Dataset Overview 📝

The dataset includes the following key indicators, collected for over 200 countries:

• Government Expenditure on Education (% of GDP): Shows the percentage of a country’s GDP allocated to education.
• Literacy Rate (Adult Total): Represents the percentage of the population aged 15 and above who can read and write.
• Primary Completion Rate: The percentage of children who complete their primary education within the official age group.
• Pupil-Teacher Ratio (Primary and Secondary Education): Indicates the average number of students per teacher at the primary and secondary levels.
• School Enrollment Rates (Primary, Secondary, Tertiary): Reflects the percentage of the relevant age group enrolled in schools across different education levels.

Data Source 🌐

World Bank: This dataset is compiled from the World Bank's educational database, providing reliable, updated statistics on educational progress worldwide.

Potential Use Cases 🔍 This dataset is ideal for anyone interested in:

Educational Research: Understanding how education spending and policies impact literacy, enrollment, and overall educational outcomes. Predictive Modeling: Building models to predict educational success factors, such as completion rates and literacy. Global Education Analysis: Analyzing trends in global education systems and how different countries allocate resources to education. Policy Development: Helping governments and organizations make data-driven decisions regarding educational reforms and funding.

Key Questions You Can Explore 🤔

How does government expenditure on education correlate with literacy rates and school enrollment across different regions? What are the trends in pupil-teacher ratios over time, and how do they affect educational outcomes? How do education indicators differ between low-income and high-income countries? Can we predict which countries will achieve universal primary education based on current trends?

Important Notes ⚠️ - Missing Data: Some values may be missing for certain years or countries. Consider using techniques like forward filling or interpolation when working with time series models. - Data Limitations: This dataset provides global averages and may not capture regional disparities within countries.

Read the Department of Education policies.

While enrolment in tertiary education has increased dramatically over the past decades, many university-aged students do not enrol, nor do they expect to earn a university degree. While it is important to promote high expectations for further education, it is equally important to ensure that students’ expectations are well-aligned with their actual abilities. Grade Expectations: How Marks and Education Policies Shape Students' Ambitions reveals some of the factors that influence students’ thinking about further education. The report also suggests what teachers and education policy makers can do to ensure that more students have the skills, as well as the motivation, to succeed in higher education. In 2009, students in 21 PISA-participating countries and economies were asked about their expected educational attainment. An analysis of PISA data finds that students who expect to earn a university degree show significantly better performance in math and reading when compared to students who do not expect to earn such a university degree. However, performance is only one of the factors that determine expectations. On average across most countries and economies, girls and socio-economically advantaged students tend to hold more ambitious expectations than boys and disadvantaged students who perform just as well; and students with higher school marks are more likely to expect to earn a university degree – regardless of what those marks really measure.

• The Ministry of the Interior and Safety publishes the 'Administrative Safety Statistical Yearbook' every year by compiling statistical data from the headquarters of the Ministry of the Interior and Safety and its affiliated organizations in accordance with the 'Ministry of the Interior and Safety Statistics Management Regulations'. - The statistical information by field included in the 'Administrative Safety Statistical Yearbook' is provided as an open API so that it can be used in various fields in both the public and private sectors. - The open API in question is the statistics on 'Local Autonomy Human Resources Development Institute General Education' among 'Others' included in the 'Administrative Safety Statistical Yearbook'. It provides general education statistical information such as the number of courses, sessions, and participants for each long-term education, basic education, specialized policy education, and other education. - In addition, the 'Administrative Safety Statistical Yearbook' can be downloaded in PDF format from the Ministry of the Interior and Safety website at Policy Data > Statistics > Statistical Yearbook/Statistics by Subject.

ABSTRACT: We present the data of a state of knowledge review study over research on the implementation of educational policies and programs published in Brazilian Public Policy journals. Two questions conducted the particular goals of this analysis: whether educational policies and programs have been represented as research objects in studies of implementation in the field of Public Policies and what the main approaches are used by researchers in the area during these investigations. This is a documentary and bibliographic work, comprising a survey of articles published in national journals qualified in the A1 class of Qualis Periodicals (Capes) in the areas of Political Science, Sociology, and Public Administration. The main results indicate that, although still poorly studied, when compared to policies in the area of health and social assistance, the implementation of educational policies and programs has grown among the objects of research in the field of Public Policies. Results also indicate two inclinations among these studies: those that are produced while tied to theoretical and conceptual references in the field of Public Policy and others that do not present interaction with this field, from the theoretical-conceptual point of view.

We introduce a global dataset on education policies and systems across modern history (EPSM), which includes measures on compulsory education, ideological guidance and content of education, governmental intervention and level of education centralization, and teacher training. EPSM covers 157 countries with populations exceeding 1 million people, and the time series extends from 1789 to the present. EPSM opens up for studying several questions concerning political control and the politicized nature of education systems. In addition to describing the measures, we detail how the data were collected and discuss validity and reliability issues. Thereafter, we describe historical trends in various characteristics of the education system. Finally, we illustrate how our data can be used to address key questions about education and politics, replicating and extending recent analyses on the (reciprocal) relationship between education and democratization, the impact of education on political attitudes, and how rural inequality interacts with regime type in influencing education systems.

Over the past three decades a reform movement bent on improving schools and educational outcomes through standards-based accountability systems and market-like competitive pressures has dominated policy debates. Many have examined reform policies’ effects on academic outcomes, but few have explored these policies’ influence on citizens' political orientations. In this study, using data from an original survey, I examine whether and how No Child Left Behind’s (NCLB) accountability-based architecture influences parents’ attitudes toward government and federal involvement in education. I find little evidence that diversity in parents’ lived policy experiences shapes their political orientations. However, the results of a survey experiment suggest that information linking school experience to policy and government action may increase parents’ confidence in their ability to contribute to the political process. Understanding whether and under what conditions parents use public school experiences to inform orientations toward government can inform the design of future reforms.

This policy outlines the requirements for registration as an Education Authority. The policy applies only to the formal stream of education particularly the care facilities, pre-schools, primary and secondary schools: government-funded, government-assisted and private schools.

Abstract The paper analyzes the public policies for higher education in Brazil, with the main objectives of demonstrating legislative evolution and qualitative and quantitative data on access to higher education by blacks and browns. The research is supported by a deductive method, since it is being collected and analyzed first and then analyzed and completed. The methods of procedure will be historical and statistical, interrelating the study of public policies of access to higher education and governmental and non-governmental data. In the empirical analysis, statistical data will be needed, specifying the quali-quantifiable attributes of the data collected for an understanding in line with theoretical construction. It can be perceived, by way of results and final considerations, that there is still a lot of evolution, but that significant changes in the protection of affirmative actions are being implemented.

ABSTRACT: In the context of the growing implementation of accountability measures in basic education identified with policies of regulation by results, this paper analyzes possible reconfigurations of institutional arrangements to account for democratic school government in terms of participation and social control. We conducted this documental research in two Brazilian capitals (Fortaleza [CE] and Palmas [TO]). We surveyed, examined, and systematized target documents, guidelines, measures, and conditions for the democratic government of public basic education, which were in line with result-based regulation policies carried out since the 2000s. Nonetheless, we conclude that the ensemble of changes in each capital may indicate some favoring of the institutional conditions of participation and social control. However, we highlight that the suggested potential of these changes seems to lose power when faced with a political-institutional framework that emphasizes measures identified with policies of regulation by results.

The Curriculum Policies Project (http://scpp.esrc.unimelb.edu.au/) dataset contains a series of 17 transcripts of interviews with 19 state curriculum experts and education policymakers, as part of the ARC Discovery project 'School Knowledge, Working Knowledge and the Knowing Subject: A Review of State Curriculum Policies 1975–2005,' based at the University of Melbourne. Responding to a noted dearth of systematic scholarship about the development of state curriculum policies, the Curriculum Policies project aimed to produce a foundation picture of developments in curriculum policies across the nation over a thirty-year period. The project provided a wide overview of the last generation of state curricula, moving past previous projects that were limited in scope to individual government reports, Commonwealth developments, subject areas or political contexts. The overarching focus of the project was on charting continuities and changes in state curriculum policies, especially regarding changing approaches to knowledge, to students, and to the marking out of academic and vocational agendas. The focus was broadly on secondary schooling, and aimed at building up snapshots of curriculum changes at ten-year intervals. As part of this research project, 34 public servants and education department officials, curriculum academics and scholars were interviewed by Lyn Yates and Cherry Collins over 2007 and 2008. 19 interviewees gave consent for the transcripts of their interviews to appear in this archive. Interviewees were asked to give their personal reflections on the broad changes in curriculum policy over the thirty years from 1975 to 2005, and were invited to shed light on the reasoning and institutional factors that lay behind various policy decisions. The interviews were broad-ranging, informal and largely open-ended; research participants were asked to give a general assessment of their own involvement in curriculum over the thirty years in question, and to highlight any landmarks that were significant to them. They were also invited to address the broader themes of the research study, namely changing attitudes to knowledge, to students and to academic/vocational agendas, and to similarities and differences between different the approaches taken in different states.

Activity standards to assist educators to plan and lead field trips. Activity standards are appendixes to the Off-Site Experiential Learning Policy.

Russia Consolidated Government Expenditure: Year to Date: SC: Education: Youth Policy & Children Health Improvement data was reported at 87.431 RUB bn in Jul 2022. This records an increase from the previous number of 71.819 RUB bn for Jun 2022. Russia Consolidated Government Expenditure: Year to Date: SC: Education: Youth Policy & Children Health Improvement data is updated monthly, averaging 21.642 RUB bn from Jan 2005 (Median) to Jul 2022, with 210 observations. The data reached an all-time high of 106.449 RUB bn in Dec 2021 and a record low of 0.100 RUB bn in Jan 2006. Russia Consolidated Government Expenditure: Year to Date: SC: Education: Youth Policy & Children Health Improvement data remains active status in CEIC and is reported by Federal Treasury. The data is categorized under Russia Premium Database’s Government and Public Finance – Table RU.FA004: Consolidated Government Expenditure: ytd.

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 were 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

In order to visit two schools per day, we clustered at the sector level choosing two schools per cluster. With a sample of 200 schools, this means that we had to allocate 100 PSUs. We combined this clustering with stratification by district and by the urban rural status of the schools. The number of PSUs allocated to each stratum is proportionate to the number of schools in each stratum (i.e. the district X urban/rural status combination).

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.

Cleaning operations

Data quality control was performed in R and Stata Code to calculate all indicators can be found on github here: https://github.com/worldbank/GEPD/blob/master/Countries/Rwanda/2019/School/01_data/03_school_data_cleaner.R

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.

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

The sample for the Global Education Policy Dashboard in SLE was based in part on a previous sample of 260 schools which were part of an early EGRA study. Details from the sampling for that study are quoted below. An additional booster sample of 40 schools was chosen to be representative of smaller schools of less than 30 learners.

EGRA Details:

"The sampling frame began with the 2019 Annual School Census (ASC) list of primary schools as provided by UNICEF/MBSSE where the sample of 260 schools for this study were obtained from an initial list of 7,154 primary schools. Only schools that meet a pre-defined selection criteria were eligible for sampling.

To achieve the recommended sample size of 10 learners per grade, schools that had an enrolment of at least 30 learners in Grade 2 in 2019 were considered. To achieve a high level of confidence in the findings and generate enough data for analysis, the selection criteria only considered schools that: • had an enrolment of at least 30 learners in grade 1; and • had an active grade 4 in 2019 (enrolment not zero)

The sample was taken from a population of 4,597 primary schools that met the eligibility criteria above, representing 64.3% of all the 7,154 primary schools in Sierra Leone (as per the 2019 school census). Schools with higher numbers of learners were purposefully selected to ensure the sample size could be met in each site.

As a result, a sample of 260 schools were drawn using proportional to size allocation with simple random sampling without replacement in each stratum. In the population, there were 16 districts and five school ownership categories (community, government, mission/religious, private and others). A total of 63 strata were made by forming combinations of the 16 districts and school ownership categories. In each stratum, a sample size was computed proportional to the total population and samples were drawn randomly without replacement. Drawing from other EGRA/EGMA studies conducted by Montrose in the past, a backup sample of up to 78 schools (30% of the sample population) with which enumerator teams can replace sample schools was also be drawn.

In the distribution of sampled schools by ownership, majority of the sampled schools are owned by mission/religious group (62.7%, n=163) followed by the government owned schools at 18.5% (n=48). Additionally, in school distribution by district, majority of the sampled schools (54%) were found in Bo, Kambia, Kenema, Kono, Port Loko and Kailahun districts. Refer to annex 9. for details on the population and sample distribution by district."

Because of the restriction that at least 30 learners were available in Grade 2, we chose to add an additional 40 schools to the sample from among smaller schools, with between 3 and 30 grade 2 students. The objective of this supplement was to make the sample more nationally representative, as the restriction reduced the sampling frame for the EGRA/EGMA sample by over 1,500 schools from 7,154 to 4,597.

The 40 schools were chosen in a manner consistent with the original set of EGRA/EGMA schools. The 16 districts formed the strata. In each stratum, the number of schools selected were proportional to the total population of the stratum, and within stratum schools were chosen with probability proportional to size.

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

Russia Regional Government Expenditure: Year to Date: SC: Education: Youth Policy & Children Health Improvement data was reported at 53.816 RUB bn in Jul 2022. This records an increase from the previous number of 40.148 RUB bn for Jun 2022. Russia Regional Government Expenditure: Year to Date: SC: Education: Youth Policy & Children Health Improvement data is updated monthly, averaging 18.250 RUB bn from Jan 2005 (Median) to Jul 2022, with 210 observations. The data reached an all-time high of 79.094 RUB bn in Dec 2021 and a record low of 0.100 RUB bn in Jan 2006. Russia Regional Government Expenditure: Year to Date: SC: Education: Youth Policy & Children Health Improvement data remains active status in CEIC and is reported by Federal Treasury. The data is categorized under Russia Premium Database’s Government and Public Finance – Table RU.FC004: Regional Government Expenditure: ytd.

This layer serves as the authoritative geographic data source for California's K-12 public school locations during the 2022-23 academic year. Schools are mapped as point locations and assigned coordinates based on the physical address of the school facility. The school records are enriched with additional demographic and performance variables from the California Department of Education's data collections. These data elements can be visualized and examined geographically to uncover patterns, solve problems and inform education policy decisions.The schools in this file represent a subset of all records contained in the CDE's public school directory database. This subset is restricted to K-12 public schools that were open in October 2022 to coincide with the official 2022-23 student enrollment counts collected on Fall Census Day in 2022 (first Wednesday in October). This layer also excludes nonpublic nonsectarian schools and district office schools.The CDE's California School Directory provides school location other basic school characteristics found in the layer's attribute table. The school enrollment, demographic and program data are collected by the CDE through the California Longitudinal Achievement System (CALPADS) and can be accessed as publicly downloadable files from the Data & Statistics web page on the CDE website. Schools are assigned X, Y coordinates using a quality controlled geocoding and validation process to optimize positional accuracy. Most schools are mapped to the school structure or centroid of the school property parcel and are individually verified using aerial imagery or assessor's parcels databases. Schools are assigned various geographic area values based on their mapped locations including state and federal legislative district identifiers and National Center for Education Statistics (NCES) locale codes.

The data and programs replicate tables and figures from "Building Social Cohesion in Ethnically Mixed Schools: An Intervention on Perspective Taking", by Alan, Baysan, Gumren, and Kubilay. Please see the readme file for additional details.

This report, building on data from the Indicators of Education Systems (INES) programme, the Teaching and Learning International Survey (TALIS) and the Programme for International Student Assessment (PISA).