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    Home / Central Data Catalog / HUMAN_DEVELOPMENT / DD-UGA-APHRC-UEG-III-UG-1.0
Human_Development

ACCESS TO EDUCATION IN URBAN INFORMAL SETTLEMENTS IN UGANDA: A CASE OF KAMPALA AND MUKONO., Urban Education Research-Uganda

UGANDA, 2021
Human Development (HD)
Dr. Moses Ngware, Charles Mukasa Lusambu
Last modified May 30, 2025 Page views 2659 Documentation in PDF Metadata DDI/XML JSON
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Identification

IDNO
DD-UGA-APHRC-UEG-III-UG-1.0
Title
ACCESS TO EDUCATION IN URBAN INFORMAL SETTLEMENTS IN UGANDA: A CASE OF KAMPALA AND MUKONO., Urban Education Research-Uganda
Subtitle
Urban Education Research-Uganda
Country
Name Country code
UGANDA UGA
Abstract
The Ugandan Government in 1997 introduced the Universal Primary Education (UPE) policy. The policy
allowed the abolishment of tuition fees to increase access to education for the most marginalized. Other
national programs and interventions exist to ensure that all children access quality education without
any form of discrimination. Additionally, the Government of Uganda is also a signatory to international
and local treaties that protect the right to education for all. Despite the UPE policy and other programs
supporting access to quality education, children from marginalized communities still face exclusion from
education opportunities. Gender, regional disparities, socio-economic status and disabilities are some
of the key forms of exclusion that children face.
To understand access to quality education in urban informal settlements in Uganda, the African Population
and Health Research Center in 2018 brought together state and non-state actors of education working
in the urban informal settlements through the urban education project. Through this project, the state
and non-state actors of education formed a Uganda Urban Education Group (UEG). Stakeholders in this
group engaged in different activities, such as forming and strengthening the UEG group for a collective
voice in advocating for access to quality education for children living in urban informal settlements.
Through this engagement and review of existing literature, the stakeholders identified a gap. The gap
in the evidence was in relation to how children in urban informal areas in Uganda access education and
where the children access education. It was after several consultations with the UEG members that the
team sought to carry out a research study in selected urban informal settlements in Uganda.
The study titled ‘The Urban Education Agenda in Uganda: A Call for Targeted Attention on Education
for the Urban Poor’ sought to answer the following objectives.
1. What are the schooling patterns among children living in urban poor households in Uganda –
including those with Special needs?
2. What explains the observed schooling patterns in small and large urban centers?
3. How do poor urban communities perceive and understand education as a right in the context of
urbanization in Uganda?
4. What available education opportunities exist for children with special needs and living in poor
households in Uganda?
5. What survival and educational mechanisms/initiatives did people in urban poor settlements adopt
during the COVID-19 pandemic?
7
Urban Education Research Report - Uganda
Data collection was carried out in two phases. The main data collection took place in October 2020,
while the school survey and the rapid household survey both took place in March 2021. The study was
conducted in 42 villages selected in seven parishes in Kampala and Mukono. Five of these parishes
were from Kampala, and two from Mukono Municipality. In selecting the study site, the research team
ensured that each of the study sites was classified as an urban informal settlement by the Uganda
Bureau of Statistics (UBOS). Additionally, the Urban Education steering committee from the Ministry
of Education and Sports (MoES) and Kampala Capital City Authority (KCCA) were also consulted in
deciding on the areas of study.
A total of five quantitative instruments were used. These included household amenities and schedule,
individual schooling history, parental and perception, rapid household and institutional tools, and 1,102
households with 2,581 children aged 3-19 years were interviewed. Descriptive and inferential statistics
were used to conduct the analysis. Tables and graphs have been used to present the findings.
Qualitative tools were also used for this study. The following methods were used: Key Informant
Interviews (KIIs) with national policy actors, In-depth Interviews (IDIs) with local administration and Focus
Group Discussions (FGD) with parents. In analyzing the qualitative data, codes were developed and the
deductive method was mainly used.
8
Urban Education Research Report - Uganda
Key Findings
Household Characteristics
1. 65.3 % of households in Uganda’s urban informal settlements have more than five members who live
in the poorest wealth quintile.
2. More than half (53.9%) of the female-headed households were in the poorest wealth quintile
compared to their male counterparts.
3. Across the three wealth index levels (poorest, middle, wealthiest),more than half of the household
heads had attained a lower secondary or above in regard to education.
4. There were more girls (54%) in the selected households compared to boys (46%) that had school
going children aged 3-19 years.
5. Across the three wealth index levels more children were attending the primary level (67%), followed
by the secondary level (19%) and lastly, the pre-primary level 14%.
School Attendance
1. Before the closure of schools due to COVID-19, 99.6% of the children aged 4 to 17 years had ever
been to school.
2. Before the closure of schools due to COVID-19, 2.1 % of children were out of school, but after full
school re-opening, this increased to 9 %.
3. By gender, before school closure, more boys (2.4%) were out of school compared to girls (2.1%),
but after full re-opening, more female learners (9.2%) were not enrolled compared to (8.6%) boys.
4. At all the primary and secondary levels, there were more learners enrolled in private schools compared
to government schools during school closures due to COVID-19 and after full school re-opening. At
the primary level before COVID-19, enrollment stood at 68.1%, but after full re-opening, this went
down to 63.8 %. At the secondary level, it was 71.7% before the school’s closure, and surprisingly,
this remained the same after full school re-opening.
5. After full school re-opening, the findings show an increase in the learners from the poorest wealth
index level at the primary level moving to government schools from 33.9% to 43.9%.
6. About 42.3% of parents transferred their children after full school reopening due to the affordability
of school fees.
7. More children from the urban informal settlements for the period 2015-2022 have predominantly
utilized private schools compared to government schools.
8. Overall, 8.2% of children had repeated a grade, with more boys (9.3%) repeating than girls (7.3%).
9. About 28.4 % of learners did not progress to the next grade after full school re-opening.
Pupil-Teacher Ratio
1. The PTR at the primary school level was high (1:55) in government schools compared to 1:19 in
private schools.
9
Urban Education Research Report - Uganda
Perceptions on Quality of Education
1. Slightly more than half (51.9%) of parents from the urban informal settlements felt that the quality
of education had improved since the introduction of the Universal Free Primary Education policy.
Stakeholders’ Understanding of the Right to Education
1. Notably, the concept of the Right to Education was well understood by all the stakeholders, including
the parents. The parents highlighted several ways in which they uphold the right to education,
which included providing uniforms and food for their children while going to school. Additionally,
they encouraged each other to enroll their children in schools while acknowledging the role the
community plays.
2. The mechanisms used to report violations of the Right to Education were better understood by
the policy actors and local administration as compared to the parents. Parents indicated using
more community-level-based methods, such as the village local council meetings compared to the
structures set up by the Ministry of Education and Sports and others.
Opportunities for Continued Learning During COVID-19
1. Overall, the poorest households (15%) accessed the least and paid (54%) more for these opportunities
compared to those households that were in the middle and wealthiest wealth index levels.
2. The main challenges in accessing learning opportunities included a lack of
resources to purchase learning materials, competing responsibilities at home
that limited the time available for study and a lack of study spaces at home.
10
Urban Education Research Report - Uganda
Conclusion
The urban informal areas in our towns and cities continue growing rapidly. This trend comes with an
increase in the population and, consequently, a growing demand for public services such as education.
In Uganda’s urban informal settlements, more children are utilizing private schools than government
public schools to access education. This pattern is associated with distance to school and hence the
reason for parents choosing private schools over government schools, which are already crowded.
Despite the UPE policy, there was an indication that children from urban poor informal settlements
largely do not benefit from the UPE policy, enhancing education inequalities and continuously denying
opportunities to the most marginalized children.
It was also evident that children from urban poor informal settlements were more likely to not access
learning opportunities during school disruptions such as that of COVID-19. Therefore, calling on the
government to develop measures and programs to cushion learners from such settings when such
instances occur. Moreover, girls are more likely to be affected by disruptions such as COVID-19 in
different ways. This includes being prone to teenage pregnancies and taking up responsibilities to take
care of younger siblings compared to boys.
The community plays a critical role in upholding the right to education and the community members
including parents trust the structures that are at the community level in addressing some of the challenges
they face in ensuring children from the urban informal communities access quality education.
Recommendations
1. The government should strengthen the Public-Private Partnership (PPP) mechanism that already
exists, despite the PPP being a model to ensure that the government increases access to quality
education for all. Some schools have been left out and hence the need to explore ways in which
private schools within the urban informal settlements could benefit from it. Additionally, there are
other PPP models that the government can explore, such as working with the private sector.
2. The government should build more public schools in informal urban settlement areas to accommodate
all learners. With Uganda increasing the number of cities, more people will continue moving into
these cities, and there is an opportunity for the government to plan and build more schools in the
urban informal settlements.
3. There is a need for sensitization among all education stakeholders on government policies that
encourage re-enrolment of pregnant teenagers to school.
4. The government and stakeholders in education should create awareness to reduce gender inequities
for girls and boys.
5. Develop and strengthen community structures in and within the communities.

Version

Version Date
2021-10-07
Version Notes
This survey data was collected 2021 and is the first version.

Scope

Keywords
Keyword Vocabulary
APHRC African Population Health Research Centre
COVID-19 Corona Virus Vaccine
EFA
FSE
Main survey
Rapid Household Survey This was a phone-based survey conducted in 2022 to collect data on the schooling status that could not be collected in 2021 due to the prolonged school closures.
UBOS
UPE universal primary education
RTE Right to Education
LCPS Low Cost Private School

Coverage

Geographic Coverage
The study focuses on urban, poor informal settlements in Uganda. Specifically, data collection occurred in 42 villages selected in seven parishes within Kampala and Mukono. The geographic coverage is primarily urban areas only, concentrated in specific informal settlements within the Kampala and Mukono municipalities.
Unit of Analysis
Households: The study examines household characteristics, wealth, and how they influence children's access to education.
Individuals (Children): The study focuses on children aged 3-19, looking at their schooling patterns, attendance, enrollment, and progression.
Schools: The study includes a school survey, analyzing school facilities, teacher ratios, and overall learning environments.
Communities: The study considers the role of community leaders and the community in protecting the right to education.
Universe
The survey covered household members, Household Heads, instituition`s heads/staff in schools, children in a household aged 3-19 years and parents/guardians/caregivers of this children.

Producers and sponsors

Authoring entity/Primary investigators
Agency Name Affiliation
Dr. Moses Ngware APHRC
Charles Mukasa Lusambu MoES Uganda
Producers
Name Affiliation Role
Charles Mukasa Lusambu Ministry of Education and Sports (MoES) Uganda Co-PI
International Day of the African Youth/Child APHRC Collaborator
Nyambura Thiong’o APHRC Co-Investigator
Francis Kiroro APHRC Co-Investigator
Maurice Mutisya APHRC Co-Investigator
Vollan Ochieng APHRC Co-Investigator
Benta Abuya APHRC Co-Investigator
Funding Agency/Sponsor
Name Abbreviation Role
Wellsprings Philanthropic Fund WPF FUNDER
Other Identifications/Acknowledgments
Name Affiliation Role
International Day of the African Youth/Child ( IDAY ), uganda collaboration and project implementation
Bonface Butichi Ingumba African Population and Health Research Center Data Governance Officer

Sampling

Sampling Procedure
This was a cross-sectional survey utilizing a mixed-methods approach. The study targeted households with school-going children (aged 3 to 19) in selected villages

While the data collected was for children aged 3 to 19 years, the analysis was restricted to children aged 4-17 years. We conducted the study in three sequential stages; i) listing of eligible households ii)Sampling for main data collection and household survey after full school re-opening and school survey. During the listing, 3059 households with 8039 individuals aged between 3 and 19 years were selected. In the main data collection, 1102 households with 2581 children aged 3 to 19 years were selected.

Sampling for the main study: Using the listing as a sampling frame, a sub-sample of 1102 households with 2581 individuals aged 3 to 19 years was drawn for the main study. The sampling of households and individuals took into consideration the study site and age of the individual. The household sample size was estimated using the following key considerations; a primary school level net enrollment rate of 85.05% (Uganda Bureau of Statistics, 2017) which provided an indicator of schooling access a 5% level of significance corresponding to a value of 1.96 from normal distribution curve (or in other words representing the 95% confidence intervals), a margin of error of 5% to ensure that our sample generates precise estimates, a power (1-ß) to reduce the probability of commiting type II error, a design effect of 2.5 and a non-response rate of 20%. Further, we made an assumption that each household on average had two children of school-going age (i.e. 3 to 19 years). Based on the above considerations, the household sample was computed using the formula recommended by Wang and Chow (2007), the household sample was therefore 1200 (rounding up 1199.5) and 2,400 children aged 3 to 19 years The sample was stratified proportionate to the two study sites based on their population and thereafter, randomly sampled the identified households to participate in the study.

Additionally, we purposely selected eighty-one participants for focus group discussions (FGDs) that were administered to parents. Four FGDs were conducted with male parents, and another four with female parents. Five (3 females and 2 males) of the FGD participants were parents of children with special learning needs. The study also had twelve (12) in-depth interviews (IDI) with respondents drawn from persons occupying elective and administrative offices within the study sites. Four key informant interviews (KIIs) were also part of the study respondents, and were all drawn from the national decision-making levels at the Ministry of Education and Sports (MoES). For both IDIs and KIIs, gender consideration was not a key inclusion criteria, and instead, the person of the office targeted was the key inclusion criteria.


Rapid survey after school re-opening: This was a phone-based survey conducted in 2022 to collect data on the schooling status that could not be collected in 2021 due to the prolonged school closures. Moreover, it was prudent to understand school resumption patterns after re-opening. The rapid survey targeted 634 households with 928 children aged 6-19 years that had been included in the main survey, not only to understand resumption of school after re-opening but also movements from one type of school to the other as well as teenage pregnancies. School survey: We identified all the schools (pre-schools, primary and secondary) located within the study sites of interest as well as those in their neighborhood that had enrolled at least 10 individuals. In total, the individuals of school going age were enrolled in over 600 institutions. Only 98 schools were selected for an in-depth school survey. The inclusion criteria included all schools that had been mentioned at least 5 times and were located within the study sites and those at least 20 kilometers outside of the study site that had enrolled at least 10 learners.
Deviations from the Sample Design
The study used a cross-sectional mixed-methods approach with a multi-stage sampling procedure. It involved listing eligible households, sampling for the main data collection, a rapid phone-based survey, and a school survey. The sampling considered stratification by study site and age, and purposeful selection for qualitative interviews.
Response Rate
Efforts were made to maximize participation. For instance, using a phone-based survey as a follow-up
Weighting
stratification proportionate to the two study sites based on their population ensured weight was adjusted for in the sampling process to ensure representativeness

Data Collection

Dates of Data Collection (YYYY/MM/DD)
Start date End date Cycle
2021-10-07 2021-10-07 UEGIII
Mode of data collection
Face-to-face [f2f]
Supervision
The study recruited and trained enumerators, sought ethical approval, and put in place other quality measures, including spot checks during data collection were performed to enhance accuracy and completeness.
Type of Research Instrument
The following survey instruments were used for data collection: a) a household schedule and amenities questionnaire; b) an Individual schooling history questionnaire; c) a parental/guardian involvement questionnaire that incorporated questions on perception d) a Focus group discussion with parents and e) an in-depth interview questionnaire with opinion and policymakers.


A HOUSEHOLD SCHEDULE AND AMENITIES QUESTIONNAIRE: This tool collected data/information about household membership, their characteristics,social-economic characteristics, including food security, household shocks, household poverty, well-being, and household schedule. The household head or someone living in that household and with enough information on the household responded to this tool.The information in this tool was used to generate the wealth quintiles..

AN INDIVIDUAL SCHOOLING HISTORY QUESTIONNAIRE : This tool collected detailed schooling information about individuals aged between 3 and 19 years . This included (enrolment, type of school enrolled, participation in preschool among others) for the year (2020) before school closures.. Caregivers responded for children aged below 12 years while there was an option for those between 12- 19 years to be respondents. The tool also collected information on opportunities for learning during the school closures.

PARENTAL/GUARDIAN INVOLVEMENT QUESTIONNAIRE THAT INCORPORATED QUESTIONS ON PERCEPTION : The tool sought information on parental involvement in their children's schooling including homework support , parental perception of student schooling experience, feeding and costs of schooling. The perception tool gathered information on parents' perception of the quality of education in the era of universal education policies, their understanding of education as a right and their support to schools to improve access and quality. This was responded to by the parents of the child (ren) living in the household.

PARENTAL PERCEPTION SURVEY: this included views of parents on childs school and education and had questions like does the school have enough teachers, enough space for learners, is there physical educvation, is there a school vehicel, views on students with special needs in the school, whether they know education is a right, whether they donate to the school and how often they attend school festivals.:


INSTITUTIONAL TOOL QUESTIONNAIRE : The tool sought to understand the schools background information, enrollment, teachers qualifications , facilities available in the schools,schooling charge and the school governance.
this constituted the institutions this childdren were schooling, the school head or staff, how long they ahve been in that school, more details on the language they used in the school, highets clss/grade in the school, how the school is equiped to cater to different needs, number of textbooks in the school, size of land used by the school, availability of amenities like electricity, availability of toiletes, water, handwashing facilities, school feeding program and how accessible they are, how many boys/girls are in the school, criteria used to admit learners, how many have special needs, how much the school chargers, number of staff and governance of the school.


FOCUS GROUP DISCUSSION (FGD) WITH PARENTS: The guide explored parents’ understanding of the right to education and the role they play in ensuring that all learners are accorded or

RAPID SURVEY AFTER SCHOOL RE-OPENING: This was a phone-based survey conducted in 2022 to collect data on the schooling status that could not be collected in 2021 due to the prolonged school closures. Moreover, it was prudent to understand school resumption patterns after re-opening. The rapid survey targeted 634 households with 928 children aged 6-19 years that had been included in the main survey, not only to understand resumption of school after re-opening but also movements from one type of school to the other as well as teenage pregnancies.

The questionnaires were in in English language but were translated to ugandan where necessary.The questionaires are also available as external resources

Data Processing

Cleaning Operations
Data was extracted from Survey CTO, labeled, and cleaned. Stata Version 17.0 was used for data analysis

Survey CTO had necessary conditional checks and skips to ensure applicable responses and timely submission of collected data ensuring automated data entry controls.

The follow-up rapid phone survey in 2022 aimed to collect data on the schooling status that could not be collected due to the prolonged school closures.
Other Processing
To ensure consistency, data were extracted from the Survey CTO, labeled, and cleaned. Stata Version 17.0. was used for data analysis. Both descriptive and inferential analysis were applied during analysis beginning with exploratory data analysis to regression modeling. Exploratory data analysis was performed using graphical plots and tabulations to observe the patterns of the data and assess the frequencies and measures of central tendency

The results have been presented using both tables and graphs. Household wealth index (scores) were calculated using the household possessions and amenities variables. The amenities included sanitation facilities (e.g drinking water sources, toilet types), house construction materials (e.g. wall, roof, floor), fuel used, lighting, while possessions ranged from ownership of car, TV, fridge, radio, to bicycles among others. We assessed internal consistency of the variables using the Cronbach Alpha to check then applied principal component analysis, which is a statistical technique that reduces the dimensionality of data and summarizes a set of variables (Jolliffe & Cadima, 2016). This summarized set of variables can be used to define a wealth score (Fry et al., 2014). The wealth score was then grouped into three equal categories (known as wealth tertiles) from the poorest (1) to the least poor/wealthiest (3).

Qualitative data analysis largely adopted deductive coding and to some extent inductive coding. The deductive coding was preferred since the interview guides explored information around already constructed thematic areas; this implies that the coding was data-led. However, there are instances where other themes initially anticipated emerged. The resulting themes were consistent with the information gathered from the study respondents’ responses. The emergent responses were then assigned to appropriate codes. The data responses were re-read to help identify identical themes, which were then assigned to an initial set of codes. The re-reading exercise was done line-by-line for all the datasets (FGDs, KIIs, and IDIs) to help obtain even more broad-ranging codes. The emergent codes were grouped to help inform how they fit within the previously developed coding frame. Additionally, thematic analysis was also performed to assist in identifying most common, unique, and consistent responses that aligned with the study’s research questions. This assisted in facilitating the understanding of the different respondents’ perceptions, including highlighting the themes’ dis/similarities or differences in relation to the study’s research questions and objectives (Braun & Clarke, 2006). The derived data was then used to write the qualitative findings’ section of this report.

Data Appraisal

Estimates of Sampling Error
a primary school level net enrollment rate of 85.05% (Uganda Bureau of Statistics, 2017) which provided an indicator of schooling access, a 5% level of significance corresponding to a value of 1.96 from normal distribution curve (or in other words representing the 95% confidence intervals), a margin of error of 5% to ensure that our sample generates precise estimates, a power (1-ß) to reduce the probability of commiting type II error, a design effect of 2.5 and a non-response rate of 20%. Further, we made an assumption that each household on average had two children of school-going age (i.e. 3 to 19 years). Based on the above considerations, the household sample was computed using the formula recommended by Wang and Chow (2007), the household sample was therefore 1200 (rounding up 1199.5) and 2,400 children aged 3 to 19 years

Based on the above considerations, the household sample was computed using the formula recommended by Wang and Chow (2007), the household sample was therefore 1200 (rounding up 1199.5) and 2,400 children aged 3 to 19 years

The sample was stratified proportionate to the two study sites based on their population and thereafter, randomly sampled the identified households to participate in the study.
Additionally, we purposely selected eighty-one participants for focus group discussions (FGDs) that were administered to parents. Four FGDs were conducted with male parents, and another four with female parents. Five (3 females and 2 males) of the FGD participants were parents of children with special learning needs. The study also had twelve (12) in-depth interviews (IDI) with respondents drawn from persons occupying elective and administrative offices within the study sites. Four key informant interviews (KIIs) were also part of the study respondents, and were all drawn from the national decision-making levels at the Ministry of Education and Sports (MoES). For both IDIs and KIIs, gender consideration was not a key inclusion criteria, and instead, the person of the office targeted was the key inclusion criteria.

Data access

Contact
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The provided data must be used for the purpose specified in the Data Request Form; any other use not specified in the form must receive additional or separate authorization.

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The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
Copyright © APHRC 2024

Metadata production

Document ID
DD-UGA-APHRC-UEG-III-UG-1.0
Producers
Name Abbreviation Affiliation Role
AFRICAN POPULATION AND HEALTH RESEARCH CENTRE (APHRC) APHRC Project implementation
International Day of the African Youth/Child, Uganda, IDAY APHRC collaborator
Date of Production
2024-06-02
Document version
Version 1.0.
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