Policy Issues for Australia’s Education Systems:
Evidence
from International and Australian Research
Gary N. Marks
Julie McMillan
John Ainley
Australian Council for Educational Research
and
Melbourne Institute for Economic and Social Research
Citation: Marks, G., McMillan, J., Ainley, J.,
(2004, April 20). Policy issues for Australia’s education systems: Evidence
from international and Australian research.
Education Policy
Analysis Archives, 12(17). Retrieved [Date] from
http://epaa.asu.edu/epaa/v12n17/.
Abstract
Our purpose here is to discuss education policy issues in the
context of empirical evidence. We note that many commonly held
beliefs about Australian education such as, the relative
performance and participation levels of Australian students; the
importance of socioeconomic background on educational outcomes
both relative to other countries and changes over-time; gender
differences in mathematics and science; and the labour market
situation of early school leavers; are not supported by empirical
research. Such findings have implications for government policies.
We also question current policy directions toward increasing Year
12 participation, expanding both secondary and post-secondary
vocational education and reducing class sizes. It is hoped that
the discussion will provide stimulus to evidence-based debates
about Australian education. |
School Education
Student Performance
A fundamental point about Australian education is that the
performance of Australian secondary school students is high by
international standards. The 1994 Third International
Mathematics and Science Study (TIMSS) found that Australian
performance in mathematics in the junior secondary years was lower
than only eight (out of 45) countries. The performance of
Australian students was significantly better than comparable
countries such as New Zealand, England and the United States. The
performance of Australian students was similar to the performance
of students in Canada, Ireland, Sweden and France. In science,
only four countries outperformed Australia: Singapore, Korea,
Japan and the Czech Republic. Australia recorded science
achievement levels similar to that for England and the United
States, as well as most of the countries that were similar to it
in mathematics (Lokan et al., 1996:15-16).
In the 1999 TIMSS study, Australian students performance in
mathematics was again well above the international average by
substantial 0.4 of a standard deviation. Australian performance
was significantly lower than six countries: Singapore, Korea,
Chinese Taipei, Japan and Flemish Belgium. It was not different
from a second group of countries that included the Netherlands,
Canada, Finland, and the Czech Republic. It performed
significantly better than the United States, England and New
Zealand (Mullis et al., 2000:32). In science, Australia also
performed above the international average by about 0.5 of a
standard deviation. Only Chinese Taipei scored significantly
higher than Australia. Australia was not different from Singapore,
Japan, Korea, the Czech Republic, England, Canada and Hong Kong.
Its students outperformed those in the United States, New Zealand
and Italy (Martin et al., 2000:32).
In the recent 2000 PISA study of 15 year olds in over 30
industrialised countries, Australian students performed well above
the OECD average in the three domains of reading, mathematics and
science. Students in Finland were the only national group that
performed significantly better in reading literacy than Australian
students. Students in Japan were the only ones who performed
significantly better than Australian students in mathematics.
Japanese and Korean students were the only national groups that
performed significantly better than Australian students in science
(Lokan et al., 2001:20-33).
Therefore, there is consistent evidence that Australian
students are performing at levels that can be regarded as very
good. Their high performance is not limited to a single
subject area. This conclusion is no doubt surprising to many who
are mindful of the inadequacies of the Australian education
system. The media generally overlooks this ‘good news’
finding and many involved in Australia education are not aware of how
well Australian students perform relative to students in
comparable countries. So it is important to find out what
Australia is ‘doing right’; is it the high quality of
teaching or teacher education, the competition between government
and non-government schools, the academic environment of schools,
the curriculum, or the community’s interest in
students’ education. Although many of these explanations may
be dismissed out-of-hand, the question remains as to why
Australian students are performing much better than students in
comparable countries. Since Australia spends slightly less of its
GNP on education than other comparable countries (Note 1), it could be argued that
Australia spends its resources more effectively than other
countries. So understanding why Australian student performance is
high by international standards is also important to policy makers
who need to know where the education dollar is best spent.
Although the performance of Australian students is higher than
most comparable countries, there is no evidence that the absolute
performance of Australian students has improved over time. Rosier
(1980) focussed on changes in mathematics achievement between 1964
and 1978 and concluded that there had been a slight decline in the
performance of 13-year-olds over that period time. Focusing on a
longer time span (1964-1994) Afrassa and Keeves (1999) concluded
that there was a decline in the mathematics performance of
13-year-olds. The magnitude of that decline was approximately 30
scale points (or 0.3 standard deviations), a non-trivial decline.
Over the period from 1975 to 1998 there was no change in
performance in reading or mathematics (Rothman, 2002). Comparison
of science performance between 1994 and 1998 suggests that the
relative position of Australia in the country league table of
student performance improved (Martin et al., 2000:35). However, in
absolute terms there was little change in mathematics and only a
slight improvement in science.
Therefore, the performance of Australian students is high by
international standards, but there is no evidence that this high
standing is due to improvements in student learning and thus
policy initiatives over the last 30 years. There are a number of
strong arguments to further increase the achievement levels of
Australian students. For individual students, proficiency in
literacy and numeracy is by far the most powerful influence on a
range of educational outcomes including early school leaving,
tertiary entrance scores, and participation in higher education
(Marks et al., 2000; Marks et al., 2001; McMillan & Marks,
2003). In addition, literacy and numeracy are important influences
on labour market outcomes such as not becoming unemployed, the
duration of unemployment, and income (Marks & Fleming, 1998b,
1998c; Marks, forthcoming; McMillan & Marks, 2003). The
International Adult Literacy Study shows large labour
market differences between high and low literacy groups (Kirsh et
al., 1993). At the macro-economic level, there is strong case to
improve student performance in literacy and numeracy since the
economy is likely to be increasingly reliant on industries based
on the manipulation of symbols (words and numbers).
An important policy question is to how to improve the
performance of students at the bottom end of the distribution.
Poor skills in literacy and numeracy are the strongest risk factor
for unsuccessful school to work transitions—a stronger risk
factor than low socioeconomic background. It is possible for a
country to achieve both high average levels of student performance
and small variation. This involves policies that lift the
performance of weaker students without undermining the performance
of other students.
Educational Participation In Senior Secondary School
One of the most dramatic changes that has occurred in
Australian education over past two decades is the rapid increase
in Year 12 participation from 35 per cent in 1980 to a peak of 77
per cent in 1992.. This rate has since declined before
rising again to around 76 per (ABS, 1984-2002). However, participation in the final year
of school in Australia is lower than that in many other countries.
According to the OECD, 78 per cent of sixteen year olds in
Australia are enrolled in upper secondary school. This figure is
lower than the OECD average of 84 per cent and is considerably
lower than enrolment rates at the same age in Austria (90 per
cent), Belgium (97 per cent), Canada (85 per cent) and Sweden (96
per cent) (OECD, 1998:170). However, school completion in
university-oriented programs in Australia is higher (66 per cent)
than the OECD average (OECD, 2001a:146).
The lower level of participation in Australia poses the policy
question of whether participation rates should be increased. This
involves an assessment of how those who do not complete secondary
school are faring in the labour market. The early labour market
experiences of non-completers are highly dependent upon the
economic climate. Research on non-completers who entered the
labour market during the early 1990s showed that this group were
experiencing substantially poorer labour market outcomes than an
equivalent group who had left school a decade earlier (Lamb et
al., 2000). On the other hand, research on a more recent group of
non-completers who entered the labour market later in the 1990s
when the economy was healthier, presents a far more positive
picture (Marks & Fleming, 1998a). Subsequent work following
the progress of this group until age 19 shows increasing levels of
full-time work, incomes and occupational status (McMillan &
Marks, 2003). Among those who did not go to university, there
was little difference between early school leavers and
school completers in full-time work in the initial years
after the leaving school. It
was non-completers who left school in Years 11 and Year 12 that
were having problems securing full-time work (Marks et al.,
Forthcoming). Furthermore, school completion in itself has little
influence on labour market outcomes among 21 to 25 year olds
(Marks et al., 2003).
Those who do not complete secondary school have poorer labour
market outcomes than those with university qualifications. It is
well established, both in Australia and overseas, that university
qualifications are associated with higher incomes, less
unemployment, and more steeply rising occupational and income
trajectories. When making comparisons between non-completers and
those school completers who do not pursue university studies, the
evidence that completing school is beneficial is equivocal. In
some regards non-completers fare better than school completers who
do not enter higher education: they are more likely to be in
full-time employment and receive higher hourly earnings, at least
initially. However, in other regards non-completers experience
less successful transitions from school: compared with completers
who did not enter higher education, male non-completers are more
likely to be unemployed, and female non-completers are more likely
to be outside the labour force and not studying (McMillan &
Marks, 2003).
During the last decade, one policy response to the labour market
outcomes of school non-completers was to increase participation in
school. This involved broadening the curriculum by including
courses that potential school leavers would find attractive so
would remain at school. This policy direction was in part a
product of research conducted during the 1980s and early 1990s
that argued that non-completers left school because they were
alienated from the academically orientated curriculum. This is
undoubtedly true for some students although the degree of student
antipathy with school has been over-stated. Longitudinal research
on a cohort of young people who were in Year 9 in the mid 1990s
shows that the majority of non-completers leave school for
positive work related reasons. About 50 per cent say the main
reason they left school was to get a job or an apprenticeship
(whether or not they actually had a job to go to), and a further 5
per cent say they wanted to earn their own money. Only 13 per cent
said their main reason for leaving was that they did not like
school, only 6 per cent left because of the subject choice at
their school, and only 2 per cent said they left on the advice of
teachers. Interestingly, only 1 per cent cited financial reasons
(McMillan & Marks, 2003). Although, subjective evaluations may
include post-hoc rationalizations –non-completers
are most often students with lower achievement levels, so are
struggling in senior secondary school–these data do
indicate that schools and the school curriculum are a much smaller
influence on school leaving than generally believed. The policy
implication of these results is that further efforts to make Year
12 more ‘attractive’ to potential school leavers may
not be the most appropriate strategy.
Given that many non-completers have positive reasons for
leaving school and the majority do obtain full-time work, is there
any reason why a student, keen to leave school and has a clear
intention of working in a particular type of job should not do so?
Analysis of the labour market outcomes on youth cohorts aged
between 17 and 25 shows that prior experience of full-time work
has considerably larger effects than qualifications on subsequent
full-time employment (Marks et al., Forthcoming; McMillan &
Marks, 2003). Experience in full-time work provides a strong basis
for continued full-time work. The strong influence of prior
experience in full-time work on subsequent full-time employment
appears to becoming stronger (Marks & Fleming, 1999). So
delaying entry to the labour market for one or two years may not
beneficial given the importance of labour force experience.
Increasing school completion is likely to have other
undesirable outcomes. Government school students are more likely
to leave school than non-government students, so if Year 12
participation is increased, students who would have otherwise left
school will be enrolled in government schools. Therefore, the
responsibility of catering for this academically weak group of
students will fall on government school systems while
non-government schools concentrate on maximising the university
entrance performance of their senior students. Thus, the gap in
performance between the government and non-government sectors will
widen and government schools will be increasingly viewed as a
residual category. Parents who can afford to send their children
to non-government schools will do so. The result will be
increasing socioeconomic inequalities in education.
Policy options for students likely to leave school early should
consider the prevailing and future economic conditions, the ease
at which school leavers can later pursue full-time education and
training, the cost to potential employers and the assistance
available to students who make unsuccessful school-to-work
transitions.
Assessments about the current and future state of the youth
labour market provide crucial contextual background for the
formulation of policy options. The substantially more favourable
labour market experiences of school leavers during the late 1990s
compared to the early and mid 1990s, is largely due to the
improvement in the macro-economy. In an analysis of unemployment
in three Australian youth cohorts, a large contextual effect of
the annual unemployment rate was found (Marks & Fleming,
1998b). The OECD reported that, in general, countries with
healthier economies and lower unemployment show more successful
school to work transitions (OECD, 2000b:37-43). Therefore,
low unemployment is a necessary precondition for allowing students to
leave school before completion of Year 12.
A second issue concerns the ease with which school leavers can
later return to full-time education. A problem with early school
leaving is that it reduces options for further (especially higher)
education. Universities typically judge prospective students on
their performance in Year 12, so non-completers face barriers if
they wish to pursue higher education at a later time. Therefore,
encouraging universities to adopt flexible entrance requirements
for young people who do not complete Year 12, and providing other
forms of further education, would represent a policy alternative
to increasing school completion. Many universities already have
some but limited provisions for later age entry.
A third issue is the cost to employers in employing young
people who have just left school. Employers need to be encouraged
to employ those who have not completed secondary school and to
provide associated training to develop their skills. This could
include the further extension of formal training provisions to
industries that do not traditionally take apprentices. This has
been the thrust of the new apprenticeships and traineeship
schemes. Another policy option is to reduce the marginal cost to
employers of employing school leavers.
Finally, it is important to assist those young people who are
experiencing unsuccessful transitions to the labour market.
Estimates from studies of recent school leavers suggest that 10
per cent (or less) of those who do not enter higher education are
facing severe difficulties in obtaining work (Marks et al.,
Forthcoming; McMillan & Marks, 2003). Policies should be
targeted at this small group that are actually experience
difficulties rather than assuming that all school non-completers
are at risk. However, before specific policies can be implemented
closer monitoring the school to work transition is required
because many do not come to the attention of government
departments if they have not applied for social security
benefits.
Vet-in-Schools
In Australia, a number of vocational education and training
(VET) programs are available to students who are still at school
and this has been a substantial area of growth throughout the
1990s. Nationally, approximately one quarter of the student cohort
from Year 9 in 1995 had participated in some form of VET as part
of their studies in Year 11 and 12 (Fullarton, 2001). These data
indicate that some 15 per cent of school students had undertaken
some VET-in-School subjects at either Year 11 or Year 12, and 7
per cent had completed subjects in both Year 11 and Year 12. Only
a few (slightly more than one per cent) had participated in a
school-based new apprenticeship or traineeship. There are
substantial differences among jurisdictions in participation in
VET. The highest level of participation is found in Queensland (41
per cent) and the lowest in Victoria (12 per cent). Participation
in VET in schools is also higher among students from government schools
and with below average achievement levels (Fullarton, 2001).
Lamb et al.
(1998) noted that VET-in-schools tends to attract students with
manual occupational backgrounds.
There is little research on whether VET-in-schools programs
benefit their participants. Malley et al. (2001) argued that
most of the participants in VET in schools would have stayed at
school anyway and that the availability of VET programs did not
encourage potential early school leavers to remain at school.
Fullarton (2001) found that after leaving school the unemployment
rate for the
VET-in-schools group was similar to that for the comparison group.
Furthermore, VET-in-schools does not facilitate entry to a
recognised form of post-secondary vocational education or
training. These results indicate that the labour market outcomes
of VET-in-schools participants should be carefully monitored. It
may be more beneficial for such students to directly enter the
labour market, and have their training needs met by the TAFE system.
Schools are arguably less equipped to provide vocational training
since they usually have only weak links to employers and have
limited financial and human resources to provide suitable
training.
Participation In Higher Education
Another important change in Australia’s education system
is an increasing level of participation in higher education. In 1999, total
higher education enrolments were 686,000, more than twice the
330,000 students enrolled in 1980 (DETYA, 2000:8,15). Estimates
from the Longitudinal Surveys of Australian Youth show that
approximately 40 per cent of recent youth cohorts participate in
higher education. The comparable figure for the early 1980s was 20
per cent (Marks et al., 2000).
Over the last decade, the growth in higher education enrolments
has been between 2 and 10 per cent per annum, a figure that is
much higher than the population growth rate. The OECD reports that
university enrolments in Australia increased by over 25 per cent
between 1990 and 1996. However, the growth in university
enrolments between 1995 and 1999 was considerably less, with
Australia showing the seventh lowest growth of 21 OECD countries
(OECD, 2001a:152).
Overall, the OECD estimates the proportion of the age cohort
entering higher education in Australia at 45 per cent (this figure
includes TAFE diplomas). This participation rate is the same as
the OECD average and comparable with the United Kingdom and the
United States (OECD, 2001a:155).
Attrition from university courses is a concern. An Australian
longitudinal study of the cohorts that commenced university in
1992 and 1993 estimated ultimate completion rates of 72 and 71 per
cent respectively. For the 1992 commencing cohort, 60 per cent had
completed an award in their original university by 1997 and 64 per
cent had completed an award by 1999 (Martin et al., 2001; Urban et
al., 1999). However, attrition in Australia is not particularly
large compared to other countries. The ratio of graduates to
enrolled students in any year is around 27 per cent
for Australia, which compares favourably with the OECD
average of 19 per cent but is less than that
for the United Kingdom and the United States (OECD, 2001a:169).
The labour market outcomes of graduates are superior to those
of non-graduates in terms of both reduced unemployment and higher
incomes. Analysing pathways over a seven-year period (from the
late 1980 to the mid 1990s), only 6 per of graduates (Note 2) experienced
extended periods of unemployment, part-time work, and not being in
the labour market. This compares with between 20 and 30 per cent
of non-graduates (Lamb, 2001:8; Lamb & McKenzie, 2001:25). In
1998, unemployment among 20-24 year old university graduates was
substantially lower (around 3 per cent) than that for other
educational groups. Similar differences are found in most
industrialized countries (OECD, 2000a:270).
The higher income returns from university qualifications are
well documented. The OECD reports higher incomes for university
graduates (compared to the mean income) in all 20 countries
investigated (OECD, 1998:352). For Australia, Borland (2002)
estimates the private rate of return for a university education
among adults at 14 percent equivalent to a lifetime net monetary
gain of nearly $400,000. In the early career, a university
qualification is one of the strongest influences on income,
increasing hourly earnings by around 20 per cent, net of other
influences (Marks & Fleming, 1998c). The increase in income
inequality observed in several countries (including Australia) is
often attributed, at least in part, to increased returns to
degrees.
The issue of increasing participation in higher education
should be considered and debated. There are compelling arguments
in favour of increasing participation. First, there is strong
demand in the labour market for university graduates. The
predictions, 20 years ago, of underemployment and decreasing wages
for graduates has not eventuated. If anything, the strong demand
for graduates is increasing. Second, much of Australia’s
economic and employment growth in the medium- to long-term is
likely to be in industries that employ graduates. In addition,
industries that have traditionally employed students with a
vocational education are likely to become more technologically
sophisticated and require a different set of skills. Finally,
there is considerable unmet demand for higher education. Surveys
of Year 9 students indicate that approximately 70 per cent intend
to go to university. Although not all students in this group are
suited to higher education, it does indicate a much higher level
of demand than supply. The main argument against increasing
participation in higher education is cost. Although the Higher
Education Contribution Scheme (HECS) and other measures have
reduced the per capita cost of university education, most
undergraduate teaching is supported from taxation revenue. Recent
reforms to the HECS system include increasing participation but there
is little debate on what the participation levels should be in 5,
10 or 20 years time and how should it be funded. (Note 3)
Post-Secondary Vocational Education and Training
Vocational education and training (VET) is an important part of
the Australia’s post-secondary education system. Most (over
95 per cent) vocational education and training is provided in
institutes of technical and further education (TAFE). Courses
include a range of vocational training from entry-level
employment preparation, through to trades, advanced vocational,
para-professional and professional courses. In addition, many
recreation and leisure programs are offered. In 1997,
approximately 121 000 TAFE students graduated with a qualification
from a vocational course of at least 200 hours or one semester in
duration (NCVER, 1998). Overall, there were 1.4 million enrolments
in VET programs in 1997. Participation is characterised by
part-time attendance and a wide age range (persons aged 15-24
years comprise 38 per cent of the clients). Entry to many courses
is possible after Year 10, but in practice nearly half of the
entrants to vocational courses have completed Year 12. In the
early 1980s, the corresponding proportion was one fifth.
Apprenticeships are an important component of VET. Over three
to four years an apprentice works for an employer (or group of
employers) and attends a training institution (traditionally a
TAFE institute, typically for a total of 800 hours). Recent
changes have occurred in response to perceived limitations
in the apprenticeship system, such as inflexibility, a
limited range of occupations, old technology,
lack of access for women and declining numbers. In 1985,
traineeships were introduced to
provide a shorter and more flexible approach to entry-level
training. Traineeships typically involved a one-year program with
an employer incorporating on-the-job and off-the-job training,
mostly in office-based and retail industries. More recently,
apprenticeships and traineeships have been integrated as part of a
more unified entry-level training system. In the mid 1990s, 18 per
cent of males had participated in an apprenticeship by age 19, 5
per cent had participated in a traineeship and 25 per cent
participated in a non-apprenticeship TAFE course. The comparable
figures for women were, 2 per cent for apprenticeships, 7 per cent
for traineeships and 29 per cent in a TAFE course (Lamb et al.,
1998:20).
Participation in vocational education is higher among males,
students from lower socioeconomic backgrounds, rural students, and
English-speaking (rather than non-English speaking backgrounds)
backgrounds. Furthermore, VET participants are more likely to have
attended government or Catholic schools (rather than independent
schools), have low achievement levels in literacy and numeracy,
and to be school non-completers (Lamb et al., 1998, pp. 19-29). This is
the opposite pattern to participation for higher education.
Overall VET participation increased between the mid-1980s and
mid-1990s. However, there were declines in the proportion
undertaking apprenticeships by age 19 (among males from 26 to 18
per cent) (Note 4) and
increases in the proportion participating in TAFE courses by age
19 (among males from 10 to 25 per cent) (Lamb et al., 1998:20).
The OECD estimates the proportion of 18-21 years olds currently
enrolled in non-university tertiary education (VET) in Australia
is around 8 per which is slightly higher than the OECD average of
5 per cent (OECD, 1998:184).
Apprenticeships are associated with lower rates of unemployment
in youth cohorts and substantially higher levels of full-time
work. Traineeship are also beneficial but to a lesser extent
(Marks et al., Forthcoming; McMillan & Marks, 2003). However,
TAFE certificates and diplomas do not have strong beneficial
effects on the labour market outcomes (Long et al., 1996; Marks et
al., Forthcoming). These findings for vocational education that
apprenticeships improve employment prospects but that vocational
education, in general, does not substantially improve labour
market outcomes is consistent with other work in Australia
(Dockery & Norris, 1996; Nevile & Saunders, 1998).
Furthermore, such findings are similar to that found in other
countries (Ryan, 2001). In part, this reflects the industries and
occupations, which these programs provide access. Furthermore,
vocational education may benefit enterprises and the overall
economy. However, the lack of evidence that vocational education
provides substantial benefits to its participants is a concern.
One interpretation is the greater benefit of apprenticeships and
traineeships compared to TAFE certificates and diplomas is because
the former involve full-time employment.
Since VET is closely aligned with industry, shifts in
employment patterns impact on its development. One source of
change arises from shifts in employment away from industrial
sectors traditionally served by VET (e.g., manufacturing) and the
growth in other sectors such as hospitality and service (clerical
and office) industries. This results in changes in the
institutional organisation of VET (e.g., within TAFE
institutions and between TAFE and other VET providers), the areas
in which programs are provided (e.g., the emergence of formal
training arrangements such as traineeships and new apprenticeships
in industries not previously involved in apprenticeships) and the
forms of provision that emphasise skill-specific modules of
training rather than structured courses leading to a
qualification. Another source of change arises from the shifting
vocational demands within industries that emphasise higher-order
transferable skills that can be adapted to new workplace
demands.
Changing VET programs in response to these pressures may result
in a closer relationship between VET and higher education, so that
TAFE diploma programs overlap with university degree programs to a
greater extent. As these changes emerge there will be a need for
greater attention to issues concerned with accreditation,
recognition of prior learning, and coordination of administration.
At present responsibility for administration and delivery of VET
resides with the state and territory governments (within a
national strategic plan developed through a ministerial council on
the advice of the Australian National Training Authority). In
terms of student fees, there have been arguments that the
principles of the Higher Education Contributions Scheme should be
applied to VET so that funding becomes more comparable with that
in universities. This may be premature given that the income
returns to VET are considerably lower than that for university
degrees and that much of the participation in VET is directed to
short duration certificates and training modules.
Equity
In Australia, gender differences in educational participation
have reversed. In 1970, boys were more likely to complete
school than girls and had higher levels of participation in higher
education. During the early 1980s, Year 12 participation for girls
was only 3 percentage points higher than that for boys. By the
late 1980s, the gender gap favouring girls in Year 12
participation had increased to around 10 percentage points. Across
the OECD world, young women show higher levels of educational
attainment than young men, the reverse of the situation for older
cohorts (OECD, 1997: 35, 320-321).
Similarly, the gender gap in higher education has increased
over time from no gap in the early 1980s to about 10 percentage
points during the late 1990s (Marks et al., 2000). These changes
have also occurred in most OECD countries. In 17 of 21 OECD
countries, school graduation rates for women exceed those by men.
Differences in university-orientated school courses are even
stronger (OECD, 2001a:140, 146). Over the last two decades there
has been a clear and continuing trend of higher female
participation in tertiary study, especially in university programs
(Bradley & Raminez, 1996). University graduation rates are
higher for women than for men (OECD, 2001a:166). However, gender
differences in graduation rates for second degrees are much
smaller, and in advanced degrees men still tend to outnumber
women. This pattern is also found in Australia, where 58 per cent
of first-degree graduates, 52 per cent of second degree graduates,
and 40 per cent of advanced degree graduates are women (OECD,
2001a:173). An Australian longitudinal study of university
commencing students in the early 1990s found that women were
almost ten per cent more likely to complete an award course than
men (Martin et al., 2001; Urban et al., 1999).
In international achievement studies of reading literacy,
females outperform males. Across all OECD countries in the 2000
PISA study of 15-year-olds, females scored higher in reading
literacy than males. The differences ranged from 14 points in
Korea to around 50 points in Finland and New Zealand, with the
average difference being 32 points (one third of a standard
deviation). In Australia, the difference between males and females
was 34 scale points, about the average for the OECD. Within
Australia there are indications that gender differences in reading
achievement have changed over time. Marks and Ainley (1997)
reported a decline in the proportion of boys
attaining mastery in reading.
In the Australian 1994 TIMSS study, differences between males
and females in mathematics and science were not statistically
significant. Australia was one of only a few countries in which
there was not a difference in favour of males (Lokan et al.,
1996). The lack of gender differences in mathematics and science
achievement observed in 1994 was replicated in the 1999 repeat of
the TIMSS study (Martin et al., 2000; Mullis et al., 2000). These
results contrasted with those reported from earlier international
studies of mathematics and science achievement (Comber &
Keeves, 1973; Rosier, 1980; Rosier & Keeves, 1991). The
results have been quite reasonably interpreted as evidence of the
impact of programs that promoted participation in mathematics and
science among girls at school, and of the impact of more general
social changes.
Gender differences are also evident for tertiary entrance
scores. In New South Wales, females are more frequently found in
the top percentiles for university admission (NSW UAC, 1998:10).
In the great majority of Year 12 courses in New South Wales,
females outperform males and the gap appears to have increased
throughout the 1990s (Collins et al., 2000:50,57-60; MacCann,
1995). The Victorian Tertiary Admission Centre (VTAC,
1998-1999:98-99107) reports higher percentages of females in the
top percentile bands, with males more common in the lower bands.
Females outperform males in the majority of subjects in Victoria
and Western Australia (Collins et al., 2000:55). In the Queensland
Cores Skills Test (QCS), there were proportionally more males in
the very top band, more females in the following high and middle
achieving bands, but more males in the lower bands. The trend
towards females outperforming males is not limited to the
Australian context (Baker & Jones, 1993).
Socioeconomic Background
As a result of a number of large-scale studies conducted at a
national and international level there is now consistent evidence
of the magnitude of the relationship between socioeconomic
background and educational outcomes. Typically, correlation
coefficients of approximately 0.3 are reported between
socioeconomic status and educational outcomes. In PISA,
achievement was positively associated with student socioeconomic
status in all countries but there were differences between
countries in the strength of this association (Note 5). A measure of the strength of
this association is provided by the gain in reading literacy
associated with a one international standard deviation increase on
the index of socioeconomic status. For Australia the size of this
measure of the association was 32 scale points, very close to the
OECD average of 34 scale points. (The standard deviation was 100
scale points). The countries showing the weakest effect of
socioeconomic background was Korea (14 points) and the
strongest was for Germany (45 points). The effects for the United
Kingdom, the United States, New Zealand and Canada were 38, 34, 32
and 26 points respectively. In terms of the socioeconomic
distribution of achievement, Australia is around the international
average and not a leader in terms of equality of outcomes (OECD,
2001b). Similar results were reported in the TIMSS studies for
mathematics and science among middle primary and junior secondary
students (Lokan et al., 1996:40; 1997:44) (Note ).
The influence of socioeconomic background on educational
outcomes is declining in many OECD countries (Rijken, 1999:51-78;
Sieben, 2001:33-55). In Australia, there is evidence that the
influence of socioeconomic background on early school leaving,
participation in Year 12 and higher education is declining
over-time (Fullarton et al., 2003; Marks & McMillan, 2003;
McMillan & Marks, 2003).
Socioeconomic background is often considered the most important
influence on educational outcomes and an important element in the
funding of schools. However, its influence on early school
leaving, Year 12 completion and University entrance performance is
considerably smaller than that of achievement in literacy and
achievement (Marks & Fleming, 1998a; Marks et al., 2000; Marks
et al., 2001). Both the Australian and international PISA reports
demonstrate large variation in achievement scores among students
with the same socioeconomic backgrounds (Lokan et al.,
2001:163-168; OECD, 2001b:185). This variation reflects the lack
of a strong association between socioeconomic background and
achievement.
From a policy perspective, it is important to further reduce
the impact of socioeconomic background. There are countries where
the impact of socioeconomic background is considerably weaker that
it is in Australia. A general rather than streamed curriculum is
helpful since school systems characterised by tracking or
streaming often (but not always) show stronger effects of
socioeconomic background (OECD, 2001b:195-196). However, a more
effective policy focus would be to focus on educational
performance rather socioeconomic background since poor performance
is the primary concern and improving the performance of low
performing students will necessary reduce socioeconomic
inequality. Furthermore, such a focus avoids the predictable
criticisms of any measure of socioeconomic background used to fund
disadvantaged schools.
Ethnic and Indigenous Minorities
Although formulas for school funding often include the
proportion of non-English speaking students, these students most
often exhibit superior educational outcomes (Marks & Fleming,
1999; Marks et al., 2000; Marks et al., 2001). Differences in
middle-secondary school achievement are often minimal so it
appears that ‘cultural factors’ are responsible for
their higher performance during the last two years of school.
However, at the primary school level students with language
backgrounds other than English tend to show lower mean achievement
levels than students with an English language background (Lokan et
al., 1997:173-178).
Indigenous students show much poorer educational outcomes than
non-indigenous students. The difference between Indigenous and
non-Indigenous students in the PISA assessments of reading,
mathematics and science was very large at around 0.8 standard
deviations (Note 7).
Similar results were found for mathematical and scientific
literacy (Lokan et al., 2001:20-33).
The educational participation of Indigenous students is much
lower than that of non-indigenous students. In 1997 the Year 8 to
Year 12 school retention rate for Indigenous students was 31 per
cent compared to 73 per cent for non-Indigenous students (Long et
al., 1999b:37). In 1996 approximately 11 per cent of
non-Indigenous 20 to 24 year-olds held a university degree
compared to only 2 per cent of 20 to 24 year-old Indigenous
Australians (Long et al., 1999b:76). Similarly, the more select
group of Indigenous students who compete for a tertiary entrance
score show scores, on average, 11 points lower than non-Indigenous
students (Marks et al., 2001). Indigenous students remain the most
educationally disadvantaged group of young Australians.
School Sector
Over the past two decades there has been a shift of school
enrolments from the government to the non-government sector. In
1984, 75 per cent of school students were enrolled in government
schools. By 2000 the percentage of students in government schools
was down to 69 per cent (ABS, 2001:34). The most current data
shows that the percentage of students in government schools is
smaller in the secondary sector (64 per cent) than the primary years (73
per cent) and smaller again for the final year of secondary school
(61 per cent). Across all levels of schooling in 2000, 20 per cent
of students were in Catholic schools and 11 per cent were in other
non-government schools. For Catholic schools there was little
difference in the enrolment share at primary (19 per cent) and
secondary (21 per cent) levels. For other non-government schools
the enrolment share for the secondary school years (15 per cent)
was almost double that for the primary school years (8 per cent).
For the final year of secondary school 22 per cent of students
were in Catholic schools and 17 per cent were in other
non-government schools.
The shift of enrolments from the government to non-government
schools poses a significant challenge to the organisation of
schooling in Australia. Schooling in Australia has been largely
through comprehensive government schools that have a broadly
representative intake, with non-government schools providing for a
smaller number of students. If the current trend continues
government secondary schools may come to be regarded as providing
for a little more than half of the student population. The issue
is compounded because the shift of enrolments is probably not
uniformly spread across the social distribution in the community.
Some organisational responses such as, the Schools of the
Future program in Victoria and Partnerships 21 in South
Australia, have attempted to respond to this challenge by
devolving more authority to individual schools and shortening the
lines of authority for operational decisions. In these respects
government schools would operate like non-government schools.
Neither program has operated for a sufficient time for a
considered evaluation of their long-term impact.
One of the most dramatic changes in Year 12 participation is
the substantial decline in school sector differences. In the early
1980s only 30 per cent of those who had attended government
schools participated in Year 12 compared to 44 per cent of
Catholic school students and 88 per cent of independent school
students. By the late 1990s, 71 per cent of government school
students participated in Year 12 whereas the participation rate of
independent school students had remained the same. Participation
among students from Catholic schools had become almost as high as
that of students from independent schools (Fullarton et al.,
2003).
School sector has a substantial impact on tertiary entrance
performance. On average, students attending independent schools
have higher mean ENTER (Equivalent National Tertiary Entrance
Rank) scores than students attending Catholic schools, who in
turn have higher ENTER scores than students attending
government schools. Differences in ENTER scores between
students attending independent and government schools are reduced
by nearly 50 per cent after controlling for differences in Year 9
achievement and the socioeconomic backgrounds of students.
Differences in ENTER scores between students attending
Catholic and government schools are reduced by about 20 per cent
after controlling for prior achievement and the socioeconomic
backgrounds of students. Achievement growth in the final years of
school is much greater among non-government than government school
students (Marks et al., 2001). So, on average, students attending
non-government schools perform better than government school
students even when taking into account the socioeconomic and
academic mix of students.
The interpretation of these differences is not clear. It is
possible that many independent schools have a more defined focus
on university entrance than many government schools and do not
need to spread their efforts over such a diverse range of
endeavours (including a wider range of vocational courses). In
general, research on school effectiveness has pointed to the
importance of the academic environment of a school for growth in
student performance (see below). The difference between government
and independent schools in tertiary entrance performance could be
attributed partly to differences in resource levels but that seems
less likely to provide an explanation for differences between
Catholic and government schools. It is also possible that because
of greater flexibility in recruitment strategies, coupled with the
availability of financial resources, non-government schools are
able to attract and retain very capable teachers. Rowe (1999) has
argued on the basis of data from one state that there are
important differences between subject areas within schools and
between classes within schools. He interprets this as an
indication of the importance of individual teachers.
School Differences in Performance
Most studies of educational outcomes identify differences among
schools in student performance. Those differences are, at least,
partly associated with differences in the social and academic mix
of the student population in each school. The extent to which
there are differences among schools indicates the effect of
national patterns of school organisation and the effect of
differences in the effectiveness of schools. Where school systems
are selective, where residential areas are socially stratified, or
where schools are differentially effective, between-school
differences will be larger. Technically, the extent of these
differences can be represented as the percentage of the variation
in student achievement that can be explained by the variation in
the average achievement for each school. If all the students in
each school achieved the same score but there were differences
between schools then 100 per cent of the variation in student
achievement could be attributed to the school attended. If all
students achieved different scores but all the schools had the
same average score then none of the variation in student
achievement could be attributed to the school attended.
One of the issues investigated in the data from PISA was the
extent to which there were variations between schools in student
performance (OECD, 2001b:60-67) (Note 8). This was indicated by the percentage of the
variation in student scores that could be attributed to
differences between schools and the percentage that could be
attributed to differences among students within schools. On
average, a little more than one third (36 per cent) of the
variance in student achievement was attributable to between-school
differences across OECD countries. Belgium, Germany and Austria,
each of which have selective school systems, have around 70 per
cent of the variance in reading achievement attributable to
between-school differences. In Italy, the Czech Republic and
Greece the figure is around 50 per cent. At the other end of the
scale are Finland, Sweden and Iceland where the percentage of
variance attributable to between school differences is less than
ten per cent. For Australia, approximately 20 per cent of the
variance in reading literacy is associated with differences among
schools. This figure is comparable with that for the United
Kingdom and New Zealand, lower than the United States (35 per
cent) and just a little higher than Canada (OECD, 2001b).
Furthermore, school differences are considerably smaller once
differences between schools in the academic mix of students are
taken into account. In general terms it can be concluded that in
Australia efforts to improve student performance need to be
directed to less-successful students within schools rather than to
improving particular schools.
School Influences on Outcomes
Differences between schools are largely the result of
differences between schools in the social and academic mix of
students. Once such differences are taken into account there is
only a minority of schools, in which the school itself is a
significant independent influence on student performance. In
Australia, only 17 per cent of schools had an independent
influence on Year 12 participation after taking into account state
or territory, and prior student achievement. This figure declined
to 12 per cent after adding school sector to the analysis (Marks
et al., 2000). Similarly, only 17 per cent of schools had
significant effects on tertiary entrance performance after
controlling for student intake (prior achievement and
socioeconomic background). After taking into account other student
factors this figure declined to 11 per cent (Marks et al., 2001).
This means that only in a minority of schools does the individual
school increase or decrease student performance to a significant
extent, net of other factors.
Although only a minority of schools significantly lift school
performance, there has been much research on the characteristics
of ‘effective’ schools. That is, schools that lift
student performance above what is expected given the
schools’ social and academic intake. After reviewing the
international literature, Kreft (1993) concluded that more
effective schools have: a higher level of parental involvement
with the school; higher levels of expectations among students;
frequent monitoring of student performance; greater involvement by
parents and teachers; an orderly school atmosphere; and strict
discipline. In a review of the US research on unusually effective
schools, Levine (1992) identified a large number of correlates
including mastery of central learning skills, students having a
sense of efficacy, school resources and support for teachers. A
more recent review of the literature concluded that research on
effective schools identifies five factors: strong educational
leadership; emphasis on acquiring basic skills; an orderly and
secure environment; high expectations of student achievement; and
frequent assessment of student progress (Scheerens & Bosker,
1997:146).
After performing meta-analyses on factors often understood as
important to school effectiveness, (Scheerens & Bosker,
1997, pp. 237-238) conclude that the most powerful factors operate at
the classroom level. Hill and Rowe (1996) reached the same
conclusion from the analysis of data on student progress through
Victorian primary schools. Differences among classrooms within
schools were greater than differences among schools. Some of these
differences may be partly attributable to the clustering of
students of similar abilities in the same classrooms but it does
appear evident that differences between classrooms are important
and that it is what individual teachers do that is crucial for
student learning.
Despite the general factors that have been identified as
characteristics of effective schools, there is little that is
specific. It is difficult to conclude which particular factors
(and therefore policy initiatives) make for effective schools.
Many inter-correlated factors are canvassed as important
influences, which may vary between school systems. It may well be
that variable-focussed modelling is appropriate for establishing
the extent to which schools vary and for identifying schools that
appear to be effective, but case centred forms of analysis (both
quantitative and qualitative) are needed to elucidate the ways in
which factors cluster to influence outcomes.
Providing additional resources to schools, and reducing class
size, are two related and much debated ways of improving
educational outcomes. One approach to the investigation of these
issues has been through the econometric analyses of education
production functions that make use of the natural variation of
class size across schools and models student achievement in
relation to class size, controlling for student characteristics
and prior achievement. It is crucial to control for prior
achievement because in many school systems low-achieving students
are often allocated to smaller classes. Greenwald, Hedges and
Laine (1996) applied meta-analytic techniques to a series of
studies and concluded that increased resources were associated
with improved student outcomes. This analysis was important
because it differed from the conclusions of Hanushek (1989), who
found little or no effects of school resources. However, even
though Greenwald et al. (1996) concluded that there was an
effect of resources, the magnitude of the effect was not
large.
A number of experimental studies of class size and achievement
have been reported. Some 20 years ago, Glass and Smith (1979)
conducted a meta-analysis of laboratory experiments using
instructional groups of different size. They concluded that
reduced class size could be expected to produce increased student
achievement but that benefits are only evident when the class size
is reduced below 20. In the United States policy had been strongly
influenced by the results of the Tennessee class-size experiment
(Finn & Achilles, 1999). In 79 schools, students and teachers
in the kindergarten year were randomly assigned to different class
sizes from kindergarten through to Grade 3. Small classes
contained between 13 and 17 students and large classes contained
between 22 and 26 students. There has been a consistent finding
that students in the smaller classes showed larger gains in
reading and mathematics achievement. The magnitude of the effect
in one year has been variously estimated as 0.21 (Word et al.,
1994) or 0.15 standard deviations (Goldstein & Blatchford,
1998). As part of a follow up it was concluded that the benefits
of the smaller classes lasted through to the later years of
primary school but with an attenuated magnitude (Nye et al.,
2001).
Although the results of the Tennessee experiment have provided
support for the proposition that reduced class size produces
enhanced learning outcomes, the conclusions for practice are not
unequivocal. Prais (1996) argues that for a given investment
alternative actions such as time for teacher professional
development, devoting resources to students with learning
difficulties, developing better curriculum resources, and varying
the time students spend in groups of different size should be seen
as better use of resources. The extent to which the results of
this study of the early primary years can be generalised to later
stages of schooling is untested. In addition, analysis of the
costs of class size reduction programs in the United States have
identified issues associated with the cost of physical resources
(such as rooms) and maintenance of teacher quality when there is a
rapid expansion of teacher numbers (Brewer et al., 1999). These
issues impact on both the cost and effectiveness of class
size reduction initiatives in school systems.
Therefore, the narrow emphasis of
class size as a way to improve school performance needs to put in
the context of its small effects and the possibility that there may
be more effective ways to improve student performance.
Discussion
In Australia, as in many other countries debates about the
education system have generally not engaged with the empirical
evidence. Governments have pursued easy policy options, such as
increasing the levels of school completion, expanding vocational
education, and reducing class sizes, which are politically less
contentious, supported by various interests groups and simple
enough to be understood by the general public. The empirical
evidence on the benefits of such policies is, at best, equivocal.
Furthermore, they are unlikely to substantially benefit future
cohorts of young people. More difficult issues such as reducing
socioeconomic inequalities in education, improving indigenous
education and reducing differences in student performance between
government and non-government schools are put into the too
‘hard’ basket.
There are a variety of contentious issues that are relevant to
many education systems. Should educational outcomes only reflect
ability and effort, or are concepts such as ‘ability’,
‘merit’, or even ‘effort’ too contentious
to be considered? Should all students complete school or is it
more important for school leavers to gain secure full-time
employment? What policies should be implemented to reduce
socioeconomic inequalities in education? Should indigenous and
minority students have similar educational outcomes to
non-indigenous students or should higher priority be given to a
culturally appropriate education. Should policies be implemented
to improve the educational and labour market outcomes of boys?
These are difficult questions and can only be resolved by
constructive evidence-based debate. Such debate may lead to
formulation of effective policies which improve student outcomes
and reduce socially based inequalities in education.
Notes
The views expressed in this article are not necessarily those
of the Australian Council for Educational Research or the
Melbourne Institute for Economic and Social Research.
- As a proportion
of Gross Domestic Product, public and private expenditure on
education in Australia (at 5.46 per cent) is slightly below the
OECD mean (5.75 per cent). Similarly, public expenditure on
education (as a proportion of GDP) is lower in Australia (4.34 per
cent) than the OECD mean (4.64) (OECD, 2001a:80). Public
expenditure on tertiary education as a proportion of GDP in
Australia (1.09) is slightly above the OECD mean (1.06 per cent)
(OECD, 2001a:81). Expenditure per primary and secondary school
student in Australia is the same as the OECD mean. Expenditure per
tertiary student in Australia is higher than the OECD mean (OECD,
2001a:59).
- In this study,
graduates were comprised of predominantly university graduates,
although a smaller group of TAFE diploma graduates was also
included.
- Reform of
university funding is a difficult issue. One argument is that
increases in participation should be funded through taxation.
Since Australia collects a smaller proportion of GDP in taxation
than many other OECD countries, then governments should simply
increase taxes. However, there are few taxation options for
Australian governments. The top marginal tax rate of 48 per cent
starting at $60,000, is a high tax regime compared to many other
industrialized countries. Australia has just emerged from a
difficult debate about indirect taxes, so it is very unlikely that
the GST will be extended or increased. Many of the European
countries, which collect larger proportions of tax, do so because
of indirect taxes. Many of the options for increasing tax revenues
such as increasing fuel taxes, taxes on the sale of the family
home, and death duties, have their own economic, social, and
political costs. Furthermore, they may not attract sufficient
revenue.
- A similar
decline in apprenticeships was found in the Youth in
Transition cohorts. The participation rate by age 19 declined
from 18 per cent in the early 1980s to 14 per cent in the mid
1990s (Long et al., 1999a:8). A decline is also evident in a more
recent LSAY cohort (who had been in Year 9 in 1995). By 2000 when
the modal age of the age was 19, 13 per cent had participated in
an apprenticeship.
- An international
index based on parental occupations was used to measure
socioeconomic status.
- The relationship
was a little stronger at junior secondary than middle primary
level.
- Based on a
sample of nearly 500 indigenous students. A total of 192 students
in the main sample identified themselves as of Indigenous origin.
The study included an additional 300 indigenous students from the same
schools as the main sample as an additional sample.
- Within Australia,
there were relatively few significant differences among
jurisdictions (Lokan et al, 2001). In reading literacy, the
performance of students from the ACT was significantly better than
that of students from Queensland, Victoria, Tasmania and the
Northern Territory. In mathematical literacy, there were few
differences among jurisdictions, but in scientific literacy both
the ACT and Western Australia had higher performance levels than
several other states.
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About the Authors
Gary N. Marks
Gary N. Marks is a Principal Research Fellow at the Australian Council for
Educational Research. Since 1996 he has authored a substantial number of
reports and articles based on the Longitudinal Studies of Australian Youth
Project, a study focusing on the transition from school to work. He is also
involved in a longitudinal study of adults and is currently working on
wealth in Australia and its influence on educational outcomes. Both
longitudinal studies have a substantial policy focus.
Julie McMillan
Julie McMillan is a Research Fellow at the Australian Council for
Educational Research, where she works on the Longitudinal Surveys of
Australian Youth project. Her current research focuses on young people's
educational and labour market pathways and outcomes. Other research
interests include the development of measures of socioeconomic disadvantage
among school students, higher education students, and the general
population.
John Ainley
+61 3 9277 5507 (Voice)
+61 3 9277 5500 (Fax)
Email: ainley@acer.edu.au
John Ainley is Research Director of National and International Surveys at
the Australian Council for Educational Research. Over the past two decades
he has directed a range of policy-oriented research studies for state and
federal education authorities. He directed a five-year longitudinal study of
Progress through High School, conducted national surveys of subject choice
and has written research reports from the Longitudinal Surveys of Australian
Youth project. Most recently he completed a five-year longitudinal study of
children's development of reading proficiency for the Catholic Education
Commission in Victoria.
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