To understand the perceptions of families, students, and teachers regarding their school. School leaders use feedback from the survey to reflect and make improvements to schools and programs. Also, results from the survey used to help measure school quality. Each year, all parents, teachers, and students in grades 6-12 take the NYC School Survey. The survey is aligned to the DOE's Framework for Great Schools. It is designed to collect important information about each school's ability to support student success.

Please note: The larger complete data file is downloadable under the Attachments Section

This file, part of a data collection effort carried out annually from 1968-1974 to look at issues of school desegregation, contains selected school district-level racial and ethnic data about students and staff for the academic year 1970-1971. The data were collected using OCR Form OS/CR 101. Each district record for each separate year of the series is identical, containing fields for all district data elements surveyed in every year. Where a particular item was not surveyed for a specific year, its corresponding field is zero (for numeric fields) or blank (for alphanumeric fields). Counts of students in various racial and ethnic groups are provided and then further categorized across additional dimensions, including whether resident or non-resident, emotionally disturbed, physically or learning disabled, or requiring special education. Other categories include school-age children in public and non-public schools or not in school, dropouts, and those expelled or suspended. Racial and ethnic counts of full-time classroom teachers and full-time instructional staff are also supplied. Other variables focus on the number of schools in the district that used ability grouping, whether a district had single-sex schools, whether students of different sexes were required to take different courses, the number of students whose language was not English, whether bilingual instruction was used, the number of schools being newly built or modified to increase capacity, the racial composition of new schools, and whether there was litigation.

Trained Teachers in Preprimary Education: Male: % of Male Teachers data was reported at 100.000 % in 2022. This stayed constant from the previous number of 100.000 % for 2021. Trained Teachers in Preprimary Education: Male: % of Male Teachers data is updated yearly, averaging 100.000 % from Dec 2014 (Median) to 2022, with 9 observations. The data reached an all-time high of 100.000 % in 2022 and a record low of 100.000 % in 2022. Trained Teachers in Preprimary Education: Male: % of Male Teachers data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Education Statistics. Trained teachers in preprimary education are the percentage of preprimary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

United States Trained Teachers in Lower Secondary Education: % of Total Teachers data was reported at 100.000 % in 2022. This stayed constant from the previous number of 100.000 % for 2021. United States Trained Teachers in Lower Secondary Education: % of Total Teachers data is updated yearly, averaging 100.000 % from Dec 2014 (Median) to 2022, with 9 observations. The data reached an all-time high of 100.000 % in 2022 and a record low of 100.000 % in 2022. United States Trained Teachers in Lower Secondary Education: % of Total Teachers data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Education Statistics. Trained teachers in lower secondary education are the percentage of lower secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;Weighted average;

Data on teachers' salaries in US dollars are presented.

This dataset includes expenditure data reported by school districts, charter schools, and virtual schools starting with fiscal year 2009. It also includes student enrollment, demographic, and performance indicators as well as teacher salary and staffing data.

In addition to showing the overall cost per pupil, this dataset provides detail about how much districts spend in major functional areas such as administration, teaching, and maintenance. For more information about the data and how to interpret it, please visit the School Finance Dashboard.

Economically Disadvantaged was used 2015-2021. Low Income was used prior to 2015, and a different version of Low Income has been used since 2022. Please see the DESE Researcher's Guide for more information.

This dataset is one of three containing the same data that is also published in the School Finance Dashboard: District Expenditures by Spending Category District Expenditures by Function Code School Expenditures by Spending Category

List of Indicators by Category

Student Enrollment

• In-District FTE Pupils
• Out-of-District FTE Pupils
• Total FTE Pupils

• Student Headcount
• Low-Income % Headcount
• English Learner % Headcount
• Students with Disabilities % Headcount

• Teacher FTE
• Teachers per 100 FTE Students
• Average Teacher Salary

• Instructional Coach FTE
• Instructional Support FTE
• Special Education Instructional Support FTE
• Paraprofessional FTE

• ELA Grades 3-8 % Meets Exceeds
• Math Grades 3-8 % Meets Exceeds
• ELA Grade 10 % Meets Exceeds
• Math Grade 10 % Meets Exceeds

• Administration
• Instructional Leadership
• Teachers
• Other Teaching Services
• Professional Development
• Instructional Materials, Equipment and Technology
• Guidance, Counseling and Testing
• Pupil Services
• Operations and Maintenance
• Insurance, Retirement Programs and Other
• Total In-District Expenditures
• Total Expenditures

The State Education Contextual Data Resource (S-ECDR) is a historical dataset that compiles state-level indicators of public education systems in the United States from 1919/20 through 1973/74. The dataset includes measures related to public school financing, teacher characteristics, school and classroom contexts, and segregation and desegregation in the U.S. South. Data were drawn from four historical sources: the Biennial Surveys of Education, the Statistics of State School Systems, a 1967 Southern Education Reporting Service report, and U.S. Census Abstracts. The dataset was created to support research on how early-life education contexts influence long-term outcomes in adulthood, particularly for cohorts who attended school during a period of significant expansion in U.S. public education. S-ECDR includes indicators that enable comparisons of state-level education investment, teacher workforce composition, and access to education across time and geographic region. The resource is designed to facilitate linkage to individual-level surveys containing state and year identifiers, enabling analysis of how historical education environments shaped later-life well-being.

The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.

Primary education, teachers in North America was reported at 2044659 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. North America - Primary education, teachers - actual values, historical data, forecasts and projections were sourced from the World Bank on May of 2025.

Abstract (en): This dataset contains records for each public elementary and secondary education agency in the 50 states, the District of Columbia, and United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands) for 1993-1994. Data were reported to the Bureau of the Census for the National Center for Education Statistics by the state education agencies. Each record provides state and federal ID numbers, name, address, and telephone number of the agency, county name and FIPS code, agency type code, student counts, graduates and other completers counts, and other codes for selected characteristics of the agency. Grade span, number of schools operated by the agency, and number of classroom teachers were also aggregated. 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.. All public elementary and secondary education agencies in the 50 states, the District of Columbia, and United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands). 1999-11-02 The SAS data definition statements have been corrected and updated, with one implied decimal point (reported to the nearest tenth) added to 20 variables (TEACH93, PKTCH93, KGTCH93, etc.). The codebook is provided as a Portable Document Format (PDF) file. 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 through the ICPSR Website on the Internet.

Secondary education, teachers in United States was reported at 1737206 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Secondary education, teachers - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

Every year, all parents, all teachers, and students in grades 6 - 12 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. NYC School Survey results contribute 10% - 15% of a school's Progress Report grade (the exact contribution to the Progress Report is dependant on school type). 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. The NYC School Survey helps school leaders understand what key members of the school community say about the learning environment at each school. The information captured by the survey is designed to support a dialogue among all members of the school community about how to make the school a better place to learn.

The Teacher Series of the Statistics of Non-University Teachings aims to show the evolution of its basic variables and indicators. The data provided are the result of a thorough review, carried out in 2006 in order to further homogenise the concepts and coverage for the different courses to which the information relates. This revision may imply slight differences for some variables with respect to the data that appear in the Detailed Results of the corresponding course.

Abstract

This impact evaluation was conducted by IDinsight for STIR Education in Delhi and Uttar Pradesh in India, and was funded by a World Bank Strategic Impact Evaluation Fund grant. The study seeks to evaluate the impact of STIR's purely motivational, pedagogically neutral, teacher-focused model on student learning levels. STIR works with teachers in low-cost and government schools in order to improve student learning by empowering teachers to act as change-makers and to innovate to overcome challenges in the classroom. IDinsight conducted two three-armed randomized control trials. The study looks at outcomes from 180 Affordable Private Schools (APS) in Delhi and 270 government schools in the Raebareli and Varanasi districts of Uttar Pradesh. The study began in early 2015, and lasted two academic years. In addition to measuring STIR's impact in two different contexts, the study simultaneously tests two iterations of STIR's model in these two contexts.

Geographic coverage

One district in Delhi - East Delhi, and two districts in Uttar Pradesh - Raebareli and Varanasi

Analysis unit

For student learning, the basic unit of analysis is students. For classroom practices, the basic unit of analysis is teachers. For teacher motivation, the basic unit of analysis is teachers.

Universe

• 180 Affordable Private Schools in Delhi, 540 teachers amongst these schools and 5,400 students
• 270 Government Schools in Uttar Pradesh, 810 teachers amongst these schools and 8,100 students

Kind of data

Sample survey data [ssd]

Sampling procedure

Baseline Respondent Identification and Sampling Strategy:

Delhi:

Teacher Motivation: STIR initially did a search process of several hundred Affordable Private Schools (APS) in east Delhi. From these schools, STIR passed school names onto IDinsight where the teachers might be interested in working with IDinsight. IDinsight attempted to sample all schools for the Teacher Motivation survey. In total, IDinsight interviewed 1,259 teachers for the Teacher Motivation survey.

Classroom Observation: From these 1,259 teachers, STIR did an additional round of screening to determine which teachers were the most interested and returned a list of 810 teachers to IDinsight. This list formed the basis of the classroom observation. However, due to attrition and refusals at the school level we were unable to meet our target of teachers and ended up surveying only 342 teachers.

Student Testing: For sampling students in the classroom, IDinsight sampled 10 students per classroom in classes (of all teachers covered for the classroom observation) with more than 10 students using the attendance register for the day the enumerator came to the class. In classes with fewer than 10 students, all children were sampled.

Uttar Pradesh:

Teacher Motivation: In Uttar Pradesh, IDinsight obtained a list of all clusters in Raebareli and Varanasi districts that STIR was working in. From this list, IDinsight selected all clusters with more than 16 schools. This was done to ensure that there would be enough schools in the cluster to assign some to the control group while also maintaining enough treatment schools for STIR to form a network. For the Teacher Motivation survey, IDinsight surveyed all teachers in the school, yielding 1,145 teachers.

Classroom Observation: For the classroom observation, IDinsight sampled roughly 2/3 of the teachers who completed the Teacher Motivation questionnaire, to get a final list of roughly 810 teachers. Teachers were added to this list due to teachers dropping out and the final number was 838 teachers.

Student Testing: For sampling students in the classroom, IDinsight sampled 10 students per classroom in classes with more than 10 students using the attendance register for the day the enumerator came to the class. In classes with fewer than 10 students, all children were sampled.

Midline Respondent Identification and Sampling Strategy:

For midline, which took place at the beginning of the second academic year, we followed up with teachers and students surveyed at baseline. Teachers were added only in the case where the number of teachers still teaching in the school from our baseline lists fell below a certain number. In Delhi, teachers were added if less than two teachers from our list in a given school were available and in Uttar Pradesh, new teachers were added only if all teachers from our baseline lists in a given school dropped out.

The sampling strategy had two clear advantages: 1) It helped us target teachers and students that have been exposed to STIR for as long as possible since the timeline for the overall evaluation is relatively short. 2) The evaluations are already quite complex and this helped have a clear interpretation and narrative surrounding the results.

Delhi:

Teacher Motivation: From the list of 1,259 teachers surveyed at teacher motivation baseline, 453 teachers dropped out of schools during the academic year and hence were not available for surveying during midline. A further 65 teachers refused to participate and 84 teachers were not available during the data collection period. Given this, the total number of teachers surveyed at teacher motivation midline was 657. These teachers formed the sample for analyses.

Classroom Observation: For classroom observations, we attempted to collect data for all 811 teachers on the Delhi original list. For those schools where the number of teachers available from our 811 list fell below two, 148 new teachers were added based on a random selection from those teachers employed at that school as of 1 July 2015. A total of 459 teachers were surveyed as part of the classroom observation midline.

Student Testing: For testing of student learning levels, all students surveyed at baseline formed the potential sample at midline. Among the 3,367 students from baseline, 1,956 students were tracked and surveyed at midline. 1,127 students had dropped out from the schools. 40 students were absent throughout the course of the data collection, and were not found in schools during any of the five revisits. The remaining 244 students were in schools where we could not survey.

Uttar Pradesh:

Teacher Motivation: From the 1,145 teachers surveyed at baseline, 288 teachers dropped out of schools during the course of the academic year and were hence not available for data collection. An additional 61 refused to participate in the data collection and 41 were not available through the course of the data collection. The final number of teachers surveyed at midline were 755. This was the sample for analysis.

Classroom Observation: From the list of 838 teachers surveyed at baseline, we successfully observed the classrooms of 734 of these teachers at midline. Another 13 teachers were added in schools where all teachers from our 838 had dropped out. 12 of these 13 were in Raebareli and 1 was in Varanasi. In total, 747 teachers were surveyed. 82 teachers dropped out of the schools in our sample. 13 teachers refused to participate in the data collection and 14 teachers were absent throughout the survey period and were not available on either of our visits.

Student Testing: Of the 7,386 students tested at baseline, a total of 4,560 students were also tested at midline. 615 students were absent all days of visits to the schools. 149 students were in the four schools that refused data collection. 2,062 dropped out of the schools in our sample.

Endline Respondent Identification and Sampling Strategy:

For endline, which took place after the end of the second academic year, we followed up with teachers and students surveyed at midline. In Delhi, one teacher was added per school to the classroom observation sample where possible. Additional teachers were added to the teacher motivation sample by offering the survey to all the teachers in our sample schools. The sampling strategy had two clear advantages:

1) It helped us target teachers and students that have been exposed to STIR for as long as possible since the timeline for the overall evaluation is relatively short. 2) The evaluations are already quite complex and this helped have a clear interpretation and narrative surrounding the results.

Delhi:

Teacher Motivation: From the list of 657 teachers surveyed at teacher motivation midline, 101 teachers dropped out of schools during the academic year and hence were not available for surveying during endline. A further 25 teachers refused to participate and 50 teachers were not available during the data collection period. Given this, the total number of teachers surveyed at teacher motivation midline was 481. These teachers formed the sample for analyses.

Classroom Observation: For classroom observations, we attempted to collect data for all 459 teachers on the Delhi midline list as well as 102 teachers we surveyed at baseline and couldn't at midline but were hopeful of covering in the last survey. A new teacher was added to each school's sample where possible. A total of 376 teachers were surveyed as part of the classroom observation endline.

Student Testing: For testing of student learning levels, all students surveyed at midline formed the potential sample at endline. Among the 1,956 students from baseline, 1,843 students were tracked and surveyed at midline. 49 students had dropped out from the schools. 45 students were absent throughout the course of the data collection, and were not found in schools during any of the five revisits.

Uttar Pradesh:

Teacher Motivation: From the 967 teachers surveyed at midline, 105 teachers were transfered and 17 retired during the course of the academic year and were hence not available for data collection. An additional 36 refused to participate in the data collection and 26 were not available through

Abstract (en): The primary purpose of the State Nonfiscal Survey is to provide basic information on public elementary and secondary school students and staff for each of the 50 states, the District of Columbia, and outlying territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands). The database provides the following information on students and staff: general information (name, address, and telephone number of the state education agency), staffing information (number of FTEs on the instructional staff, guidance counselor staff, library staff, support staff, and administrative staff), and student information (membership counts by grade, counts of high school completers, counts of high school completers by racial/ethnic breakouts, and breakouts for dropouts by grade, sex, race). 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.. All public elementary and secondary education agencies in the 50 states, the District of Columbia, United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands), and Department of Defense schools outside of the United States. 2006-01-18 File DOC2450.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 CB2450.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads. (1) Part 2, Imputed Data, is a different version of the data in Part 1, Reported Data. The National Center for Education Statistics (NCES) imputed and adjusted some reported values in order to create a data file (Part 2) that more accurately reflects student and staff counts and improves comparability between states. Imputations are defined as cases where the missing value is not reported at all, indicating that subtotals for the category are under-reported. An imputation by NCES assigns a value to the missing item, and the subtotals containing this item increase by the amount of the imputation. Imputations and adjustments were performed on the 50 states and Washington, DC, only. Since all states and Washington, DC, reported data in this survey, these imputations and adjustments were implemented to correct for item nonresponse only. This process consisted of several stages and steps, and varied as to the nature of the missing data. No adjustments or imputations were made to high school graduates or other high school completer categories, nor were any adjustments or imputations performed on the race/ethnicity data. (2) The Instruction Manual that is included with this data collection also applies to COMMON CORE OF DATA: PUBLIC EDUCATION AGENCY UNIVERSE, 1995-1996 (ICPSR 2468) and COMMON CORE OF DATA: PUBLIC SCHOOL UNIVERSE, 1995-1996 (ICPSR 2470). (3) The codebook, data collection instrument, and instruction manual are provided as two Portable Document Format (PDF) files. The PDF file format was developed by Adobe Systems Incorporated and can be accessed using the Adobe Acrobat Reader (version 3.0 or later). Information on how to obtain a copy of the Acrobat Reader is provided through the ICPSR Website on the Internet.

Abstract (en): This dataset contains records for each public elementary and secondary school in the 50 states, the District of Columbia, United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands), and Department of Defense schools outside the United States for 1996-1997. Records in this file provide the National Center for Education Statistics and state identification numbers, name and ID number of the agency operating the school, name, address, and phone number of the school, school type (regular, special education, vocational education, alternative), locale code (seven categories from urban to rural), number of students by grade and ungraded, number of students eligible for free lunch, and number of students by five race/ethnic categories. 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.. All public elementary and secondary schools in the 50 states, the District of Columbia, United States territories (American Samoa, Guam, Puerto Rico, the Virgin Islands, and the Marshall Islands), and Department of Defense schools outside the United States during 1996-1997. (1) The data contain high ASCII, accented Spanish characters. (2) Users are encouraged to check the NCES homepage (http://www.ed.gov/NCES/ccd/) for additional information on this collection. (3) The codebook and instruction manual are provided 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 through the ICPSR Website on the Internet.

The Teacher Series of the Statistics of Non-University Teachings aims to show the evolution of its basic variables and indicators. The data provided are the result of a thorough review, carried out in 2006 in order to further homogenise the concepts and coverage for the different courses to which the information relates. This revision may imply slight differences for some variables with respect to the data that appear in the Detailed Results of the corresponding course.

I downloaded this data from the ElSi (Elementary/Secondary Information System) tableGenerator hosted by the Institute of Educational Sciences' National Center for Education Statistics. ELSI tableGenerator

The cleaned, analysis-ready files are "finances_2001_2017.csv" and "pupils_fte_teachers_2001_2019.csv".

I am going to add graduation rate data. This is for an undergrad project on marijuana legalization and high school graduation rates.

Variable Definitions: "Total Expenditures (TE11+E4D+E7A1) per Pupil (MEMBR) [State Finance] This is the Total Expenditures (Digest) divided by the fall membership as reported in the state finance file. The Total Expenditures (Digest) is the subtotal of Direct State Support Expenditures for Private Schools (e4d), Debt Services Expenditures - Interest (e7a1) and Total Expenditures for Education (te11). These data are from the CCD National Public Education Financial Survey."

"Total revenues per student are the total revenues from all sources (tr) divided by the fall membership as reported in the state finance file. These data are from the CCD National Public Education Financial Survey."

"Full-Time Equivalent (FTE) Teachers [State] This is the total number of full-time equivalent teachers in a state as defined by the CCD State Nonfiscal Survey."

"Grades 9-12 Students [State] This is the number of students in a state who are enrolled in ninth grade through twelfth grade. These data are taken from the CCD State Nonfiscal survey."

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This dataset provides information on 5 in Massachusetts, United States as of May, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

This dataset tracks annual total classroom teachers amount from 1991 to 2023 for American Fork Jr High School