These data are gathered as part of the Summary of Annual Examination Results exercise. This exercise takes place between May and December of each year and collects information on the examination performance of post-primary pupils in Year12 and Year 14 in Northern Ireland.

Interactive resource provided by the Department for Education showing individual school performance for every school in Barnet.

Year 1 (Y1) primary school pupils phonics data who met the Expected Standard for Phonics by School Ward for the period 2013 onwards.The data is by school location, rather than by pupil residence. In determining, which ward the data relates to, a Schools list by wards is available. The data source is the National Consortium of Examination Results (NCER).

A summary of Calderdale school performance can be found on the Council website: School performance tables. School performance for individual schools can be found at Compare school performance.

Please note some DFE numbers might have changed please see previous DFE code on Schools list.

Now re-named Performance Tables, these statistics contain school and college level information on the performance of pupils reaching the end of their Key Stage 4 education in England. Source agency: Education Designation: Official Statistics not designated as National Statistics Language: English Alternative title: 2009/10

Attainment data for children at various stages in early years and primary education:

• Early years foundation stage profile (EYFSP);
• Year 1 Phonics;
• Key Stage 1 (KS1);
• Key Stage 2 (KS2).

The data is by school location, rather than by pupil residence, in determining which ward the data relates to. A list of schools by wards is also provided.

The data source is the National Consortium of Examination Results (NCER).

A summary of Calderdale school performance can be found on the Council website: School performance tables .

School performance for individual schools can be found at Compare school performance .

Key Stage 1 (KS1) data for primary school pupils in Year 2 who met or exceeded the Expected Standard (EXS+) by School Ward for the 2016 onwards. The data is by school location, rather than by pupil residence. In determining, which ward the data relates to, a Schools list by wards is available. The data source is the National Consortium of Examination Results (NCER). A summary of Calderdale school performance can be found on the Council website: School performance tables. School performance for individual schools can be found at Compare school performance. Please note some DFE numbers might have changed please see previous DFE code on Schools list.

Calderdale schools including status, type, principals / head teachers, address, website, number on roll as at May census, longitude and latitude, and eastings and northings. Routinely updated when notified of changes.

You can also search online for school details, maps, performance tables and ofsted reports - Search for Schools

Also see - School Clusters and Federations and Other schools data

Now re-named Performance Tables, these statistics contain school and college level information on the performance of pupils reaching the end of their Key Stage 5 education in England.

Source agency: Education

Designation: Official Statistics not designated as National Statistics

Language: English

Alternative title: Achievement and Attainment Tables for GCE/VCE/Applied A/AS and Equivalent Results in England

This data approach student achievement in secondary education of two Portuguese schools. The data attributes include student grades, demographic, social and school related features) and it was collected by using school reports and questionnaires. Two datasets are provided regarding the performance in two distinct subjects: Mathematics (mat) and Portuguese language (por). In [Cortez and Silva, 2008], the two datasets were modeled under binary/five-level classification and regression tasks. Important note: the target attribute G3 has a strong correlation with attributes G2 and G1. This occurs because G3 is the final year grade (issued at the 3rd period), while G1 and G2 correspond to the 1st and 2nd period grades. It is more difficult to predict G3 without G2 and G1, but such prediction is much more useful (see paper source for more details).

Attributes for both Maths.csv (Math course) and Portuguese.csv (Portuguese language course) datasets:

These grades are related with the course subject, Math or Portuguese:

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SCHOOL PROFICIENCY INDEXSummaryThe school proficiency index uses school-level data on the performance of 4th grade students on state exams to describe which neighborhoods have high-performing elementary schools nearby and which are near lower performing elementary schools. The school proficiency index is a function of the percent of 4th grade students proficient in reading (r) and math (m) on state test scores for up to three schools (i=1,2,3) within 1.5 miles of the block-group centroid. S denotes 4th grade school enrollment:Elementary schools are linked with block-groups based on a geographic mapping of attendance area zones from School Attendance Boundary Information System (SABINS), where available, or within-district proximity matches of up to the three-closest schools within 1.5 miles. In cases with multiple school matches, an enrollment-weighted score is calculated following the equation above. Please note that in this version of the data (AFFHT0004), there is no school proficiency data for jurisdictions in Kansas, West Virginia, and Puerto Rico because no data was reported for jurisdictions in these states in the Great Schools 2013-14 dataset. InterpretationValues are percentile ranked and range from 0 to 100. The higher the score, the higher the school system quality is in a neighborhood. Data Source: Great Schools (proficiency data, 2015-16); Common Core of Data (4th grade school addresses and enrollment, 2015-16); Maponics (attendance boundaries, 2016).Related AFFH-T Local Government, PHA and State Tables/Maps: Table 12; Map 7.

To learn more about the School Proficiency Index visit: https://www.hud.gov/program_offices/fair_housing_equal_opp/affh ; https://www.hud.gov/sites/dfiles/FHEO/documents/AFFH-T-Data-Documentation-AFFHT0006-July-2020.pdf, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Date of Coverage: 07/2020

Key Stage 2 (KS2) data for year 6 primary school pupils who met or exceeded the Expected Standard (EXS+) by School Ward for the period 2016 onwards. The data is by school location, rather than by pupil residence. In determining, which ward the data relates to, a Schools list by wards is available. The data source is the National Consortium of Examination Results (NCER) but the figures come from the Department of Education (DfE). A summary of Calderdale school performance can be found on the Council website: School performance tables. School performance for individual schools can be found at Compare school performance. Please note some DFE numbers might have changed please see previous DFE code on Schools list.

Early Years Foundation Stage Profile (EYFSP) data for reception aged primary school pupils who met Good Level of Development (GLD) Standard by School Ward for the 2013 onwards. The data is by school location, rather than by pupil residence. In determining, which ward the data relates to, a Schools list by wards is available. The data source is the National Consortium of Examination Results (NCER).

A summary of Calderdale school performance can be found on the Council website: School performance tables. School performance for individual schools can be found at Compare school performance.

Please note some DFE numbers might have changed please see previous DFE code on Schools list.

Abstract

Abstract Over the years, Kenya has made progress in promoting gender access, equality, and equity in education through policy and legislative reforms that target empowerment for effective participation and contribution to national development. The overall outcome of this is increased representation of women in various institutions. However, evidence indicates that women continue to face systemic barriers and challenges that inhibit fair access, equality, and equity in education. Some of these challenges emanate from shortcomings in the education system; such as the curriculum, teacher training, and ineffective pedagogical approaches that consequently exacerbate the systemic barriers and challenges faced by women and girls. There is a dearth of empirical evidence on gender mainstreaming practices being implemented in classrooms in Kenya as part of efforts to promote gender access, equality, and equity in education. Therefore to address the research gap, this exploratory study seeks to examine three issues: 1) how gender mainstreaming practices are implemented in the teacher training programs; 2) how gender mainstreaming is practiced in primary and secondary classrooms in Kenya (pedagogy, instruction, and interactions), and 3) to explore how the basic education curriculum implementation promotes gender equity. We will utilize a mixed-methods sequential exploratory design to explore the effect of observed gender mainstreaming practices in classrooms, teacher-training programs, and in the basic education curriculum as well as the relationships between the aspects. Data for the study will consist of both qualitative (focus group discussion, key informant interviews) and quantitative (institutional questionnaire, assessments, classroom observations). The data will be collected at the school level (250), as well as among education managers at both county and national education offices. The data analysis is expected to generate evidence on the impact of gender mainstreaming practices on learners' outcomes in Math, English, and Sciences as well as a deep understanding of the nature of the gender mainstreaming practices. The study will provide implications and recommendations for effective gender mainstreaming policies and practice responses.

Geographic coverage

National coverage covering 10 counties (Busia, Garissa, Mandera, Marsabit, Tana River, Turkana, Samburu, Wajir, Nairobi, and West Pokot)

Analysis unit

The unit of analysis for the institutional questionnaire was the schools The unit of analysis for the student questionnaires was the students The unit of analysis for the classroom observation rubric was the class The unit of analysis for the teacher training college tutor knowledge skills and attitude survey was the tutor The unit of analysis for the teacher trainee knowledge skills and attitude survey was the teacher trainee

Universe

10 counties in Kenya comprised of 9 counties with the highest rates of child poverty and Nairobi county because it has high concentration of informal urban settlements.

Sampling procedure

Sampling Procedures and Participants Primary data was collected from students in pre-primary, primary, and secondary schools (mixed gender day schools) (primary grade 6, and secondary form 2), in-service teachers, headteachers and principals, pre-service teachers, teacher training tutors/lecturers, county/national education curriculum support officers, and quality assurance officers, and officials at the Ministry of Education and the Teacher Service Commission. We targeted 250 schools (125 primary and 125 secondary) spread in 10 counties in Kenya with the highest rates of child poverty - above 60% (KNBS, 2018). The counties include (Busia, Garissa, Mandera, Marsabit, Tana River, Turkana, Samburu, Wajir, Nairobi, and West Pokot). We chose these counties because children, girls in particular girls in these areas, encounter some form of marginalization, due to child poverty levels. Additionally, vulnerable boys and girls have diminished chances of access to inclusive education because they belong to schools that serve poor households in a low-resource context. Hence may require targeted actions in mainstreaming gender issues in education.

Our overall sampling strategy took into consideration school performance in the most recent national examinations - the Kenya Certificate for Primary Education (KCPE) for primary schools and Kenya Certificate for Secondary Education (KCSE) for secondary schools. In particular, we grouped schools into three categories based on their performance - low, medium, and high performing. In each of the 10 counties, primary, and secondary schools were listed according to the league tables (best performing to worst performer). Thereafter, we created quintiles with schools falling in the lower two (40%) quintiles constituting low performing schools; those in the 3rd quintile forming the middle performing schools; while those in the upper two quintiles (top 40%) forming the best performing category. A similar procedure was followed to identify day secondary schools - day secondary schools admit the majority of students and are located in almost all parts of the country/county). After our sample size was identified, they were proportionately distributed in the three groupings taking the number of schools in a county into consideration.

Out of the 250 schools sampled for the study, 125 schools were sampled for classroom observations, that is, 62 primary and 63 secondary schools. At the primary school level, 21 observations in mathematics, 21 in science, and 20 in English were done. An equal distribution of 21 observations for mathematics, English, and science were done for secondary schools. We observed a total of 147 teachers. A further random selection was employed to distribute the science classroom observations at the secondary school level, translating to 7 observations each for physics, chemistry, and biology. An illustration of the classroom observation distribution is provided below. The grade to be observed in a subject was randomly selected, such that we had only one subject observed per school. In the case of secondary school where there are several science subjects, we focused on physics, biology, and chemistry. The subject observeded in a particular school was randomly selected. Once a subject was observeded in a selected school, it was not observeded in a subsequently selected school until all the other subjects in question were observed. It is worth noting that in Kenya, traditionally, girls perform better in English while boys perform better in Math). KNEC assessment data was collected from the school head teacher/principal for each of the observed grades. All head teachers and principals of selected schools responded to an institutional questionnaire. The questionnaire collected information on the school background, facilities, enrollment, schooling charges, staffing, and governance. Twenty (20) students from all selected schools and from the targeted grade (except in PP2) completed a student questionnaire that gathers information on individual student's background, homework engagement, school background, and subject choices

We conducted qualitative interviews that shed light on how the teacher-training curriculum responded to gender mainstreaming policies, gender-inclusive teaching practices inside the classroom, and strategies implemented by the Government and private sector to mainstream and promote gender issues in the curriculum. The KIIs targeted a total of 40 in-service teachers - 4 teachers in each county - categorized by type of school (public, private, day, boarding, primary, secondary, single/mixed gender; 6 pre-service tutors from 4 teacher training colleges (TTCs) and 2 Universities; 10 curriculum support officers and 10 quality assurance officers from each county; 2 officials from the Ministry of Education (Directorate for basic education and gender officer); and 1 official from the Teacher Service Commission (in-charge of teacher training). In addition, we conducted 6 FGDs with pre-service teachers from 4 TTCs. 10 FGDs were conducted with students - one in each county; five in primary schools (3 with girls and 2 with boys), and five in secondary schools (3 with boys and 2 with girls). Each FGD was held with 6 participants. The KII guides and FGD guides were pilot tested and revised accordingly to ensure the reliability and clarity of the tools. The KII and FGD guides were sent to the selected respondents before the interviews for familiarity purposes and adequate preparation for the actual interviews. The KIIs lasted a duration of up to 1 hour whereas the FGDs up to 2 hours.

Sampling deviation

N/A

Mode of data collection

Face-to-face [f2f]

Research instrument

Institutional questionnaire: targeting School heads/administrators in each of the school sampled and collected data on school background information, school facilities, enrolment for the current school year, school charges, staffing, and governance.

Student questionnaires: targeting Grade 6 and Form 2 students in each of the sampled school and collected data on Student background information, social-economic status, homework, and homework support, choice of subjects, school environment, absenteeism, and extra tuition.

Classroom observation rubric: targeting PP2, grade 6 and Form 2 teachers and tutors in teacher training colleges (TTCs) and collected data on Gender and inclusion equitable practices in the classroom: language use, lesson planning, teaching, and learning materials, asking questions, group work, demonstration or practical lessons, feedback to students, classroom set up and

Key Stage 2 (KS2) data for year 6 primary school pupils who met or exceeded the Expected Standard (EXS+) by School Ward for the period 2016 onwards. The data is by school location, rather than by pupil residence. In determining, which ward the data relates to, a Schools list by wards is available. The data source is the National Consortium of Examination Results (NCER) but the figures come from the Department of Education (DfE).

A summary of Calderdale school performance can be found on the Council website: School performance tables. School performance for individual schools can be found at Compare school performance.

Please note some DFE numbers might have changed please see previous DFE code on Schools list.