This map answers the question "What is the most common, or predominant, education level for people in this area?" The map shows predominant educational attainment in each census tract. Darker colors indicate a greater gap between the predominant group and the next largest group.The U.S. Census Bureau asks citizens to indicate how far they went in formal education. The database includes seven different columns, each representing a count of population by that education level. A simple routine in compares the seven columns of information, and finds which one has the highest value, writing that to a string field. Each tract's transparency is set by a transparency field added to the data.Predominance maps can be created in ArcGIS Online by adding two fields, calculating their values, and setting up the renderer based on those two fields. See this blog by Jim Herries for details on how to create a predominance map in ArcGIS Online from any feature layer.See this GitHub repo by Jennifer Bell for a script you can run in ArcMap as a script tool, to calculate predominance for any columns of data you have.

School enrollment data are used to assess the socioeconomic condition of school-age children. Government agencies also require these data for funding allocations and program planning and implementation.

Data on school enrollment and grade or level attending were derived from answers to Question 10 in the 2015 American Community Survey (ACS). People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to “include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree.” Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.

School enrollment is only recorded if the schooling advances a person toward an elementary school certificate, a high school diploma, or a college, university, or professional school (such as law or medicine) degree. Tutoring or correspondence schools are included if credit can be obtained from a public or private school or college. People enrolled in “vocational, technical, or business school” such as post secondary vocational, trade, hospital school, and on job training were not reported as enrolled in school. Field interviewers were instructed to classify individuals who were home schooled as enrolled in private school. The guide sent out with the mail questionnaire includes instructions for how to classify home schoolers.

Enrolled in Public and Private School – Includes people who attended school in the reference period and indicated they were enrolled by marking one of the questionnaire categories for “public school, public college,” or “private school, private college, home school.” The instruction guide defines a public school as “any school or college controlled and supported primarily by a local, county, state, or federal government.” Private schools are defined as schools supported and controlled primarily by religious organizations or other private groups. Home schools are defined as “parental-guided education outside of public or private school for grades 1-12.” Respondents who marked both the “public” and “private” boxes are edited to the first entry, “public.”

Grade in Which Enrolled – From 1999-2007, in the ACS, people reported to be enrolled in “public school, public college” or “private school, private college” were classified by grade or level according to responses to Question 10b, “What grade or level was this person attending?” Seven levels were identified: “nursery school, preschool;” “kindergarten;” elementary “grade 1 to grade 4” or “grade 5 to grade 8;” high school “grade 9 to grade 12;” “college undergraduate years (freshman to senior);” and “graduate or professional school (for example: medical, dental, or law school).”

In 2008, the school enrollment questions had several changes. “Home school” was explicitly included in the “private school, private college” category. For question 10b the categories changed to the following “Nursery school, preschool,” “Kindergarten,” “Grade 1 through grade 12,” “College undergraduate years (freshman to senior),” “Graduate or professional school beyond a bachelor’s degree (for example: MA or PhD program, or medical or law school).” The survey question allowed a write-in for the grades enrolled from 1-12.

Question/Concept History – Since 1999, the ACS enrollment status question (Question 10a) refers to “regular school or college,” while the 1996-1998 ACS did not restrict reporting to “regular” school, and contained an additional category for the “vocational, technical or business school.” The 1996-1998 ACS used the educational attainment question to estimate level of enrollment for those reported to be enrolled in school, and had a single year write-in for the attainment of grades 1 through 11. Grade levels estimated using the attainment question were not consistent with other estimates, so a new question specifically asking grade or level of enrollment was added starting with the 1999 ACS questionnaire.

Limitation of the Data – Beginning in 2006, the population universe in the ACS includes people living in group quarters. Data users may see slight differences in levels of school enrollment in any given geographic area due to the inclusion of this population. The extent of this difference, if any, depends on the type of group quarters present and whether the group quarters population makes up a large proportion of the total population. For example, in areas that are home to several colleges and universities, the percent of individuals 18 to 24 who were enrolled in college or graduate school would increase, as people living in college dormitories are now included in the universe.

The University of Washington - Beyond High School (UW-BHS) project surveyed students in Washington State to examine factors impacting educational attainment and the transition to adulthood among high school seniors. The project began in 1999 in an effort to assess the impact of I-200 (the referendum that ended Affirmative Action) on minority enrollment in higher education in Washington. The research objectives of the project were: (1) to describe and explain differences in the transition from high school to college by race and ethnicity, socioeconomic origins, and other characteristics, (2) to evaluate the impact of the Washington State Achievers Program, and (3) to explore the implications of multiple race and ethnic identities. Following a successful pilot survey in the spring of 2000, the project eventually included baseline and one-year follow-up surveys (conducted in 2002, 2003, 2004, and 2005) of almost 10,000 high school seniors in five cohorts across several Washington school districts. The high school senior surveys included questions that explored students' educational aspirations and future career plans, as well as questions on family background, home life, perceptions of school and home environments, self-esteem, and participation in school related and non-school related activities. To supplement the 2000, 2002, and 2003 student surveys, parents of high school seniors were also queried to determine their expectations and aspirations for their child's education, as well as their own educational backgrounds and fields of employment. Parents were also asked to report any financial measures undertaken to prepare for their child's continued education, and whether the household received any form of financial assistance. In 2010, a ten-year follow-up with the 2000 senior cohort was conducted to assess educational, career, and familial outcomes. The ten year follow-up surveys collected information on educational attainment, early employment experiences, family and partnership, civic engagement, and health status. The baseline, parent, and follow-up surveys also collected detailed demographic information, including age, sex, ethnicity, language, religion, education level, employment, income, marital status, and parental status.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES EDUCATIONAL ATTAINMENT - DP02 Universe - Total households Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Educational attainment data are tabulated for people 18 years old and over. Respondents are classified according to the highest degree or the highest level of school completed. The question included instructions for persons currently enrolled in school to report the level of the previous grade attended or the highest degree received.

Office for National Statistics' national and subnational Census 2021. Highest level of qualificationThis dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales by their highest level of qualification. The estimates are as at Census Day, 21 March 2021. Highest level of qualification definition: The highest level of qualification is derived from the question asking people to indicate all qualifications held, or their nearest equivalent. This may include foreign qualifications where they were matched to the closest UK equivalent. The types of qualification included in each level are:Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential SkillsLevel 2 qualifications: 5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA DiplomaLevel 3 qualifications: 2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced DiplomaLevel 4 qualifications or above: degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)Other qualifications: vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)Quality information: There are quality considerations about higher education qualifications, including those at Level 4+, responses from older people and international migrants, and comparability with 2011 Census data.Comparability with 2011: Broadly comparableThe categories for this variable are the same as the ones in the 2011 Census. However, in Census 2021 the question was revised and split up to group together different qualifications. This means that the way people answered the question in Census 2021 cannot be fully compared with the answers from the 2011 Census. For example, some people who hold an older or non-UK qualification when answering the question in Census 2021 may have chosen a higher qualification level than they did in the 2011 Census, although they hold the same qualifications. This data is issued at (BGC) Generalised (20m) boundary type for:Country - England and WalesRegion - EnglandUTLA - England and WalesLTLA - England and WalesWard - England and WalesMSOA - England and WalesLSOA - England and WalesOA - England and WalesIf you require the data at full resolution boundaries, or if you are interested in the range of statistical data that Esri UK make available in ArcGIS Online please enquire at content@esriuk.com.The data services available from this page are derived from the National Data Service. The NDS delivers thousands of open national statistical indicators for the UK as data-as-a-service. Data are sourced from major providers such as the Office for National Statistics, Public Health England and Police UK and made available for your area at standard geographies such as counties, districts and wards and census output areas. This premium service can be consumed as online web services or on-premise for use throughout the ArcGIS system.Read more about the NDS.

MathE is a mathematical platform developed under the MathE project (mathe.pixel-online.org). The dataset has 9546 answers to questions in the Mathematical topics taught in higher education. The file has eight features, named: Student ID, Student Country, Question ID, Type of answer (correct or incorrect), Question level (basic or advanced), Math Topic, Math Subtopic, and Question Keywords. The question level was associated with the professor who submitted the question. The data was obtained from February 2019 until December 2023.

Individual educational attainment prediction model performance.

This repository includes the questionnaire and dataset collected for the paper "DEI in Computing Higher Education: Survey and Analysis of Brazilian and Finnish University Practices," which was submitted to ESEM 2025.

Paper Abstract:

Background: Efforts have been made in STEM, for example, to encourage women to pursue careers in computing or promote the importance of team diversity in the field. However, implementing Diversity and Inclusion (DEI) in university-level computing education remains underexplored.
Aims: This study compares the current state of DEI in Brazilian and Finnish universities.
Method: We replicated in Brazil an online survey conducted in Finland.
Results: We received 68 responses from Brazilian teachers. We compared the Brazilian and Finnish scenarios for incorporating DEI aspects in the classes.
Conclusions: While the importance of DEI in education is recognized, the implementation of DEI practices varies significantly across institutions and countries. Several challenges hinder this implementation, including a lack of teaching materials, insufficient training, limited institutional support, and concerns about addressing these topics appropriately. Regarding countries' differences, Brazilian professors rate DEI more important but report lower satisfaction than Finns, highlighting cultural and demographic factors affecting DEI practices.

Files Description:

1. Responses.xlxs: This spreadsheet contains eight sheets. The "Original (Portuguese)" sheet includes responses to all questions in Brazilian Portuguese. The other sheets contain translated responses in English, organized by topics: approaches employed by teachers, additional approaches mentioned in open-ended questions, the importance of DEI (Diversity, Equity, and Inclusion), sample demographics, attitudes towards DEI, challenges in implementing DEI approaches, and other comments provided by the respondents.
2. Questionnaire.pdf: This file contains the questionnaire distributed to respondents, written in Brazilian Portuguese. By reviewing the PDF, you can see how we implemented the questionnaire using Google Forms. The English version of the questionnaire is available from the source from which we replicated it.

Replicated Study:

• Reference: Hyrynsalmi SM. Challenges and opportunities: Implementing diversity and inclusion in software engineering university level education in Finland. Journal of Systems and Software. 2024 Oct 16:112239.
• Zenodo package: zenodo.org/records/12791197

This dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in England and Wales by highest level of qualification and by sex. The estimates are as at Census Day, 21 March 2021.

There are quality considerations about higher education qualifications, including those at Level 4+, responses from older people and international migrants, and comparability with 2011 Census data. Read more about this quality notice.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Lower tier local authorities

Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.

Coverage

Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Highest level of qualification

The highest level of qualification is derived from the question asking people to indicate all qualifications held, or their nearest equivalent.

This may include foreign qualifications where they were matched to the closest UK equivalent.

Sex

This is the sex recorded by the person completing the census. The options were “Female” and “Male”.

Since the beginning of the 1960s, Statistics Sweden, in collaboration with various research institutions, has carried out follow-up surveys in the school system. These surveys have taken place within the framework of the IS project (Individual Statistics Project) at the University of Gothenburg and the UGU project (Evaluation through follow-up of students) at the University of Teacher Education in Stockholm, which since 1990 have been merged into a research project called 'Evaluation through Follow-up'. The follow-up surveys are part of the central evaluation of the school and are based on large nationally representative samples from different cohorts of students.

Evaluation through follow-up (UGU) is one of the country's largest research databases in the field of education. UGU is part of the central evaluation of the school and is based on large nationally representative samples from different cohorts of students. The longitudinal database contains information on nationally representative samples of school pupils from ten cohorts, born between 1948 and 2004. The sampling process was based on the student's birthday for the first two and on the school class for the other cohorts.

For each cohort, data of mainly two types are collected. School administrative data is collected annually by Statistics Sweden during the time that pupils are in the general school system (primary and secondary school), for most cohorts starting in compulsory school year 3. This information is provided by the school offices and, among other things, includes characteristics of school, class, special support, study choices and grades. Information obtained has varied somewhat, e.g. due to changes in curricula. A more detailed description of this data collection can be found in reports published by Statistics Sweden and linked to datasets for each cohort.

Survey data from the pupils is collected for the first time in compulsory school year 6 (for most cohorts). Questionnaire in survey in year 6 includes questions related to self-perception and interest in learning, attitudes to school, hobbies, school motivation and future plans. For some cohorts, questionnaire data are also collected in year 3 and year 9 in compulsory school and in upper secondary school.

Furthermore, results from various intelligence tests and standartized knowledge tests are included in the data collection year 6. The intelligence tests have been identical for all cohorts (except cohort born in 1987 from which questionnaire data were first collected in year 9). The intelligence test consists of a verbal, a spatial and an inductive test, each containing 40 tasks and specially designed for the UGU project. The verbal test is a vocabulary test of the opposite type. The spatial test is a so-called ‘sheet metal folding test’ and the inductive test are made up of series of numbers. The reliability of the test, intercorrelations and connection with school grades are reported by Svensson (1971).

For the first three cohorts (1948, 1953 and 1967), the standartized knowledge tests in year 6 consist of the standard tests in Swedish, mathematics and English that up to and including the beginning of the 1980s were offered to all pupils in compulsory school year 6. For the cohort 1972, specially prepared tests in reading and mathematics were used. The test in reading consists of 27 tasks and aimed to identify students with reading difficulties. The mathematics test, which was also offered for the fifth cohort, (1977) includes 19 assignments. After a changed version of the test, caused by the previously used test being judged to be somewhat too simple, has been used for the cohort born in 1982. Results on the mathematics test are not available for the 1987 cohort. The mathematics test was not offered to the students in the cohort in 1992, as the test did not seem to fully correspond with current curriculum intentions in mathematics. For further information, see the description of the dataset for each cohort.

For several of the samples, questionnaires were also collected from the students 'parents and teachers in year 6. The teacher questionnaire contains questions about the teacher, class size and composition, the teacher's assessments of the class' knowledge level, etc., school resources, working methods and parental involvement and questions about the existence of evaluations. The questionnaire for the guardians includes questions about the child's upbringing conditions, ambitions and wishes regarding the child's education, views on the school's objectives and the parents' own educational and professional situation.

The students are followed up even after they have left primary school. Among other things, data collection is done during the time they are in high school. Then school administrative data such as e.g. choice of upper secondary school line / program and grades after completing studies. For some of the cohorts, in addition to school administrative data, questionnaire data were also collected from the students.

New sample design compared to previous cohorts. The selection was carried out in two steps. In the first, municipalities were chosen and in the second, school classes with pupils in year 6. A stratified sample was selected from 29 municipalities, after which the school classes were chosen with the help of the class registers in the municipalities in question. In the small municipalities all classes were included, while a random sample was made from the larger ones. The final sample consisted of approximately 9601 students divided into 437 classes in year 6 spring term 1980, and mainly born in 1967. This was at the end 9114 due to the refusal in various forms.

The information obtained in 1980 for rides was:

1. School administrative data (school form, class type, year and grades). This information was collected by Statistics Sweden for all in the sample. Tasks 2-5 were collected by the Department of Education at the Stockholm University of Education.

2. Information about the parents' profession and education, housing, guardians, values ​​of school and education, etc. This information was collected mainly through a questionnaire to guardians, which was new compared to the two previous cohorts. Information is available for about 70%.

3. Answers to questions that shed light on students' school attitudes, self-assessments and values, leisure activities and study and vocational plans, including motives for choosing alternative courses.

4. Results on three aptitude tests, one verbal, one spatial and one inductive.

The aptitude tests were completely identical, while the questionnaires were partially reworked compared to the two previous cohorts. This information is available to just over 90 percent of the students.

1. Standard test results in reading, writing, mathematics and English, in the cases where they occurred in the municipality in question at the time of the examination. Standard test results are available for fewer individuals (approx. 5,600) mainly due to the fact that grading and the use of standard tests only occurred in approximately half of the municipalities included in the sample.

Abstract (en): This poll, fielded May 30-June 2, 1990, is part of a continuing series of monthly surveys that solicit public opinion on the presidency and on a range of other political and social issues. The focus of this data collection was the educational system in the United States. Respondents were asked to list the most important problems facing the country, and were then asked whether President George H.W. Bush had made any progress in improving education and whether they trusted him to make the right decisions regarding this issue. A series of questions addressed the federal government's spending on education and its involvement in local schools, which country the respondent thought did the best job of educating its children, and what single change would bring about the greatest improvement in the American education system. Respondents rated the public schools in their community and commented on the most important problems the schools were facing, the quality of local teachers, whether teachers were respected and paid well enough, and whether the respondent would be willing to pay more taxes to support local schools. Additional topics addressed the basic responsibilities of elementary and high schools, the best ways to evaluate children's progress in school, and whether proposed changes would help or hurt the education of students. Other questions asked respondents about their own educational experiences, and what career they would choose for their child. Respondents who had children currently attending elementary or high school were asked about the type of school their children attended, the frequency and type of interaction they had with their children's teachers, the amount of time spent helping their child with homework, their familiarity with their children's textbooks, and whether they would be willing to run for local school board. Demographic information includes age, race, sex, education level, household income, and political party affiliation. The data contain a weight variable that should be used for analysis. Adult population of the United States aged 18 and over having a telephone at home. Stratified random digit dialing. Within households, respondents were selected using a method developed by Leslie Kish and modified by Charles Backstrom and Gerald Hursh (see Backstrom and Hursh, SURVEY RESEARCH [Evanston, IL: Northwestern University Press, 1963]). telephone interview (1) These data have not been processed by ICPSR staff and are being released in essentially the same format as they were received. (2) The data available for download are not weighted, and users will need to weight the data prior to analysis. (3) Some of the values in the weight variable contain embedded blanks or are otherwise unusable. Please use caution when using the weight variable. (4) The data and documentation for this study were acquired from the Roper Center for Public Opinion Research.

Baseline characteristics of participants in cohort.

This dataset originates from a research study analyzing university students' perceptions of gender in STEM (Science, Technology, Engineering, and Mathematics) fields across Brazil and Spain. It explores the intersection of gender, race, and academic fields to uncover the cultural, social, and systemic influences on opinions about gender disparities in STEM education and careers.

The dataset includes responses from 1,298 participants in Brazil and comparative data from Spain, collected using a validated questionnaire (QSTEMHE, Questionnaire with university students on STEM studies in Higher Education). The questionnaire assesses gender stereotypes, self-perceptions, interest, attitudes, and expectations regarding STEM fields. The Brazilian data was adapted for linguistic and cultural relevance and incorporates additional variables like race, which was not included in the Spanish analysis.

Empirical Dimensions:

Gender Stereotypes (GS)

Perceptions and Self-Perceptions (PSP)

Interest in STEM (INT)

Attitudes (AC)

Expectations about Sciences (EXP)

Methodology: The data was collected through an online questionnaire distributed across higher education institutions in Brazil, ensuring representation of diverse academic levels, socioeconomic statuses, and racial backgrounds. The analysis includes descriptive and inferential statistics, such as Mann-Whitney U tests, to explore differences by gender, field of study, and race.

This dataset provides Census 2021 estimates that classify usual residents aged 16 years and over in households in England and Wales by highest level of qualification and by household composition. The estimates are as at Census Day, 21 March 2021.

There are quality considerations about higher education qualifications, including those at Level 4+, responses from older people and international migrants, and comparability with 2011 Census data. Read more about this quality notice.

Data about household relationships might not always look consistent with legal partnership status. This is because of complexity of living arrangements and the way people interpreted these questions. Take care when using these two variables together. Read more about this quality notice.

Area type

Census 2021 statistics are published for a number of different geographies. These can be large, for example the whole of England, or small, for example an output area (OA), the lowest level of geography for which statistics are produced.

For higher levels of geography, more detailed statistics can be produced. When a lower level of geography is used, such as output areas (which have a minimum of 100 persons), the statistics produced have less detail. This is to protect the confidentiality of people and ensure that individuals or their characteristics cannot be identified.

Lower tier local authorities

Lower tier local authorities provide a range of local services. There are 309 lower tier local authorities in England made up of 181 non-metropolitan districts, 59 unitary authorities, 36 metropolitan districts and 33 London boroughs (including City of London). In Wales there are 22 local authorities made up of 22 unitary authorities.

Coverage

Census 2021 statistics are published for the whole of England and Wales. However, you can choose to filter areas by:

• country - for example, Wales
• region - for example, London
• local authority - for example, Cornwall
• health area – for example, Clinical Commissioning Group
• statistical area - for example, MSOA or LSOA

Highest level of qualification

The highest level of qualification is derived from the question asking people to indicate all qualifications held, or their nearest equivalent.

This may include foreign qualifications where they were matched to the closest UK equivalent.

Household composition

Households according to the relationships between members.

One-family households are classified by:

• the number of dependent children
• family type (married, civil partnership or cohabiting couple family, or lone parent family)

Other households are classified by:

• the number of people
• the number of dependent children
• whether the household consists only of students or only of people aged 66 and over

Predictive performance of CVD hospitalization models using different educational attainment methods.

Research Questiona:

In this study we aim to answer the following research questions: - RQ1. Do university students show an improvement in generic skills after interacting with serious games? - RQ2. Do serious games make learning about the key components of assessment easier? - RQ3. Do serious games promote the development of students' competence in assessment? - RQ4. Are serious games useful and do they serve to transfer learning about the components of the assessment process, the skills and competencies required into other academic and professional contexts?

These data were collected by two different questionnaires: QSG-EVA-SG Questionnaire A Day with Eva and QSG-EVONG-SG Questionnaire EVONG-Assessment in Action.

The questionnaires are structured into categorical questions (university, year of study, degree course, subject area and gender), Likert-type questions with six levels of response (1 = minimum; 6 = maximum) organized in dimensions.

Abstract

The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

Geographic coverage

National

Analysis unit

Schools, teachers, students, public officials

Kind of data

Sample survey data [ssd]

Sampling procedure

The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level. We also wish to detect differences by urban/rural location.

For our school survey, we will employ a two-stage random sample design, where in the first stage a sample of typically around 200 schools, based on local conditions, is drawn, chosen in advance by the Bank staff. In the second stage, a sample of teachers and students will be drawn to answer questions from our survey modules, chosen in the field. A total of 10 teachers will be sampled for absenteeism. Five teachers will be interviewed and given a content knowledge exam. Three 1st grade students will be assessed at random, and a classroom of 4th grade students will be assessed at random. Stratification will be based on the school’s urban/rural classification and based on region. When stratifying by region, we will work with our partners within the country to make sure we include all relevant geographical divisions.

For our Survey of Public Officials, we will sample a total of 200 public officials. Roughly 60 officials are typically surveyed at the federal level, while 140 officials will be surveyed at the regional/district level. For selection of officials at the regional and district level, we will employ a cluster sampling strategy, where roughly 10 regional offices (or whatever the secondary administrative unit is called) are chosen at random from among the regions in which schools were sampled. Then among these 10 regions, we also typically select around 10 districts (tertiary administrative level units) from among the districts in which schools werer sampled. The result of this sampling approach is that for 10 clusters we will have links from the school to the district office to the regional office to the central office. Within the regions/districts, five or six officials will be sampled, including the head of organization, HR director, two division directors from finance and planning, and one or two randomly selected professional employees among the finance, planning, and one other service related department chosen at random. At the federal level, we will interview the HR director, finance director, planning director, and three randomly selected service focused departments. In addition to the directors of each of these departments, a sample of 9 professional employees will be chosen in each department at random on the day of the interview.

Sampling deviation

For our school survey, we select only schools that are supervised by the Minsitry or Education or are Private schools. No schools supervised by the Ministry of Defense, Ministry of Endowments, Ministry of Higher Education , or Ministry of Social Development are included. This left us with a sampling frame containing 3,330 schools, with 1297 private schools and 2003 schools managed by the Minsitry of Education. The schools must also have at least 3 grade 1 students, 3 grade 4 students, and 3 teachers. We oversampled Southern schools to reach a total of 50 Southern schools for regional comparisons. Additionally, we oversampled Evening schools, for a total of 40 evening schools.

A total of 250 schools were surveyed.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The dashboard project collects new data in each country using three new instruments: a School Survey, a Policy Survey, and a Survey of Public Officials. Data collection involves school visits, classroom observations, legislative reviews, teacher and student assessments, and interviews with teachers, principals, and public officials. In addition, the project draws on some existing data sources to complement the new data it collects. A major objective of the GEPD project was to develop focused, cost-effective instruments and data-collection procedures, so that the dashboard can be inexpensive enough to be applied (and re-applied) in many countries. The team achieved this by streamlining and simplifying existing instruments, and thereby reducing the time required for data collection and training of enumerators.

More information pertaining to each of the three instruments can be found below:

• School Survey: The School Survey collects data primarily on practices (the quality of service delivery in schools), but also on some de facto policy indicators. It consists of streamlined versions of existing instruments—including Service Delivery Surveys on teachers and inputs/infrastructure, Teach on pedagogical practice, Global Early Child Development Database (GECDD) on school readiness of young children, and the Development World Management Survey (DWMS) on management quality—together with new questions to fill gaps in those instruments. Though the number of modules is similar to the full version of the Service Delivery Indicators (SDI) Survey, the number of items and the complexity of the questions within each module is significantly lower. The School Survey includes 8 short modules: School Information, Teacher Presence, Teacher Survey, Classroom Observation, Teacher Assessment, Early Learner Direct Assessment, School Management Survey, and 4th-grade Student Assessment. For a team of two enumerators, it takes on average about 4 hours to collect all information in a given school. For more information, refer to the Frequently Asked Questions.

• Policy Survey: The Policy Survey collects information to feed into the policy de jure indicators. This survey is filled out by key informants in each country, drawing on their knowledge to identify key elements of the policy framework (as in the SABER approach to policy-data collection that the Bank has used over the past 7 years). The survey includes questions on policies related to teachers, school management, inputs and infrastructure, and learners. In total, there are 52 questions in the survey as of June 2020. The key informant is expected to spend 2-3 days gathering and analyzing the relavant information to answer the survey questions.

• Survey of Public Officials: The Survey of Public Officials collects information about the capacity and orientation of the bureaucracy, as well as political factors affecting education outcomes. This survey is a streamlined and education-focused version of the civil-servant surveys that the Bureaucracy Lab (a joint initiative of the Governance Global Practice and the Development Impact Evaluation unit of the World Bank) has implemented in several countries. The survey includes questions about technical and leadership skills, work environment, stakeholder engagement, impartial decision-making, and attitudes and behaviors. The survey takes 30-45 minutes per public official and is used to interview Ministry of Education officials working at the central, regional, and district levels in each country.

Sampling error estimates

The aim of the Global Education Policy Dashboard school survey is to produce nationally representative estimates, which will be able to detect changes in the indicators over time at a minimum power of 80% and with a 0.05 significance level.

This method returns Census 2021 estimates that classify usual residents aged 16 years and over by their highest level of qualification.

The highest level of qualification is derived from the question asking people to indicate all qualifications held, or their nearest equivalent. This may include foreign qualifications where they were matched to the closest UK equivalent.

The types of qualification included in each level are:

• Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential Skills.
• Level 2 qualifications: 5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA Diploma.
• Level 3 qualifications: 2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced Diploma.
• Level 4 qualifications or above: degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy).
• Other qualifications: vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown).

Highest level of qualification is split into 8 categories including total.

The estimates are as at Census Day, 21 March 2021.

The highest level of qualification is derived from the question asking people to indicate all qualifications held, or their nearest equivalent. This may include foreign qualifications where they were matched to the closest UK equivalent.The types of qualification included in each level are:Level 1 and entry level qualifications: 1 to 4 GCSEs grade A* to C , Any GCSEs at other grades, O levels or CSEs (any grades), 1 AS level, NVQ level 1, Foundation GNVQ, Basic or Essential SkillsLevel 2 qualifications: 5 or more GCSEs (A* to C or 9 to 4), O levels (passes), CSEs (grade 1), School Certification, 1 A level, 2 to 3 AS levels, VCEs, Intermediate or Higher Diploma, Welsh Baccalaureate Intermediate Diploma, NVQ level 2, Intermediate GNVQ, City and Guilds Craft, BTEC First or General Diploma, RSA DiplomaLevel 3 qualifications: 2 or more A levels or VCEs, 4 or more AS levels, Higher School Certificate, Progression or Advanced Diploma, Welsh Baccalaureate Advance Diploma, NVQ level 3; Advanced GNVQ, City and Guilds Advanced Craft, ONC, OND, BTEC National, RSA Advanced DiplomaLevel 4 qualifications or above: degree (BA, BSc), higher degree (MA, PhD, PGCE), NVQ level 4 to 5, HNC, HND, RSA Higher Diploma, BTEC Higher level, professional qualifications (for example, teaching, nursing, accountancy)Other qualifications: vocational or work-related qualifications, other qualifications achieved in England or Wales, qualifications achieved outside England or Wales (equivalent not stated or unknown)Quality information: There are quality considerations about higher education qualifications, including those at Level 4+, responses from older people and international migrants, and comparability with 2011 Census data.CoverageThis dataset is focused on the data for Birmingham at Ward level. Also available at LSOA, MSOA and Constituency levels.About the 2021 CensusThe Census takes place every 10 years and gives us a picture of all the people and households in England and Wales.Protecting personal dataThe ONS sometimes need to make changes to data if it is possible to identify individuals. This is known as statistical disclosure control. In Census 2021, they:

Swapped records (targeted record swapping), for example, if a household was likely to be identified in datasets because it has unusual characteristics, they swapped the record with a similar one from a nearby small area. Very unusual households could be swapped with one in a nearby local authority. Added small changes to some counts (cell key perturbation), for example, we might change a count of four to a three or a five. This might make small differences between tables depending on how the data are broken down when they applied perturbation.For more geographies, aggregations or topics see the link in the Reference below. Or, to create a custom dataset with multiple variables use the ONS Create a custom dataset tool.Population valueThe value column represents All usual residents aged 16 years and over.The percentage shown is the value as a percentage of All usual residents aged 16 years and over within the given geography.

This table contains figures on the participation in lifelong learning of the population aged 15 to 75 (excluding the institutional population) in the Netherlands. The data can be broken down by different background characteristics such as gender, age, highest educational attainment and labour market position (active, unemployed and the non-occupational population). At the same time, people undergo formal training as non-formal training. These persons are included in this table among those undergoing formal training. As a result, the number of persons undergoing non-formal training in this table is somewhat lower than the actual number of persons undergoing non-formal training.

Due to changes in the research design and questionnaire of the EBB, a revision of the figures for reporting year 2021 was carried out in the first quarter of 2022. The figures for 2021 are not necessarily comparable to the previous reporting periods. In this table, we see a break with previous years in the figures on participation in non-formal education. In this, the EBB questionnaire has become personal, whereas respondents were asked about the situation for the whole family or household. Now everyone answers only for themselves and not for others anymore. For non-formal courses, it appears that if they are reported by others, they are less well measured.

Data available from 2003 to 2021

Status of the figures: The figures in this table are final.

Amendments as of 15 November 2022: None, this table has been discontinued.

Changes as of 17 May 2022: Due to changes in the research design and questionnaire of the EBB, a revision of the figures for reporting year 2021 has been carried out. The figures for 2021 are not necessarily comparable to the previous reporting periods.

Changes as of 14 November 2019: The figures on the level of education in this table have been corrected for the period 2012-2018. This is a correction in the distraction of the level of education of persons who indicate that they have obtained a diploma abroad with a level similar to the higher education level. This group was wrongly awarded the level associated with an MBO2 training.

When are new figures coming? No longer applicable. This table is followed up by the Lifelong Learning Table; population (15 to 75 years). See paragraph 3.