funding for Schooling panel, the Nous Group
conducted an analysis which concluded that much of the variability in performance across
schools in Australia is explained by Socio-Educational Advantage (SEA). The analysis
demonstrated a strong relationship between a school’s average Index of Community SocioEducational Advantage (ICSEA) value and the school’s average results.
Intent of the low SES loading
The low SES loading is designed to provide additional resources to support schools to
address the particular educational needs of students from educationally disadvantaged
backgrounds and to improve educational outcomes for these students.
The loading is not intended to address all aspects of disadvantage associated with
educational disadvantage. Rather, it aims to address the educational disadvantage of
students whose families may not be well equipped to support their child’s participation and
achievement in education, as reflected in the lower occupation and education levels of their
parents. Many studies show positive correlations between mothers’ educational attainment
and children’s wellbeing, cognitive development and academic outcomes.
Options for measuring educational disadvantage
At the national level, there are a number of different forms of educational disadvantage
measures used in the Australian schooling system, noting that most states have their own
measures developed for specific purposes such as administering grants.
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In general, these measures can be categorised as follows:
• ‘Individual based measures’ which take into account an individual’s personal
educational disadvantage characteristics
• ‘Area/community based measures’ developed by compiling educational disadvantage
characteristics of all individuals living in an area
• ‘Mixed measures’ combine both individual and area based measures.
Information on the four key educational disadvantage measures used at the national level is
set out below.
Socio-educational advantage (SEA)
SEA is a measure of a student’s socio-educational advantage. Developed by the Australian
Curriculum, Assessment and Reporting Authority (ACARA), it is derived from data relating to
parental education and occupation. Derived from the student level SEA, the school level SEA
is published on My School in the form of the distribution of students in a school across four
quarters representing the relative educational disadvantage (“bottom quarter”) through to
relative advantage (“top quarter”).
ACARA calculates SEA from parental education and occupation data provided by states and
territories and non-government schools. The data is drawn from enrolment records where
parents are asked questions about their education and occupation. Missing data is imputed.
SEA is what is currently used to calculate the low SES loading. The distribution of SEA in as
school is published on the My School website and ACARA use the SEA in the construction of
the Index of Community Socio-Educational Advantage.
Index of Community Socio-Educational Advantage (ICSEA)
ICSEA is calculated by ACARA. It is a scale that represents the levels of educational
advantage at Australian schools. ICSEA was developed to enable fair and meaningful
comparisons of the literacy and numeracy performance of students in a given school, as
assessed by the National Assessment Program—Literacy and Numeracy (NAPLAN) tests,
with the performance of students at schools catering for statistically similar students in
terms of the level of SEA.
ICSEA takes into account socio-economic factors related to the student, including parental
occupation and education and school level variables, including the geographical location and
the proportion of Indigenous students the school caters for. ICSEA is used to make
appropriate comparisons of student achievement across schools.
As a result of recent improvements to ICSEA data, recent modelling of 2012 data by ACARA
indicates that ICSEA can explain 81 per cent variance when school performance is predicted
by its ICSEA.
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Socio-economic status score (SES)
The Australian Government Department of Education (the Department) calculates the SES
score for each non-government school. The SES calculation involves linking student
residential address data to Australian Bureau of Statistics (ABS) national Census data to
obtain a measure of the capacity of the school community to support its school. The Census
data used to develop the measure includes occupation, education, household and family
income. A school’s SES score is an average of the student scores based on their area of
residence.
Under the Australian Education Act 2013, Australian Government funding for nongovernment schools incorporates a capacity to contribute calculation, which is a measure of
the capacity of the school community to contribute towards the operating costs of the
school. This percentage is based on the SES of the school or the Approved System Authority
and is applied to the estimate of a primary or secondary school’s base amount for a
programme year to determine the public contribution towards these base amounts. Note
the capacity to contribute setting is not applied to loadings.
Socio-economic Index for Areas (SEIFA)/Socio-economic Index for Individuals (SEIFI)
SEIFA is an area based measure of SES developed by the ABS. SEIFA uses Census data to
create a composite index based on the proportion of the population in an area meeting
various criteria for disadvantage.
SEIFI is a multi-dimensional measure of SES designed to measure an individual’s relative
access to material and social resources based on personal attributes such as income,
educational background or housing status using information from the 2006 Census and
produced by the ABS.
Impact of concentration of educational disadvantage
When compared to other high-performing OECD countries, Australia’s schooling system is
characterised by a strong concentration of disadvantaged students in certain schools.
Research commissioned by the Nous Group found that one-third of all Australian schools
serve a student population where the average socio-economic background of students is
below the national average. Within these schools, the majority of students are from the
lowest socio-economic backgrounds (58 per cent), with much smaller proportions of
students from middle (32 per cent) and high (just 11 per cent) socioeconomic backgrounds.
The measure of educational disadvantage concentration for the purposes of calculating the
low SES loading is based on data collected from schools and systems by ACARA. Socio
Educational Advantage (SEA) Quarters have been calculated and published by ACARA since
2009, and measures the occupational and educational status of parents/guardians of school
students. It includes occupation, completed school education and highest level of postschool education.
The percentage of quartile 1 students in a school is based on the number of students who
are in the lowest 25 per cent of all students nationally ordered from the lowest SEA score to
the highest. The number of quartile 2 students in a school is based on the number of
students who are in the second lowest quarter (from 25 to 50 per cent) of all students
nationally ordered from the lowest SEA score to the highest.
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2010 SEA data
2010 SEA data were originally used to calculate the payment of 2014 school funding
entitlements. This was due to perceived inconsistencies with the 2011 and 2012 data sets.
For most schools, 2010 SEA is based on data that is collected directly by schools from
parents at the point of student enrolment, but where this is not available for schools data is
sourced indirectly from the ABS population Census based on student residential addresses
held by the school.
The Review of Funding for Schooling panel recognised that the impact of disadvantage is
broader than the lowest SEA quarter alone. For this reason it included in its modelling,
loadings for the proportion of students in both the lowest and the second lowest SEA
quartile, noting that the loading for the second lowest quartile was at half the rate for the
lowest quartile. This responded to evidence that a significant proportion of students in the
second lowest SEA quarter also experience poor educational outcomes.
The loading proposed by the panel also was based on set thresholds where any low SEA
concentration in a certain range attracted the same loading percentage.
While the final loading retained a loading for the both bottom quartiles, the loading moved
to a linear scale that increased the loading percentage for every increase in the
concentration up to a maximum (described below).
Calculation of the low SES loading
The Schooling Resource Standard (SRS) model calculates a low SES loading for a school
based on the proportion of students at the school who are in the lowest two SEA quartiles.
The loading percentage applies to the per student amount to derive the value of the
loading. The loading percentage that applies increases with the proportion of students in
each quartile:
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A 15 per cent loading - equals $1 391 per primary student and $1 829 per secondary
student for the first student in the lowest SES quartile (Q1) increasing up to a
maximum of a 50 per cent loading where the concentration of students in Q1
reaches 75 per cent – equals $4 635 per primary student and $6 096 per secondary
student.
A 7.5 per cent loading – equals $695 per primary student and $914 per secondary
student for the first student in the second lowest SES quartile (Q2) increasing up to a
maximum 37.5 per cent loading where the concentration of students in Q2 reaches
75 per cent – equals $3 477 per primary student and $4 572 per secondary student.
Applies to the lowest 50 per cent of students – approximately 9,000 schools,
benefiting 1.7m students.
Improvements in 2013 SEA data
The 2010 SEA quartile data is now three years old and it is likely that student body
compositions have changed across schools since 2010.
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During 2013, ACARA conducted a review of the process for calculating ICSEA and SEA. At the
request of Education Ministers, ACARA investigated the possibility of using student-level
data, obtained directly from students’ families, to calculate ICSEA, rather than indirect (ABS)
Census data.
The modelling undertaken indicated that by using direct student-level parent occupation
and parent education data, it is possible to obtain a stronger measure of SEA, with improved
statistical reliability of ICSEA and reduced year-to-year variability. As a result of the
enhancement of the ICSEA calculation process, the 2013 ICSEA and SEA quarters for schools
have been calculated using only the direct parental background data.
The new process improves the calculation of the SEA component by applying a single
measurement model to estimate the indicator for a student’s SEA rather than treating
responses to six parental background questions as separate indicators of educational
advantage.
The benefit of this approach is that the measurement model is able to generate estimates of
student socio-educational advantage even when some parental data might be missing,
thereby mitigating the impact of missing data.
In May 2014, the decision was made by the Department to update the SEA data to the 2013
dataset for the July 2014 payment of school funding entitlements. The use of the full 2013
data set will significantly reduce the number of schools with imputed values and address the
issue of new schools without 2010 values. Anecdotal feedback has suggested that the 2013
SEA percentages are more consistent with school expectations.
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