100+ datasets found
  1. i

    Global Education Policy Dashboard 2019 - Jordan

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Feb 19, 2025
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    Sergio Venegas Marin (2025). Global Education Policy Dashboard 2019 - Jordan [Dataset]. https://catalog.ihsn.org/catalog/12721
    Explore at:
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Marta Carnelli
    Reema Nayar
    Sergio Venegas Marin
    Brian Stacy
    Halsey Rogers
    Time period covered
    2019 - 2020
    Area covered
    Jordan
    Description

    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.

  2. i

    Global Education Policy Dashboard 2020-2021 - Ethiopia

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Feb 19, 2025
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    Sergio Venegas Marin (2025). Global Education Policy Dashboard 2020-2021 - Ethiopia [Dataset]. https://catalog.ihsn.org/catalog/12722
    Explore at:
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Sergio Venegas Marin
    Brian Stacy
    Marta Carnelli
    Reema Nayar
    Halsey Rogers
    Time period covered
    2020 - 2021
    Area covered
    Ethiopia
    Description

    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

    Overall, we draw a sample of 300 public schools from each of the regions of Ethiopia. As a comparison to the total number of schools in Ethiopia, this consistutes an approximately 1% sample. Because of the large size of the country, and because there can be very large distances between Woredas within the same region, we chose a cluster sampling approach. In this approach, 100 Woredas were chosen with probability proportional to 4th grade size. Then within each Woreda two rural and one urban school were chosen with probability proportional to 4th grade size.

    Because of conflict in the Tigray region, an initial set of 12 schools that were selected had to be trimmed to 6 schools in Tigray. These six schools were then distributed to other regions in Ethiopia.

    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.

  3. i

    Global Education Policy Dashboard 2020 - Rwanda

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Nov 7, 2024
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    Sergio Venegas Marin (2024). Global Education Policy Dashboard 2020 - Rwanda [Dataset]. https://catalog.ihsn.org/catalog/12616
    Explore at:
    Dataset updated
    Nov 7, 2024
    Dataset provided by
    Sergio Venegas Marin
    Brian Stacy
    Marta Carnelli
    Reema Nayar
    Halsey Rogers
    Time period covered
    2020
    Area covered
    Rwanda
    Description

    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.

  4. f

    Data from: The Right to Education of Students with Disability: the...

    • scielo.figshare.com
    xls
    Updated May 31, 2023
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    Flávia Pedrosa de CAMARGO; Cynthia PAES DE CARVALHO (2023). The Right to Education of Students with Disability: the Management of Inclusive Education Policy in Municipal Schools According to the Implementing Agents [Dataset]. http://doi.org/10.6084/m9.figshare.11267054.v1
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    SciELO journals
    Authors
    Flávia Pedrosa de CAMARGO; Cynthia PAES DE CARVALHO
    License

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

    Description

    ABSTRACT: This work sought to investigate the implementation of a public policy for inclusive education in the Municipal Education Network of Corumbá/Mato Grosso do Sul, Brazil, through the actions and perceptions of the implementing agents, both within the Secretariat of Education and the school. We sought to learn how education policies aimed at students with disabilities are implemented and the conditions of assistance to these students in the Municipal Network. As theoretical framework, we used the studies on Middle-Level and Street-Level Bureaucracy to understand the perceptions and interactions among agents. Disability Studies provided us with important keys for interpreting phenomena through the sociological perspective of disability, especially the concept of Ableism. Initially, we conducted a survey on enrollment and schools from the School Census. Then, a survey was applied to the management teams and teachers of all urban schools of the Municipal Network, from which three schools were chosen for qualitative research. The results showed that the implementing agents, despite their efforts to carry out the work, found difficulties that interfere directly with their performance.

  5. d

    Grade Expectations How Marks and Education Policies Shape Students'...

    • catalog.data.gov
    • cloud.csiss.gmu.edu
    Updated Mar 30, 2021
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    U.S. Department of State (2021). Grade Expectations How Marks and Education Policies Shape Students' Ambitions [Dataset]. https://catalog.data.gov/dataset/grade-expectations-how-marks-and-education-policies-shape-students-ambitions
    Explore at:
    Dataset updated
    Mar 30, 2021
    Dataset provided by
    U.S. Department of State
    Description

    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.

  6. i

    Global Education Policy Dashboard 2022 - Sierra Leone

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Nov 1, 2024
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    Adrien Ciret (2024). Global Education Policy Dashboard 2022 - Sierra Leone [Dataset]. https://datacatalog.ihsn.org/catalog/12615
    Explore at:
    Dataset updated
    Nov 1, 2024
    Dataset provided by
    Marie Helene Cloutier
    Sergio Venegas Marin
    Brian Stacy
    Adrien Ciret
    Halsey Rogers
    Time period covered
    2022
    Area covered
    Sierra Leone
    Description

    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
  7. Pittsburgh Public Schools Enrollment by Individualized Education Plan (IEP)

    • data.wprdc.org
    csv
    Updated May 21, 2023
    + more versions
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    Pittsburgh Public Schools (2023). Pittsburgh Public Schools Enrollment by Individualized Education Plan (IEP) [Dataset]. https://data.wprdc.org/dataset/pittsburgh-public-schools-individualized-education-plan-iep
    Explore at:
    csv(550), csv(1907), csv(822)Available download formats
    Dataset updated
    May 21, 2023
    Dataset provided by
    Pittsburgh School Districthttps://www.pghschools.org/
    License

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

    Area covered
    Pittsburgh School District
    Description

    This dataset captures students attending a Pittsburgh Public School that are classified as either gifted or having some other type of Individualized Education Plan (IEP).

    According to the Pennsylvania Department of Education, an IEP is ​"the written plan for the education of a student who has a disability or is gifted. The IEP is based on the individual student's needs and describes the special help the student will receive in school. "

    The data categories students as having either a gifted IEP, a non-gifted IEP, or no IEP. This data includes only students enrolled in a Pittsburgh Public School. Students enrolled in a charter, private, or parochial school are excluded from this dataset.

    When analyzing this data, it's important to note that IEP evaluations may not be conducted until students reach the second or third grades. Please refer to the table showing IEP's by grade to see how data varies by grade level of the student.

    Neighborhoods were sometimes combined with other adjacent neighborhoods to enable reporting and overcome the District's restriction on reporting totals for any group with fewer than 11 cases. Neighborhood data is reported for K-12 students.

    Data was extracted from the Pittsburgh Public Schools data system in January, 2021. It captures the school where the student was enrolled on October 1st. The neighborhood school the student feeds into based on their address as of the beginning of the 2020-21 school year.

  8. P

    Language Education Policy

    • pacificdata.org
    pdf
    Updated May 30, 2021
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    ['MInistry of Education'] (2021). Language Education Policy [Dataset]. https://pacificdata.org/data/dataset/activity/language-education-policy
    Explore at:
    pdf(1145974)Available download formats
    Dataset updated
    May 30, 2021
    Dataset provided by
    ['MInistry of Education']
    Description

    The policy intends to change that so that English and Kajin Aelōñ Kein continue as teaching languages in a bilingual arrangement.

  9. d

    Ministry of Education annual policy direction

    • data.gov.tw
    csv
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    Department of Planning, Ministry of Education annual policy direction [Dataset]. https://data.gov.tw/en/datasets/42582
    Explore at:
    csvAvailable download formats
    Dataset authored and provided by
    Department of Planning
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    Further studies...................................

  10. State School Health Policy Database

    • search.datacite.org
    • data.niaid.nih.gov
    Updated 2009
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    :Unav (2009). State School Health Policy Database [Dataset]. http://doi.org/10.7910/dvn/2cceak
    Explore at:
    Dataset updated
    2009
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Harvard Dataverse
    Authors
    :Unav
    Description

    Users can view brief descriptions of laws and policies pertaining to the health of students Topics include: wellness policy, health education curriculum, school meal programs, physical activity, emergency response, bullying, and facility safety, among others. Background The State School Health Policy Database was developed by the National Association of State Boards of Education and is supported by the Division of Adolescent and School Health of the Centers (DASH) of the Centers for Disease Control and Prevention (CDC) and the Robert Wood Johnson Foundation. This database is useful for school policymakers interested in viewing strategies and policies across states and researchers and policy evaluators seeking to track changes in polici es across the United States. Topics include: wellness policies, health education curriculum; school meal programs, school food environment, physical activity, drug-free schools, bullying, emergency response, tobacco use, air quality, pesticide use, and facility safety. User Functionality Users can view brief descriptions of laws and policies pertaining to the health of students. When possible, hyperlinks to full written policies are included. Data Notes The data base is updated regularly with new and revised laws and policies from across the United States.

  11. d

    Replication Data for: Group Power and Policy Change in Education

    • dataone.org
    • search.datacite.org
    Updated Nov 22, 2023
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    Finger, Leslie (2023). Replication Data for: Group Power and Policy Change in Education [Dataset]. http://doi.org/10.7910/DVN/WQ90WX
    Explore at:
    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Finger, Leslie
    Description

    Interest group scholars have struggled to document whether and how interest groups impact policy outcomes. At the same time, large, powerful vested interests like teachers’ unions have been accused of getting in the way of policy change, despite a lack of consistent evidence. This dissertation uses the case of education reform to disentangle the role of different types of interest groups in U.S. state policymaking. Through four essays, this dissertation shows that interest group power comes in multiple forms, that interest groups benefit where they have legislative allies, and that interest competition impacts policy. Bucking the conventional wisdom that, as the strongest interest group in education, teachers’ unions’ preferences dictate education policy outcomes, I show that teachers’ unions most strongly impact those policies that affect them organizationally. For other policies, however, other groups matter more. I show that education reform groups use information and assistance, while philanthropic foundations use funding to state bureaucracies to further policies that teachers’ unions oppose.

  12. Κ

    Data from: Placement programme of the Department of Social and Educational...

    • datacatalogue.sodanet.gr
    pdf, tsv
    Updated Nov 14, 2024
    + more versions
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    Κατάλογος Δεδομένων SoDaNet (2024). Placement programme of the Department of Social and Educational Policy, University of the Peloponnese [Dataset]. http://doi.org/10.17903/FK2/3D25AT
    Explore at:
    pdf(239189), tsv(17704)Available download formats
    Dataset updated
    Nov 14, 2024
    Dataset provided by
    Κατάλογος Δεδομένων SoDaNet
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    Sep 1, 2010 - Jun 30, 2019
    Area covered
    Peloponnese Region, Greece
    Dataset funded by
    Operational Programme "Education and Lifelong Learning", NSRF 2007-2013 and 2014-2020
    Description

    The Placement Programme (PP) is conducted in the Department of Social and Educational Policy (SEPD) since the academic year 2010/11. PP has been included in the Department's curriculum as a compulsory academic activity lasting three months. By the establishment of the PP, the Department defines the basic terms of its operation (definition of organizational committees at Institutional and/or Departmental level, conditions of participation of the students, criteria for selection of the organization, criteria for matching the company and the student). The PP is assessed both by the student and the employer. In this data project, students' assessment is documented.

  13. d

    Ministry of Education Government Data Open Action Plan

    • data.gov.tw
    json
    Updated Jun 27, 2025
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    Department of Technological and Vocational Education (2025). Ministry of Education Government Data Open Action Plan [Dataset]. https://data.gov.tw/en/datasets/27959
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Department of Technological and Vocational Education
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    Provide the Ministry of Education's government information open action plan.

  14. Prospects of Free Senior High School Education Policy in Ghana Surveys.xlsx

    • figshare.com
    xlsx
    Updated Mar 30, 2024
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    Kwame Norvixoxo (2024). Prospects of Free Senior High School Education Policy in Ghana Surveys.xlsx [Dataset]. http://doi.org/10.6084/m9.figshare.24449446.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Mar 30, 2024
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Kwame Norvixoxo
    License

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

    Area covered
    Ghana
    Description

    The data is from a research that reviews the prospects of Ghana's free High School Education policy that was implemented 7 years ago. Data was collected from students, parents and school management in all the regions in Ghana.

  15. Strategic Plan FY13-14 - Department of Higher Education

    • data.wu.ac.at
    • data.colorado.gov
    csv, json, xml
    Updated Dec 17, 2014
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    Colorado Department of Higher Education (2014). Strategic Plan FY13-14 - Department of Higher Education [Dataset]. https://data.wu.ac.at/schema/data_colorado_gov/anozeC1qdHAy
    Explore at:
    json, csv, xmlAvailable download formats
    Dataset updated
    Dec 17, 2014
    Dataset provided by
    Colorado Department of Higher Educationhttps://highered.colorado.gov/
    Description

    Higher education must fulfill its essential role in creating the conditions for a healthy state economy, a productive society and a high quality of life for the people of the state. While serving these greater societal needs, the department and the state’s institutions understand that their main purpose is the rigorous instruction of students. The department, working together with the state’s institutions of postsecondary education, seeks a future for Colorado in which its institutions are accountable for continued improvement in the quality, efficiency and results of postsecondary education and are adequately funded to do so.

  16. Data from: Carnegie Commission National Survey of Higher Education: Faculty...

    • icpsr.umich.edu
    ascii
    Updated Feb 16, 1992
    + more versions
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    Ladd, Everett; Lipset, S.M.; Trow, Martin (1992). Carnegie Commission National Survey of Higher Education: Faculty Study Subsample, 1969 [Dataset]. http://doi.org/10.3886/ICPSR07078.v1
    Explore at:
    asciiAvailable download formats
    Dataset updated
    Feb 16, 1992
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Ladd, Everett; Lipset, S.M.; Trow, Martin
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/7078/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/7078/terms

    Time period covered
    1969
    Description

    This study contains data obtained from one-third of a national sample of college and university faculty surveyed under the sponsorship of the Carnegie Commission on Higher Education (see CARNEGIE COMMISSION NATIONAL SURVEY OF HIGHER EDUCATION: FACULTY STUDY, 1969 [ICPSR 7501]). The original data were collected by the Survey Research Center, University of California at Berkeley, while the subsample was provided by the Social Science Data Center at the University of Connecticut. The subsample for the present study was randomly drawn and the 20,008 selected respondents were weighted to 148,372. The variables provide information on the faculty's social and educational backgrounds and professional activities, their views on a wide range of social and political issues, and opinions on educational policy. Demographic data cover age, sex, race, marital status, number of children, religion, income, and parents' levels of education and occupations. In addition to the original survey data, this study includes a number of derived measures in the form of indexes and scales.

  17. California Public Schools 2021-22

    • catalog.data.gov
    • data.ca.gov
    • +2more
    Updated Jul 24, 2025
    + more versions
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    California Department of Education (2025). California Public Schools 2021-22 [Dataset]. https://catalog.data.gov/dataset/california-public-schools-2021-22
    Explore at:
    Dataset updated
    Jul 24, 2025
    Dataset provided by
    California Department of Educationhttps://www.cde.ca.gov/
    Area covered
    California
    Description

    This layer serves as the authoritative geographic data source for California's K-12 public school locations during the 2021-22 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 2021 to coincide with the official 2021-22 student enrollment counts collected on Fall Census Day in 2021(first Wednesday in October). This layer also excludes nonpublic nonsectarian schools and district office schools.The CDE's California School Directoryprovides 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 & Statisticsweb 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.

  18. Policy Statement and Guidelines for School Grants

    • pacificdata.org
    pdf
    Updated Jul 10, 2020
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    ['MEHRD'] (2020). Policy Statement and Guidelines for School Grants [Dataset]. https://pacificdata.org/data/dataset/groups/policy-statement-and-guidelines-for-school-grants
    Explore at:
    pdf(734889)Available download formats
    Dataset updated
    Jul 10, 2020
    Dataset provided by
    Ministry of Education and Human Resources Development
    Description

    The Policy Statement and Guidelines for Grants to Schools is the document that shall be the governing instrument for all grants to registered schools in the Solomon Islands.

  19. P

    Teacher Education and Development Policy Statement

    • pacificdata.org
    pdf
    Updated Jun 1, 2021
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    ['Ministry of Education'] (2021). Teacher Education and Development Policy Statement [Dataset]. https://pacificdata.org/data/dataset/groups/teacher-education-and-development-policy-statement
    Explore at:
    pdf(118980)Available download formats
    Dataset updated
    Jun 1, 2021
    Dataset provided by
    ['Ministry of Education']
    Description

    The purpose of this statement is to guide the general education policy development of the Ministry of Education and Human Resources Development with respect to teacher education and development.

  20. f

    Data from: Interferences in the class: teachers’ dynamic and perceptions

    • scielo.figshare.com
    jpeg
    Updated Jun 1, 2023
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    Mariana Martins Lemes (2023). Interferences in the class: teachers’ dynamic and perceptions [Dataset]. http://doi.org/10.6084/m9.figshare.14304995.v1
    Explore at:
    jpegAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELO journals
    Authors
    Mariana Martins Lemes
    License

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

    Description

    Abstract Instances of school institutions directly intervene on the public schools (state and municipal) in the city of São Paulo. There is a “dynamic of interferences”: a set of frequent and direct interventions in the class, normally connected to the enactment of educational policies. This accumulation of projects in the schools lead to constant interruptions in teachers’ work. We have researched its consequences on teachers and school education, based on the analysis of official texts and teachers’ statements. We have found that, though such policies are supported by a discourse of quality in education, according to the teachers the dynamic of interferences hinders teachers’ work and, possibly, school education.

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Sergio Venegas Marin (2025). Global Education Policy Dashboard 2019 - Jordan [Dataset]. https://catalog.ihsn.org/catalog/12721

Global Education Policy Dashboard 2019 - Jordan

Explore at:
Dataset updated
Feb 19, 2025
Dataset provided by
Marta Carnelli
Reema Nayar
Sergio Venegas Marin
Brian Stacy
Halsey Rogers
Time period covered
2019 - 2020
Area covered
Jordan
Description

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.

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