In 2022, there were close to *** 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.

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.

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 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 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 the United States, there are far more public school students than private school students. In 2021, about **** million students were enrolled in private schools in the United States. For public school students, this figure stood at close to ** million students.

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 https://nces.ed.gov/ccd/files.asp#Fiscal:2,LevelId:5,SchoolYearId:35,Page:1">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: https://www.cdc.gov/mmwr/volumes/70/wr/mm7039e2.htm" target="_blank">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

1. K-12 School Opening Tracker. Burbio 2021; https://cai.burbio.com/school-opening-tracker/. June 2021.
2. COVID-19 IMPACT: School District Operational Status. MCH Strategic Data: 2021; https://www.mchdata.com/covid19/schoolclosings. (30 June 2021, date last accessed).
3. Return to Learn Tracker. American Enterprise Institute 2021; https://www.returntolearntracker.net/. (30 June 2021, date last accessed).
4. Colorado School District Reopening Plans. Colorado Department of Education 2021; https://docs.google.com/spreadsheets/d/e/2PACX-1vQipdjO8QWhilhhJ4bX0FBebnHEzK1G3LEDQbE_S-xRvs2t0oHNm--acHwMRFmL9uKw4cXcOUqy1V66/pubhtml. (30 June 2021, date last accessed).
5. Connecticut Report Cards. Connecticut State Department of Education 2021; http://edsight.ct.gov/SASPortal/main.do. (30 June 2021, date last accessed).
6. COVID Planning Tool. Hawaii Department of Education 2021; https://public.tableau.com/views/COVIDPlanningTool-Embed700px/SimpleDashboard. (30 June 2021, date last accessed).
7. Idaho School District Status. Idaho State Department of Education 2021; https://ioem.maps.arcgis.com/apps/opsdashboard/index.html#/379299e56f234fa89cff3c8c6acf3ac8. (30 June 2021, date last accessed).
8. How Illinois Districts Are Providing Instruction: Virtual, In-Person, and Blended Learning. Illinois State Board of Education 2021; https://isp.maps.arcgis.com/apps/opsdashboard/index.html#/fceeacb37da04de4b237ed941dd7d5c4. (30 June 2021, date last accessed).
9. Digital Learning Model Schools. Louisiana Department of Education 2021; https://analytics.la.gov/t/DOE/views/DigitalLearningModel/SchoolLevelModeofLearning. (30 June 2021, date last accessed).
10. Safe Learning Model Dashboard. Minnesota Department of Education 2021; https://analytics.education.state.mn.us/t/MDEPublic/views/MN_Safe_Learning_Model/Dashboard. (30 June 2021, date last accessed).
11. Coronavirus (COVID-19) information. Missouri Department of Elementary & Secondary Education 2021; https://dese.mo.gov/communications/coronavirus-covid-19-information. (30 June 2021, date last accessed).
12. North Carolina School Dashboard. North Carolina Department of Public Instruction 2021. https://docs.google.com/spreadsheets/d/1We8gDpa4Do5NR83Nf8niGE_YxzLDf-KZh-tVWifStxE/edit#gid=0. (30 June 2021, date last accessed).
13. Ring the Bell: Return to In-Person Learning. New Mexico Public Education Department 2021; https://webnew.ped.state.nm.us/reentry-district-and-school-guidance/. (30 June 2021, date last accessed).
14. Reset and Restart Education. Ohio Department of Education 2021; http://education.ohio.gov/Topics/Reset-and-Restart. (30 June 2021, date last accessed).
15. 2020-21 School Status. Oregon Department of Education 2021; https://www.oregon.gov/ode/students-and-family/healthsafety/Pages/2020-21-School-Status.aspx. (30 June 2021, date last accessed).
16. Current Operational Status. South Carolina Department of Education 2021; https://ed.sc.gov/districts-schools/schools/district-and-school-closures/operational-status/#blk2102. (30 June 2021, date last accessed).
17. Tennessee Department of Education COVID-19 District Information. Tennessee Department of Education 2021; https://districtinformation.tnedu.gov/covid-information/search/-1. (30 June 2021, date last accessed).
18. State Snapshot: Virginia School Operational Status. Virginia Department of Education 2021; https://www.doe.virginia.gov/support/health_medical/office/reopen-status.shtml. (30 June 2021, date last accessed).
19. Current Reopening Status of Vermont's K-12 Public Schools. Vermont Department of Financial Regulation 2021; https://dfr.vermont.gov/about-us/covid-19/school-reopening#public-school. (30 June 2021, date last accessed).
20. School Reopening Data. Washington Office of Superintendent of Public Instruction 2021; https://www.k12.wa.us/about-ospi/press-releases/novel-coronavirus-covid-19-guidance-resources/school-reopening-data. (30 June 2021, date last accessed).
21. Public school districts. National Center for Education Statistics 2021; https://nces.ed.gov/ccd/districtsearch/. (30 June 2021, date last accessed).

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.

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.

This file includes Report Card enrollment data from 2024-25 school year. Data is disaggregated by school, district, and the state level and includes counts of students by the following groups: grade level, gender, race/ethnicity, and student programs and special characteristics. Please review the notes below for more information.

Overall attendance data include students in Districts 1-32 and 75 (Special Education). Students in District 79 (Alternative Schools & Programs), charter schools, home schooling, and home and hospital instruction are excluded. Pre-K data do not include NYC Early Education Centers or District Pre-K Centers; therefore, Pre-K data are limited to those who attend K-12 schools that offer Pre-K. Transfer schools are included in citywide, borough, and district counts but removed from school-level files. Attendance is attributed to the school the student attended at the time. If a student attends multiple schools in a school year, the student will contribute data towards multiple schools. Starting in 2020-21, the NYC DOE transitioned to NYSED's definition of chronic absenteeism. Students are considered chronically absent if they have an attendance of 90 percent or less (i.e. students who are absent 10 percent or more of the total days). In order to be included in chronic absenteeism calculations, students must be enrolled for at least 10 days (regardless of whether present or absent) and must have been present for at least 1 day. The NYSED chronic absenteeism definition is applied to all prior years in the report. School-level chronic absenteeism data reflect chronic absenteeism at a particular school. In order to eliminate double-counting students in chronic absenteeism counts, calculations at the district, borough, and citywide levels include all attendance data that contribute to the given geographic category. For example, if a student was chronically absent at one school but not at another, the student would only be counted once in the citywide calculation. For this reason, chronic absenteeism counts will not align across files. All demographic data are based on a student's most recent record in a given year. Students With Disabilities (SWD) data do not include Pre-K students since Pre-K students are screened for IEPs only at the parents' request. English language learner (ELL) data do not include Pre-K students since the New York State Education Department only begins administering assessments to be identified as an ELL in Kindergarten. Only grades PK-12 are shown, but calculations for "All Grades" also include students missing a grade level, so PK-12 may not add up to "All Grades". Data include students missing a gender, but are not shown due to small cell counts. Data for Asian students include Native Hawaiian or Other Pacific Islanders . Multi-racial and Native American students, as well as students missing ethnicity/race data are included in the "Other" ethnicity category. In order to comply with the Family Educational Rights and Privacy Act (FERPA) regulations on public reporting of education outcomes, rows with five or fewer students are suppressed, and have been replaced with an "s". Using total days of attendance as a proxy , rows with 900 or fewer total days are suppressed. In addition, other rows have been replaced with an "s" when they could reveal, through addition or subtraction, the underlying numbers that have been redacted. Chronic absenteeism values are suppressed, regardless of total days, if the number of students who contribute at least 20 days is five or fewer. Due to the COVID-19 pandemic and resulting shift to remote learning in March 2020, 2019-20 attendance data was only available for September 2019 through March 13, 2020. Interactions data from the spring of 2020 are reported on a separate tab. Interactions were reported by schools during remote learning, from April 6 2020 through June 26 2020 (a total of 57 instructional days, excluding special professional development days of June 4 and June 9). Schools were required to indicate any student from their roster that did not have an interaction on a given day. Schools were able to define interactions in a way that made sense for their students and families. Definitions of an interaction included: • Student submission of an assignment or completion of an assessment, in whichever manner the school is collecting • Student participation in an online forum, chat log, or discussion thread • Student/family phone call, email or response to teacher email • Phone, email, and/or other digital communication with a family member which confirms student interaction/engagement • Other evidence of participation as determined by the principal. Interactions data are attributed to students' school of record on a given day. A student participating in a Shared Instruction (SHIN) model may have recorded interactions at multiple schools on a given day, but only one record is counted for the interaction rate, attributed to students' school of record for that day. Due to the shift to hybrid learning, attendance data for the 2020-21 school year include both in-person and remote instruction. Total days, days absent, and days present fields include both in-person and remote attendance.

More information on attendance policies can be found here: https://www.schools.nyc.gov/school-life/rules-for-students/attendance

Private schools have struggled to maintain enrollment and revenue as the population of children in the K-12 age range evaporates. The Federal Reserve Bank of Dallas and the International Monetary Fund report that the fertility rate has continued to plunge further below replacement levels, and the National Center for Health Statistics reports a drop of over 100,000 births per year since 2020. This demographic shift has led to fewer children entering the K-12 age range and smaller graduating classes. Immigration helps reduce low birth rates' impact on the US population, but less than a tenth of immigrating students attend private K-12 schools. Ultimately, the National Center for Education Statistics projects a drop in private school enrollment from 6.0 million in 2020 to 5.5 million by 2025. To mitigate these challenges, many private schools have increased tuition fees, which may exclude families unable to afford the higher costs. Revenue has been sinking at a CAGR of 1.5% to an estimated $79.3 billion over the five years through 2025, including an expected 0.3% slump in 2025 alone. Declining birth rates, alongside the rise of charter schools, have reshaped the educational landscape. Charter schools now operate in 45 states, offering specialized education at lower costs than private schools and attracting many parents. This expansion has resulted in only a slight 2.3% slump in public school enrollment since 2020, compared to an 8.2% drop in private schools. However, government assistance is beginning to help private schools become more accessible. School choice programs, especially vouchers and Education Savings Accounts (ESAs), are becoming especially prevalent and have the full support of the Trump administration. Private schools will continue becoming more accessible as parents gain the ability to use public funds for private education. Birth rates will continue dropping, but government assistance and growing incomes will help stave off further dips in revenue. Larger, well-established private schools may better navigate challenges by balancing tuition hikes with financial aid offerings targeted at higher-income families. To stay competitive with charter and public alternatives, private schools might offer more personalized educational experiences. By leveraging potential government support and adjusting their strategies, private schools will buoy enrollment and revenue amid persisting headwinds. Revenue is set to see stagnant growth and will reach $73.4 billion by the end of 2030.

The 2021-2022 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 2021-2022 school year and the Fall 2022 semester, from August 2021 – December 2022.

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 https://nces.ed.gov/ccd/files.asp#Fiscal:2,LevelId:5,SchoolYearId:35,Page:1">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.

• 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: https://www.cdc.gov/mmwr/volumes/70/wr/mm7039e2.htm" target="_blank">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.

• Data from August 1, 2021 to June 24, 2022 correspond to the 2021-2022 school year. During this time frame, data from the AEI/Return to Learn Tracker and most state dashboards were not available. Inferred modalities with a probability below 0.6 were deemed inconclusive and were omitted. During the Fall 2022 semester, modalities for districts with a school closure reported by Burbio were updated to either “Remote”, if the closure spanned the entire week, or “Hybrid”, if the closure spanned 1-4 days of the week.
• Data from August 1, 2022 to December 31, 2022 correspond to the 2022-2023 school year and were processed in a similar manner to data from the 2021-2022 school year.
• 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.

1. K-12 School Opening Tracker. Burbio 2021; https://cai.burbio.com/school-opening-tracker/. June 2021.
2. COVID-19 IMPACT: School District Operational Status. MCH Strategic Data: 2021; https://www.mchdata.com/covid19/schoolclosings. (30 June 2021, date last accessed).
3. Return to Learn Tracker. American Enterprise Institute 2021; https://www.returntolearntracker.net/. (30 June 2021, date last accessed).
4. Colorado School District Reopening Plans. Colorado Department of Education 2021; https://docs.google.com/spreadsheets/d/e/2PACX-1vQipdjO8QWhilhhJ4bX0FBebnHEzK1G3LEDQbE_S-xRvs2t0oHNm--acHwMRFmL9uKw4cXcOUqy1V66/pubhtml. (30 June 2021, date last accessed).
5. Connecticut Report Cards. Connecticut State Department of Education 2021; http://edsight.ct.gov/SASPortal/main.do. (30 June 2021, date last accessed).
6. COVID Planning Tool. Hawaii Department of Education 2021; https://public.tableau.com/views/COVIDPlanningTool-Embed700px/SimpleDashboard. (30 June 2021, date last accessed).
7. Idaho School District Status. Idaho State Department of Education 2021; https://ioem.maps.arcgis.com/apps/opsdashboard/index.html#/379299e56f234fa89cff3c8c6acf3ac8. (30 June 2021, date last accessed).
8. How Illinois Districts Are Providing Instruction: Virtual, In-Person, and Blended Learning. Illinois State Board of Education 2021; https://isp.maps.arcgis.com/apps/opsdashboard/index.html#/fceeacb37da04de4b237ed941dd7d5c4. (30 June 2021, date last accessed).
9. Digital Learning Model Schools. Louisiana Department of Education 2021; https://analytics.la.gov/t/DOE/views/DigitalLearningModel/SchoolLevelModeofLearning. (30 June 2021, date last accessed).
10. Safe Learning Model Dashboard. Minnesota Department of Education 2021; https://analytics.education.state.mn.us/t/MDEPublic/views/MN_Safe_Learning_Model/Dashboard. (30 June 2021, date last accessed).
11. Coronavirus (COVID-19) information. Missouri Department of Elementary & Secondary Education 2021; https://dese.mo.gov/communications/coronavirus-covid-19-information. (30 June 2021, date last accessed).
12. North Carolina School Dashboard. North Carolina Department of Public Instruction 2021. https://docs.google.com/spreadsheets/d/1We8gDpa4Do5NR83Nf8niGE_YxzLDf-KZh-tVWifStxE/edit#gid=0. (30 June 2021, date last accessed).
13. Ring the Bell: Return to In-Person Learning. New Mexico Public Education Department 2021; https://webnew.ped.state.nm.us/reentry-district-and-school-guidance/. (30 June 2021, date last accessed).
14. Reset and Restart Education. Ohio Department of Education 2021; http://education.ohio.gov/Topics/Reset-and-Restart. (30 June 2021, date last accessed).
15. 2020-21 School Status. Oregon Department of Education 2021; https://www.oregon.gov/ode/students-and-family/healthsafety/Pages/2020-21-School-Status.aspx. (30 June 2021, date last accessed).
16. Current Operational Status. South Carolina Department of Education 2021; https://ed.sc.gov/districts-schools/schools/district-and-school-closures/operational-status/#blk2102. (30 June 2021, date last accessed).
17. Tennessee Department of Education COVID-19 District Information. Tennessee Department of Education 2021; https://districtinformation.tnedu.gov/covid-information/search/-1. (30 June 2021, date last accessed).
18. State Snapshot: Virginia School Operational Status. Virginia Department of Education 2021; https://www.doe.virginia.gov/support/health_medical/office/reopen-status.shtml. (30 June 2021, date last accessed).
19. Current Reopening Status of Vermont's K-12 Public Schools. Vermont Department of Financial Regulation 2021; https://dfr.vermont.gov/about-us/covid-19/school-reopening#public-school. (30 June 2021, date last accessed).
20. School Reopening Data. Washington Office of Superintendent of Public Instruction 2021; https://www.k12.wa.us/about-ospi/press-releases/novel-coronavirus-covid-19-guidance-resources/school-reopening-data. (30 June 2021, date last accessed).
21. Public school districts. National Center for Education Statistics 2021; https://nces.ed.gov/ccd/districtsearch/. (30 June 2021, date last accessed).

According to a 2019 survey, around 63 percent of high school students in the United States use digital learning tools at school to learn every day. This compares to 45 percent of elementary students, although the actual figure may be lower as the survey only included elementary school students in the third grade or above.

This dataset contains the counts of students that enrolled in and completed Dual Credit courses while enrolled as students in WA Public K12 school, broken out by various disaggregations (year, type of dual credit course, student characteristics)

The K-12 education technology market, valued at $4.23 billion in 2025, is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 10.09% from 2025 to 2033. This expansion is driven by several key factors. Increasing government initiatives promoting digital learning, coupled with a rising demand for personalized and engaging educational experiences, are fueling market growth. Parents and educators are increasingly recognizing the benefits of technology in enhancing learning outcomes and improving student engagement, leading to higher adoption rates of educational software, online platforms, and digital learning resources. Furthermore, the growing prevalence of blended learning models, which integrate online and traditional classroom instruction, is contributing to market expansion. Competition within the sector is fierce, with established players like McGraw-Hill Education and Pearson Education Inc. vying for market share alongside innovative EdTech startups such as BYJU'S and Desmos. The market is segmented based on various factors, including the type of technology used (e.g., learning management systems, educational apps, virtual reality), grade level, and geographical location. While data on specific regional breakdowns is unavailable, the global nature of many of the listed companies suggests a geographically diverse market. The restraints on market growth primarily involve factors such as the digital divide, particularly in underserved communities lacking access to reliable internet and technology infrastructure. Concerns regarding data privacy and security related to student information also present a challenge. However, ongoing technological advancements, increasing affordability of educational technology, and the continuous development of user-friendly interfaces are mitigating these challenges. The long-term outlook for the K-12 EdTech market remains positive, driven by ongoing technological advancements and the increasing recognition of technology's transformative potential in education. The market is expected to witness significant innovation in areas such as artificial intelligence (AI)-powered personalized learning, gamification of education, and immersive learning experiences using virtual and augmented reality. Recent developments include: July 2024: AudioEye Inc., a digital accessibility company, and Finalsite, a K-12 school community relationship management platform, strengthened their collaboration to boost digital accessibility in K-12 schools. The enhanced partnership, backed by ambitious growth objectives and a thorough go-to-market approach, leverages AudioEye's advanced platform for accessibility testing and remediation. This move comes in response to the Department of Justice's recent rule, under Title II of the Americans with Disabilities Act (ADA), mandating stringent accessibility standards for websites and mobile apps, especially for state and local government bodies, which include public schools.June 2024: Unacademy, a prominent edtech startup backed by SoftBank, actively explored a merger with K12 Techno, the entity behind Orchids International Schools. These talks, spanning four weeks, aim to culminate in a joint venture where both parties will hold an equal 50% stake. Unacademy had initially invested in K12 Techno, the parent of Orchids International Schools, three years ago. Also, it is worth mentioning that Peak XV, an investment firm, holds stakes in both Unacademy and K12 Techno. Unacademy attempted to acquire K12 Techno in 2021, but those discussions failed.May 2024: Clever, a platform that serves over 100,000 schools, unveiled its latest security offering explicitly tailored for K-12 institutions. This solution focuses on bolstering identity and access management, which is crucial for the unique challenges faced by K-12 schools. Clever's layered security approach is a comprehensive shield, consolidating various protective measures under one reliable provider. Crafted with a focus on K-12 education, these solutions protect students and the entire district community, including teachers and staff. Clever's release comes at a reasonable time. With cyber threats looming over educational institutions, especially those with limited resources, the need for strong defenses has never been more urgent.. Key drivers for this market are: Growing Popularity of Online Learning. Potential restraints include: Growing Popularity of Online Learning. Notable trends are: The Public K-12 Education Segment to Witness Major Growth.

Public school enrolments in regular programs for youth in elementary and secondary schools, by grade and sex.

According to a survey conducted during the 2023-24 school year, **************** was the top learning management system used by K-12 students and teachers in the United States. Learning management systems are used to provide schools with a centralized platform to facilitate course management, content authoring and delivery, reporting grades and data, and communication between students, families, and educators. In that same year, the top study tool in K-12 schools was *******, while the top site or learning resource was *******.

Competition has intensified for education consultants as new owner-operated consulting firms have taken advantage of low barriers to entry and solid demand. These smaller operations increased price-based competition, making consumers more value-conscious and dragging down education consultants' profit. Despite some headwinds, education consultants have leveraged their ability to operate remotely to provide insight for students who are becoming increasingly unsure of the choice to enroll in postsecondary education. STEM-focused consultants are outperforming competitors as economic uncertainty pushes students and young adults toward careers in burgeoning industries. Revenue has been climbing at a CAGR of 2.0% to an estimated $3.0 billion over the five years through 2024, including an expected rise of 0.9% in 2024 alone. The escalating cost and uncertain return on investment of a college degree have led many potential students to reevaluate their higher education plans. Some students are remedying these concerns by choosing affordable community colleges, but others are aiming for prestigious institutions to justify the investment. Competition for spots at Ivy Leagues and other major schools is intensifying, promoting education consultants. Education consulting agencies have seen growing demand as high-earning parents prepare their children for college at an earlier age than ever. A college degree's hefty price tag has also helped bolster demand for consultants who can help aspiring students secure scholarships and grants for students. Through 2029, mounting technological advancement across the economy will encourage consumers to return to college and learn the skills of new workplaces. Growing college enrollment will heighten demand for education consultants despite the ongoing shift among institutions toward optional standardized testing. Still, the downward trend in birth rates represents a long-term challenge, with a shrinking number of K-12 students causing a delayed downturn in the number of college students. Online test prep courses will remain a minor threat, but education consultants will leverage their in-depth, personalized services to maintain their competitive advantage. A focus on core demographics and digital flexibility will play a significant role in supporting growth moving forward. Education consultants' revenue is set to swell at a CAGR of 1.5% to an estimated $3.2 billion through the end of 2029.

This Private Schools feature dataset is composed of private elementary and secondary education facilities in the United States as defined by the Private School Survey (PSS, https://nces.ed.gov/surveys/pss/), National Center for Education Statistics (NCES, https://nces.ed.gov), US Department of Education for the 2017-2018 school year. This includes all prekindergarten through 12th grade schools as tracked by the PSS. 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 2675 new records, modifications to the spatial location and/or attribution of 19836 records, the removal of 254 records no longer applicable. Additionally, 10,870 records were removed that previously had a STATUS value of 2 (Unknown; not represented in the most recent PSS data) and duplicate records identified by ORNL.