Global Education Policy Dashboard 2019
Peru, 2019
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PER_2019_GEPD_v01_M
Global Education Policy Dashboard 2019
GEPD 2019
| Name | Country code |
|---|---|
| Peru | PER |
Sample survey data [ssd]
Schools, teachers, students, public officials
Version
v01, harmonized and anonymized data
2022-11-04
Scope
Populating the dashboard requires, aside from the expert-filled Policy Survey, collecting nationally representative data from two field surveys, as noted above—the school and public official surveys. The sample sizes are as follows:
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Sample of Schools – The sample size for the School Survey normally consists of 200 to 300 schools, a number that allows for the reporting of nationally representative estimates with a high level of precision for all the GEPD indicators. Within this sample of schools, the team interviews 200-300 school principals and 1,000-1,500 teachers, while also conducting assessments of 600-900 1st-graders and (depending on classroom size) 4,000-6,000 4th-graders.
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Sample of Public Officials – The sample size for the Survey of Public Officials is 200. These public officials work in the Ministry of Education at either the central, regional, or district level. In the typical country, the breakdown of the sample is 60 officials at the central level, 70 at the regional level, and 70 at the district level. Other than the director(s) and the person in charge of human resources of each office, who are always interviewed, all public officials are randomly selected.
Coverage
National
Producers and sponsors
| Name | Affiliation |
|---|---|
| Halsey Rogers | World Bank |
| Sergio Venegas Marin | World Bank |
| Reema Nayar | World Bank |
| Marta Carnelli | World Bank |
| Brian Stacy | World Bank |
| Name |
|---|
| Bill and Melinda Gates Foundation |
| UK’s Foreign, Commonwealth, and Development Office (FCDO) |
| Government of Japan |
Sampling
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.
MELQO data was merged with the Peru school frame in order to optimally stratify. We stratified on the basis of urban/rual and department. There are 25 departments in Peru. In 2017, Peru conducted an examination of around 4,500 children between 5 and 8 years old, with a median age of 6. The MELQO exam is quite similar to our ECD examination module. We are able to use data from this 2017 survey to choose the number of schools in each province optimally by calculating means and standard deviations by province and feeding this information into the optimal stratification algorithm. See https://cran.r-project.org/web/packages/SamplingStrata/vignettes/SamplingStrata.html. Provinces with low standard deviations among students in terms of their MELQO development scores are allocated fewer schools compared to an allocation that is simply based on population, and provinces with high standard deviations are allocated more schools.
203 schools were chosen for our survey after optimally stratifying.
GEPD survey estimates must be properly weighted using a sampling weight to estimate the population of interest.
School, teacher, and pupil-level sampling weights are stored in each file file.
Survey 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:
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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.
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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.
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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.
Datasets have been cleaned, anonymized, and harmonized using R and Stata.
Personal identifying information has been removed from the data file including names, addresses, and geolocation coordinates. Additionally, some continuous variables have been recoded to discrete bins to decrease the likelihood of reidentification including the number of students enrolled in the school and salary information for public officials.
Data collection
| Start | End |
|---|---|
| 2019-09-01 | 2019-10-01 |
- Computer Assisted Personal Interview [capi]
World Bank
Data collected using Survey Solutions platform.
Data appraisal
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.
Depositor information
| Name |
|---|
| World Bank |
Data Access
| Name |
|---|
| GEPD team |
| Confidentiality declaration text |
|---|
| Personal identifying information has been removed from the data file including names, addresses, and geolocation coordinates. Additionally, some continuous variables have been recoded to discrete bins to decrease the likelihood of reidentification including the number of students enrolled in the school and salary information for public officials. |
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
Halsey Rogers (World Bank), Sergio Venegas Marin (World Bank), Reema Nayar (World Bank), Marta Carnelli (World Bank), Brian Stacy (World Bank). Peru - Global Education Policy Dashboard 2019 (GEPD 2019). Ref: PER_2019_GEPD_v01_M. Downloaded from [uri] on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Contacts
| Name | |
|---|---|
| GEPD team | educationdashboard@worldbank.org |
Metadata production
DDI_PER_2019_GEPD_v01_M_WB
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the study |
2024-11-13
Metadata version
Version 01 (2024-11-13)