{"doc_desc":{"title":"UEG_III_STUDY_UGANDA","idno":"DD-UGA-APHRC-UEG-III-UG-1.0","producers":[{"name":"AFRICAN POPULATION AND HEALTH RESEARCH CENTRE (APHRC)","abbreviation":"APHRC","affiliation":"","role":"Project implementation"},{"name":"International Day of the African Youth\/Child, Uganda,","abbreviation":"IDAY","affiliation":"APHRC","role":"collaborator"}],"prod_date":"2024-06-02","version_statement":{"version":"Version 1.0."}},"study_desc":{"title_statement":{"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.","sub_title":"Urban Education Research-Uganda","alt_title":"UEG_III_UG_2023"},"authoring_entity":[{"name":"Dr. Moses Ngware","affiliation":"APHRC"},{"name":"Charles Mukasa Lusambu","affiliation":"MoES Uganda"}],"oth_id":[{"name":"International Day of the African Youth\/Child ( IDAY ), uganda","affiliation":"","email":"","role":"collaboration and project implementation"},{"name":"Bonface Butichi Ingumba","affiliation":"African Population and Health Research Center","email":"","role":"Data Governance Officer"}],"production_statement":{"producers":[{"name":"Charles Mukasa Lusambu","affiliation":"Ministry of Education and Sports (MoES) Uganda","role":"Co-PI"},{"name":"International Day of the African Youth\/Child","affiliation":"APHRC","role":"Collaborator"},{"name":"Nyambura Thiong\u2019o","affiliation":"APHRC","role":"Co-Investigator"},{"name":"Francis Kiroro","affiliation":"APHRC","role":"Co-Investigator"},{"name":"Maurice Mutisya","affiliation":"APHRC","role":"Co-Investigator"},{"name":"Vollan Ochieng","affiliation":"APHRC","role":"Co-Investigator"},{"name":"Benta Abuya","affiliation":"APHRC","role":"Co-Investigator"}],"copyright":"Copyright \u00a9 APHRC 2024","funding_agencies":[{"name":"Wellsprings Philanthropic Fund","abbreviation":"WPF","role":"FUNDER"}]},"series_statement":{"series_name":"Other Household Survey [hh\/oth]","series_info":"N\/A"},"version_statement":{"version_date":"2021-10-07","version_notes":"This survey data was collected  2021 and is the first version."},"study_info":{"keywords":[{"keyword":"APHRC","vocab":"African Population Health Research Centre","uri":""},{"keyword":"COVID-19","vocab":"Corona Virus Vaccine","uri":""},{"keyword":"EFA","vocab":"","uri":""},{"keyword":"FSE","vocab":"","uri":""},{"keyword":"Main survey","vocab":"","uri":""},{"keyword":"Rapid Household Survey","vocab":" 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.","uri":""},{"keyword":"UBOS","vocab":"","uri":""},{"keyword":"UPE","vocab":"universal primary education","uri":""},{"keyword":"RTE","vocab":"Right to Education","uri":""},{"keyword":"LCPS","vocab":" Low Cost Private School","uri":""}],"abstract":"The Ugandan Government in 1997 introduced the Universal Primary Education (UPE) policy. The policy\nallowed the abolishment of tuition fees to increase access to education for the most marginalized. Other\nnational programs and interventions exist to ensure that all children access quality education without\nany form of discrimination. Additionally, the Government of Uganda is also a signatory to international\nand local treaties that protect the right to education for all. Despite the UPE policy and other programs\nsupporting access to quality education, children from marginalized communities still face exclusion from\neducation opportunities. Gender, regional disparities, socio-economic status and disabilities are some\nof the key forms of exclusion that children face.\nTo understand access to quality education in urban informal settlements in Uganda, the African Population\nand Health Research Center in 2018 brought together state and non-state actors of education working\nin the urban informal settlements through the urban education project. Through this project, the state\nand non-state actors of education formed a Uganda Urban Education Group (UEG). Stakeholders in this\ngroup engaged in different activities, such as forming and strengthening the UEG group for a collective\nvoice in advocating for access to quality education for children living in urban informal settlements.\nThrough this engagement and review of existing literature, the stakeholders identified a gap. The gap\nin the evidence was in relation to how children in urban informal areas in Uganda access education and\nwhere the children access education. It was after several consultations with the UEG members that the\nteam sought to carry out a research study in selected urban informal settlements in Uganda.\nThe study titled \u2018The Urban Education Agenda in Uganda: A Call for Targeted Attention on Education\nfor the Urban Poor\u2019 sought to answer the following objectives.\n1. What are the schooling patterns among children living in urban poor households in Uganda \u2013\nincluding those with Special needs?\n2. What explains the observed schooling patterns in small and large urban centers?\n3. How do poor urban communities perceive and understand education as a right in the context of\nurbanization in Uganda?\n4. What available education opportunities exist for children with special needs and living in poor\nhouseholds in Uganda?\n5. What survival and educational mechanisms\/initiatives did people in urban poor settlements adopt\nduring the COVID-19 pandemic?\n7\nUrban Education Research Report - Uganda\nData collection was carried out in two phases. The main data collection took place in October 2020,\nwhile the school survey and the rapid household survey both took place in March 2021. The study was\nconducted in 42 villages selected in seven parishes in Kampala and Mukono. Five of these parishes\nwere from Kampala, and two from Mukono Municipality. In selecting the study site, the research team\nensured that each of the study sites was classified as an urban informal settlement by the Uganda\nBureau of Statistics (UBOS). Additionally, the Urban Education steering committee from the Ministry\nof Education and Sports (MoES) and Kampala Capital City Authority (KCCA) were also consulted in\ndeciding on the areas of study.\nA total of five quantitative instruments were used. These included household amenities and schedule,\nindividual schooling history, parental and perception, rapid household and institutional tools, and 1,102\nhouseholds with 2,581 children aged 3-19 years were interviewed. Descriptive and inferential statistics\nwere used to conduct the analysis. Tables and graphs have been used to present the findings.\nQualitative tools were also used for this study. The following methods were used: Key Informant\nInterviews (KIIs) with national policy actors, In-depth Interviews (IDIs) with local administration and Focus\nGroup Discussions (FGD) with parents. In analyzing the qualitative data, codes were developed and the\ndeductive method was mainly used.\n8\nUrban Education Research Report - Uganda\nKey Findings\nHousehold Characteristics\n1. 65.3 % of households in Uganda\u2019s urban informal settlements have more than five members who live\nin the poorest wealth quintile.\n2. More than half (53.9%) of the female-headed households were in the poorest wealth quintile\ncompared to their male counterparts.\n3. Across the three wealth index levels (poorest, middle, wealthiest),more than half of the household\nheads had attained a lower secondary or above in regard to education.\n4. There were more girls (54%) in the selected households compared to boys (46%) that had school\ngoing children aged 3-19 years.\n5. Across the three wealth index levels more children were attending the primary level (67%), followed\nby the secondary level (19%) and lastly, the pre-primary level 14%.\nSchool Attendance\n1. Before the closure of schools due to COVID-19, 99.6% of the children aged 4 to 17 years had ever\nbeen to school.\n2. Before the closure of schools due to COVID-19, 2.1 % of children were out of school, but after full\nschool re-opening, this increased to 9 %.\n3. By gender, before school closure, more boys (2.4%) were out of school compared to girls (2.1%),\nbut after full re-opening, more female learners (9.2%) were not enrolled compared to (8.6%) boys.\n4. At all the primary and secondary levels, there were more learners enrolled in private schools compared\nto government schools during school closures due to COVID-19 and after full school re-opening. At\nthe primary level before COVID-19, enrollment stood at 68.1%, but after full re-opening, this went\ndown to 63.8 %. At the secondary level, it was 71.7% before the school\u2019s closure, and surprisingly,\nthis remained the same after full school re-opening.\n5. After full school re-opening, the findings show an increase in the learners from the poorest wealth\nindex level at the primary level moving to government schools from 33.9% to 43.9%.\n6. About 42.3% of parents transferred their children after full school reopening due to the affordability\nof school fees.\n7. More children from the urban informal settlements for the period 2015-2022 have predominantly\nutilized private schools compared to government schools.\n8. Overall, 8.2% of children had repeated a grade, with more boys (9.3%) repeating than girls (7.3%).\n9. About 28.4 % of learners did not progress to the next grade after full school re-opening.\nPupil-Teacher Ratio\n1. The PTR at the primary school level was high (1:55) in government schools compared to 1:19 in\nprivate schools.\n9\nUrban Education Research Report - Uganda\nPerceptions on Quality of Education\n1. Slightly more than half (51.9%) of parents from the urban informal settlements felt that the quality\nof education had improved since the introduction of the Universal Free Primary Education policy.\nStakeholders\u2019 Understanding of the Right to Education\n1. Notably, the concept of the Right to Education was well understood by all the stakeholders, including\nthe parents. The parents highlighted several ways in which they uphold the right to education,\nwhich included providing uniforms and food for their children while going to school. Additionally,\nthey encouraged each other to enroll their children in schools while acknowledging the role the\ncommunity plays.\n2. The mechanisms used to report violations of the Right to Education were better understood by\nthe policy actors and local administration as compared to the parents. Parents indicated using\nmore community-level-based methods, such as the village local council meetings compared to the\nstructures set up by the Ministry of Education and Sports and others.\nOpportunities for Continued Learning During COVID-19\n1. Overall, the poorest households (15%) accessed the least and paid (54%) more for these opportunities\ncompared to those households that were in the middle and wealthiest wealth index levels.\n2. The main challenges in accessing learning opportunities included a lack of\nresources to purchase learning materials, competing responsibilities at home\nthat limited the time available for study and a lack of study spaces at home.\n10\nUrban Education Research Report - Uganda\nConclusion\nThe urban informal areas in our towns and cities continue growing rapidly. This trend comes with an\nincrease in the population and, consequently, a growing demand for public services such as education.\nIn Uganda\u2019s urban informal settlements, more children are utilizing private schools than government\npublic schools to access education. This pattern is associated with distance to school and hence the\nreason for parents choosing private schools over government schools, which are already crowded.\nDespite the UPE policy, there was an indication that children from urban poor informal settlements\nlargely do not benefit from the UPE policy, enhancing education inequalities and continuously denying\nopportunities to the most marginalized children.\nIt was also evident that children from urban poor informal settlements were more likely to not access\nlearning opportunities during school disruptions such as that of COVID-19. Therefore, calling on the\ngovernment to develop measures and programs to cushion learners from such settings when such\ninstances occur. Moreover, girls are more likely to be affected by disruptions such as COVID-19 in\ndifferent ways. This includes being prone to teenage pregnancies and taking up responsibilities to take\ncare of younger siblings compared to boys.\nThe community plays a critical role in upholding the right to education and the community members\nincluding parents trust the structures that are at the community level in addressing some of the challenges\nthey face in ensuring children from the urban informal communities access quality education.\nRecommendations\n1. The government should strengthen the Public-Private Partnership (PPP) mechanism that already\nexists, despite the PPP being a model to ensure that the government increases access to quality\neducation for all. Some schools have been left out and hence the need to explore ways in which\nprivate schools within the urban informal settlements could benefit from it. Additionally, there are\nother PPP models that the government can explore, such as working with the private sector.\n2. The government should build more public schools in informal urban settlement areas to accommodate\nall learners. With Uganda increasing the number of cities, more people will continue moving into\nthese cities, and there is an opportunity for the government to plan and build more schools in the\nurban informal settlements.\n3. There is a need for sensitization among all education stakeholders on government policies that\nencourage re-enrolment of pregnant teenagers to school.\n4. The government and stakeholders in education should create awareness to reduce gender inequities\nfor girls and boys.\n5. Develop and strengthen community structures in and within the communities.","coll_dates":[{"start":"2021-10-07","end":"2021-10-07","cycle":"UEGIII"}],"nation":[{"name":"UGANDA","abbreviation":"UGA"}],"geog_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.","analysis_unit":"Households: The study examines household characteristics, wealth, and how they influence children's access to education.\nIndividuals (Children): The study focuses on children aged 3-19, looking at their schooling patterns, attendance, enrollment, and progression.\nSchools: The study includes a school survey, analyzing school facilities, teacher ratios, and overall learning environments.\nCommunities: 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.","notes":"The scope of this survey includes,\n\nHOUSEHOLD HEAD \/ MEMBERS : This included household heads, thier age, gender , level of educatuion, members in the houshold, access to serices and secondary wants in the household, whether any member in the household has undergone any event of suffering from predefined options, highest level of education within the houshold, access to facilities like toilets, type of schools, whether they receive any help and donations, wealthnscores of the household  and general welfare of the household .\n\nCHILDREN AND THEIR SCHOOLING HISTORY : this looked into whether the child named in a household attended school, the levels they reached, reasons if they did not attend school, their physical wellbeing and if they have any disabilities, his\/her schooling before covid 19, thier grades, access to learning materials and platforms, and challenges faced during studying in the midst of covid 19. This information was got from parent\/guardians \/caregivers. However, Caregivers responded for children aged below 12 years while there was an option for those between 12- 19 years to be respondents.\n\nPARENT\/GUARDIANS \/ CAREGIVERS : this loked into the relationship betwwen the corespondent and the child in the household,  why they sent the child to the schools they did, how they rate that school, how the child receives and does homework, the materials their child had during covid 19, if they can afford fees, whether they know about education rights in uganda, and how they supported their child during covid 19. \n\nINSTITUTIONS HEADS\/ HEAD TEACHERS\/ DEPUTIES : this looked into the institutions this childfren 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.","study_scope":"The scope of this survey includes,\n\nHOUSEHOLD HEAD \/ MEMBERS : This included household heads, thier age, gender , level of educatuion, members in the houshold, access to serices and secondary wants in the household, whether any member in the household has undergone any event of suffering from predefined options, highest level of education within the houshold, access to facilities like toilets, type of schools, whether they receive any help and donations, wealthnscores of the household  and general welfare of the household .\n\nCHILDREN AND THEIR SCHOOLING HISTORY : this looked into whether the child named in a household attended school, the levels they reached, reasons if they did not attend school, their physical wellbeing and if they have any disabilities, his\/her schooling before covid 19, thier grades, access to learning materials and platforms, and challenges faced during studying in the midst of covid 19. This information was got from parent\/guardians \/caregivers. However, Caregivers responded for children aged below 12 years while there was an option for those between 12- 19 years to be respondents.\n\nPARENT\/GUARDIANS \/ CAREGIVERS : this loked into the relationship betwwen the corespondent and the child in the household,  why they sent the child to the schools they did, how they rate that school, how the child receives and does homework, the materials their child had during covid 19, if they can afford fees, whether they know about education rights in uganda, and how they supported their child during covid 19. \n\nINSTITUTIONS HEADS\/ HEAD TEACHERS\/ DEPUTIES : this looked into the institutions this childfren 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."},"method":{"data_collection":{"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\n\nWhile 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.\n\n 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-\u00df) 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. \n\nAdditionally, 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. \n\n\nRapid 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.","sampling_deviation":"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.","coll_mode":"Face-to-face [f2f]","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. \n\n\nA 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..\n\nAN 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.\n\nPARENTAL\/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.\n\nPARENTAL 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.:\n\n\nINSTITUTIONAL 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. \nthis 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.\n\n\nFOCUS GROUP DISCUSSION (FGD) WITH PARENTS:  The guide explored parents\u2019 understanding of the right to education and the role they play in ensuring that all learners are accorded or \n\nRAPID 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.\n\nThe questionnaires were in in English language but were translated to ugandan where necessary.The questionaires are also available as external resources","act_min":"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.","weight":"stratification proportionate to the two study sites based on their population ensured weight was adjusted for in the sampling process to ensure representativeness","cleaning_operations":"Data was extracted from Survey CTO, labeled, and cleaned. Stata Version 17.0 was used for data analysis\n\nSurvey CTO had necessary conditional checks and skips to ensure applicable responses and timely submission of collected data ensuring automated data entry controls.\n\nThe 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.","method_notes":"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\n\nThe 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).\n\nQualitative 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\u2019 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\u2019s research questions. This assisted in facilitating the understanding of the different respondents\u2019 perceptions, including highlighting the themes\u2019 dis\/similarities or differences in relation to the study\u2019s research questions and objectives (Braun & Clarke, 2006). The derived data was then used to write the qualitative findings\u2019 section of this report."},"analysis_info":{"response_rate":"Efforts were made to maximize participation. For instance, using a phone-based survey as a follow-up","sampling_error_estimates":"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-\u00df) 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\n\nBased 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\n\nThe 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. \nAdditionally, 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":{"dataset_use":{"contact":[{"name":"African Population and Health Research Center","affiliation":"","email":"datarequest@aphrc.org","uri":"www.aphrc.org"}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download","conditions":"APHRC data access condition\nAll non-APHRC staff seeking to use data generated at the Center must obtain written approval to use the data from the Director of Research. This form is developed to assess applications for data use and facilitate responsible sharing of data with external partners\/ collaborators\/researchers. By entering into this agreement, the undersigned agrees to use these data only for the purpose for which they were obtained and to abide by the conditions outlined below:\n\n1.Data Ownership: \nThe data remain the property of APHRC; any unauthorized reproduction and sharing of the data is strictly prohibited. The user will, therefore, not release nor permit others to use or release the data to any other person without the written authorization from the Center.\n\n2.Purpose: \nThe 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.\n\n3.Respondent Identifiers: \nThe Center is committed to protecting the identity of the respondents who provide information in its research. All analytical data sets (both qualitative and quantitative) released by the Data Unit MUST are stripped of respondent identifiers to protect the identity of the respondents. By accepting to use APHRC data, the user is pledging that he\/she will not, under any circumstance, regenerate the identifiers or permit others to use the data to learn the identity of any individual, household or community included in any data set.\n\n4.Confidentiality pledge: \nThe user will not use nor permit others to use the data to report any information in the data sets that could identify, directly or by inference, individuals or households.\n\n5.Reporting of errors or inconsistencies: \nThe user will promptly notify the Head of the Statistics and Survey Unit any errors discovered in the data as soon as the errors are discovered.\n\n6.Publications resulting from APHRC data: \nThe Center requires external collaborators to work with APHRC staff on all publications resulting from its data. In order to facilitate this, lead authors should send a detailed concept note of the paper (including the background, rationale, data, analytical methods, and preliminary findings) to the Principle Investigator (or Theme Leader) for the project (with a copy to the Director of Research), who will circulate the abstract to concerned researchers for possible expression of interest in participating in the publication as co-authors. Any exception to the involvement of APHRC staff should be approved by the Director of Research, APHRC.\n\n7.Security: \nThe user will take responsibility for the security of the data by ensuring that the data are used and stored in a secure environment where access is password protected. This will ensure that non-authorized people should not have access to the data.\n\n8.Loss of privilege to use data: \nIn the event that APHRC determines that the data user is in violation of the conditions for using the data, or if the user wishes to cancel this agreement, the user will destroy the data files provided to him\/her. APHRC retains the right to revoke this agreement or informs publishers to withhold publication of any work based wholly or in part on its data if the conditions for using the data are violated.\n\n9.Acknowledgement:\nAny work\/reports from this data must acknowledge APHRC as the source of these data. For example, the suggested acknowledgement for NUHDSS data is: \"This research uses livelihoods data collected under the longitudinal Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2006. The NUHDSS is carried out by the African Population and Health Research Center in two slums settlements (Korogocho and Viwandani) in Nairobi City.\"Additionally all funders, the study communities that provided the data, and staff who collected and analyzed or processed the data should be acknowledged.\n\n10.Deposit of Reports\/Papers: \nThe user should submit electronic and paper copies of all publications generated using APHRC data to the Policy Engagement and Communications Department, with copies to the Director of Research.\n\n11.Change of contact details: \nThe user will promptly inform the Director of Research of any change in your personal details as contained on this data request form.","disclaimer":"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."}}}}