The National Household Education Survey, 2007 Parent and Family Involvement in Education (PFI-NHES:2007), is a study that is part of the National Household Education Survey (NHES) program. PFI-NHES:2007 (https://nces.ed.gov/nhes/) is a cross-sectional survey that collects data directly from households on educational issues. This study was conducted using address based sample, self-administered questionnaires of households. Households in 2007 were sampled. The study's response rate was 53.2 percent. Key statistics produced from PFI-NHES:2007 are parent involvement in education.

Abstract (en): The National Household Education Survey (NHES) reports on the condition of education in the United States by collecting data at the household level rather than using a traditional, school-based data collection system. The surveys attempt to address many current issues in education, such as preprimary education, school safety and discipline, adult education, and activities related to citizenship. This survey included three topical survey components. The Early Childhood Program Participation (ECPP) Survey (Part 1) gathered information on the nonparental care arrangements and educational programs of preschool children, such as care by relatives, care by persons to whom they were not related, and participation in day care centers and preschool programs including Head Start. The Before- and After-School Programs and Activities (ASPA) Survey (Part 2) addressed relative and nonrelative care for school-age children during the out-of-school hours, including home schooling as well as participation in before- and/or after-school programs, activities, and self-care. The Adult Education and Lifelong Learning (AELL) Survey (Part 3) collected data such as type of program, employer support, and credential sought for participation in the following types of adult educational activities: English as a second language, adult basic education, credential programs, apprenticeships, work-related courses, and personal interest courses. Some information on work-related informal learning activities was gathered as well. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. National sample of household members in the United States. National sample of households. 2006-01-18 File UG3198.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-01-18 File QU3198.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. The codebooks, user guide, and data collection instrument are provided by the ICPSR as Portable Document Format (PDF) files. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using PDF reader software, such as the Adobe Acrobat Reader. Information on how to obtain a copy of the Acrobat Reader is provided on the ICPSR Web site.

The National Household Education Surveys Program (NHES) provides descriptive data on the educational activities of the U.S. population and offers researchers, educators, and policymakers a variety of statistics on the condition of education in the United States.The NHES surveys cover learning at all ages, from early childhood to school age through adulthood. The most recent data collection in 2012 consisted of two surveys: Parent and Family Involvement in Education and Early Childhood Program Participation.

description: The National Household Education Survey, 2007 School Readiness (SR-NHES:2007), is a study that is part of the National Household Education Survey (NHES) program. SR-NHES:2007 (https://nces.ed.gov/nhes/) is a cross-sectional survey that collects data directly from households on educational issues. This study was conducted using address based sample, self-administered questionnaires of households. Households in 2007 were sampled. The study s response rate was 53.2 percent. Key statistics produced from SR-NHES:2007 are children s readiness for school.; abstract: The National Household Education Survey, 2007 School Readiness (SR-NHES:2007), is a study that is part of the National Household Education Survey (NHES) program. SR-NHES:2007 (https://nces.ed.gov/nhes/) is a cross-sectional survey that collects data directly from households on educational issues. This study was conducted using address based sample, self-administered questionnaires of households. Households in 2007 were sampled. The study s response rate was 53.2 percent. Key statistics produced from SR-NHES:2007 are children s readiness for school.

The National Household Education Survey Program, 2012 Early Childhood Program Participation Survey (ECPP-NHES:2012), is a study that is part of the National Household Education Survey (NHES) program. ECPP-NHES:2012 (https://nces.ed.gov/nhes/) is a cross-sectional survey that collects data directly from households on educational issues. This study was conducted using address based sample, self-administered questionnaires of households. Households in 2012 were sampled. Key statistics produced from ECPP-NHES:2012 are early childhood care and education.

The National Household Education Survey, 2005 After-School Programs and Activities (ASPA-NHES:2005), is a study that is part of the National Household Education Survey (NHES) program. ASPA-NHES:2005 (https://nces.ed.gov/nhes/) is a cross-sectional survey that collects data directly from households on educational issues. This study was conducted using address based sample, self-administered questionnaires of households. Households in 2005 were sampled. The study response rate was 67.5 percent. Key statistics produced from ASPA-NHES:2005 are participation in after-school programs and activities.

Abstract

UNHCR India implemented a telephone survey to measure the satisfaction with educational services provided by UNHCR and NGO partners. Most reported financial issues as reasons for their children not attending UNHCR partner led schools and lack of devices for not being able to make use of the online program. The survey also covers a few questions on the impact of COVID-19 on school attendance, and the education quality of public schools. The household survey spans a sample of more than 1,500 households and 2,200 children.

Geographic coverage

National coverage

Analysis unit

Households

Universe

Refugees in India

Kind of data

Sample survey data [ssd]

Sampling procedure

Not Applicable

Mode of data collection

Computer Assisted Telephone Interview [cati]

The National Household Education Survey, 2005 Adult Education (AE-NHES:2005), is a study that is part of the National Household Education Survey (NHES) program. AE-NHES:2005 (https://nces.ed.gov/nhes/) is a cross-sectional survey that collects data directly from households on educational issues. This study was conducted using address based sample, self-administered questionnaires of households. Households in 2005 were sampled. The study�s response rate was 67.5 percent. Key statistics produced from AE-NHES:2005 are participation in adult and continuing education and lifelong learning.

The National Household Education Survey, 2003 Adult Education for Work-Related Seasons (AEWR-NHES:2003), is a study that is part of the National Household Education Survey (NHES) program. AEWR-NHES:2003 (https://nces.ed.gov/nhes/) is a cross-sectional survey that collects data directly from households on educational issues. This study was conducted using an address based sample of self-administered questionnaires of households. Households in 2003 were sampled. The study response rate was 64.7 percent. Key statistics produced from AEWR-NHES:2003 are participation in adult and continuing education.

The Fast Response Survey System (FRSS) was established in 1975 by the National Center for Education Statistics (NCES), United States Department of Education. FRSS is designed to collect issue-oriented data within a relatively short time frame. FRSS collects data from state education agencies, local education agencies, public and private elementary and secondary schools, public school teachers, and public libraries. To ensure minimal burden on respondents, the surveys are generally limited to three pages of questions, with a response burden of about 30 minutes per respondent. Sample sizes are relatively small (usually about 1,000 to 1,500 respondents per survey) so that data collection can be completed quickly. Data are weighted to produce national estimates of the sampled education sector. The sample size is large enough to permit limited breakouts by classification variables. However, as the number of categories within the classification variables increases, the sample size within categories decreases, which results in larger sampling errors for the breakouts by classification variables. The Arts Education Surveys of Elementary School Teachers provide national estimates on arts education and arts instructors in public elementary schools during the 2009-10 school year. This data collection contains three surveys that provide information about music specialists, visual arts specialists, and self-contained classroom teachers. These three surveys are part of a set of seven surveys that collected data on arts education during the 2009-10 school year. In addition to these elementary teacher surveys, the set includes a survey of elementary school principals, a survey of secondary school principals, and two secondary teacher-level surveys. A stratified sample design was used to select teachers and arts specialists (music and visual arts) for the Arts Education Surveys of Elementary School Teachers. Data collection was conducted September 2009 through August 2010. Altogether, 1,148 eligible music specialists, 918 eligible visual arts specialists, and 734 eligible self-contained classroom teachers completed the surveys by web, mail, fax, or telephone. The elementary teacher surveys collected data on the availability of curriculum-based arts education activities outside of regular school hours, teaching load of music and visual arts specialists in elementary schools, teacher participation in various professional development activities, the ways in which self-contained classroom teachers teach arts education as part of their instructional program, and teachers' use of formal methods of assessment of students' achievement in the arts. Furthermore, teachers were also asked to provide administrative information such as school level, school enrollment size, school community type, and percent of students eligible for free or reduced-price lunch.

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized allowing comparison between and within countries over time.

The Education SDIs include teacher effort, teacher knowledge and ability, and the availability of key inputs (for example, textbooks, basic teaching equipment, and infrastructure such as blackboards and toilets). The indicators provide a snapshot of the learning environment and the key resources necessary for students to learn.

Kenya's Service Delivery Indicators Education Survey was implemented in May-July 2012 by the Economic Policy Research Center and Kimetrica, in close coordination with the World Bank SDI team. The data were collected from a stratified random sample of 239 public and 67 private schools to provide a representative snapshot of the learning environment in both public and private schools. The survey assessed the knowledge of 1,679 primary school teachers, surveyed 2,960 teachers for an absenteeism study, and observed 306 grade 4 lessons. In addition, learning outcomes were measured for almost 3,000 grade 4 students.

Geographic coverage

National

Analysis unit

Schools, teachers, students.

Universe

All primary schools

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). In the case of education, SDI surveys also aim to produce accurate information on grade four pupils’ performance through a student assessment. The multistage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

Detailed information about the specific sampling process conducted for the 2012 Kenya Education SDI is available in the SDI Country Report (“SDI-Report-Kenya”) included as part of the documentation that accompanies these datasets.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Education Survey Questionnaire consists of six modules:

Module 1: School Information - Administered to the head of the school to collect information on school type, facilities, school governance, pupil numbers, and school hours. It includes direct observations of school infrastructure by enumerators.

Module 2a: Teacher Absence and Information - Administered to the headteacher and individual teachers to obtain a list of all school teachers, to measure teacher absence, and to collect information on teacher characteristics.

Module 2b: Teacher Absence and Information - Unannounced visit to the school to assess the absence rate.

Module 3: School Finances - Administered to the headteacher to collect information on school finances (this data is unharmonized)

Module 4: Classroom Observation - An observation module to assess teaching activities and classroom conditions.

Module 5: Pupil Assessment - A test of pupils to have a measure of pupil learning outcomes in mathematics and language in grade four. The test is carried out orally and one-on-one with each student by the enumerator.

Module 6: Teacher Assessment - A test of teachers covering mathematics and language subject knowledge and teaching skills.

Cleaning operations

Data entry was done using CSPro; quality control was performed in Stata.

Sampling error estimates

At the national level, an anticipated standard error of 1.6 percentage points for absenteeism, and 4.4 percentage points for pupil literacy were calculated. At the county level, an anticipated standard error of 3.1 percent for absenteeism and 9.0 percent for literacy were estimated.

The Annual Arts Education survey collects information on student participation in and access to arts education at NYCDOE schools. Please note the following arts-related data are now collected from other sources: The number of certified art teachers and non-certified teachers teaching the arts is collected form the HR and BEDS survey The arts instructional hours provided to elementary students are collected from the Student Transcript and Academic Recording System (STARS) The middle and high school participation in the arts data and the NYSED requirement data are collected form STARS and the HS arts sequence data are also collected form STARS

This study provides data obtained from one-fourth of a randomly drawn national sample of graduate students surveyed under the sponsorship of the Carnegie Commission on Higher Education (see CARNEGIE COMMISSION NATIONAL SURVEY OF HIGHER EDUCATION: GRADUATE STUDY, 1969 [ICPSR 7502]). The original data were collected at the Survey Research Center, University of California, Berkeley, while the subsample was provided by the Social Science Data Center at the University of Connecticut. Questions elicited information regarding respondents' social and educational backgrounds, their degree and career plans, and their opinions on their institutions and departments, educational policy in general, and a wide range of social and political issues. Demographic variables cover age, sex, race, religion, marital status, family income, citizenship, and parents' levels of education and occupations.

Open Science in (Higher) Education – data of the February 2017 survey This data set contains: Full raw (anonymised) data set (completed responses) of Open Science in (Higher) Education February 2017 survey. Data are in xlsx and sav format. Survey questionnaires with variables and settings (German original and English translation) in pdf. The English questionnaire was not used in the February 2017 survey, but only serves as translation. Readme file (txt) Survey structure The survey includes 24 questions and its structure can be separated in five major themes: material used in courses (5), OER awareness, usage and development (6), collaborative tools used in courses (2), assessment and participation options (5), demographics (4). The last two questions include an open text questions about general issues on the topics and singular open education experiences, and a request on forwarding the respondent’s e-mail address for further questionings. The online survey was created with Limesurvey[1]. Several questions include filters, i.e. these questions were only shown if a participants did choose a specific answer beforehand ([n/a] in Excel file, [.] In SPSS). Demographic questions Demographic questions asked about the current position, the discipline, birth year and gender. The classification of research disciplines was adapted to general disciplines at German higher education institutions. As we wanted to have a broad classification, we summarised several disciplines and came up with the following list, including the option “other” for respondents who do not feel confident with the proposed classification: Natural Sciences Arts and Humanities or Social Sciences Economics Law Medicine Computer Sciences, Engineering, Technics Other The current job position classification was also chosen according to common positions in Germany, including positions with a teaching responsibility at higher education institutions. Here, we also included the option “other” for respondents who do not feel confident with the proposed classification: Professor Special education teacher Academic/scientific assistant or research fellow (research and teaching) Academic staff (teaching) Student assistant Other We chose to have a free text (numerical) for asking about a respondent’s year of birth because we did not want to pre-classify respondents’ age intervals. It leaves us options to have different analysis on answers and possible correlations to the respondents’ age. Asking about the country was left out as the survey was designed for academics in Germany. Remark on OER question Data from earlier surveys revealed that academics suffer confusion about the proper definition of OER[2]. Some seem to understand OER as free resources, or only refer to open source software (Allen & Seaman, 2016, p. 11). Allen and Seaman (2016) decided to give a broad explanation of OER, avoiding details to not tempt the participant to claim “aware”. Thus, there is a danger of having a bias when giving an explanation. We decided not to give an explanation, but keep this question simple. We assume that either someone knows about OER or not. If they had not heard of the term before, they do not probably use OER (at least not consciously) or create them. Data collection The target group of the survey was academics at German institutions of higher education, mainly universities and universities of applied sciences. To reach them we sent the survey to diverse institutional-intern and extern mailing lists and via personal contacts. Included lists were discipline-based lists, lists deriving from higher education and higher education didactic communities as well as lists from open science and OER communities. Additionally, personal e-mails were sent to presidents and contact persons from those communities, and Twitter was used to spread the survey. The survey was online from Feb 6th to March 3rd 2017, e-mails were mainly sent at the beginning and around mid-term. Data clearance We got 360 responses, whereof Limesurvey counted 208 completes and 152 incompletes. Two responses were marked as incomplete, but after checking them turned out to be complete, and we added them to the complete responses dataset. Thus, this data set includes 210 complete responses. From those 150 incomplete responses, 58 respondents did not answer 1st question, 40 respondents discontinued after 1st question. Data shows a constant decline in response answers, we did not detect any striking survey question with a high dropout rate. We deleted incomplete responses and they are not in this data set. Due to data privacy reasons, we deleted seven variables automatically assigned by Limesurvey: submitdate, lastpage, startlanguage, startdate, datestamp, ipaddr, refurl. We also deleted answers to question No 24 (email address). References Allen, E., & Seaman, J. (2016). Opening the Textbook: Educational Resources in U.S. Higher Education, 2015-16. First results o...

Every year, all parents, all teachers, and students take the NYC School Survey. The survey ranks among the largest surveys of any kind ever conducted nationally. Survey results provide insight into a school's learning environment and contribute a measure of diversification that goes beyond test scores on the Progress Report. Survey questions assess the community's opinions on academic expectations, communication, engagement, and safety and respect. School leaders can use survey results to better understand their own school's strengths and target areas for improvement.

This dataset contains data from the National Center for Education Statistics' Academic Library Survey, which was gathered every two years from 1996 - 2014, and annually in IPEDS starting in 2014 (this dataset has continued to only merge data every two years, following the original schedule). This data was merged, transformed, and used for research by Starr Hoffman and Samantha Godbey.This data was merged using R; R scripts for this merge can be made available upon request. Some variables changed names or definitions during this time; a view of these variables over time is provided in the related Figshare Project. Carnegie Classification changed several times during this period; all Carnegie classifications were crosswalked to the 2000 classification version; that information is also provided in the related Figshare Project. This data was used for research published in several articles, conference papers, and posters starting in 2018 (some of this research used an older version of the dataset which was deposited in the University of Nevada, Las Vegas's repository).SourcesAll data sources were downloaded from the National Center for Education Statistics website https://nces.ed.gov/. Individual datasets and years accessed are listed below.[dataset] U.S. Department of Education, National Center for Education Statistics, Academic Libraries component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Academic Libraries Survey (ALS) Public Use Data File, Library Statistics Program, (2012, 2010, 2008, 2006, 2004, 2002, 2000, 1998, 1996), https://nces.ed.gov/surveys/libraries/aca_data.asp[dataset] U.S. Department of Education, National Center for Education Statistics, Institutional Characteristics component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Fall Enrollment component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014, 2012, 2010, 2008, 2006, 2004, 2002, 2000, 1998, 1996), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Human Resources component, Integrated Postsecondary Education Data System (IPEDS), (2020, 2018, 2016, 2014, 2012, 2010, 2008, 2006), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Employees Assigned by Position component, Integrated Postsecondary Education Data System (IPEDS), (2004, 2002), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7[dataset] U.S. Department of Education, National Center for Education Statistics, Fall Staff component, Integrated Postsecondary Education Data System (IPEDS), (1999, 1997, 1995), https://nces.ed.gov/ipeds/datacenter/login.aspx?gotoReportId=7

The consolidated (CN) survey form was used for the first time in 1990-1991 to collect information from a subset of the 10,500 postsecondary institutions in the Integrated Postsecondary Education Data System (IPEDS) universe. IPEDS collects information on such topics as institutional characteristics, enrollments, completions, finance, staff, and libraries. All schools in the IPEDS universe were asked to complete an institutional characteristics form. Approximately 3,600 institutions of higher education (i.e., those that are accredited at the college level by an agency recognized by the Secretary, United States Department of Education) plus another 400 nonaccredited schools that grant a bachelor's, master's, doctoral, or first-professional degree were asked to complete the full complement of IPEDS surveys. Of the remaining 6,500 postsecondary schools who were eligible to receive the Consolidated (CN) survey form, 2,998 schools were sent the form, of which 2,472 responded. The following data were requested from institutions using the CN survey form: (1) fall enrollment for 1990, by racial/ethnic category and sex of student, (2) completions for the 1989-1990 academic year, by field of study and award level and by racial/ethnic category and sex of recipient, (3) financial statistics for fiscal year 1990, including revenue/tuition fees, expenditures/scholarship, and other expenditures, and (4) selected data on libraries on total FTE staff, operating expenses, and total circulation transactions. The single CN form was substituted for the four more detailed IPEDS surveys that were sent to the accredited/degree-granting institutions. Data for the CN respondent institutions appear on both the CN file and on the individual IPEDS adapt files for the fall enrollment, completions, finance, and libraries surveys.

This data collection contains information gathered in the Survey of Income and Education (SIE) conducted in April-July 1976 by the Census Bureau for the United States Department of Health, Education, and Welfare (HEW). Although national estimates of the number of children in poverty were available each year from the Census Bureau's Current Population Survey (CPS), those estimates were not statistically reliable on a state-by-state basis. In enacting the Educational Amendments of 1974, Congress mandated that HEW conduct a survey to obtain reliable state-by-state data on the numbers of school-age children in local areas with family incomes below the federal poverty level. This was the statistic that determined the amount of grant a local educational agency was entitled to under Title 1, Elementary and Secondary Education Act of 1965. (Such funds were distributed by HEW's Office of Education.) The SIE was the survey created to fulfill that mandate. Its questions include those used in the Current Population Survey regarding current employment, past work experience, and income. Additional questions covering school enrollment, disability, health insurance, bilingualism, food stamp recipiency, assets, and housing costs enabled the study of the poverty concept and of program effectiveness in reaching target groups. Basic household information also was recorded, including tenure of unit (a determination of whether the occupants of the living quarters owned, rented, or occupied the unit without rent), type of unit, household language, and for each member of the household: age, sex, race, ethnicity, marital history, and education.

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized allowing comparison between and within countries over time.

The Education SDIs include teacher effort, teacher knowledge and ability, and the availability of key inputs (for example, textbooks, basic teaching equipment, and infrastructure such as blackboards and toilets). The indicators provide a snapshot of the learning environment and the key resources necessary for students to learn.

Madagascar Service Delivery Indicators Education Survey was implemented from April 2016 (for enumerator training and pre-testing of the instruments) to May and June 2016 (for fieldwork and data collection) by CAETIC Development, a strong local think-tank and survey firm. The sampling strategy was done by INSTAT the national institute for statistics. Information was collected from 473 primary schools, 2,130 teachers (for skills assessment), 2,475 teachers (for absence rate), and 3,960 pupils across Madagascar. The survey also collected basic information on all the 3,049 teachers or staff that teach in the 473 primary schools visited or are non-teaching directors.

Geographic coverage

National

Analysis unit

Schools, teachers, students.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage sampling method was adopted. First, in each stratum schools were chosen within the selected councils. Once at a selected school, the enumerator selected teachers and pupils depending on the structure of the classrooms.

The schools were chosen using probability proportional to size (PPS), where size was the number of standard two pupils as provided by the 2014 EMIS database. As for the selection of the cluster, the use of PPS implied that each standard four pupil within a stratum had an equal probability for her school to be selected.

Finally, within each school, up to 10 standard four pupils and 10 teachers were selected. Pupils were randomly selected among the grade-four pupil body, whereas for teachers, there were two different procedures for measuring absence rate and assessing knowledge. For absence rate, 10 teachers were randomly selected from the teachers’ roster and the whereabouts of those teachers was ascertained in a return surprise visit. For the knowledge assessment, however, all teachers who were currently teaching in primary four or taught primary three the previous school year were included in the sample. Then a random number of teachers in upper grades were included to top up the sample. These procedures implied that pupils across strata, as well as teachers across strata and within a school (for the knowledge assessment) did not all have the same probability of selection. It was, therefore, warranted to compute weights for reporting the survey results.

The sampling strategy for the SDI in Madagascar was done by INSTAT the national statistics office.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Education Survey Questionnaire consists of six modules:

Module 1: School Information - Administered to the head of the school to collect information about school type, facilities, school governance, pupil numbers, and school hours. Includes direct observations of school infrastructure by enumerators.

Module 2a: Teacher Absence and Information - Administered to headteacher and individual teachers to obtain a list of all school teachers, to measure teacher absence, and to collect information about teacher characteristics.

Module 2b: Teacher Absence and Information - Unannounced visit to the school to assess absence rate.

Module 3: School Finances - Administered to the headteacher to collect information about school finances (this data is unharmonized).

Module 4: Classroom Observation - An observation module to assess teaching activities and classroom conditions.

Module 5: Pupil Assessment - A test of pupils to have a measure of pupil learning outcomes in mathematics and language in grade four.

Module 6: Teacher Assessment - A test of teachers covering mathematics and language subject knowledge and teaching skills.

Cleaning operations

Data quality control was performed in Stata.

Most social surveys collect data on respondents’ educational attainment. Current measurement practice involves a closed question with country-specific response options, which are needed because of the differences between educational systems. However, these are quite difficult to compare across countries. This is a challenge for both migrant and international surveys. Therefore, a measurement tool for educational attainment that was initially developed for German migrant surveys in the CAMCES project (Schneider, Briceno-Rosas, Herzing, et al. 2018; Schneider, Briceno-Rosas, Ortmanns, et al. 2018) was extended in the SERISS-project in work package 8, Task 8.3. In deliverable D8.8, we provide a database of educational qualifications and levels for 100 countries, including the definition of a search tree interface to facilitate the navigation of categories for respondents in computer-assisted surveys. All country-specific categories are linked to 3-digit codes of UNESCO's International Standard Classification of Education 2011 for Educational Attainment (ISCED-A), as well as to the education coding scheme used in the European Social Survey (ESS), "edulvlb". A live search of the database via two different interfaces, a search box (for a limited set of countries) and a search tree (for all countries), is available at the surveycodings website at https://surveycodings.org/articles/codings/levels-of-education. The search box and search tree can be implemented in survey questionnaires and thereby be used for respondents’ self-classification in computer-assisted surveys. The live search feature can also be used for post-coding open answers in already collected data.