100+ datasets found
  1. f

    Table_2_Improving early childhood development in the context of the...

    • figshare.com
    docx
    Updated Jun 13, 2023
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    Mary Abboah-Offei; Patrick Amboka; Margaret Nampijja; George Evans Owino; Kenneth Okelo; Patricia Kitsao-Wekulo; Ivy Chumo; Ruth Muendo; Linda Oloo; Maryann Wanjau; Elizabeth Mwaniki; Maurice Mutisya; Emma Haycraft; Robert Hughes; Paula Griffiths; Helen Elsey (2023). Table_2_Improving early childhood development in the context of the nurturing care framework in Kenya: A policy review and qualitative exploration of emerging issues with policy makers.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2022.1016156.s002
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    docxAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    Frontiers
    Authors
    Mary Abboah-Offei; Patrick Amboka; Margaret Nampijja; George Evans Owino; Kenneth Okelo; Patricia Kitsao-Wekulo; Ivy Chumo; Ruth Muendo; Linda Oloo; Maryann Wanjau; Elizabeth Mwaniki; Maurice Mutisya; Emma Haycraft; Robert Hughes; Paula Griffiths; Helen Elsey
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Kenya
    Description

    IntroductionThe Nurturing Care Framework (NCF) describes “nurturing care” as the ability of nations and communities to support caregivers and provide an environment that ensures children's good health and nutrition, protects them from threats, and provides opportunities for early learning through responsive and emotionally supportive interaction. We assessed the extent to which Kenyan government policies address the components of the NCF and explored policy/decision makers' views on policy gaps and emerging issues.MethodsA search strategy was formulated to identify policy documents focusing on early childhood development (ECD), health and nutrition, responsive caregiving, opportunities for early learning and security and safety, which are key components of the NCF. We limited the search to policy documents published since 2010 when the Kenya constitution was promulgated and ECD functions devolved to county governments. Policy/decision-maker interviews were also conducted to clarify emerging gaps from policy data. Data was extracted, coded and analyzed based on the components of the NCF. Framework analysis was used for interview data with NCF being the main framework of analysis. The Jaccard's similarity coefficient was used to assess similarities between the themes being compared to further understand the challenges, successes and future plans of policy and implementation under each of the NCF domains.Results127 policy documents were retrieved from government e-repository and county websites. Of these, n = 91 were assessed against the inclusion criteria, and n = 66 were included in final analysis. The 66 documents included 47 County Integrated Development Plans (CIDPs) and 19 national policy documents. Twenty policy/decision-maker interviews were conducted. Analysis of both policy and interview data reveal that, while areas of health and nutrition have been considered in policies and county level plans (coefficients >0.5), the domains of early learning, responsive caregiving and safety and security face significant policy and implementation gaps (coefficients ≤ 0.5), particularly for the 0–3 year age group. Inconsistencies were noted between county level implementation plans and national policies in areas such as support for children with disabilities and allocation of budget to early learning and nutrition domains.ConclusionFindings indicate a strong focus on nutrition and health with limited coverage of responsive caregiving and opportunities for early learning domains. Therefore, if nurturing care goals are to be achieved in Kenya, policies are needed to support current gaps identified with urgent need for policies of minimum standards that provide support for improvements across all Nurturing Care Framework domains.

  2. o

    Group Meetings and Boosters to Sustain Early Impacts on Child Development:...

    • openicpsr.org
    Updated Sep 8, 2023
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    Italo Lopez Garcia; Jill E. Luoto; Frances E. Aboud; Lia C. H. Fernald (2023). Group Meetings and Boosters to Sustain Early Impacts on Child Development: Experimental Evidence from Kenya [Dataset]. http://doi.org/10.3886/E193707V1
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    Dataset updated
    Sep 8, 2023
    Dataset provided by
    McGill University. Department of Psychology
    University of California-Berkeley. School of Public Health
    University of Southern California. Center for Economic and Social Research (CESR)
    Authors
    Italo Lopez Garcia; Jill E. Luoto; Frances E. Aboud; Lia C. H. Fernald
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Kenya
    Description

    This repository contains the Data used to generate all the tables and figures of the working paper titled "Group Meetings and Boosters to Sustain Early Impacts on Child Development: Experimental Evidence from Kenya."Abstract of the paper: We present results two years after the end of a group-based parenting intervention tested in a cluster randomized control trial in rural Kenya. The original program consisted of 16 fortnightly village-based sessions over 8 months and had large positive impacts on children’s cognition and parenting behaviors immediately after its end. Over the next two years, a random half of intervention villages received a light-touch “booster” intervention to offer continued yet less intensive program support. With and without the booster extension, early program impacts were sustained two years later, albeit smaller in magnitude. Boosters had a small positive added value on parenting behaviors and children’s socioemotional development, despite the interruption of COVID-19 to their delivery. Sustained impacts on children’s development were strongly mediated by improvements in parenting behaviors, disadvantaged families accrued the largest benefits, and two years later our program remains one of the most cost-effective and potentially scalable programs globally to date. These results point to encouraging paths forward for maximizing the reach and longer-term effectiveness of early childhood development programs to improve child development in low-resource remote settings. (JEL No: H43, I10, I20, I38, O15)Keywords: parenting intervention, parenting behaviors, early child development, group-based delivery, rural Kenya Citation of the paper: Lopez Garcia, I., Luoto, J., Aboud, F., & Fernald, L. (2023). Group Meetings and Boosters to Sustain Early Impacts on Child Development: Experimental Evidence from Kenya

  3. f

    Table_1_An Implementation Evaluation of A Group-Based Parenting Intervention...

    • frontiersin.figshare.com
    docx
    Updated Jun 1, 2023
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    Jill E. Luoto; Italo Lopez Garcia; Frances E. Aboud; Daisy R. Singla; Rebecca Zhu; Ronald Otieno; Edith Alu (2023). Table_1_An Implementation Evaluation of A Group-Based Parenting Intervention to Promote Early Childhood Development in Rural Kenya.docx [Dataset]. http://doi.org/10.3389/fpubh.2021.653106.s001
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    Jill E. Luoto; Italo Lopez Garcia; Frances E. Aboud; Daisy R. Singla; Rebecca Zhu; Ronald Otieno; Edith Alu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Kenya
    Description

    Early childhood development (ECD) parenting interventions can improve child developmental outcomes in low-resource settings, but information about their implementation lags far behind evidence of their effectiveness, hindering their generalizability. This study presents results from an implementation evaluation of Msingi Bora (“Good Foundation” in Swahili), a group-based responsive stimulation and nutrition education intervention recently tested in a cluster randomized controlled trial across 60 villages in rural western Kenya. Msingi Bora successfully improved child cognitive, receptive language, and socioemotional outcomes, as well as parenting practices. We conducted a mixed methods implementation evaluation of the Msingi Bora trial between April 2018 and November 2019 following the Consolidated Advice for Reporting ECD implementation research (CARE) guidelines. We collected qualitative and quantitative data on program inputs, outputs, and outcomes, with a view to examining how aspects of the program's implementation, such as program acceptance and delivery fidelity, related to observed program impacts on parents and children. We found that study areas had initially very low levels of familiarity or knowledge of ECD among parents, community delivery agents, and even supervisory staff from our partner non-governmental organization (NGO). We increased training and supervision in response, and provided a structured manual to enable local delivery agents to successfully lead the sessions. There was a high level of parental compliance, with median attendance of 13 out of 16 fortnightly sessions over 8 months. For delivery agents, all measures of delivery performance and fidelity increased with program experience. Older, more knowledable delivery agents were associated with larger impacts on parental stimulation and child outcomes, and delivery agents with higher fidelity scores were also related to improved parenting practices. We conclude that a group-based parenting intervention delivered by local delivery agents can improve multiple child and parent outcomes. An upfront investment in training local trainers and delivery agents, and regular supervision of delivery of a manualized program, appear key to our documented success. Our results represent a promising avenue for scaling similar interventions in low-resource rural settings to serve families in need of ECD programming. This trial is registered at ClinicalTrials.gov, NCT03548558, June 7, 2018. https://clinicaltrials.gov/ct2/show/NCT03548558.

  4. w

    Service Delivery Indicators Kenya Education Survey 2012 - Harmonized Public...

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Aug 25, 2021
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    Waly Wane (2021). Service Delivery Indicators Kenya Education Survey 2012 - Harmonized Public Use Data - Kenya [Dataset]. https://microdata.worldbank.org/index.php/catalog/2755
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    Dataset updated
    Aug 25, 2021
    Dataset authored and provided by
    Waly Wane
    Time period covered
    2012
    Area covered
    Kenya
    Description

    Abstract

    The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized allowing comparison between and within countries over time.

    The Education SDIs include teacher effort, teacher knowledge and ability, and the availability of key inputs (for example, textbooks, basic teaching equipment, and infrastructure such as blackboards and toilets). The indicators provide a snapshot of the learning environment and the key resources necessary for students to learn.

    Kenya's Service Delivery Indicators Education Survey was implemented in May-July 2012 by the Economic Policy Research Center and Kimetrica, in close coordination with the World Bank SDI team. The data were collected from a stratified random sample of 239 public and 67 private schools to provide a representative snapshot of the learning environment in both public and private schools. The survey assessed the knowledge of 1,679 primary school teachers, surveyed 2,960 teachers for an absenteeism study, and observed 306 grade 4 lessons. In addition, learning outcomes were measured for almost 3,000 grade 4 students.

    Geographic coverage

    National

    Analysis unit

    Schools, teachers, students.

    Universe

    All primary schools

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

    The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). In the case of education, SDI surveys also aim to produce accurate information on grade four pupils’ performance through a student assessment. The multistage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

    Detailed information about the specific sampling process conducted for the 2012 Kenya Education SDI is available in the SDI Country Report (“SDI-Report-Kenya”) included as part of the documentation that accompanies these datasets.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The SDI Education Survey Questionnaire consists of six modules:

    Module 1: School Information - Administered to the head of the school to collect information on school type, facilities, school governance, pupil numbers, and school hours. It includes direct observations of school infrastructure by enumerators.

    Module 2a: Teacher Absence and Information - Administered to the headteacher and individual teachers to obtain a list of all school teachers, to measure teacher absence, and to collect information on teacher characteristics.

    Module 2b: Teacher Absence and Information - Unannounced visit to the school to assess the absence rate.

    Module 3: School Finances - Administered to the headteacher to collect information on school finances (this data is unharmonized)

    Module 4: Classroom Observation - An observation module to assess teaching activities and classroom conditions.

    Module 5: Pupil Assessment - A test of pupils to have a measure of pupil learning outcomes in mathematics and language in grade four. The test is carried out orally and one-on-one with each student by the enumerator.

    Module 6: Teacher Assessment - A test of teachers covering mathematics and language subject knowledge and teaching skills.

    Cleaning operations

    Data entry was done using CSPro; quality control was performed in Stata.

    Sampling error estimates

    At the national level, an anticipated standard error of 1.6 percentage points for absenteeism, and 4.4 percentage points for pupil literacy were calculated. At the county level, an anticipated standard error of 3.1 percent for absenteeism and 9.0 percent for literacy were estimated.

  5. K

    Kenya KE: Trained Teachers in Lower Secondary Education: % of Total Teachers...

    • ceicdata.com
    Updated Jun 30, 2018
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    CEICdata.com (2018). Kenya KE: Trained Teachers in Lower Secondary Education: % of Total Teachers [Dataset]. https://www.ceicdata.com/en/kenya/education-statistics/ke-trained-teachers-in-lower-secondary-education--of-total-teachers
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    Dataset updated
    Jun 30, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2009
    Area covered
    Kenya
    Variables measured
    Education Statistics
    Description

    Kenya KE: Trained Teachers in Lower Secondary Education: % of Total Teachers data was reported at 96.806 % in 2009. This records a decrease from the previous number of 98.416 % for 2008. Kenya KE: Trained Teachers in Lower Secondary Education: % of Total Teachers data is updated yearly, averaging 98.666 % from Dec 2004 (Median) to 2009, with 6 observations. The data reached an all-time high of 99.436 % in 2006 and a record low of 96.806 % in 2009. Kenya KE: Trained Teachers in Lower Secondary Education: % of Total Teachers data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank: Education Statistics. Trained teachers in lower secondary education are the percentage of lower secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.; ; UNESCO Institute for Statistics; Weighted Average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

  6. d

    Qualitative Accounts of Changes to School-aged Children’s Diets due to the...

    • b2find.dkrz.de
    Updated Jan 31, 2020
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    (2020). Qualitative Accounts of Changes to School-aged Children’s Diets due to the COVID-19 Pandemic in Rural, Central, Kenya, 2020 - Dataset - B2FIND [Dataset]. https://b2find.dkrz.de/dataset/a8728ea3-0475-5f09-b177-91c6ac53f19f
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    Dataset updated
    Jan 31, 2020
    Description

    The COVID-19 pandemic has caused disruption to food security in many countries, including Kenya. However, the impact of this on food provision to children at an individual level is unknown. This small study aimed to provide a qualitative snapshot of the diets of children during the COVID-19 pandemic. During completion of 24-h food recalls, with 15 families with children aged 5–8 years, caregivers were asked about changes they had made to foods given to their children due to the pandemic. Food recalls were analysed to assess nutrient intakes. Qualitative comments were thematically analysed. Most of the families reported making some changes to foods they provided to their children due to COVID-19. Reasons for these changes fell into three themes, inability to access foods (both due to formal restriction of movements and fear of leaving the house), poorer availability of foods, and financial constraints (both decreases in income and increases in food prices). The COVID-19 pandemic has affected some foods parents in rural Kenya can provide to their children.We develop a new way to address educational disadvantage in rural Africa, through a collaboration between academics from Kenya, Zambia and the UK, teachers, families and community groups. The connection between home and school is key to sustainable education: (i) parents must recognise the school's priorities if they are to support their child's continuing education, (ii) teachers need to understand their pupils' home environment so they can build on positive home experiences and (iii) schools must build on children's existing skills and knowledge and fit with their goal of a successful life in their community. There is currently a serious disconnect between home and school in Africa and this is exacerbated in rural Kenya and Zambia by the predominance of non-local teachers who often don't speak pupils' native languages. We aim to connect home and school learning by targeting Early Childhood Education and Development programmes (ECDE; age 4 - 6). Unlike primary and secondary schools, ECDE centres recruit teachers from the local community. The relationship between parents and teachers is closest in ECDE settings, providing a crucial opportunity to build bridges between home and school. It is also a critical opportunity for mitigating early disadvantages for girls and empowering females in leadership roles since ECDE teachers are predominantly female. We prioritise language and nutrition as fundamental to all later learning, and aim to (i) identify positive practices in the home that benefit early language development and nutrition and (ii) to work together with ECDE teachers as researchers to empower them to develop teacher and parent networks to share best practice in school and at home. We target mealtimes for our observations of behaviour and language since they are a particularly rich time for social interaction, and the focus on eating gives an authentic setting for natural communication. Our objectives are (i) to measure home and school mealtime behaviour and language to identify practices that are most crucial for raising the quality of language children are exposed to (e.g., whether adults and children sit together; whether they have a television) (ii) to observe eating behaviours in the home, assess the extent to which girls' eat less food, or less nutritious foods, and identify practices that raise levels of female nutrition (e.g., girls may eat more if they share food as a family, rather than when girls and women eat separately) (iii) to work together with our teacher-researchers and community advisors to co-develop a teacher-network and parent outreach programme, based on evidence from objectives 1 and 2. The aim is to raise awareness and share practices that increase the quality of language children are exposed to at home and in school and raise levels of female nutrition, motivated by evidence of gender inequalities. Objective 3 will be achieved firstly by working together to identify key messages that are culturally appropriate and achievable (e.g., switch the TV off before eating at home; encourage teachers to sit together with pupils when eating in ECDE centres). Second, by working together in practitioner networks, guidance will be developed to inform a parent outreach programme to be shared with well-established groups in the community. The network will also provide a platform for teachers to conduct their own research, share research findings and discuss best practice. Importantly, it will provide a vital link to teachers in primary and secondary education, to develop continuity in children's education. Finally, the evidence base we provide through objectives 1 and 2, and the networks created in objective 3 provide a powerful basis for contributing to the development of the new ECDE curriculum in Kenya and to lobby for similar priorities in Zambia. Qualitative: 24-hour food recalls, with 15 families with children aged 5-8 years, caregivers were asked about changes they had made to foods given to their children due to the pandemic. Food recalls were analysed to assess nutrient intakes. Qualitative comments were thematically analysed.

  7. r

    The National Special Needs Education Policy Framework (2009) of Kenya: Its...

    • researchdata.edu.au
    Updated 2019
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    Charteris Jennifer; Sims Margaret; Mutuota Rose; Rose Njoki Mutuota; Njoki Mutuota Rose; Njoki Mutuota Rose; Margaret Sims; Jennifer Charteris (2019). The National Special Needs Education Policy Framework (2009) of Kenya: Its Impact on Teachers’ Instructional Design and Practice in Inclusive Classrooms in Kenya [Dataset]. https://researchdata.edu.au/national-special-needs-classrooms-kenya/1595148
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    Dataset updated
    2019
    Dataset provided by
    University of New England
    University of New England, Australia
    Authors
    Charteris Jennifer; Sims Margaret; Mutuota Rose; Rose Njoki Mutuota; Njoki Mutuota Rose; Njoki Mutuota Rose; Margaret Sims; Jennifer Charteris
    Area covered
    Kenya
    Description

    The data consists of semi-structured interviews with teachers and principals in 4 schools in Kenya, including students with disabilities in mainstream classrooms is considered an important factor in meeting the needs and ensuring the rights of students with disabilities. In 2009 Kenya passed The National Special Needs Education Policy Framework which, while it made the inclusion of students with disabilities a formal policy, the strategies for inclusion remain unresolved. This study was conducted in two phases; the first used a Western methodology (Universal Design for Learning) and the second an Indigenous Gīkūyū methodology. Eight teachers and four principals were interviewed and eight classrooms were observed in four schools in Kenya to identify the inclusive strategies employed by the teachers. Results were analysed using thematic analysis. The findings of the study showed ways in which Kenyan teachers used Gīkūyū Indigenous strategies, drawn from Gīkūyū knowledges, to support students in inclusive classrooms. The study also highlighted the importance of revitalising Gīkūyū knowledges, values and practices in schools. The research adds to the scholarship on the place of Indigenous knowledges, values and practices in schools to support students with and without disabilities, and the place of family relationships and family-school partnerships among the Gīkūyū in inclusive education. This study has the potential to inform educational policy and practice in Kenya specifically and in Africa generally. It has created the space for the voices of Gīkūyū teachers and principals to be heard in their pursuit to preserve Gīkūyū knowledges that have for centuries supported the care and education of children with disabilities through strong family and group relationships.

  8. K

    Kenya KE: Trained Teachers in Lower Secondary Education: Male: % of Male...

    • ceicdata.com
    Updated Jun 30, 2018
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    CEICdata.com (2018). Kenya KE: Trained Teachers in Lower Secondary Education: Male: % of Male Teachers [Dataset]. https://www.ceicdata.com/en/kenya/education-statistics/ke-trained-teachers-in-lower-secondary-education-male--of-male-teachers
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    Dataset updated
    Jun 30, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2004 - Dec 1, 2008
    Area covered
    Kenya
    Variables measured
    Education Statistics
    Description

    Kenya KE: Trained Teachers in Lower Secondary Education: Male: % of Male Teachers data was reported at 97.725 % in 2008. This records a decrease from the previous number of 98.597 % for 2005. Kenya KE: Trained Teachers in Lower Secondary Education: Male: % of Male Teachers data is updated yearly, averaging 98.597 % from Dec 2004 (Median) to 2008, with 3 observations. The data reached an all-time high of 99.099 % in 2004 and a record low of 97.725 % in 2008. Kenya KE: Trained Teachers in Lower Secondary Education: Male: % of Male Teachers data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank: Education Statistics. Trained teachers in lower secondary education are the percentage of lower secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.; ; UNESCO Institute for Statistics; Weighted Average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

  9. Tusome Early Grade Reading Program Kenya

    • catalog.data.gov
    Updated Jun 25, 2024
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    data.usaid.gov (2024). Tusome Early Grade Reading Program Kenya [Dataset]. https://catalog.data.gov/dataset/tusome-early-grade-reading-program-kenya
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    Dataset updated
    Jun 25, 2024
    Dataset provided by
    United States Agency for International Developmenthttp://usaid.gov/
    Area covered
    Kenya
    Description

    The Tusome Early Grade Reading Program involves a national effort in Kenya to scale up a proven model for improved results in early grade literacy. Based on positive findings during a rigorous impact evaluation of a pilot test of this intervention, the Government of Kenya (GOK) asked USAID/Kenya to assist with the nationwide rollout of an activity to improve reading skills and increase the capacity of educators and the GOK to deliver and administer early grade reading (EGR) programs modeled on the pilot activity’s success. Tusome, which means “Let’s Read” in Kiswahili, targeted 28,000 formal and nonformal public and low-cost private primary schools in the 47 counties in Kenya (nationwide). About 1,000 of these are informal schools that exist mostly in urban “slums,” while the vast majority of the remaining 27,000 schools are in rural areas. Roughly 5.4 million children who entered primary school between 2014 and 2017 are expected to benefit from this scaling-up initiative. Intermediate beneficiaries include: 1) approximately 60,000 class 1 and 2 teachers, 2) 28,000 primary school head teachers, 3) 1,052 Teacher Advisory Center (TAC) tutors, plus “coaches” for nonformal schools and 4) 300 senior education personnel. Tusome also assisted the GOK at the technical and policy levels to sustainably improve reading skills beyond the span of the activity.

  10. Kenya Demographic and Health Survey 2022 - Kenya

    • statistics.knbs.or.ke
    Updated Sep 10, 2024
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    Kenya National Bureau of Statistics (2024). Kenya Demographic and Health Survey 2022 - Kenya [Dataset]. https://statistics.knbs.or.ke/nada/index.php/catalog/128
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    Dataset updated
    Sep 10, 2024
    Dataset authored and provided by
    Kenya National Bureau of Statistics
    Time period covered
    2022
    Area covered
    Kenya
    Description

    Abstract

    The 2022 Kenya Demographic and Health Survey (2022 KDHS) is the seventh DHS survey implemented in Kenya. The Kenya National Bureau of Statistics (KNBS) in collaboration with the Ministry of Health (MoH) and other stakeholders implemented the survey. Survey planning began in late 2020 with data collection taking place from February 17 to July 19, 2022. ICF provided technical assistance through The DHS Program, which is funded by the United States Agency for International Development (USAID) and offers financial support and technical assistance for population and health surveys in countries worldwide. Other agencies and organizations that facilitated the successful implementation of the survey through technical or financial support were the Bill & Melinda Gates Foundation, the World Bank, the United Nations Children's Fund (UNICEF), the United Nations Population Fund (UNFPA), Nutrition International, the World Food Programme (WFP), the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women), the World Health Organization (WHO), the Clinton Health Access Initiative, and the Joint United Nations Programme on HIV/AIDS (UNAIDS).

    SURVEY OBJECTIVES The primary objective of the 2022 KDHS is to provide up-to-date estimates of demographic, health, and nutrition indicators to guide the planning, implementation, monitoring, and evaluation of population and health-related programs at the national and county levels. The specific objectives of the 2022 KDHS are to: Estimate fertility levels and contraceptive prevalence Estimate childhood mortality Provide basic indicators of maternal and child health Estimate the Early Childhood Development Index (ECDI) Collect anthropometric measures for children, women, and men Collect information on children's nutrition Collect information on women's dietary diversity Obtain information on knowledge and behavior related to transmission of HIV and other sexually transmitted infections (STIs) Obtain information on noncommunicable diseases and other health issues Ascertain the extent and patterns of domestic violence and female genital mutilation/cutting

    Geographic coverage

    National coverage

    Analysis unit

    Household, individuals, county and national level

    Universe

    The survey covered sampled households

    Sampling procedure

    The sample for the 2022 KDHS was drawn from the Kenya Household Master Sample Frame (K-HMSF). This is the frame that KNBS currently operates to conduct household-based sample surveys in Kenya. In 2019, Kenya conducted a Population and Housing Census, and a total of 129,067 enumeration areas (EAs) were developed. Of these EAs, 10,000 were selected with probability proportional to size to create the K-HMSF. The 10,000 EAs were randomized into four equal subsamples. The survey sample was drawn from one of the four subsamples. The EAs were developed into clusters through a process of household listing and geo-referencing. To design the frame, each of the 47 counties in Kenya was stratified into rural and urban strata, resulting in 92 strata since Nairobi City and Mombasa counties are purely urban.

    The 2022 KDHS was designed to provide estimates at the national level, for rural and urban areas, and, for some indicators, at the county level. Given this, the sample was designed to have 42,300 households, with 25 households selected per cluster, resulting into 1,692 clusters spread across the country with 1,026 clusters in rural areas and 666 in urban areas.

    Mode of data collection

    Computer Assisted Personal Interview [capi]

    Research instrument

    Eight questionnaires were used for the 2022 KDHS: 1. A full Household Questionnaire 2. A short Household Questionnaire 3. A full Woman's Questionnaire 4. A short Woman's Questionnaire 5. A Man's Questionnaire 6. A full Biomarker Questionnaire 7. A short Biomarker Questionnaire 8. A Fieldworker Questionnaire.

    The Household Questionnaire collected information on: o Background characteristics of each person in the household (for example, name, sex, age, education, relationship to the household head, survival of parents among children under age 18) o Disability o Assets, land ownership, and housing characteristics o Sanitation, water, and other environmental health issues o Health expenditures o Accident and injury o COVID-19 (prevalence, vaccination, and related deaths) o Household food consumption

    The Woman's Questionnaire was used to collect information from women age 15-49 on the following topics: o Socioeconomic and demographic characteristics o Reproduction o Family planning o Maternal health care and breastfeeding o Vaccination and health of children o Children's nutrition o Woman's dietary diversity o Early childhood development o Marriage and sexual activity o Fertility preferences o Husbands' background characteristics and women's employment activity o HIV/AIDS, other sexually transmitted infections (STIs), and tuberculosis (TB) o Other health issues o Early Childhood Development Index 2030 o Chronic diseases o Female genital mutilation/cutting o Domestic violence

    The Man's Questionnaire was administered to men age 15-54 living in the households selected for long Household Questionnaires. The questionnaire collected information on: o Socioeconomic and demographic characteristics o Reproduction o Family planning o Marriage and sexual activity o Fertility preferences o Employment and gender roles o HIV/AIDS, other STIs, and TB o Other health issues o Chronic diseases o Female genital mutilation/cutting o Domestic violence

    The Biomarker Questionnaire collected information on anthropometry (weight and height). The long Biomarker Questionnaire collected anthropometry measurements for children age 0-59 months, women age 15-49, and men age 15-54, while the short questionnaire collected weight and height measurements only for children age 0-59 months.

    The Fieldworker Questionnaire was used to collect basic background information on the people who collected data in the field. This included team supervisors, interviewers, and biomarker technicians.

    All questionnaires except the Fieldworker Questionnaire were translated into the Swahili language to make it easier for interviewers to ask questions in a language that respondents could understand.

    Cleaning operations

    Data were downloaded from the central servers and checked against the inventory of expected returns to account for all data collected in the field. SyncCloud was also used to generate field check tables to monitor progress and flag any errors, which were communicated back to the field teams for correction.

    Secondary editing was done by members of the central office team, who resolved any errors that were not corrected by field teams during data collection. A CSPro batch editing tool was used for cleaning and tabulation during data analysis.

    Response rate

    A total of 42,022 households were selected for the sample, of which 38,731 (92%) were found to be occupied. Among the occupied households, 37,911 were successfully interviewed, yielding a response rate of 98%. The response rates for urban and rural households were 96% and 99%, respectively. In the interviewed households, 33,879 women age 15-49 were identified as eligible for individual interviews. Interviews were completed with 32,156 women, yielding a response rate of 95%. The response rates among women selected for the full and short questionnaires were the similar (95%). In the households selected for the male survey, 16,552 men age 15-54 were identified as eligible for individual interviews and 14,453 were successfully interviewed, yielding a response rate of 87%.

  11. d

    Primary Mathematics and Reading Initiative Kenya

    • datasets.ai
    • s.cnmilf.com
    • +1more
    21
    Updated Aug 7, 2024
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    US Agency for International Development (2024). Primary Mathematics and Reading Initiative Kenya [Dataset]. https://datasets.ai/datasets/primary-mathematics-and-reading-initiative-kenya
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    21Available download formats
    Dataset updated
    Aug 7, 2024
    Dataset authored and provided by
    US Agency for International Development
    Area covered
    Kenya
    Description

    The USAID/Kenya Primary Math and Reading (PRIMR) initiative is a task order under the USAID Education Data for Decision Making (EdData II) project that operates in collaboration with the Kenyan Ministry of Education, Science and Technology (MoEST) and USAID/Kenya, and implemented by RTI International. The program is a randomized controlled trial intervention that included formal (public or government) schools and low-cost private schools (LCPS) located in Nairobi, Kiambu, Nakuru and Kisumu counties. PRIMR and its Kenyan partners created, published, and distributed new teaching and learning materials, based on the existing Kenyan curriculum; designed and led professional development to build the skills of educators and improve student literacy outcomes; and introduced a number of innovative teaching methods. Teachers and head teachers received training to encourage active learning and participation by both girls and boys in the classroom and were further supported with frequent visits and advising by trained instructional coaches. By mutual agreement among the MoEST, USAID, and RTI, approximately 500 formal schools and LCPSs located in Nairobi, Kiambu, Nakuru, and Kisumu counties were to participate in the PRIMR Initiative. To choose the sample of formal schools, the project team first selected all eligible zones from within the selected locations, then randomly assigned a subset of zones to groups that would receive the PRIMR treatment in phases (Cohorts 1, 2, and 3). Across all three cohorts, 262 formal schools were selected. Sampling for LCPSs began by clustering the schools into geographic groups of either 10 or 15 schools from across Nairobi’s divisions. Twenty clusters then were randomly assigned to Cohorts 1, 2, or 3, stratified by geographic region. The number of LCPSs selected was 240. In January 2012, the Cohort 1 schools (125 schools: 66 public, 59 LCPS) began implementing the reading interventions using PRIMR-designed materials and techniques, and the math intervention followed beginning in July 2012. The Cohort 2 schools (185: 65 public, 120 LCPS) began reading and math interventions in January 2013. Cohort 3 schools (101: 51 public, 50 LCPS) served as a control group for most of the program, and then began receiving the full intervention during the final stages of PRIMR (January 2014). In addition, it was decided that the 2014 phase of the intervention would be extended to all 547 remaining schools, rather than only to Cohort 3 as originally planned. As a result, the number of pupils benefitting increased from 12,755 in January 2012 to 56,036 in January 2014. Randomly selected students from all treatment and control schools were assessed via administration of a combined Early Grade Reading Assessment (EGRA), Early Grade Mathematics Assessment (EGMA), and Snapshot of School Management Effectiveness (SSME) at three time points: baseline, midterm, and endline. The PRIMR Initiative’s research design included several “experiments within an experiment.” These consisted of a study of three different combinations of information and communication technology (ICT) as teaching and learning aids in selected schools in Kisumu County; a longitudinal study of about 600 students who were assessed at all three time points, with their reading and numeracy competency levels compared and contrasted across the assessments; and MoEST-driven policy research on various education issues at the national level.

  12. f

    Data_Sheet_1_Developing an intervention to improve the quality of childcare...

    • figshare.com
    • frontiersin.figshare.com
    docx
    Updated Jul 17, 2023
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    Linda Oloo; Helen Elsey; Mary Abboah-Offei; Martin Kiyeng; Patrick Amboka; Kenneth Okelo; Patricia Kitsao-Wekulo; Elizabeth Kimani-Murage; Nelson Langa't; Margaret Nampijja (2023). Data_Sheet_1_Developing an intervention to improve the quality of childcare centers in resource-poor urban settings: a mixed methods study in Nairobi, Kenya.docx [Dataset]. http://doi.org/10.3389/fpubh.2023.1195460.s001
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    docxAvailable download formats
    Dataset updated
    Jul 17, 2023
    Dataset provided by
    Frontiers
    Authors
    Linda Oloo; Helen Elsey; Mary Abboah-Offei; Martin Kiyeng; Patrick Amboka; Kenneth Okelo; Patricia Kitsao-Wekulo; Elizabeth Kimani-Murage; Nelson Langa't; Margaret Nampijja
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Nairobi, Kenya
    Description

    BackgroundGlobally, 350 million under-5s do not have adequate childcare. This may damage their health and development and undermine societal and economic development. Rapid urbanization is changing patterns of work, social structures, and gender norms. Parents, mainly mothers, work long hours for insecure daily wages. To respond to increasing demand, childcare centers have sprung up in informal settlements. However, there is currently little or no support to ensure they provide safe, nurturing care accessible to low-income families. Here, we present the process of co-designing an intervention, delivered by local government community health teams to improve the quality of childcare centers and ultimately the health and development of under-5 children in informal settlements in Kenya.MethodsThis mixed methods study started with a rapid mapping of the location and basic characteristics of all childcare centers in two informal settlements in Nairobi. Qualitative interviews were conducted with parents and grandparents (n = 44), childcare providers, and community health teams (n = 44). A series of 7 co-design workshops with representatives from government and non-governmental organizations (NGOs), community health teams, and childcare providers were held to design the intervention. Questionnaires to assess the knowledge, attitudes, and practices of community health volunteers (n = 22) and childcare center providers (n = 66) were conducted.ResultsIn total, 129 childcare centers were identified −55 in Korogocho and 77 in Viwandani. School-based providers dominated in Korogocho (73%) while home-based centers were prevalent in Viwandani (53%). All centers reported minimal support from any organization (19% supported) and this was particularly low among home-based (9%) and center-based (14%) providers. Home-based center providers were the least likely to be trained in early childhood development (20%), hence the co-designed intervention focused on supporting these centers. All co-design stakeholders agreed that with further training, community health volunteers were well placed to support these informal centers. Findings showed that given the context of informal settlements, support for strengthening management within the centers in addition to the core domains of WHO's Nurturing Care Framework was required as a key component of the intervention.ConclusionImplementing a co-design process embedded within existing community health systems and drawing on the lived experiences of childcare providers and parents in informal settlements facilitated the development of an intervention with the potential for scalability and sustainability. Such interventions are urgently needed as the number of home-based and small center-based informal childcare centers is growing rapidly to meet the demand; yet, they receive little support to improve quality and are largely unregulated. Childcare providers, and government and community health teams were able to co-design an intervention delivered within current public community health structures to support centers in improving nurturing care. Further research on the effectiveness and sustainability of support to private and informal childcare centers in the context of low-income urban neighborhoods is needed.

  13. A pragmatic randomized maternal education trial in rural Uganda - Eight...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Jun 28, 2023
    + more versions
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    Paul Kakwangire; Grace Muhoozi; Moses Ngari; Nicholas Matovu; Ane Westerberg; Per Iversen; Prudence Atukunda (2023). A pragmatic randomized maternal education trial in rural Uganda - Eight years of sustained improvement in child development [Dataset]. http://doi.org/10.5061/dryad.n8pk0p31r
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    zipAvailable download formats
    Dataset updated
    Jun 28, 2023
    Dataset provided by
    Oslo University Hospital
    Queen's University Belfast
    Kyambogo University
    Kenya Medical Research Institute
    University of Bergen
    University of Oslo
    Authors
    Paul Kakwangire; Grace Muhoozi; Moses Ngari; Nicholas Matovu; Ane Westerberg; Per Iversen; Prudence Atukunda
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Uganda
    Description

    Background Nutrition and stimulation interventions may promote early childhood development, but little is known about the long-term benefits of such interventions, particularly in low- and middle-income countries. We now conducted a follow-up study on a cluster-randomized maternal education trial that was conducted when their children were 6–8 months old, to assess the sustainability of the developmental benefits eight years after the intervention. Methods and findings The intervention consisted of education in nutrition, hygiene, oral sanitation and child stimulation. In the current study, we assessed child processing and cognitive abilities using the Kaufman Assessment Battery for Children Second Edition (KABC-II) and attention and inhibitory control using the Test of Variables of Attention (TOVA). Using Stata version 17.0, t-tests and multi-level regression were employed to compare scores from KABC-II and TOVA tests in the two study groups adjusting for clustering effect. The data were analyzed by intention-to-treat. The original trial included 511 mother-child pairs (intervention n=263, control n=248), whereas in the current study, 361 (71%; intervention n=185, control n=176) pairs were available for analyses. The intervention group scored higher than the controls (all P-values<0.001) on all five KABC-II sub-scales, as well as on the KABC-II global score (mean difference: 14, 95% CI: 12–16; P<0.001). Furthermore, for all five TOVA variables, the intervention group scored higher than the controls in both the visual and auditory tasks (all P-values <0.05). The main limitation is that we were unable to determine the exact individual contribution of each component (nutrition, hygiene and stimulation) of the intervention to the developmental benefits since they were all delivered as a combined package. Conclusions The intervention group consistently scored markedly higher on both psychometric tests. Thus, even eight years after the original maternal education intervention, the developmental benefits that we observed at child age of one, two and three years, were sustained. Methods The data was collected through field-work where we approached the study participants in their home communitites. We then cleaned the data, analyzed them statistically and finally interpretated the findings. More details can be found in the Method-section of the paper.

  14. T

    Kenya - Population Of The Official Age For Secondary Education, Both Sexes

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 16, 2017
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    TRADING ECONOMICS (2017). Kenya - Population Of The Official Age For Secondary Education, Both Sexes [Dataset]. https://tradingeconomics.com/kenya/population-of-the-official-age-for-secondary-education-both-sexes-number-wb-data.html
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    json, xml, excel, csvAvailable download formats
    Dataset updated
    Jun 16, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Kenya
    Description

    School age population, secondary education, both sexes (number) in Kenya was reported at 7686730 Persons in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Population of the official age for secondary education, both sexes - actual values, historical data, forecasts and projections were sourced from the World Bank on January of 2025.

  15. T

    Kenya - Duration Of Compulsory Education (years)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2017
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    TRADING ECONOMICS (2017). Kenya - Duration Of Compulsory Education (years) [Dataset]. https://tradingeconomics.com/kenya/duration-of-compulsory-education-years-wb-data.html
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    xml, json, csv, excelAvailable download formats
    Dataset updated
    May 28, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Kenya
    Description

    Compulsory education, duration (years) in Kenya was reported at 12 years in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Duration of compulsory education (years) - actual values, historical data, forecasts and projections were sourced from the World Bank on January of 2025.

  16. K

    Kenya KE: Current Education Expenditure: Tertiary: % of Total Expenditure in...

    • ceicdata.com
    Updated Sep 15, 2022
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    CEICdata.com (2022). Kenya KE: Current Education Expenditure: Tertiary: % of Total Expenditure in Tertiary Public Institutions [Dataset]. https://www.ceicdata.com/en/kenya/education-statistics/ke-current-education-expenditure-tertiary--of-total-expenditure-in-tertiary-public-institutions
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    Dataset updated
    Sep 15, 2022
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2011 - Dec 1, 2015
    Area covered
    Kenya
    Variables measured
    Education Statistics
    Description

    Kenya KE: Current Education Expenditure: Tertiary: % of Total Expenditure in Tertiary Public Institutions data was reported at 97.618 % in 2015. This records a decrease from the previous number of 100.000 % for 2014. Kenya KE: Current Education Expenditure: Tertiary: % of Total Expenditure in Tertiary Public Institutions data is updated yearly, averaging 97.618 % from Dec 2011 (Median) to 2015, with 5 observations. The data reached an all-time high of 100.000 % in 2014 and a record low of 92.878 % in 2012. Kenya KE: Current Education Expenditure: Tertiary: % of Total Expenditure in Tertiary Public Institutions data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank.WDI: Education Statistics. Current expenditure is expressed as a percentage of direct expenditure in public educational institutions (instructional and non-instructional) of the specified level of education. Financial aid to students and other transfers are excluded from direct expenditure. Current expenditure is consumed within the current year and would have to be renewed if needed in the following year. It includes staff compensation and current expenditure other than for staff compensation (ex. on teaching materials, ancillary services and administration).; ; United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics.; Median;

  17. T

    Kenya - Share Of Youth Not In Education, Employment Or Training, Total

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 10, 2020
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    TRADING ECONOMICS (2020). Kenya - Share Of Youth Not In Education, Employment Or Training, Total [Dataset]. https://tradingeconomics.com/kenya/share-of-youth-not-in-education-employment-or-training-total-percent-of-youth-population-wb-data.html
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    xml, csv, json, excelAvailable download formats
    Dataset updated
    Mar 10, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Kenya
    Description

    Share of youth not in education, employment or training, total (% of youth population) in Kenya was reported at 18.73 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kenya - Share of youth not in education, employment or training, total - actual values, historical data, forecasts and projections were sourced from the World Bank on January of 2025.

  18. CPI for education in Kenya 2019-2021

    • statista.com
    Updated Sep 22, 2023
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    Statista (2023). CPI for education in Kenya 2019-2021 [Dataset]. https://www.statista.com/statistics/1165969/cpi-for-education-in-kenya/
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    Dataset updated
    Sep 22, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2019 - Jan 2021
    Area covered
    Kenya
    Description

    As of January 2021, the Consumer Price Index (CPI) for education in Kenya decreased to 104.92 points, after reaching a peak at 105.04 points at the end of 2020. The indicator, that measures price changes over time, overall increased along the period started in February 2019.

  19. K

    Kenya Trained teachers in primary education - données, graphique |...

    • fr.theglobaleconomy.com
    csv, excel, xml
    Updated Jul 17, 2024
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    Globalen LLC (2024). Kenya Trained teachers in primary education - données, graphique | TheGlobalEconomy.com [Dataset]. fr.theglobaleconomy.com/Kenya/Trained_teachers_primary_education/
    Explore at:
    csv, xml, excelAvailable download formats
    Dataset updated
    Jul 17, 2024
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 2003 - Dec 31, 2009
    Area covered
    Kenya
    Description

    Kenya: Trained teachers in primary education, percent of total: Pour cet indicateur, UNESCO fournit des données pour la Kenya de 2003 à 2009. La valeur moyenne pour Kenya pendant cette période était de 98.54 pour cent avec un minimum de 96.81 pour cent en 2009 et un maximum de 99.43 pour cent en 2006.

  20. w

    Assessing the Educational Impact of Malaria Prevention in Kenyan Schools...

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Dec 5, 2019
    + more versions
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    Matthew Jukes (2019). Assessing the Educational Impact of Malaria Prevention in Kenyan Schools 2010-2012 - Kenya [Dataset]. https://microdata.worldbank.org/index.php/catalog/671
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    Dataset updated
    Dec 5, 2019
    Dataset provided by
    Matthew Jukes
    Simon Brooker
    Time period covered
    2010 - 2012
    Area covered
    Kenya
    Description

    Abstract

    The Government of Kenya is interested in understanding how malaria prevention and treatment can improve the education of school children when it is combined with effective teaching. This project examines the impact of school-based malaria intermittent screening and treatment and enhanced literacy training and support for teachers on children's health and educational outcomes.

    A cluster randomized trial was implemented with 5,233 children in 101 government primary schools on the south coast of Kenya in 2010-2012. The intervention was delivered to children randomly selected from classes 1 and 5 who were followed up for 24 months. Once a school term, children were screened by public health workers using malaria rapid diagnostic tests (RDTs), and children (with or without malaria symptoms) found to be RDT-positive were treated with a six dose regimen of artemether-lumefantrine (AL). Given the nature of the intervention, the trial was not blinded. The primary outcomes were anemia and sustained attention. Secondary outcomes were malaria parasitaemia and educational achievement. Data were analyzed on an intention to treat basis. The study is registered with ClinicalTrials.gov, NCT00878007.

    The schools were randomly assigned to one of four experimental groups: some schools have been tested and treated for malaria; some schools have had extra support for teachers of English and Swahili; some schools have been both tested for malaria and received extra teacher support; and other schools have gotten neither of the two programs.

    Following recruitment, baseline health and education surveys were undertaken in January-February 2010, which were followed by the first round of intermittent screening and treatment (IST) and the teacher training workshop. Classroom observations occurred in May 2010, followed by the second round of IST in June-July 2010. The third round of IST occurred in September 2010. The first follow-up education surveys were carried out in November 2010 and the first health surveys - in February and March 2011, followed by a round of IST as well as refresher teacher training for the literacy intervention. The final round of IST was conducted in September 2011 with the 24 months follow-up health and education survey in February-March 2012.

    The data from the baseline and follow-up surveys is documented here.

    Geographic coverage

    Kwale and Msambweni districts

    Analysis unit

    Individuals, households, schools

    Universe

    The survey cover children in grades 1 and 5 in government schools in Kwale and Msambweni districts, their parents/guardians, head teaches of schools in above mentioned districts.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    School selection was made from the 197 government primary schools in Kwale and Msambweni districts. In Kwale district, a separate study is evaluating the impact of an alternative literacy intervention in two of the four zones; therefore only 20 schools in this district were included in our study allowing the two interventions to proceed without leakage. In Msambweni district, 81 of 112 schools were selected; schools 70 km or further away from the project office, were excluded due to logistical constraints.

    The randomization of the 101 schools into the four experimental groups was conducted in two stages, each involving public randomization ceremonies:

    Stage 1 - Literacy intervention randomization a) Clusters of schools (groups of between 3-6 schools that meet and share information) were randomised either to receive the literacy intervention or to serve as a control schools. b) This randomization was stratified by (i) cluster size, to ensure equal numbers of schools in the experimental groups; and (ii) average primary school leaving exam scores across the cluster, to balance the two groups for school achievement. c) District officials and representatives from all 26 school clusters were invited to a meeting. Volunteers were asked to randomly draw envelopes each containing a cluster name from 10 pre-stratified ballot boxes and to sequentially place the envelopes in group A and group B.

    Stage 2 - Health intervention randomization a) The health intervention was randomly allocated amongst the 51 schools assigned to the literacy intervention and the 50 schools allocated to serve as control schools during the first randomization. b) Schools were stratified by average primary school leaving exam scores into 5 quintiles and by literacy intervention group, producing 10 strata overall. c) Representatives from the 101 schools and local communities were invited to this randomization ceremony. Volunteers were asked to draw envelopes from the 10 pre-stratified ballot boxes and sequentially place the envelopes in group 1 and group 2.

    During January and February 2010, schools were visited and a census of all children in classes 1 and 5 was conducted, including children absent on the day of visit. This census served as a basis for making a random selection of 25 children with consent from class 1 and 30 children with consent from class 5. Fewer children were selected from class 1 because of the extra educational assessments undertaken with these children and the practical feasibility of conducting the tests in a single day. Some of the classes were small, and this meant that in these classes all children with consent were recruited.

    Of the 5,233 children enrolled initially, 4,446 (85.0%) were included in the 12 month follow-up health survey and 4201 (80.3%) were included in the 24 month health survey. Overall, 4,656 (89.0%) of children were included in the 9 month follow-up education survey and 4,106 (78.5%) in the 24 month follow-up survey.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The following questionnaires and forms are available:

    1) School Questionnaire The school questionnaire is administered to the head teachers of each school during the initial school selection; if absent, the deputy head was interviewed. Information is collected on the characteristics of the school such as the number of boys and girls enrolled in each class, examination results in English, mathematics and Kiswahili, school features such as number of desks and teachers, facilities available such as latrines and the presence of school health activities and materials. Locations of each school were mapped using a handheld Global Positioning System (GPS) receiver, (eTrex Garmin Ltd., Olathe, KS).

    2) Parent questionnaire for class 1 students The parent questionnaire for class 1 students assesses the educational and socio-economic environment of the children's households. This is administered to the parent or guardian at the time of consent. Questions relate to their own reading ability, schooling, and involvement in their children's school, as well as questions on family composition, household construction, asset ownership and mosquito net ownership and use.

    3) Parent questionnaire for class 5 students The parent questionnaire for class 5 students assesses the educational and socio-economic environment of the children's households. This is administered to the parent or guardian at the time of consent. The section on education environment is reduced as the literacy intervention was focused on the class 1 children, so a less extensive knowledge of attitudes to education was required for parents of class 5 children. Questions relate to their schooling level achieved, as well as questions on family composition, household construction, asset ownership, and mosquito net ownership and use.

    4) Nurse survey form for classes 1 and 5 The child ID, child name, and parent name of the randomly selected children are already entered on the form before arrival at the school. The nurse records the attendance of each child, completing the reasons using the codes at the bottom of the form. Height, weight and temperature of each child is recorded on the form. The child is also asked their age, which is recorded.

    5) Health Technician survey form for classes 1 and 5 The child ID, child name, and parent name of the randomly selected children are already entered on the form before arrival at the school. The technician notes whether the child is present, and then records the hemoglobin reading, whether or not a blood slide has been taken, and the timing and result of the malaria rapid diagnostic test (RDT). This form is for assessment of children in the intervention schools where P falciparum infection is assessed.

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Mary Abboah-Offei; Patrick Amboka; Margaret Nampijja; George Evans Owino; Kenneth Okelo; Patricia Kitsao-Wekulo; Ivy Chumo; Ruth Muendo; Linda Oloo; Maryann Wanjau; Elizabeth Mwaniki; Maurice Mutisya; Emma Haycraft; Robert Hughes; Paula Griffiths; Helen Elsey (2023). Table_2_Improving early childhood development in the context of the nurturing care framework in Kenya: A policy review and qualitative exploration of emerging issues with policy makers.DOCX [Dataset]. http://doi.org/10.3389/fpubh.2022.1016156.s002

Table_2_Improving early childhood development in the context of the nurturing care framework in Kenya: A policy review and qualitative exploration of emerging issues with policy makers.DOCX

Related Article
Explore at:
docxAvailable download formats
Dataset updated
Jun 13, 2023
Dataset provided by
Frontiers
Authors
Mary Abboah-Offei; Patrick Amboka; Margaret Nampijja; George Evans Owino; Kenneth Okelo; Patricia Kitsao-Wekulo; Ivy Chumo; Ruth Muendo; Linda Oloo; Maryann Wanjau; Elizabeth Mwaniki; Maurice Mutisya; Emma Haycraft; Robert Hughes; Paula Griffiths; Helen Elsey
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
Kenya
Description

IntroductionThe Nurturing Care Framework (NCF) describes “nurturing care” as the ability of nations and communities to support caregivers and provide an environment that ensures children's good health and nutrition, protects them from threats, and provides opportunities for early learning through responsive and emotionally supportive interaction. We assessed the extent to which Kenyan government policies address the components of the NCF and explored policy/decision makers' views on policy gaps and emerging issues.MethodsA search strategy was formulated to identify policy documents focusing on early childhood development (ECD), health and nutrition, responsive caregiving, opportunities for early learning and security and safety, which are key components of the NCF. We limited the search to policy documents published since 2010 when the Kenya constitution was promulgated and ECD functions devolved to county governments. Policy/decision-maker interviews were also conducted to clarify emerging gaps from policy data. Data was extracted, coded and analyzed based on the components of the NCF. Framework analysis was used for interview data with NCF being the main framework of analysis. The Jaccard's similarity coefficient was used to assess similarities between the themes being compared to further understand the challenges, successes and future plans of policy and implementation under each of the NCF domains.Results127 policy documents were retrieved from government e-repository and county websites. Of these, n = 91 were assessed against the inclusion criteria, and n = 66 were included in final analysis. The 66 documents included 47 County Integrated Development Plans (CIDPs) and 19 national policy documents. Twenty policy/decision-maker interviews were conducted. Analysis of both policy and interview data reveal that, while areas of health and nutrition have been considered in policies and county level plans (coefficients >0.5), the domains of early learning, responsive caregiving and safety and security face significant policy and implementation gaps (coefficients ≤ 0.5), particularly for the 0–3 year age group. Inconsistencies were noted between county level implementation plans and national policies in areas such as support for children with disabilities and allocation of budget to early learning and nutrition domains.ConclusionFindings indicate a strong focus on nutrition and health with limited coverage of responsive caregiving and opportunities for early learning domains. Therefore, if nurturing care goals are to be achieved in Kenya, policies are needed to support current gaps identified with urgent need for policies of minimum standards that provide support for improvements across all Nurturing Care Framework domains.

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