Analysis and monitoring of equitable access

and full participation in education in South

Africa: the challenge of data quality 

Jean Baxen, Yvonne Nsubuga, Lori Diane

Hill and Anne Craig

Abstract

Indicators to measure educational access serve the useful purpose of facilitating the
evaluation and analysis of progress made towards achieving stated educational access
objectives. In South Africa, data from the Gross Enrolment Ratio (GER) and Net Enrolment
Ratio (NER) are commonly used to report on progress made towards universal educational
access. The critique in the use of these data is threefold; first, that they are computed from
inaccurate school data and second, that their conceptual basis stems from a structural
approach to educational access that gives primacy to the onset or final phases of the
schooling process (primary or secondary) rather than also to what not only happens during
school but also in classrooms. Subsumed and arising from the first two, the third critique
relates to the nature of indicators used to measure educational access. Put differently,
conceptualisations premised on a structural approach have not only had consequences for
the source of data and indicators used to measure educational access but also for its analysis
and interpretation.Established therefore, is that conceptions of educational access not only
influence the choice of indicators that are regarded to be effective and suitable to describe
educational access (Fataar, 1997; Lewin, 2007; Hill, Baxen, Craig and Namakula, 2012) but
they also impact the nature of data generated for this purpose.

Through a review of conceptualisations of educational access and through the use of data
drawn from a study of two Eastern Cape secondary schools, this paper argues that a shift in
discourses on education access is necessary for this country to fully understand and respond
to the discontinuities that persist to characterise the education system. It calls for a shift
from a structural discourse to one that intersects equity and full participation concerns. The
paper highlights how such a shift in conceptualisation not only has implications for the
nature of data gathered but importantly for indicators produced and applied to describe and
measure educational access.



66         Journal of Education, No. 59, 2014

Data for monitoring educational access in South Africa

Prior to 1994, the nine racially desegregated education departments that
existed in South Africa at that time each had  their own ways of collecting
information on education provision and delivery (Parliamentary Monitoring
Group, 2007). The National Education Policy Information Act of 2004
established a unified Education Management Information system (EMIS)
intended to oversee the collection, storage, processing, analysis and
dissemination of information as a strategy towards encouraging evidence-
based decision-making in the education sector. Serious doubts have been
expressed over the reliability and validity of EMIS data (Van Wyk, 2006; The
Ministerial Committee on Learner Retention, 2007). Limited information on
education access in South Africa can also be gleaned from the analysis of
census and general household survey data. Apart from these two databases
and what can be gleaned from the Grade 12 national examination results,
South Africa has no other major sources of data to monitor and evaluate
educational access. As we show in the section that follows, these data are
underpinned by a notion of access that emphasises a structural and systemic
analysis using quantitative measures as the primary source. Initial use of such
an approach was important, and indeed crucial, given the inequitable
education system inherited by the democratic government of 1994. But as
conceptualisations of access to education evolve to become more complex, so
should data sources and indicators. Yet the link between the two has received
little attention in research. Equally, little to no attention is paid to the type of
indicators arising from various conceptualisations; concerns at the heart of
this paper.

Conceptualisations of educational access and

indicators to measure educational access objectives

Since the end of apartheid, South Africa has made a concerted effort towards
not only improving structural or physical access to education but also to
quality education for all her citizens, especially previously disadvantaged
population groups. The country’s new Constitution (RSA, 1996a) guarantees
all children the right to basic education (Grade 1 to 9), and further stipulates
that “[E]veryone has the right to further education, which the state, through
reasonable measures, must make progressively available and accessible”
(RSA, 1996a, p.1257). The South African Schools Act (RSA, 1996b) makes it



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        67

mandatory for all children to attend school until the end of Grade 9 or age 15.
One of the essential elements in determining whether South Africa has
achieved its goals of access to education for all is the development of good
indicators and the collection of high quality data that includes both qualitative
and quantitative measures. 

Results with respect to structural access have been impressive with enrolment
in school in South Africa widely acknowledged as being among the highest in
sub-Saharan Africa (SSA), middle income countries. For example, the 2010
MDG report concluded that South Africa has accomplished the goal of
universal primary education before the targeted date of 2015. The 2010 Gross
Enrolment Ratio (GER) for ordinary secondary education in South Africa
stood at 86%, up from 81% in 2002, while the sector’s Gender Parity Index
(GPI) estimate of 1.07 (Department of Basic Education (DBE), 2012, p.6)
indicates that South Africa’s female learners have a slight edge over their
male counterparts in participating in secondary education.

The above notwithstanding and while structural access to school is guaranteed
for all children, the mainly quantitative indicators, easily translatable into
percentages as in above, mask the inequities attendant in a schooling system
beleaguered with low completion rates, slow progression through the system,
high dropout rates especially after Grade 10 and poor performance in the key
subjects of Mathematics, Physical Sciences and Accounts (DBE, 2010b;
2011a). Put differently, and to make a broader point, the quantitative
measures drawn from the use of particular indicators, premised on structural
conceptions of educational access, foreground what occurs at the onset or end
of schooling (primary or secondary) and thus do not also account for what
happens during the process of schooling.

Despite various initiatives introduced by the post-apartheid government that
include improved school infrastructure and management, professional
development of teachers, the introduction of no-fee schools, a school feeding
scheme, and the revision of curriculum frameworks aimed at improving the
quality of teaching and learning (Motala, Dieltiens, Carrim, Kgobe, Moyo and
Rembe, 2007; DBE, 2010a)to enhance access to education at all levels of the
education system, equitable access and full participation remain a challenge.
Indeed, even though government action indicates a shift toward a more
complex conceptualisation of access to education that reflects a combination
of structural, social and economic factors, the dominance of a structural



68         Journal of Education, No. 59, 2014

approach persists in reporting gains made in access to education. Over-
reliance on quantitative indicators, therefore, does not reflect the
discontinuities inherent in the process of education in a country where high
numbers of children who enter the system do not complete.

Recent conceptualisations of access to education focus on the intersections of
a complex array of issues that mediate and militate against learners’
participation in the schooling experience (Motala et al., 2007; Hill, Baxen,
Craig and Namakula, 2012) and thus already encapsulate forms of access that
move beyond a structural notion of the term. For example, Sayed’s (2002)
analysis of access to education stems from an inclusion and exclusion
perspective. He acknowledges that despite having physical access to schools,
there are factors both inside and outside school that contribute to the
educational exclusion of learners. He identifies four features that need to be
considered in measuring access to education beyond the physical. These
include points of access (e.g. access policies and geographical location of
schools); institutional setting and ethos (e.g. school culture and practices);
curriculum (e.g. content and world views); and the interplay of multiple forms
of injustice (Sayed, 2002, p.29). Instructive in such a conceptualisation is
attention paid to structural forces that press upon schools in ways that
negatively impact experiences of equitable access to education. Such a
discourse though under plays factors outside school as well as what happens
in classrooms that precludes full participation in school. Sayed (2002) also
stops short in operationalising the concept by not specifying indicators to
measure the four points of access. He is also silent on the nature, form and
analysis of data. The implication is that while there is a notable conceptual
shift, the practice of data generation, analysis and interpretation remains
unchanged, in part, due to the structural roots inherent in such a discourse.

The Consortium for Research on Educational Access Transitions and Equity
(CREATE), through a conceptualisation of meaningful access, extends
Sayed’s (2002) framework by identifying five key dimensions not already
taken into account. These include high and regular school attendance rates
among learners, little or no grade repetition, and learners’ ages that are
appropriate for their grades, achievement of expected learning outcomes
including learners’ mastery of basic knowledge, skills and competences as
stipulated by curriculum requirements, high transition rates to higher grades
or phases by the majority of learners and the provision of equitable learning
opportunities to all learners including those from marginalised population



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        69

groups (Lewin, 2007, p.21).The CREATE framework represents an advance
in conceptualisation of the term in that it not only focuses on the physical and
structural mechanisms, but also on participation in the process of schooling. It
considers the current and historical instances of marginalisation that may
impact individual students’ ability to meaningfully access educational
opportunities. Participation in this instance thus includes structural as well as
processual aspects of schooling and is accounted for in three ways. The first
coincides with physical access and is subsumed in Sayed’s (2002) concept of
inclusion and the identification of mechanisms that militate against children
entering the education system. The second, partially captured by rates of
retention and completion, describes the state of staying in school. The third
incorporates aspects of classroom life that allow students to become
successful constructors of their own knowledge (Lewin, 2011). This
notwithstanding and like Sayed (2002), the CREATE framework does not
make explicit the implication such a framework has for the nature of data and
the kind of indicators governments, policy makers, and researchers require to
measure the attainment of education access.

We propose a conceptualisation of educational access as full participation.
While taking account of and subsuming structural and processual elements
that Sayed (2002) and Lewin (2011) propose, full participation shifts the gaze
towards the classroom and on learners. The basic premise is that factors
impacting learners’ access to education as well as those shaping teaching and
learning are integral to any conceptualisation of educational access. Learning
is understood to be situated and produced and reproduced within broader
social and historical practices, which come together in complex ways to
produce what is valued in the field (Bourdieu, 1990) or community of practice
(Lave and Wenger, 1991). Fully participation not only requires time for
immersion in the practice but importantly, also access to the rules attendant
with the practice. Learner positionality and legitimacy as contributors to the
learning process are fundamental to such a conception. Initially, learners
might be marginal to the learning process, but with time, experience and the
attendant social, material and cultural resources made available, should come
to not only embody the values of the practice but also embody concomitant
social and individual identities (O'Donnell and Tobbell, 2007). Central to
such a conceptualisation is the need to take account of the reciprocal and
semiotic relationship between actors, context, and process of interaction and
as such acknowledgment of the intersection between structural, processual,
cultural, and agential (Archer, 2007) factors in producing educational access



70         Journal of Education, No. 59, 2014

There are nine provinces in South Africa, each sub-divided into local municipalities.1

and outcomes. Full participation, therefore, necessitates simultaneously
paying attention to structural, cultural and agential elements because it is their
intersectionality that produces particular forms of educational access and
success. A conception of educational access premised on full participation,
therefore, would require data resulting from indicators that focus on
structural, processual, and agential elements at the level of the school and
classroom. 

We use data derived from two secondary schools in the Eastern Cape to
highlight limitations in current discourses and in so doing, propose the type of
data and indicators that would arise from conceptualisations of full
participation.

Research context

The paper draws on a study that focused on two secondary schools and that
took place in the Grahamstown Education District of Makana in the Eastern
Cape.  On average, secondary schools serving predominantly black learners in1

this education district perform better in the National School Certificate (NSC)
examinations (administered at the end of Grade 12) than the provincial
average. However, given that the pass rate in Eastern Cape in general is
extremely low, there is great concern over the low numbers participating in
the examination in the first instance and poor quality of these passes
(Grocott’s Mail, January 6, 2012). Lack of NCS success at the level that
allows access to tertiary education opportunities is a major obstacle to
achieving admission to Grahamstown’s prestigious Rhodes University and
other higher education institutions in the country. It also flies in the face of
post-apartheid government efforts to address the social injustices of the past
through improvement in education, skills and income levels among the
country’s previously disadvantaged population groups.  

The two schools in the study were relatively representative of peri-urban
secondary schools. With respect to matric pass rates, they are neither the best
nor the worst in the area. They are relatively well-resourced with poverty
index ratings of 4 and 5 respectively, indicating that, based on Provincial
Department of Education calculations; they are in the top 40% of schools



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        71

Documents used by all public schools in Eastern Cape to capture summaries of learner profiles2

and academic performance at the end of each school semester.

economically. An initial inspection of their EMIS data revealed high
enrolment rates, especially in the lower Grades of 8 and 9. The higher Grades
of 10 to 12 showed a worrying trend that raised questions about learner
throughput, repetition, and retention rates in school.

Methodology

Our approach to examining the data requirements for effective analysis and
monitoring of full participation comprised three stages. First, and to frame the
data requirement analysis, we used the five key dimensions of the meaningful
access CREATE framework as the basis to analyze data from the two
participating schools, which included mark schedules,  snap survey forms,2

and school annual survey forms. For purposes of this analysis though, two of
the CREATE framework dimensions, (‘little or no grade repetition’ and ‘high
transition rates to higher grades or phases by the majority of learners’) were
collapsed into ‘grade progression’. The aim of this component of the analysis
was to highlight the gaps that exist between the kind of learner data that is
currently collected in South Africa to monitor educational access and the kind
that is required to assess meaningful access to education. 

The next step was to (a) generate a list of indicators deemed important to
monitor meaningful access, given that the framework provided a conceptual
tool and categories of analysis but not specific indicators, and (b) highlight
the gap in data sources. This, with the view to highlighting the gaps that exist
in the type of data and indicators in the use of meaningful access and to make
the argument that conceptions of full participation have potential to generate
data and indicators that better reflect school and classroom factors that
militate against educational outcomes and success beyond merely a structural
analysis. 

Results

Using the dimensions employed in the CREATE’s meaningful access
framework, Table 1 below shows the results of the analysis of the available



72         Journal of Education, No. 59, 2014

data in the two schools. The data required to effectively analyse and monitor
progress in educational access attainment in each of the four aspects about
learners are outlined in Column 2 of the table. The table also displays the
available data on learners regarding educational access that were collected in
the schools’ mark schedules, and snap and annual surveys.

 



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        73

Table 1: A comparison between the data on learners that are required to
effectively monitor meaningful access to education, and the
actual data that are collected by the two secondary schools

Dimension Required data on
learners

Mark schedule
data 

Snap survey
data

Annual survey
data

School
attendance

Identity of all learners in
each grade 

Names and identity
number of learners in
each grade

No data No data

Learner enrollment
figures 

Number of learners in
each grade by gender
and population group

Number of
learners in
each grade by
gender

Number of classes per
grade

Number learners in
each grade by
population group &
gender

Number of days each
learner in each grade was
present/absent from
school in a particular
school year.

No data No data No data

Average number of days
in a particular school year
learners in each grade
were present/absent from
school by gender,
population group and
home language

No data No data No data

Main reasons for learner
absenteeism in each
grade by gender,
population group and
home language

No data No data No data

Identity of learners in
each grade who left the
school in a particular year

Names, identity
numbers, gender,
population group and
home language of
learners who did not
write the end of
semester examination

No data No data

Number and % of
learners in each grade
who left the school
during a particular year
by gender, population
group and home language

No data No data Number of deceased
learners in each grade
by gender and cause
of death

Number of learner
pregnancies in each
grade

Number of learner
transfers to and from
the school in each
grade by gender



74         Journal of Education, No. 59, 2014

Grade

progression 

Number and % of over-

age and under-age

learners in each grade by

gender, population group

and home language

No data No data Number of learners in

each grade by date of

birth

Number and % of

repeaters in each grade in

a particular school year

by gender, population

group and home

language

Number of years each

learner has spent in

the grade in a

particular school year

No data Number of repeaters

in each grade, gender

and population group

Learning

achievement  

Identity of learners who

passed/failed their grade

in a particular school

year

Names and identity

numbers of learners

who passed/failed

their grade at the end

of each school

semester

No data No data

Number and % of

learners who

passed/failed their grade

in a particular school

year by gender,
population group and

home language

Number of learners

who passed/failed

their grade at the end

of each school

semester by gender

No data Number of failures in

each grade by gender

and population group

Individual learners’ end-

of- year marks in Maths,

English, Accounts and

Physical Sciences for

each grade 

Individual learners’

end of semester

marks in all subjects

for each grade

No data No data

Average marks for each

grade for Maths, English,

home-language,

Accounts and Physical

Science

No data No data No data

Individual learner’s

participation and

achievement in non-

academic school

activities 

No data No data No data

Access to

learning

opportunities

Individual profiles of

learners in each grade

including their physical,

mental, health, nutrition

status, and home

background 

Gender of learners in

each grade 

No data No data



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        75

Access to

learning

opportunities

(continued) 

Number and % of

learners in each grade by

type of disability

No data No data Number of disabled

learners in each grade

by gender, population

group and disability

type

Number and % of

learners in each grade by

gender, population group

and home language

No data Number of

learners in

each grade

by gender

Number learners in

each grade by gender

and population group

Number of learners in

each grade by

preferred language of

instruction and

gender

Number of learners in

each grade by content

subject, gender and

population group

Number of learners

from outside the

Eastern Cape by

province or country

Number and % of

orphaned learners in

each grade by gender,

population group and

home language

No data No data Number and type of

orphaned learners in

each grade by gender 

Number of learners in

each grade who are on

social grants by gender,

population group and

home language

No data No data Number of learners in

each grade registered

but not receiving/

social grants

Number of learners in

each grade receiving/

social grants

Number and % of

learners in each grade

taking Maths,

Accounting, Physical

Sciences by gender,

population group,  home

language and disability

Individual learner’s

performance in all

subjects for each

grade

No data Number of learners in

each grade by content

subject, gender and

population group.  

Number of learners

taking subjects

outside the NCS in

each grade



76         Journal of Education, No. 59, 2014

Comparisons across the columns in Table 1 indicate that none of the three
school data sets that were examined during the study contained the full
complement of data on learners that are at a minimum, required for more
effective monitoring of meaningful access to education. Of the three school
data sets that were examined, the annual school survey forms provided the
most comprehensive data on learners regarding educational access, while the
snap survey forms provided the least data. Even if the data on learners from
all three sources were combined, there were still gaps in the information on
learners that would be required to effectively monitor meaningful access to
education. It should be noted that, given the lack of a uniform learner
identification system, combining data from different sources is neither
straightforward nor feasible on a large scale.

School attendance

None of the three school data sets that were examined contained detailed data
on learners’ school attendance levels. Of the three forms, the annual school
survey provided the most data on learners’ school attendance, although this
was mainly by way of numbers of learners in each grade who, for example,
were deceased or transferred from/to the school. Although, all three forms
provided data on learner enrolment figures, they all lacked data on individual
learners’ school attendance. None of the forms asked for data on reasons for
learners’ absenteeism, although the annual survey form collected data in each
grade on learner deaths and their causes by gender.

Grade progression 

Information on learners’ progression was inadequate in all the three data sets.
The mark schedules only provided the number of years a particular student
had spent in current grade. The annual survey form requested information on
numbers of learners repeating the grade by gender, and was not specific to
individual learners. The snap survey form collected no information on
learners’ progression.



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        77

Learning achievement

Of the three forms, only mark schedules provided data on learners’ level of
educational achievement. This included the overall academic performance of
each learner, and individual scores in each subject examination, by grade.
None of the three forms supplied data on learners’ non-academic
performance. No data was available regarding students’ transition rates to
higher grades or phases of education.

Access to learning opportunities

Mark schedules provided the most in-depth personal data on learners, which
in addition to their population group and gender, also included their names
and identity numbers. However, data on learners’ backgrounds in the annual
survey covered a wider scope and included for example learners’ home
language, preferred language of teaching and learning, pregnancy levels, and
home province/country. Only the annual survey form provided data on
learners’ social circumstances. However, this information was not linked to
individual learners, and was limited to number and type of orphans in each
grade by gender, learners who are receiving/not receiving social grants and
causes of learner mortality. 

Results from the first stage above showed the limitations in the available data,
when dimensions of meaningful access were applied to monitor meaningful
access to education. To advance full participation as a conceptualisation of
education access, Table 2 below elaborates on the type of data as well as
proposed indicators for its operationalisation. We draw attention to
differences in indicators and data necessary to assess education access
objectives in each case.



78         Journal of Education, No. 59, 2014

Table 2: Indicators and data to measure full participation

Dimension Full Participation Meaningful Participation

Learner profiles • Learners’ name, gender, identity number,

population group, home language  and grade 

• Number and % of special needs learners in

each grade and nature of disability

• Learners’ name, gender,

identity number, population

group/home language  and

grade 

• Number and % of

marginalised learners in each

grade

Learner

background

• Descriptions of individual learner’s life

history, health, nutritional status, learning

needs, distance travelled to school, means of

transport to school etc.

• Number and % of learners receiving social

grants by grade, gender and population group

• Number of learners living in child-headed

households by grade, gender and population

group

• Descriptions of individual learners’ home

circumstances including cultural
back-ground, socioeconomic status, parents’

educational levels, etc.

x

x

x

x

School profile • Type (rural/urban),  quintile  distance from 

nearest town, etc

• School accessibility by phone and road

x

x

School

enrolment

• Number of learners in each grade by  gender,

population group and disability

• Number of learners in each 

grade by  gender, and

marginalised group

Schooling costs • Number and % of learners receiving school

uniform aid

x

• Number and % of learners unable to pay 

school levies, contributions, etc.

x

School

attendance

• Number of days each learner attended/was 

absent from school

• Number of days a particular 

learner is present/absent from

school by grade, gender, age

and marginalised group

• Number of learners per reason for

absenteeism

x

• Number of regular late comers in each grade 

by gender and reason for late coming

x



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        79

• Number and % of learners who left the

school the previous year by grade, gender

and population group, and reasons for

leaving

• Number and % of learners 

who left the school the

previous year by grade,

gender and population group,

and reasons for leaving

• Number of days schooling was disrupted by 

cause of disruption, e.g. strike sports, etc.)

x

• Number and % of learners who left the

school the previous year by grade, gender

and population group, and reasons for

leaving grade

• Number and % of learners 

who left the school the

previous year by grade,

gender and marginalised

population group, and reasons

for leaving grade

School

infrastructure

• Types of school infrastructure available

(water, electricity, classroom, staff room,

labs, library, toilets, etc.) and their condition 

x

Facilities for

special needs

learners

• Types and condition of facilities for disabled

learners 

x

School
sanitation

• Types and condition of school toilets x

School furniture • Types and condition of school furniture x

Provision of

school lunch

• Total number of days in the semester school

lunch was provided

x

Safety at school • Number of cases of bullying, harassment,

drugs physical punishment and other forms

of abuse in the year 

x

Teacher

absenteeism

• Total number of days teachers absent from

school per semester 

x

Teacher

quantity and

quality

• Teacher: learner ratio for each grade

• Teacher: key subject ratio

• Teachers’ qualifications and teaching

experience

• Teacher’s competency in the LoLT 

• Teacher’s subject knowledge expertise 

• Teachers pedagogical knowledge

• Teachers’ professional development 

x

x

x

x

x

x

x



80         Journal of Education, No. 59, 2014

Teaching and

learning

resources

• Learner: essential school textbook ratio in

each classroom

• Learner:  computers ratio

• Learner: chair/desk ratio in each classroom

• Condition of school furniture, blackboard,

etc. in each class

• Correct workbooks, textbooks, etc delivered

on time 

• Types of facilities in the classroom for

special needs learners

• Types of additional educational resources

available in each classroom

x

x

x

x

x

x

x

School’s

language policy

• Number and % of learners in each grade

whose home language is the LoLT

• Home languages of learners

School’s

curriculum

policy

• Subjects offered by the school

• Number and % of learners enrolled in key

subjects in each grade by gender and

population group

• Subjects offered by the school

• Number and % of learners

enrolled in key subjects in

each grade by gender and

population group

Teachers’

practice

• Teachers’ coverage of prescribed curriculum

requirements in each grade 

x

Learners’

progression

• Number and % of under-aged / over-aged

learners in each grade by gender and

population group

• Number and % of repeaters in the grade by

gender and population group

• Number of learners who left school in each

grade by gender, population group and

reason for leaving

• Number and % of under-aged/

over-aged learners in each

grade by population group

• Number and % of repeaters in

the grade by population group 

• Number of learners who left

school in each grade by 

population group and reason

for leaving

Learners’

transition rates

to higher phases

• Number and % of learners who passed each

phase by gender and population group

• Number and % of matrics from the school

who joined HEIs by gender and population

group

• Number and % of learners

who passed each phase by 

population group

• Number and % of matrics

from the school who joined

HEIs by population group



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        81

Learner

performance

• Number and % of learners who passed /failed

the grade in the previous year by gender and

population group

• Performance of individual learners in the

year- end, mid-year and other standardised

test marks 

• Number and % of learners who passed /failed

the NSC and ANAs by gender, population

group and quality of pass

• Number and % of learners who passed /

failed key subjects in each grade by gender

and population group each semester

• Pass rate and average marks in key subjects

in the ANAs and the NSC by gender and

population group

• Number and % of learners

who passed/failed the grade in

the previous year by 

population group 

• Performance of individual

learners in the year- end,

mid-year and other

standardised test marks 

• Number and % of learners

who passed/failed the NSC

and ANAs by population

group and quality of pass

• Number and % of learners

who passed / failed key

subjects in each grade by

population group each

semester

• Pass rate and average marks

in key subjects in the ANAs

and the NSC by gender and

population group

Discussion 

Two challenges to effective monitoring of access to secondary education in
South Africa are the inadequate availability of indicators of educational
access (mainly due to incomplete conceptualisation of educational access),
and inaccurate and incomplete data on educational access that are generated
by schools. While, with the introduction of electronic tools, the Department of
Education is to be commended for taking steps to improve the quality of data
on educational access, for the majority of under-resourced schools in the
country, mark schedules, snap surveys and annual schools surveys remain the
main means by which data on educational access are generated. 

The CREATE framework of meaningful access to education was a useful
starting point in that it provided an analytical tool to guide the identification
of indicators and some data types for a more effective analysis and monitoring
of educational access. By demonstrating the disparity that exists between the
data on learners that are generated by these three data forms and the data that
should be in place for effective reporting on meaningful educational access to
secondary education in South Africa, the study highlighted the need for
broader conceptualisations of educational access and that of more research
into indicators of educational access that best capture the secondary education



82         Journal of Education, No. 59, 2014

experience of the majority of South African learners. The paper proposed a
conceptualisation of full participation, which, we put forward as having
promise for contextualised and nuanced descriptions of education access.
Such an orientation shifts the gaze towards the classroom and onto learners;
necessitating data with indicators that focus on learners and teaching and
learning which have not been taken account of in the five CREATE
dimensions.

The range of data on learners that are needed to effectively report on progress
towards meeting educational access objectives require frameworks that draw
on large data sources, usually quantitative in nature, some data are necessary
to understand the conditions of learners and teaching and learning not always
captured quantitatively. Put differently, although most of the required data are
quantitative, for example number of learners in each grade, number of days an
individual learner is absent, and number of repeaters in the grade, some are
qualitative, for example learners’ physical condition, socio-economic status
and performance in non-academic school activities. The need for data on
educational access to be disaggregated stands out in our study, not only to
grade, gender and population group (for example, learners in a grade,
repeaters in a particular year), but also to individual learners (for example,
learner absenteeism and learning achievement). Analysis of the required data
on learners and teaching and learning strengthens the argument for profiling
and identification of all learners in the secondary school system as an initial
step towards effective monitoring of their access to education. A step which
has been planned for and approved by the Department of Education
(LURTIS), but whose implementation has been stalled for various reasons.

As Table 1 showed, none of the three data sets currently used to gather school
data contained the full complement of minimum data on learners that are
needed for effective analysis and monitoring of meaningful access to
education. Nor did the three data sets, taken together, provide all the data
needed. All three forms that were examined during the study mainly focused
on the collection of quantitative data on learners, reflecting a structural
approach to educational access. While numbers (for example of learners by
grade and of orphans by gender) and percentages (for example of repeaters
and over-age repeaters in the grade) were commonly recorded, qualitative
data on learners were rare. Examples of such data include reasons for learners
dropping out of school, and descriptions of learners’ social circumstances.
The latter data are especially important as it has been shown in numerous



Baxen, Nsubuga, Hill and Craig: Analysis and monitoring. . .        83

studies that learners’ socio-economic circumstances are a key determinant of
learner achievement in South Africa (van der Berg, 2007; Howie, 2003). 

The data on learners’ grade progression was another example of the
incompleteness in data sources. In the annual survey form, this was expressed
as the ‘number of repeaters by grade and gender,’ and in the mark schedules
as ‘number of years spent in grade.’ Age distribution of learners by grade,
gender, population group and social circumstances would give a more
comprehensive and nuanced picture of learners’ progression. Lastly, the data
from the three forms were mostly disaggregated to grade, gender and
population group. Only mark schedules disaggregated data on individual
learners, and this was limited to learners’ academic performance.
Disaggregation of key data on educational access to minority groups and
individual learners is especially important in identifying and addressing their
specific educational access needs. 

Table 2 showed that a conception of full participation provides an extension
in data source and indicators to measure educational access outcomes in ways
not possible when ‘meaningful access’ Lewin, 2011) is applied. Additional
data sources were necessary to not only understand learners and aspects of
their lives that impact their experience of access, but also factors in the
classroom that mediate their learning experience. While some of the measures
to access experience are quantifiable, as was the argument earlier on, some
would require data only obtainable through qualitative forms of data
generation.  

Conclusions and recommendations

Full participation as a conceptualisation of access not only provides the
impetus to focus on the actions and interactions of learners at the classroom
level but also on elements impacting teaching and learning. Laying this
framework of participation against previous conceptualisations of access
gives a useful tool for thinking about what it means to fully participate in
education. The most basic aspects of access, structural access also form the
most basic form of participation but that is not the whole story. It offers a way
of generating data and indicators that extend the current development of
Lewin’s (2011) ‘meaningful access’. It requires a deeper examination of the
schooling context and the actual experiences of learners in the classroom and



84         Journal of Education, No. 59, 2014

in so doing might enable education decision makers to ask questions about
why in the face of meeting the structural access imperatives, many children
still stop short of completing school. The recent initiatives such as South
African School Administration Management System (SA-SAMS) and the
National Learner Unit Record Information and Tracking System (LURITS)
would go a long way toward making high quality, usable data on learner
progression and achievement available were it to also consider conceptions of
full participation as a conceptual framework to monitor educational access
outcomes.

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Jean Baxen
School of Education
University of the Witwatersrand

jean.baxen@wits.ac.za

Yvonne Nsubuga
Faculty of Education
University of Fort Hare (Alice)

ynsbga@yahoo.com

Lori Hill
American Educational Research Association and University of Michigan

lohill@umich.edu

Anne T. Craig
The University of Michigan

atcraig@umich.edu

mailto:jean.baxen@wits.ac.za
mailto:ynsbga@yahoo.com
mailto:lohill@umich.edu
mailto:atcraig@umich.edu