In 2021, about 1.5 million students were enrolled in private high schools or similar institutions in the United States. There were significantly more students enrolled in public high schools across the United States, at 15.4 million students.

In California in 2022, 20.5 percent of students enrolled in K-12 public schools were white, 11.9 percent were Asian, and 56.2 percent were Hispanic. In the United States overall, 44.7 percent of K-12 public school students were white, 5.5 percent were Asian, and 28.7 percent were Hispanic.

The number of K-12 students represents the total student enrollment in both public and private kindergarten, elementary and secondary schools. Data and forecasts are sourced from the US Department of Education's National Center for Education Statistics.

In 2022, there were close to 6 million students enrolled in public elementary and secondary schools in California, the most out of any state in the United States. Texas, Florida, New York, and Illinois rounded out the top five states for public school enrollment in that year.

In 2019, there were around 4.1 million students of Hispanic background enrolled in secondary schools in the United States. In the same year, there were about 8.4 million white students enrolled in secondary schools in the U.S.

From 2022 to 2031, the projected percentage change in enrollment in U.S. public schools for grades K (kindergarten) through 12 in Idaho was 10.8 percent, the greatest increase in enrollment expected out of all U.S. states.

This data collection contains information from the first wave of High School and Beyond (HSB), a longitudinal study of American youth conducted by the National Opinion Research Center on behalf of the National Center for Education Statistics (NCES). Data were collected from 58,270 high school students (28,240 seniors and 30,030 sophomores) and 1,015 secondary schools in the spring of 1980. Many items overlap with the NCES's NATIONAL LONGITUDINAL STUDY OF THE CLASS OF 1972 (ICPSR 8085). The HSB study's data are contained in eight files. Part 1 (School Data) contains data from questionnaires completed by high school principals about various school attributes and programs. Part 2 (Student Data) contains data from surveys administered to students. Included are questionnaire responses on family and religious background, perceptions of self and others, personal values, extracurricular activities, type of high school program, and educational expectations and aspirations. Also supplied are scores on a battery of cognitive tests including vocabulary, reading, mathematics, science, writing, civics, spatial orientation, and visualization. To gather the data in Part 3 (Parent Data), a subsample of the seniors and sophomores surveyed in HSB was drawn, and questionnaires were administered to one parent of each of 3,367 sophomores and of 3,197 seniors. The questionnaires contain a number of items in common with the student questionnaires, and there are a number of items in common between the parent-of-sophomore and the parent-of-senior questionnaires. This is a revised file from the one originally released in Autumn 1981, and it includes 22 new analytically constructed variables imputed by NCES from the original survey data gathered from parents. The new data are concerned primarily with the areas of family income, liabilities, and assets. Other data in the file concentrate on financing of post-secondary education, including numerous parent opinions and projections concerning the educational future of the student, anticipated financial aid, student's plans after high school, expected ages for student's marriage and childbearing, estimated costs of post-secondary education, and government financial aid policies. Also supplied are data on family size, value of property and other assets, home financing, family income and debts, and the age, sex, marital, and employment status of parents, plus current income and expenses for the student. Part 4 (Language Data) provides information on each student who reported some non-English language experience, with data on past and current exposure to and use of languages. In Parts 5-6, there are responses from 14,103 teachers about 18,291 senior and sophomore students from 616 schools. Students were evaluated by an average of four different teachers who had the opportunity to express knowledge or opinions of HSB students whom they had taught during the 1979-1980 school year. Part 5 (Teacher Comment Data: Seniors) contains 67,053 records, and Part 6 (Teacher Comment Data: Sophomores) contains 76,560 records. Questions were asked regarding the teacher's opinions of their student's likelihood of attending college, popularity, and physical or emotional handicaps affecting school work. The sophomore file also contains questions on teacher characteristics, e.g., sex, ethnic origin, subjects taught, and time devoted to maintaining order. The data in Part 7 (Twins and Siblings Data) are from students in the HSB sample identified as twins, triplets, or other siblings. Of the 1,348 families included, 524 had twins or triplets only, 810 contained non-twin siblings only, and the remaining 14 contained both types of siblings. Finally, Part 8 (Friends Data) contained the first-, second-, and third-choice friends listed by each of the students in Part 2, along with identifying information allowing links between friendship pairs.

"Enrollment counts are based on the October 31 Audited Register for the 2017-18 to 2019-20 school years. To account for the delay in the start of the school year, enrollment counts are based on the November 13 Audited Register for 2020-21 and the November 12 Audited Register for 2021-22. * Please note that October 31 (and November 12-13) enrollment is not audited for charter schools or Pre-K Early Education Centers (NYCEECs). Charter schools are required to submit enrollment as of BEDS Day, the first Wednesday in October, to the New York State Department of Education." Enrollment counts in the Demographic Snapshot will likely exceed operational enrollment counts due to the fact that long-term absence (LTA) students are excluded for funding purposes. Data on students with disabilities, English Language Learners, students' povery status, and students' Economic Need Value are as of the June 30 for each school year except in 2021-22. Data on SWDs, ELLs, Poverty, and ENI in the 2021-22 school year are as of March 7, 2022. 3-K and Pre-K enrollment totals include students in both full-day and half-day programs. Four-year-old students enrolled in Family Childcare Centers are categorized as 3K students for the purposes of this report. All schools listed are as of the 2021-22 school year. Schools closed before 2021-22 are not included in the school level tab but are included in the data for citywide, borough, and district. Programs and Pre-K NYC Early Education Centers (NYCEECs) are not included on the school-level tab. Due to missing demographic information in rare cases at the time of the enrollment snapshot, demographic categories do not always add up to citywide totals. Students with disabilities are defined as any child receiving an Individualized Education Program (IEP) as of the end of the school year (or March 7 for 2021-22). NYC DOE "Poverty" counts are based on the number of students with families who have qualified for free or reduced price lunch, or are eligible for Human Resources Administration (HRA) benefits. In previous years, the poverty indicator also included students enrolled in a Universal Meal School (USM), where all students automatically qualified, with the exception of middle schools, D75 schools and Pre-K centers. In 2017-18, all students in NYC schools became eligible for free lunch. In order to better reflect free and reduced price lunch status, the poverty indicator does not include student USM status, and retroactively applies this rule to previous years. "The school’s Economic Need Index is the average of its students’ Economic Need Values. The Economic Need Index (ENI) estimates the percentage of students facing economic hardship. The 2014-15 school year is the first year we provide ENI estimates. The metric is calculated as follows: * The student’s Economic Need Value is 1.0 if: o The student is eligible for public assistance from the NYC Human Resources Administration (HRA); o The student lived in temporary housing in the past four years; or o The student is in high school, has a home language other than English, and entered the NYC DOE for the first time within the last four years. * Otherwise, the student’s Economic Need Value is based on the percentage of families (with school-age children) in the student’s census tract whose income is below the poverty level, as estimated by the American Community Survey 5-Year estimate (2020 ACS estimates were used in calculations for 2021-22 ENI). The student’s Economic Need Value equals this percentage divided by 100. Due to differences in the timing of when student demographic, address and census data were pulled, ENI values may vary, slightly, from the ENI values reported in the School Quality Reports. In previous years, student census tract data was based on students’ addresses at the time of ENI calculation. Beginning in 2018-19, census tract data is based on students’ addresses as of the Audited Register date of the g

According to Cognitive Market Research, The Global K 12 International Schools market size is USD 7.8 billion in 2023 and will expand at a compound annual growth rate (CAGR) of 9.00% from 2023 to 2030.

The demand for K-12 International Schools is rising due to the growing international education.
Demand for English language international schools remains higher in the K 12 International Schools market.
The international baccalaureate category held the highest K 12 International Schools market revenue share in 2023.
North American K 12 International Schools will continue to lead, whereas the European K 12 International Schools market will experience the most substantial growth until 2030.

Increase in Government Initiatives to Provide Viable Market Output

The increasing government initiatives propel the growth of the K 12 International Schools market. Policymakers worldwide are increasingly recognizing the importance of quality education and are implementing initiatives to enhance the accessibility and standards of K12 education. Financial support, curriculum development, and infrastructure improvements are common focus areas. These initiatives aim to foster a conducive learning environment, boost student outcomes, and prepare future generations for a rapidly evolving global landscape. As governments actively invest in education the K12 international schools market benefits from a supportive regulatory framework and increased resources, fostering growth and innovation in the sector.

For instance, Saudi Arabia announced the 'Madrasati' e-learning platform in 2020. In 2021, the Online Learning Consortium (OLC) ranked it among the seven top global e-learning platforms.

(Source:www.arabnews.com/node/1918431/saudi-arabia)

Growing Demand for International Education to Propel Market Growth

The growth of international education has significantly impacted the K 12 International Schools market. Parents increasingly recognize the importance of a globally oriented curriculum that fosters cultural awareness and equips students with a competitive edge in the global job market. International schools offer diverse and comprehensive learning experiences, often incorporating internationally recognized curricula such as the International Baccalaureate (IB) or Cambridge Assessment International Education. This demand is further fueled by the rise in expatriate populations, the desire for English language proficiency, and the aspiration for a well-rounded education beyond traditional academic metrics. As a result, the K12 international schools sector is witnessing sustained growth to meet the evolving educational preferences of a globally-minded generation.

For instance, on October 26, 2022, US-headquartered investment house Safanad and international education platform Global School Management propounded an initial investment of $200 million in the Middle East to take over education assets. It significantly boosted their investment as they spread their portfolio of K-12 schools in the region.

(Source:safanad.com/posts_news/safanad-and-global-school-management-plan-investments-of-us200-million-in-mena-education-sector/)

Rising Demand of Online Education Fuels the Market

Market Dynamics of the K 12 International Schools

Strict Admission Criteria to Restrict Market Growth

Strict admission criteria constrain the market's growth. These criteria often require students to meet rigorous academic, language proficiency, and financial prerequisites. While intended to maintain educational standards and a diverse student body, they can exclude potential candidates, reducing overall revenue and expansion prospects. This restraint may limit the school's reach and diversity, potentially affecting its competitiveness and profitability in a highly competitive market.

Impact of COVID–19 on the K 12 International Schools Market

The rapid shift to online learning, lockdowns, and other restrictions impact school revenues and enrollment. Many international schools faced challenges adapting to virtual education and addressing the digital divide. Safety measures led to changes in classroom setups and curricular adjustments. However, the crisis also accelerated technology adoption and innovative teaching methods. Post-pandemic, the market is expected to continue evolving, with a greater emphasis on blended learning and digital tools, while adapting t...

Report on Demographic Data in New York City Public Schools, 2020-21Enrollment counts are based on the November 13 Audited Register for 2020. Categories with total enrollment values of zero were omitted. Pre-K data includes students in 3-K. Data on students with disabilities, English language learners, and student poverty status are as of March 19, 2021. Due to missing demographic information in rare cases and suppression rules, demographic categories do not always add up to total enrollment and/or citywide totals. NYC DOE "Eligible for free or reduced-price lunch” counts are based on the number of students with families who have qualified for free or reduced-price lunch or are eligible for Human Resources Administration (HRA) benefits. English Language Arts and Math state assessment results for students in grade 9 are not available for inclusion in this report, as the spring 2020 exams did not take place. Spring 2021 ELA and Math test results are not included in this report for K-8 students in 2020-21. Due to the COVID-19 pandemic’s complete transformation of New York City’s school system during the 2020-21 school year, and in accordance with New York State guidance, the 2021 ELA and Math assessments were optional for students to take. As a result, 21.6% of students in grades 3-8 took the English assessment in 2021 and 20.5% of students in grades 3-8 took the Math assessment. These participation rates are not representative of New York City students and schools and are not comparable to prior years, so results are not included in this report. Dual Language enrollment includes English Language Learners and non-English Language Learners. Dual Language data are based on data from STARS; as a result, school participation and student enrollment in Dual Language programs may differ from the data in this report. STARS course scheduling and grade management software applications provide a dynamic internal data system for school use; while standard course codes exist, data are not always consistent from school to school. This report does not include enrollment at District 75 & 79 programs. Students enrolled at Young Adult Borough Centers are represented in the 9-12 District data but not the 9-12 School data. “Prior Year” data included in Comparison tabs refers to data from 2019-20. “Year-to-Year Change” data included in Comparison tabs indicates whether the demographics of a school or special program have grown more or less similar to its district or attendance zone (or school, for special programs) since 2019-20. Year-to-year changes must have been at least 1 percentage point to qualify as “More Similar” or “Less Similar”; changes less than 1 percentage point are categorized as “No Change”. The admissions method tab contains information on the admissions methods used for elementary, middle, and high school programs during the Fall 2020 admissions process. Fall 2020 selection criteria are included for all programs with academic screens, including middle and high school programs. Selection criteria data is based on school-reported information. Fall 2020 Diversity in Admissions priorities is included for applicable middle and high school programs. Note that the data on each school’s demographics and performance includes all students of the given subgroup who were enrolled in the school on November 13, 2020. Some of these students may not have been admitted under the admissions method(s) shown, as some students may have enrolled in the school outside the centralized admissions process (via waitlist, over-the-counter, or transfer), and schools may have changed admissions methods over the past few years. Admissions methods are only reported for grades K-12. "3K and Pre-Kindergarten data are reported at the site level. See below for definitions of site types included in this report. Additionally, please note that this report excludes all students at District 75 sites, reflecting slightly lower enrollment than our total of 60,265 students

This Public Schools feature dataset is composed of all Public elementary and secondary education facilities in the United States as defined by the Common Core of Data (CCD, https://nces.ed.gov/ccd/ ), National Center for Education Statistics (NCES, https://nces.ed.gov ), US Department of Education for the 2017-2018 school year. This includes all Kindergarten through 12th grade schools as tracked by the Common Core of Data. Included in this dataset are military schools in US territories and referenced in the city field with an APO or FPO address. DOD schools represented in the NCES data that are outside of the United States or US territories have been omitted. This feature class contains all MEDS/MEDS+ as approved by NGA. 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 release includes the addition of 3065 new records, modifications to the spatial location and/or attribution of 99,287 records, and removal of 2996 records not present in the NCES CCD data.

Public schools have managed to maintain revenue growth despite significant shifts in funding, enrollment and parental preferences. Class sizes are shrinking every year as birth rates drop and the high school retention rate stagnates, straining revenue as smaller schools see lessened funding from governments. Public schools have contended with heightened competition from alternative education options, especially homeschooling and private institutions, as parents seek more personalized educational experiences. States have increasingly adopted school choice systems, allowing parents to use public funds or tax credits to pay for private schooling. The Trump administration has taken steps to promote these programs even more and has proposed establishing a federal voucher system. Despite heightened competition and a rigorous competitive atmosphere, strong per-pupil funding amid strong state and local budgets has buoyed public schools. Public schools' revenue has been climbing at a CAGR of 1.4% to an estimated $1.0 billion over the five years through 2025, including a rise of 0.9% in 2025 alone. Governments fully fund public schools. Support from state and local governments is especially vital, as they provide nearly nine-tenths of public schools' revenue. Despite a slight dip in 2022, strong tax income pushed up government funding for primary and secondary schools by 6.2% in 2023. These resources are enabling public schools to invest in tutoring and counseling to improve their educational outcomes and better compete with alternative primary and secondary schools. Public schools also used funds to help transition to online and augmented education and have avoided taking on further losses as shrinking class sizes leave them without pressure to continue purchasing new laptops or tablets. Still, public schools are not profitable and largely operate at a loss every year. Public schools are set to face a continued drop in enrollment as well as intensifying competition. To sustain revenue and support, schools will focus on retaining students and improving academic outcomes despite potential federal funding changes. The expansion of school choice programs will compel public schools to enhance their quality and offer additional services like after-school programs to sustain enrollment and win parental support as families gain more access to private schools. Still, charter schools will leverage their unique value propositions to remain competitive and buoy enrollment in the public school system. Public schools' revenue is set to stagnate, swelling at a CAGR of just 0.2% to an estimated $1.0 billion through the end of 2030.

This dataset tracks annual american indian student percentage from 1992 to 2023 for Ennis K-12 Schools School District vs. Montana

The 2020-2021 School Learning Modalities dataset provides weekly estimates of school learning modality (including in-person, remote, or hybrid learning) for U.S. K-12 public and independent charter school districts for the 2020-2021 school year, from August 2020 – June 2021. These data were modeled using multiple sources of input data (see below) to infer the most likely learning modality of a school district for a given week. These data should be considered district-level estimates and may not always reflect true learning modality, particularly for districts in which data are unavailable. If a district reports multiple modality types within the same week, the modality offered for the majority of those days is reflected in the weekly estimate. All school district metadata are sourced from the National Center for Educational Statistics (NCES) for 2020-2021. School learning modality types are defined as follows: In-Person: All schools within the district offer face-to-face instruction 5 days per week to all students at all available grade levels. Remote: Schools within the district do not offer face-to-face instruction; all learning is conducted online/remotely to all students at all available grade levels. Hybrid: Schools within the district offer a combination of in-person and remote learning; face-to-face instruction is offered less than 5 days per week, or only to a subset of students. Data Information School learning modality data provided here are model estimates using combined input data and are not guaranteed to be 100% accurate. This learning modality dataset was generated by combining data from four different sources: Burbio [1], MCH Strategic Data [2], the AEI/Return to Learn Tracker [3], and state dashboards [4-20]. These data were combined using a Hidden Markov model which infers the sequence of learning modalities (In-Person, Hybrid, or Remote) for each district that is most likely to produce the modalities reported by these sources. This model was trained using data from the 2020-2021 school year. Metadata describing the location, number of schools and number of students in each district comes from NCES [21]. You can read more about the model in the CDC MMWR: COVID-19–Related School Closures and Learning Modality Changes — United States, August 1–September 17, 2021. The metrics listed for each school learning modality reflect totals by district and the number of enrolled students per district for which data are available. School districts represented here exclude private schools and include the following NCES subtypes: Public school district that is NOT a component of a supervisory union Public school district that is a component of a supervisory union Independent charter district “BI” in the state column refers to school districts funded by the Bureau of Indian Education. Technical Notes Data from September 1, 2020 to June 25, 2021 correspond to the 2020-2021 school year. During this timeframe, all four sources of data were available. Inferred modalities with a probability below 0.75 were deemed inconclusive and were omitted. Data for the month of July may show “In Person” status although most school districts are effectively closed during this time for summer break. Users may wish to exclude July data from use for this reason where applicable. Sources K-12 School Opening Tracker. Burbio 2021; https

Seeking a comprehensive database that encompasses high school students, college attendees, young professionals, or individuals interested in continuing education opportunities?

We offer unparalleled access to premium student data lists, including detailed information on students by name, their parents, college attendees, graduates, and much more. Whether you're aiming to spearhead a direct mail initiative for college readiness programs, further education courses, or even school dance attire, our comprehensive database positions you to seamlessly connect with your ideal customer.

What sort of data do we have?

• College Bound HS Students
• K-12 Data
• College Student Mailing lists
• Homeschool Mailing Lists

We understand the challenges marketers face when reaching prospective students. Our solutions provide a data-driven, results-oriented roadmap to enrollment success. Accurate, demographics-rich student marketing data is critical to your school’s successful marketing plan, especially in today’s competitive environment. Our data alliances enable us to bring to market the most robust portfolio of data lists, including students and their parents, young adults, and working professionals for continuing education programs.

Why Buy Leads From Us? With McGRAW’s student leads, you can build a robust pipeline, drive enrollment growth, and achieve your institution's educational and financial objectives. Our education leads offer:

Targeted Outreach: Connect with students interested in specific programs and fields of study. Comprehensive Data: Gain insights into students' academic interests, career goals, and preferred locations. High Engagement Rates: Reach students who are actively exploring educational options, ensuring higher response rates. Scalable Solutions: Access a wide range of leads to match your institution's enrollment goals and capacity. Quick Integration: Seamlessly integrate leads into your CRM for efficient follow-up and management. Compliance and Accuracy: Ensure all leads are generated through compliant and ethical methods, providing accurate and reliable data. What other industries can utilize the data? There are obvious ways to utilize education data and leads, but there may be some additional industries that could benefit.

Book publishers Colleges Universities Religious Organizations Education Supply Companies Office Supply Companies Fundraising Product Companies

The U.S. K12 Education Market Size Was Worth USD 4 Billion in 2023 and Is Expected To Reach USD 31 Billion by 2032, CAGR of 21%.

In 2022, there were over 1.93 million students enrolled in public high schools in California, the highest figure in the United States. This is in comparison to the District of Columbia, which had 21,239 students enrolled in public high schools.

Historical Dataset starting with School Year 2016-2017 through the most Current School Year enrollments for all publicly funded schools in Pennsylvania as reported by school districts, area vocational-technical schools, charter schools, intermediate units, and state operated educational facilities. Local education agencies were asked to report those students who were enrolled and attending as of October 1, of the later year.

County and Statewide Totals Notes:

Statewide and county totals include counts of students attending education classes on a full-time basis outside their parents' district of residence. This data was obtained from the Bureau of Special Education.

Intermediate Unit and CTC Part-day enrollments are excluded from county and state totals.

Statewide and county totals are unique counts of students being educated by public Local Education Agencies. LEA and School level reports may not sum to the County and Statewide totals.

Source: Pennsylvania Information Management System (PIMS)

Notes regarding County Totals:

Enrollment for School Districts, Charter Schools, State Juvenile Correctional Institutions and Comprehensive CTCs are included. Enrollments for Occupational CTCs and IUs are not included.

Counts of students attending education classes on a full-time basis outside their parents' district of residence are included. This data was obtained from the Bureau of Special Education.

Morning and afternoon detail for Half day grades is not available in PENN Data. Therefore, PKH equals the sum of PKA and PKP enrollment, K4H equals the sum of K4A and K4P enrollment, and K5H equals the sum of K5A and K5P enrollment.

County totals are unique counts of students being educated by public Local Education Agencies. LEA and School level reports may not sum to the County total.

The Minnesota Department of Education (MDE) generates and publishes downloadable spreadsheets containing student information in the state of Minnesota.
The reports on the site linked here provide information on student enrollements, graduation rates, and languages, for multiple school years and at various levels.
A basic understanding of MDE's district and school identiers is required to link this data to the published spatial data on school program locations and school district boundaries.
To obtain a report, visit the site and follow the instructions provided. For example, to obtain school enrollment data for public schools in school year 2022, choose "Enrollment" from the "Category" dropdown,
"2022" from the "Year" dropdown, choose "State/District/School/County" in the "Level" dropdown, then click "List files". Click the "xlsx" link under the resulting "Data Files" column to download the spreadsheet.

The Private School Universe Survey, 2003-04 (PSS 2003-04), is a study that is part of the Private School Universe program. PSS 2003-04 (https://nces.ed.gov/surveys/pss/) is a cross-sectional survey that collects data on private elementary and secondary schools, including religious orientation, level of school, length of school year, length of school day, total enrollment (K-12), race/ethnicity of students, number of high school graduates, number of teachers employed, program emphasis, and existence and type of kindergarten program. The study was conducted using mail questionnaires and telephone follow-up of all private schools in the United States. The PSS universe consists of a diverse population of schools. It includes both schools with a religious orientation (e.g., Catholic, Lutheran, or Jewish) and nonsectarian schools with programs ranging from regular to special emphasis and special education. The study's unweighted and weighted response rates were both 94 percent. Key statistics produced from PSS 2003-04 are on the growth of religiously affiliated schools, the number of private high school graduates, the length of the school year for various private schools, and the number of private school students and teachers.