This is the percentage of pupils in state-funded primary schools meeting the expected standard in reading, writing, and mathematics (RWM) at key stage 2 (KS2). The expected standard in reading and mathematics is a scaled score of 100 or above. The expected standard in writing is a teacher assessment of 'working at the expected standard' (EXS) or 'working at greater depth within the expected standard' (GDS).

All children in state-funded primary schools, including most academies and free schools, are required to take part in KS2 national curriculum assessments before they move to secondary school. Tests and teacher assessments provide complementary information about pupils' attainment. The tests are designed to show what pupils have achieved in selected parts of a subject at the end of each key stage. Teacher assessment is the teachers' judgement of each pupil's performance in the whole subject over the whole academic year.

The description 'state-funded primary schools' refers to LA maintained schools, academies, and free schools. Excludes alternative provision and independent schools. The 'England state-funded schools' figures here may be slightly different from the 'England state-funded schools only' figures in the national tables. The figures presented here have been calculated on the same basis as the LA figures in this table (i.e., including pupils with missing results or pending maladministration).

Writing teacher assessment and reading, writing, and maths (combined) measures from 2018 onwards are not directly comparable to previous years due to changes in the writing teacher assessment frameworks. Data is not available for 2020 and 2021 as assessments were cancelled in these years due to the COVID-19 pandemic.

Data is Powered by LG Inform Plus and automatically checked for new data on the 3rd of each month.

Out of all ethnic groups, pupils from the White Irish and Chinese ethnic groups were most likely to meet the expected standard in reading in 2018/19.

Abstract

Education Quality Improvement Programme in Tanzania (EQUIP-T) is a six-year (2014-20) Government of Tanzania programme, funded by the United Kingdom Department for International Development (DFID), which seeks to improve the quality of primary education and to improve pupil learning outcomes, especially for girls. The programme focuses on strengthening professional capacity and performance of teachers, school leadership and management, systems which support district management of education, and community participation in education. Initially, the programme was intended to run for four years, with activities targeted at seven of the most educationally disadvantaged regions in Tanzania. In 2017 the programme was extended for a further two years, and the extension introduced some new sub-components to the seven regions, and introduced a reduced package of interventions to two new regions.

The independent Impact Evaluation (IE) of EQUIP-T is a five-year study funded by DFID. It is designed to: i) generate evidence on the impact of EQUIP-T on primary pupil learning outcomes, including any differential effects for boys and girls; ii) examine perceptions of effectiveness of different EQUIP-T components; iii) provide evidence on the fiscal affordability of scaling up EQUIP-T post-endline; and iv) communicate evidence generated by the impact evaluation to policy-makers and key education stakeholders. The evaluation uses a quasi-experimental approach to quantitative estimation of impact that combines propensity score matching (PSM) with difference-indifferences (DID).

The research priorities for the quantitative endline IE are captured in a comprehensive endline evaluation matrix (see Annex C in the 'EQUIP-Tanzania Impact Evaluation. Endline Quantitative Technical Report, Volume I: Results and Discussion' under Reports and policy notes). The matrix sets out evaluation questions linked to the programme theory of change. It asks questions related to the expected results at each stage along the results chain (from the receipt of inputs to delivery of outputs, and contributions to outcomes and impact) under each of the programme's components. The aim is to establish: (i) whether changes have happened as expected; (ii) why they happened or did not happen (i.e. whether key assumptions in the theory of change hold or not); (iii) whether there are any important unanticipated changes; and (iv) what links there are between the components in driving changes.

The main IE research areas are: -Impact of EQUIP-T on standard 3 pupil learning in Kiswahili and mathematics. -Impact of EQUIP-T on teacher absence from school and from classrooms. -Impact of EQUIP-T on selected aspects of school leadership and management.

The IE uses a mixed methods approach that includes: -A quantitative survey of 100 government primary schools in 17 programme treatment districts and 100 schools in 8 control districts in 2014, 2016 and 2018 covering: *Standard three pupils and their parents/caregivers; *Teachers who teach standards 1-3 Kiswahili; *Teachers who teach standards 1-3 mathematics; *Schools; *Head teachers; and *Standard two lesson observations in Kiswahili and mathematics.

-Qualitative fieldwork in a few treatment schools that overlap with a sub-set of the quantitative survey schools, in 2014, 2016 and 2019, consisting of key informant interviews (KIIs) and focus group discussions (FGDs) with head teachers, teachers, pupils, parents, school committee (SC) members, PTP members, region, district and ward education officials and EQUIP-T programme staff.

The endline data available in the World Bank Microdata Catalog are from the EQUIP-T IE quantitative endline survey conducted in 2018. The endline qualitative research will take place in mid-2019 with results available in early 2020.

Geographic coverage

The survey is representative of 17 EQUIP-T programme treatment districts. The survey is NOT representative of the 8 control districts. For more details see the section on Representativeness in 'EQUIP-Tanzania Impact Evaluation. Final Baseline Technical Report, Volume I: Results and Discussion' and 'EQUIP-Tanzania Impact Evaluation. Final Baseline Technical Report, Volume II: Methods and Technical Annexes' under Reports and policy notes.

The 17 treatment districts are:

-Dodoma Region: Bahi DC, Chamwino DC, Kongwa DC, Mpwapwa DC -Kigoma Region: Kakonko DC, Kibondo DC -Shinyanga Region: Kishapu DC, Shinyanga DC -Simiyu Region: Bariadi DC, Bariadi TC, Itilima DC, Maswa DC, Meatu DC -Tabora Region: Igunga DC, Nzega DC, Sikonge DC, Uyui DC

The 8 control districts are:

-Arusha Region: Ngorongoro DC -Mwanza Region: Misungwi DC -Pwani Region: Rufiji DC
-Rukwa Region: Nkasi DC -Ruvuma Region: Tunduru DC -Singida Region: Ikungi DC, Singida DC -Tanga Region: Kilindi DC

Analysis unit

• School
• Teacher
• Pupil
• Lesson (not sampled)
• EQUIP-T training session

Kind of data

Sample survey data [ssd]

Sampling procedure

Because the EQUIP-T regions and districts were purposively selected (see 'EQUIP-Tanzania Impact Evaluation. Final Baseline Technical Report, Volume I: Results and Discussion' under Reports and policy notes), the IE sampling strategy used propensity score matching (PSM) to: (i) match eligible control districts to the pre-selected and eligible EQUIP-T districts (see below), and (ii) match schools from the control districts to a sample of randomly selected treatment schools in the treatment districts. The same schools are surveyed for each round of the IE (panel of schools) and a cross section of standard 3 pupils and Standard 1-3 teachers will be interviewed at each round of the survey (no pupil panel or teacher panel).

Identifying districts eligible for matching

Eligible control and treatment districts were those not participating in any other education programme or project that may confound the measurement of EQUIP-T impact. To generate the list of eligible control and treatment districts, all districts that are contaminated because of other education programmes or projects or may be affected by programme spill-over were excluded as follows:

-All districts located in Lindi and Mara regions as these are part of the EQUIP-T programme but implementation started later in these two regions (the IE does not cover these two regions); -Districts that will receive partial EQUIP-T programme treatment or will be subject to potential EQUIP-T programme spillovers; -Districts that are receiving other education programmes/projects that aim to influence the same outcomes as the EQUIP-T programme and would confound measurement of EQUIP-T impact; -Districts that were part of pre-test 1 (two districts); and -Districts that were part of pre-test 2 (one district).

Sampling frame

To be able to select an appropriate sample of pupils and teachers within schools and districts, the sampling frame consisted of information at three levels:

-District; -School; and -Within school.

The sampling frame data at the district and school levels was compiled from the following sources: the 2002 and 2012 Tanzania Population Censuses, Education Management Information System (EMIS) data from the Ministry of Education and Vocational Training (MoEVT) and the Prime Minister's Office for Regional and Local Government (PMO-RALG), and the UWEZO 2011 student learning assessment survey. For within school level sampling, the frames were constructed upon arrival at the selected schools and was used to sample pupils and teachers on the day of the school visit.

Sampling stages

Stage 1: Selection of control districts

Because the treatment districts were known, the first step was to find sufficiently similar control districts that could serve as the counterfactual. PSM was used to match eligible control districts to the pre-selected, eligible treatment districts using the following matching variables: Population density, proportion of male headed households, household size, number of children per household, proportion of households that speak an ethnic language at home, and district level averages for household assets, infrastructure, education spending, parental education, school remoteness, pupil learning levels and pupil drop out.

Stage 2: Selection of treatment schools

In the second stage, schools in the treatment districts were selected using stratified systematic random sampling. The schools were selected using a probability proportional to size approach, where the measure of school size was the standard two enrolment of pupils. This means that schools with more pupils had a higher probability of being selected into the sample. To obtain a representative sample of programme treatment schools, the sample was implicitly stratified along four dimensions:

-District; -PSLE scores for Kiswahili; -PSLE scores for mathematics; and -Total number of teachers per school.

Stage 3: Selection of control schools

As in stage one, a non-random PSM approach was used to match eligible control schools to the sample of treatment schools. The matching variables were similar to the ones used as stratification criteria: Standard two enrolment, PSLE scores for Kiswahili and mathematics, and the total number of teachers per

Background:
The Millennium Cohort Study (MCS) is a large-scale, multi-purpose longitudinal dataset providing information about babies born at the beginning of the 21st century, their progress through life, and the families who are bringing them up, for the four countries of the United Kingdom. The original objectives of the first MCS survey, as laid down in the proposal to the Economic and Social Research Council (ESRC) in March 2000, were:

• to chart the initial conditions of social, economic and health advantages and disadvantages facing children born at the start of the 21st century, capturing information that the research community of the future will require
• to provide a basis for comparing patterns of development with the preceding cohorts (the National Child Development Study, held at the UK Data Archive under GN 33004, and the 1970 Birth Cohort Study, held under GN 33229)
• to collect information on previously neglected topics, such as fathers' involvement in children's care and development
• to focus on parents as the most immediate elements of the children's 'background', charting their experience as mothers and fathers of newborn babies in the year 2000, recording how they (and any other children in the family) adapted to the newcomer, and what their aspirations for her/his future may be
• to emphasise intergenerational links including those back to the parents' own childhood
• to investigate the wider social ecology of the family, including social networks, civic engagement and community facilities and services, splicing in geo-coded data when available

Additional objectives subsequently included for MCS were:

• to provide control cases for the national evaluation of Sure Start (a government programme intended to alleviate child poverty and social exclusion)
• to provide samples of adequate size to analyse and compare the smaller countries of the United Kingdom, and include disadvantaged areas of England

Further information about the MCS can be found on the Centre for Longitudinal Studies web pages.

The content of MCS studies, including questions, topics and variables can be explored via the CLOSER Discovery website.

The first sweep (MCS1) interviewed both mothers and (where resident) fathers (or father-figures) of infants included in the sample when the babies were nine months old, and the second sweep (MCS2) was carried out with the same respondents when the children were three years of age. The third sweep (MCS3) was conducted in 2006, when the children were aged five years old, the fourth sweep (MCS4) in 2008, when they were seven years old, the fifth sweep (MCS5) in 2012-2013, when they were eleven years old, the sixth sweep (MCS6) in 2015, when they were fourteen years old, and the seventh sweep (MCS7) in 2018, when they were seventeen years old. End User Licence versions of MCS studies:
The End User Licence (EUL) versions of MCS1, MCS2, MCS3, MCS4, MCS5, MCS6 and MCS7 are held under UK Data Archive SNs 4683, 5350, 5795, 6411, 7464, 8156 and 8682 respectively. The longitudinal family file is held under SN 8172.

Sub-sample studies:
Some studies based on sub-samples of MCS have also been conducted, including a study of MCS respondent mothers who had received assisted fertility treatment, conducted in 2003 (see EUL SN 5559). Also, birth registration and maternity hospital episodes for the MCS respondents are held as a separate dataset (see EUL SN 5614).


How to access genetic and/or bio-medical sample data from a range of longitudinal surveys:
For information on how to access biomedical data from MCS that are not held at the UKDS, see the CLS Genetic data and biological samples webpage.

Secure Access datasets:
Secure Access versions of the MCS have more restrictive access conditions than versions available under the standard End User Licence or Special Licence (see 'Access data' tab above).

Secure Access versions of the MCS include:

• detailed sensitive variables not available under EUL. These have been grouped thematically and are held under SN 8753 (socio-economic, accommodation and occupational data), SN 8754 (self-reported health, behaviour and fertility), SN 8755 (demographics, language and religion) and SN 8756 (exact participation dates). These files replace previously available studies held under SNs 8456 and 8622-8627
  
• detailed geographical identifier files which are grouped by sweep held under SN 7758 (MCS1), SN 7759 (MCS2), SN 7760 (MCS3), SN 7761 (MCS4), SN 7762 (MCS5 2001 Census Boundaries), SN 7763 (MCS5 2011 Census Boundaries), SN 8231 (MCS6 2001 Census Boundaries), SN 8232 (MCS6 2011 Census Boundaries), SN 8757 (MCS7), SN 8758 (MCS7 2001 Census Boundaries) and SN 8759 (MCS7 2011 Census Boundaries). These files replace previously available files grouped by geography SN 7049 (Ward level), SN 7050 (Lower Super Output Area level), and SN 7051 (Output Area level)
• linked education administrative datasets for Key Stages 1, 2, 4 and 5 held under SN 8481 (England). This replaces previously available datasets for Key Stage 1 (SN 6862) and Key Stage 2 (SN 7712)
  
• linked education administrative datasets for Key Stage 1 held under SN 7414 (Scotland)
• linked education administrative dataset for Key Stages 1, 2, 3 and 4 under SN 9085 (Wales)
  
• linked NHS Patient Episode Database for Wales (PEDW) for MCS1 – MCS5 held under SN 8302
• linked Scottish Medical Records data held under SNs 8709, 8710, 8711, 8712, 8713 and 8714;
• Banded Distances to English Grammar Schools for MCS5 held under SN 8394
• linked Health Administrative Datasets (Hospital Episode Statistics) for England for years 2000-2019 held under SN 9030
• linked Health Administrative Datasets (SAIL) for Wales held under SN 9310
  
• linked Hospital of Birth data held under SN 5724.

The linked education administrative datasets held under SNs 8481,7414 and 9085 may be ordered alongside the MCS detailed geographical identifier files only if sufficient justification is provided in the application. Users are also only allowed access to either 2001 or 2011 of Geographical Identifiers Census Boundaries studies. So for MCS5 either SN 7762 (2001 Census Boundaries) or SN 7763 (2011 Census Boundaries), for the MCS6 users are only allowed either SN 8231 (2001 Census Boundaries) or SN 8232 (2011 Census Boundaries); and the same applies for MCS7 so either SN 8758 (2001 Census Boundaries) or SN 8759 (2011 Census Boundaries).

Researchers applying for access to the Secure Access MCS datasets should indicate on their ESRC Accredited Researcher application form the EUL dataset(s) that they also wish to access (selected from the MCS Series Access web page).

Millennium Cohort Study: Linked Education Administrative Datasets (KS1-KS4), Wales: Secure Access

These datasets include education administrative records for Wales up to age 16 to survey data for cohort members in the MCS. The main aim of this data linkage exercise is to enhance the research potential of the study, by combining administrative education records with the rich information collected in the surveys.

Datasets include anonymised Local Education Authorities (LEA) to allow comparison of results across LEA. The data were obtained only for children whose parents/carers gave consent to data linkage, and who were successfully matched.