Social Gradients, Early Childhood Education and Schools Performing Above the Demographic ...

160 Pages·2017·3.3 MB·English

Social Gradients, Early Childhood
Education and Schools Performing Above
the Demographic Expectation: Empirical
Insights into Educational Issues
by
Janeli Kotzé
Dissertation presented for the degree of
Doctor of Philosophy (Economics) at the
University of Stellenbosch
Promoter: Prof. Servaas van der Berg
Faculty of Economic and Management Sciences
Department of Economics
March 2017
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Declaration
By submitting this dissertation electronically, I declare that the entirety of the work contained
therein is my own, original work, that I am the sole author therefore (save to the extent explicitly
otherwise state), that reproduction and publication therefore by Stellenbosch University will not
infringe any third party right and that I have not previously in its entirety or in part submitted it
for obtaining any qualification.
Copyright © 2017 Stellenbosch University
All rights reserved
Notwithstanding the above, the following chapter of the present work have been submitted for
publication and subsequently accepted. The publication of this article does not infringe upon my
right to use this article in this dissertation or to publish the completed dissertation via
Stellenbosch University’s SunScholar portal. The publication is listed in full below:
Chapter 3:
Kotzé. J. (2015). The readiness of the South African education system for a pre-Grade R. South
African Journal of Childhood Education. Vol 5(1), p1-28.
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Abstract
This dissertation exploits the wide variety of datasets available on the South African education
system to consider select education issues. The purpose of this is to contribute relevant empirical
research to inform current debates and discussions relating to issues and policies in the South
African education system which might be entrenching the inequalities of the past and thereby
impeding on future improvement.
The first part of the dissertation provides a new perspective on within country educational
inequality among different education systems by comparing data from seven Sub-Saharan
countries and sixteen Latin-American countries. When comparing the effect of socio-economic
status (SES) on education across countries, researchers have always been faced with a trade-off
between the accuracy of the SES measure within countries and the comparability of the measure
across countries. This has often caused measures of SES to be incorrectly used to compare relative
wealth across different countries and contexts. This chapter sets forth a new methodology to
adjust the traditional measures of SES and make them more comparable across countries and
surveys. Furthermore, the comparable SES measure is applied to compare children in equally
impoverished circumstances across countries, sub-samples and datasets to more accurately
identify the most disadvantaged children across the world. More specifically this method will be
applied to the SACMEQ (Sub-Saharan Africa) and SERCE (Latin America) education datasets to
compare the educational outcomes of those students living under the $3.10 a day poverty line.
Most strikingly, the comparison shows that Ugandan and Mozambican children living under the
$3.10 a day poverty line achieve much higher educational outcomes than similarly poor children
in middle-income countries such as South Africa and the Dominican Republic.
Investment in Early Childhood Development (ECD) has the prospect of cultivating extraordinary
potential within individuals and can assist in bridging the social equity gap from a very young age.
Over the past decade Grade R has been the strongest policy lever used by the Department of Basic
Education to early learning. The National Development Plan has, however, called for universal
access to two years of early childhood development prior to entering Grade 1. Chapter three
explores the merits of this proposal given the specific South African context. More specifically,
this analysis intends to bring new information to bear on three matters. The first relates to the
demand-side and aims to identifying participation trends among four- and five-year-olds.
Moreover, an attempt is made to obtain a profile of those learners not attending any form of
preschooling currently.
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The second objective is to consider the supply-side and aims to understand the policy space in
which pre-Grade R will function, the quality and quantity of infrastructure already in place, and
the expertise of ECD practitioners. Finally, the implementation of a universally accessible pre-
Grade R within a constrained system and the requirements for ensuring that it will have a
significant impact on those children most in need are discussed.
Drawing on three uniquely constructed datasets using the 2012-2014 Universal Annual National
Assessments (U-ANAs), the 2013 Verification ANA (V-ANA) and the 2011 School Monitoring
Survey, the fourth chapter investigates the prevalence and performance of poor schools which
manage to perform above the demographic expectation. Overall it is evident that only 5% of all
Quintile 1 – 3 schools, serving only 4% of the learner population in Quintile 1 – 3 schools, manage
to perform at an acceptable level. The study estimates that poor learners who attend these above
average schools, gain up to a year of additional learning relative to their peers in weak performing
schools. Finally the study shows that strong school management and governance and supportive
bureaucratic accountability are associated with the higher performance observed in these
schools.

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Opsomming
Hierdie tesis maak gebruik van die wye verskeidenheid van datastelle wat beskikbaar is
aangaande die Suid-Afrikaanse onderwysstelsel, om spesifieke kwessies met betrekking tot die
onderwyskrisis te ondersoek. Die doel is om met behulp van relevante empiriese navorsing ’n
bydra te lewer tot die huidige gesprekke oor die kwessies en beleidvorming in die Suid-
Afrikaanse onderwysstelsel wat die ongelykhede van die verlede verder vaslê, en sodoende
vooruitgang belemmer.
Die eerste gedeelte van die tesis lewer ʼn nuwe perspektief oor die ongelykhede in opvoedkundige
uitkomstes wat bestaan in lande, deur die ongelykhede van sewe Sub-Sahara lande en sestien
Latyn-Amerikaanse lande met mekaar te vergelyk. In die vergelyking van die verhouding tussen
sosio-ekonomiese status (SES) en leerder-prestasie, het navorsers nog altyd met die keuse gesit
tussen ʼn meer akkurate meting van SES of ʼn meer vergelykbare meting van SES. Hierdie keuse
het gewoonlik gelei tot die ontoepaslike gebruik van SES om relatiewe rykdom te vergelyk tussen
verskillende lande. Hierdie hoofstuk stel ʼn nuwe metode voor om die tradisionele meting van SES
aan te pas sodat dit beide ʼn meer akkurate meting van rykdom binne in ʼn land sal verskaf, en
meer vergelykbaar tussen lande sal wees. Die nuwe meting word toegepas om kinders te vergelyk
wat van ewe verarmde omstandighede afkomstig is, maar in verskillende lande woon. Verder kan
die meting ook gebruik word om kinders in verskillende datastelle met mekaar te vergelyk.
Sodoende kan die mees gemarginaliseerde kinders in die wêreld geïdentifiseer word. Meer
spesifiek word hierdie metode toegepas op die SACMEQ (Sub-Sahara Afrika) en SERCE (Latyn
Amerika) datastelle om die opvoedkundige uitkomstes van die leerders wat onder die $3.10 ʼn
dag broodlyn lewe te vergelyk. Die mees treffendste wat hier gevind is, is dat leerders wat onder
die $3.10 ʼn dag broodlyn lewe in laer inkomste lande soos Uganda en Mosambiek, beter vaar as
leerders van ewe arm omstandighede in middel inkomste lande soos Suid-Afrika en die
Dominikaanse Republiek.
Investering in vroeë kinderontwikkeling het die vermoë om uitsonderlike potensiaal in individue
te ontgin, en kan ʼn belangrike rol speel om die sosiale ongelykheidsgaping van ʼn jong ouderdom
al te oorbrug. Oor die laaste dekade was Graad R gesien as die sterkste beleidshefboom wat
gebruik was deur die Departement van Basiese onderwys om vroeë kinderontwikkeling te
beïnvloed. Die Nasionale Ontwikkelingsplan stel egter voor dat alle kinders moet toegang kry tot
twee verpligte jare van vroeë kinderontwikkeling voordat hulle Graad 1 betree. Die derde
hoofstuk oorweeg die meriete van hierdie voorstel gegewe die spesifieke Suid-Afrikaanse
konteks. Meer spesifiek, hierdie analise poog om nuwe inligting na vore te bring rakende drie
sake. Die eerste handel oor die vraag-kant en identifiseer die deelname/bywoningskoerse van
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vier- en vyf-jariges. ʼn Poging word ook aangewend om ʼn profiel vas te stel van die kinders wat
geen vorm van voorskool bywoon nie. Die tweede doel is om die aanbod-kant te oorweeg, deur ʼn
beter begrip te kry van die beleidsomgewing waarin Voor-Graad R sal funksioneer, die kwaliteit
en hoeveelheid hulpbronne wat daar reeds beskikbaar is, en die bekwaamheid van die
voorskoolse opvoeders. Laastens word die implementering van ’n universeel toeganklike Voor-
Graad R in ʼn beperkte stelsel bespreek, veral met die doel om vas te stel watter vereistes daar is
om te verseker dat Voor-Graad R die gewenste impak het op die kinders wat die meeste daarby
kan baat.
Deur gebruik gemaak van drie datastelle wat spesifiek saamgestel is uit die 2012-2014 “Annual
National Assessments (ANA)”, die 2013 “Verification ANA” en die 2011 “School Monitoring
Survey”, ondersoek die vierde hoofstuk die voorkoms en prestasie van arm skole wat dit regkry
om bo verwagtinge te presteer. Dit blyk dat net 5% van alle kwintiel 1 – 3 skole, wat net 4% van
die leerders in 1 – 3 skole bedien, dit regkry om teen ʼn aanvaarbare vlak te presteer. Hierdie
studie beraam dat arm leerders wat hulle in hierdie bo-gemiddelde arm skole bevind tot ʼn volle
jaar ekstra kan leer relatief tot ewe arm kinders wat swakker skole bywoon. Laastens wys hierdie
studie dat sterk leierskap en bestuur in ʼn skool, asook ondersteuning deur burokratiese
aanspreeklikheid, geassosieer kan word met die beter prestasie in hierdie skole.

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Acknowledgements
Dissertations are not possible without the input and support of a number of individuals and
organisations. The financial assistance of the National Research Foundation (NRF) towards this
research is hereby acknowledged. The author is grateful for the assistance given by numerous
individuals in the Department of Basic Education to gain access to the required data and who
provided useful insights into the collection of this data. Opinions expressed and conclusions
arrived at in this dissertation are those of the author and are not necessarily to be attributed to
the organisations or individuals referred to.
I am grateful to my supervisor Prof, Servaas van der Berg, who provided valuable guidance in
refining the ideas contained in this dissertation. The process of this PhD has not only been
informative, but played an important role in shaping my character. Dr. Gabrielle Wills, you have
an incredible gift of speaking wisdom and light, thank you for using that to encourage and inspire
greatness in those around you. Dr. Stephen Taylor, thank you for convincing me to attempt this
degree and for mentoring me through this process. To everyone else in ReSEP, I appreciate your
patience in answering all the numerous questions and the comments, suggestions and input
provided along the way.
To Light Project Management and particularly Sean Freimond, thank you for sponsoring my desk
space and listening to my endless lamenting about the state of education in South Africa. Wicus
Kotzé, thank you for choosing to support me each day and for selflessly enduring all the emotions
that accompanied this process. To my parents, Robbie and Ria Viljoen, thank you for making every
effort to ensure that I got the best education and for being unceasing in your love and support.
To God alone be all the glory.

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Table of Contents

Chapter 1

Introduction and overview of research questions ........................................................................ 14
1.1. Introduction ................................................................................................................................................. 14
1.2. Background on educational data in South Africa.......................................................................... 15
1.3. Investigating cognitive performance differentials by socio-economic status across
international assessments: Towards a new methodology ....................................................... 17
1.4. The readiness of the South African education system for pre-Grade R............................... 20
1.5. Schools performing above expectations: Analysis using three constructed datasets ... 22
1.6. Conclusion ..................................................................................................................................................... 24

Chapter 2

Investigating cognitive performance differentials by socio-economic status across
international assessments: Towards a new methodology ........................................ 24
2.1. Introduction ................................................................................................................................................ 24
2.2. Asset indices as measures of wealth ................................................................................................. 25
2.3. Methodology and data ............................................................................................................................ 27
2.3.1. The method ........................................................................................................................ 27
2.3.2. The data ............................................................................................................................... 31
2.3.3. The assumptions ............................................................................................................. 33
2.4. Comparing social gradients across contexts ................................................................................. 34
2.4.1. Comparisons across countries ................................................................................... 35
2.4.2. Comparisons across sub-samples within a country ......................................... 38
2.4.3. Comparisons across datasets ..................................................................................... 40
2.5. Sensitivity checks .................................................................................................................................... 42
2.5.1. The general measure versus the country specific measure .......................... 43
2.5.2. MCA, PCA or Polychoric PCA ...................................................................................... 45
2.6. Conclusion .................................................................................................................................................. 47
2.7. Chapter 2 Appendix ................................................................................................................................ 49

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Chapter 3

The readiness of the South African education system for pre-Grade R ................................ 53
3.1. Introduction ................................................................................................................................................ 53
3.2. Early childhood development in South Africa .............................................................................. 54
3.3. Available datasets ..................................................................................................................................... 57
3.3.1. National Income Dynamics Study............................................................................. 58
3.3.2. General Household Survey .......................................................................................... 59
3.3.3. 2013 ECD Audit ................................................................................................................ 59
3.4. The demand for ECD services .............................................................................................................. 59
3.4.1. Participation Rates ......................................................................................................... 60
3.4.2. Factors associated with children participating in ECD.................................... 64
3.5. Supply of early childhood education services .............................................................................. 66
3.5.1. Governance ........................................................................................................................ 66
3.5.2. Physical resource challenges ...................................................................................... 67
3.5.3. Human resource capacity ............................................................................................ 69
3.5.4. Registration and funding of ECD centers .............................................................. 72
3.6. Non-registered and conditionally registered centers................................................................ 74
3.6.1. The conditions in these centers ................................................................................ 74
3.6.2. Binding constraints to registration .......................................................................... 77
3.7. Discussion .................................................................................................................................................... 82
3.8. Conclusion ................................................................................................................................................... 83
3.9. Chapter 3 Appendix ................................................................................................................................. 86

Chapter 4

Schools performing above expectations: An analysis using three constructed datasets
4.1. Introduction ................................................................................................................................................ 96
4.2. Above expectation, poor schools ........................................................................................................ 98
4.3. Data and methodology ......................................................................................................................... 100
4.3.1. Data .................................................................................................................................... 101
4.3.2. Defining an “above average” school ..................................................................... 105
4.3.3. Estimation framework ............................................................................................... 109
4.3.3.1. Value-added framework ...................................................................................... 109
4.3.3.2. Examining the factors predicting the treatment effect ......................... 113
4.4. Results ........................................................................................................................................................ 114
4.4.1. Access to above average, poor schools ................................................................ 114
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4.4.2. What is the benefit to attending an above average, poor school? ............ 115
4.4.2.1. Robustness checks ....................................................................................... 117
4.4.3. Factors driving higher performance among poor schools .......................... 121
4.4.3.1. Insights from the 2011 School Monitoring Survey ......................... 121
4.4.3.2. Insights from the 2013 Verification ANA ........................................... 123
4.5. Conclusion ................................................................................................................................................ 125
4.6. Chapter 4 Appendix .............................................................................................................................. 127

Chapter 5

5.1. Summary .................................................................................................................................................. 139
5.2. Chapter 2: Investigating cognitive performance differentials by socio-economic status
across international assessments ................................................................................................... 139
5.3. Chapter 3: The readiness of the South African education system to implement a pre-
Grade R ....................................................................................................................................................... 141
5.4. Chapter 4: Schools performing above expectations: Analysis using three constructed
datasets ..................................................................................................................................................... 144
5.5. Chapter 5: Final Comments .............................................................................................................. 146

Bibliography ............................................................................................................................................ 148

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