The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated school district boundary composite files that include public elementary, secondary, and unified school district boundaries clipped to the U.S. shoreline. School districts are special-purpose governments and administrative units designed by state and local officials to provide public education for local residents. District boundaries are collected for NCES by the U.S. Census Bureau to develop demographic estimates and to support educational research and program administration. The NCES Common Core of Data (CCD) program is an annual collection of basic administrative characteristics for all public schools, school districts, and state education agencies in the United States. These characteristics are reported by state education officials and include directory information, number of students, number of teachers, grade span, and other conditions. The administrative attributes in this layer were developed from the 2021-2022 CCD collection. For more information about NCES school district boundaries, see: https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries. For more information about CCD school district attributes, see: https://nces.ed.gov/ccd/files.asp. Notes: -1 or MIndicates that the data are missing. -2 or N Indicates that the data are not applicable. -9 Indicates that the data do not meet NCES data quality standards. All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The National Center for Education Statistics' (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated point locations (latitude and longitude) for public elementary and secondary schools included in the NCES Common Core of Data (CCD). The CCD program annually collects administrative and fiscal data about all public schools, school districts, and state education agencies in the United States. The data are supplied by state education agency officials and include basic directory and contact information for schools and school districts, as well as characteristics about student demographics, number of teachers, school grade span, and various other administrative conditions. CCD school and agency point locations are derived from reported information about the physical _location of schools and agency administrative offices. The point locations and administrative attributes in this data layer were developed from the 2021-2022 CCD collection. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations. For more information about these CCD attributes, as well as additional attributes not included, see: https://nces.ed.gov/ccd/files.asp.Notes:-1 or MIndicates that the data are missing.-2 or NIndicates that the data are not applicable.-9Indicates that the data do not meet NCES data quality standards.All information contained in this file is in the public _domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

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

The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program develops bi-annually updated point locations (latitude and longitude) for private schools included in the NCES Private School Survey (PSS). The PSS is conducted to provide a biennial count of the total number of private schools, teachers, and students. The PSS school _location and associated geographic area assignments are derived from reported information about the physical _location of private schools. The school geocode file includes supplemental geographic information for the universe of schools reported in the 2021-2022 PSS school collection, and they can be integrated with the survey files through use of institutional identifiers included in both sources. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations and https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries.All information contained in this file is in the public _domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program develops annually updated point locations (latitude and longitude) for postsecondary institutions included in the NCES Integrated Postsecondary Education Data System (IPEDS). The IPEDS program annually collects information about enrollments, program completions, graduation rates, faculty and staff, finances, institutional prices, and student financial aid from colleges, universities, and technical and vocational institutions that participate in federal student financial aid programs under the Higher Education Act of 1965 (as amended). The NCES EDGE program uses address information reported in the annually updated IPEDS directory file to develop point locations for all institutions reported in IPEDS. The point locations in this data layer were developed from the 2021-2022 IPEDS collection. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

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).

Identify the public/private school locations in the city of Placentia_June 2023School Type Codes1-Regular Elementary and Secondary Schools2-Special Education3-Vocational/Technical Schools4-Other/Alternative SchoolsSchool Information: NCES (National Center for Education Statistics)Source: CCD Public School data 2021-2022 school year PSS Private School data 2017-2018 school year

The National Center for Education Statistics' (NCES) Education Demographic and Geographic Estimate (EDGE) program develops annually updated point locations (latitude and longitude) for public elementary, secondary, unified, and supervisory school district administrative offices included in the NCES Common Core of Data (CCD). The CCD is an annual collection of basic administrative characteristics that includes the physical address for all public schools, school districts, and state education agencies in the United States. The point locations in this data layer were developed from the 2022-2021 CCD collection. For more information about NCES school point data, see: https://nces.ed.gov/programs/edge/Geographic/SchoolLocations.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

This data layer produced by the National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program provides a geographic locale framework that classifies all U.S. territory into twelve categories ranging from Large Cities to Remote Rural areas. NCES uses this framework to describe the type of geographic area where schools and school districts are located. The criteria for these classifications are defined by NCES, and rely on standard geographic areas developed and maintained by the U.S. Census Bureau. The NCES Locale boundaries are based on geographic areas represented in Census TIGER/Line. For more information about the NCES locale framework, and to download the data, see: https://nces.ed.gov/programs/edge/Geographic/LocaleBoundaries. The classifications include:City - Large (11): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population of 250,000 or more.City - Midsize (12): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population less than 250,000 and greater than or equal to 100,000.City - Small (13): Territory inside an Urban Area with a population of 50,000 or more and inside a Principal City with population less than 100,000.Suburb – Large (21): Territory outside a Principal City and inside an Urban Area with population of 250,000 or more.Suburb - Midsize (22): Territory outside a Principal City and inside an Urban Area with population less than 250,000 and greater than or equal to 100,000.Suburb - Small (23): Territory outside a Principal City and inside an Urban Area with population less than 100,000. Town - Fringe (31): Territory inside an Urban Area with a population less than 50,000 that is less than or equal to 10 miles from an Urban Area with a population of 50,000 or more.Town - Distant (32): Territory inside an Urban Area with a population less than 50,000 that is more than 10 miles and less than or equal to 35 miles from an Urban Area with a population of 50,000 or more.Town - Remote (33): Territory inside an Urban Area with a population less than 50,000 that is more than 35 miles of an Urban Area with a population of 50,000 or more.Rural - Fringe (41): Census-defined rural territory that is less than or equal to 5 miles from an Urban Area of 50,000 or more, as well as rural territory that is less than or equal to 2.5 miles from an Urban Area with a population less than 50,000.Rural - Distant (42): Census-defined rural territory that is more than 5 miles but less than or equal to 25 miles from an Urban Area with a population of 50,000 or more, as well as rural territory that is more than 2.5 miles but less than or equal to 10 miles from an Urban Area with a population less than 50,000.Rural - Remote (43): Census-defined rural territory that is more than 25 miles from an Urban Area with a population of 50,000 or more and is also more than 10 miles from an Urban Area with a population less than 50,000.All information contained in this file is in the public domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

🇺🇸 미국 English 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.

The National Center for Education Statistics’ (NCES) Education Demographic and Geographic Estimates (EDGE) program develops annually updated school district boundary composite files that include public elementary, secondary, and unified school district boundaries clipped to the U.S. shoreline. School districts are special-purpose governments and administrative units designed by state and local officials to organize and provide public education for local residents. District boundaries are collected for NCES by the U.S. Census Bureau to support educational research and program administration, and the boundaries are essential for constructing district-level estimates of the number of children in poverty. The Census Bureau’s School District Boundary Review program (SDRP) (https://www.census.gov/programs-surveys/sdrp.html) obtains the boundaries, names, and grade ranges from state officials, and integrates these updates into Census TIGER. Census TIGER boundaries include legal maritime buffers for coastal areas by default, but the NCES composite file removes these buffers to facilitate broader use and cleaner cartographic representation. The inputs for this data layer were developed from Census TIGER/Line 2022 and represent boundaries reported for the 2021-2022 school year. For more information about NCES school district boundary data, see: https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries.All information contained in this file is in the public _domain. Data users are advised to review NCES program documentation and feature class metadata to understand the limitations and appropriate use of these data.

Analysis of ‘Postsecondary School Locations 2020-21’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c39a38ef-05f7-403c-9092-0ddd5d640b7d on 11 February 2022.

--- Dataset description provided by original source is as follows ---

--- Original source retains full ownership of the source dataset ---

This layer serves as the authoritative geographic data source for California's K-12 public school locations during the 2021-22 academic year. Schools are mapped as point locations and assigned coordinates based on the physical address of the school facility. The school records are enriched with additional demographic and performance variables from the California Department of Education's data collections. These data elements can be visualized and examined geographically to uncover patterns, solve problems and inform education policy decisions.The schools in this file represent a subset of all records contained in the CDE's public school directory database. This subset is restricted to K-12 public schools that were open in October 2021 to coincide with the official 2021-22 student enrollment counts collected on Fall Census Day in 2021(first Wednesday in October). This layer also excludes nonpublic nonsectarian schools and district office schools.The CDE's California School Directoryprovides school location other basic school characteristics found in the layer's attribute table. The school enrollment, demographic and program data are collected by the CDE through the California Longitudinal Achievement System (CALPADS) and can be accessed as publicly downloadable files from the Data & Statisticsweb page on the CDE website. Schools are assigned X, Y coordinates using a quality controlled geocoding and validation process to optimize positional accuracy. Most schools are mapped to the school structure or centroid of the school property parcel and are individually verified using aerial imagery or assessor's parcels databases. Schools are assigned various geographic area values based on their mapped locations including state and federal legislative district identifiers and National Center for Education Statistics (NCES) locale codes.

The School Pulse Panel (SPP), sponsored by the National Center for Education Statistics (NCES), part of the Institute of Education Sciences (IES), within the United States Department of Education, collects insightful data on U.S. public schools. Originally focusing on the 2021-22 school year to assess the impact of the COVID-19 pandemic on students and staff, the survey has since broadened its scope to address various evolving educational topics. Conducted by the U.S. Census Bureau, the SPP continues into the 2024-25 school year, surveying school principals monthly on key issues such as staffing, attendance, after-school programs, learning recovery, digital literacy, mental health, and more. The September 2021 SPP survey asked about schools' offering performing arts activities (for example, band, choir, orchestra, or drama) and how these activities were affected by the COVID-19 pandemic. For detailed information on the survey content and methodology, visit the NCES website.

This dataset tracks annual science proficiency from 2021 to 2022 for Francis Howell Central High School vs. Missouri and Francis Howell R-III School District

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

An interactive dashboard and visualizations of these data are available https://public-data-hub-dhhs.hub.arcgis.com/pages/school-learning-modalities" target="_blank">here.

Data Information and Disclaimers School learning modality data provided here are model estimates using combined input data from https://cai.burbio.com/school-opening-tracker/" target="_blank">Burbio and https://www.mchdata.com/covid19/schoolclosings" target="_blank">MCH and are not guaranteed to be 100% accurate. A probabilistic Hidden Markov Model (HMM) was implemented to determine the learning modality of each district by week. This is an unsupervised model which infers the sequence of learning modalities most likely to produce the observed data and includes reported modality data from each source. The HMM was trained using data from MCH Strategic Data, Burbio, American Enterprise Institute’s Return to Learn tracker, and available state education dashboards (including Colorado, Connecticut, Hawaii, Idaho, Illinois, Louisiana, Minnesota, Missouri, New Mexico, North Carolina, Ohio, Oregon, South Carolina, Tennessee, Vermont, Virginia, and Washington). You can read more about the model in the CDC MMWR article here: https://www.cdc.gov/mmwr/volumes/70/wr/mm7039e2.htm?s_cid=mm7039e2_e&ACSTrackingID=USCDC_921-DM66537&ACSTrackingLabel=MMWR%20Early%20Release%20-%20Vol.%2070%2C%20September%2024%2C%202021&deliveryName=USCDC_921-DM66537" target = "_blank">COVID-19 Related School Closures and Learning Modalities Changes.

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 include the following NCES subtypes and exclude private schools:

• 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

July data is included but schools are closed during this month.

The study's primary goal is to assess whether a mixed-mode professional development (PD) model that combines virtual and in-person delivery of PD activities can serve as a viable alternative to the original face-to-face delivery approach in supporting teachers' use of the Assessment-to-Instruction (A2i) system, facilitating their implementation of differentiated small-group instruction, and improving students' reading skills in a large, diverse set of schools. There are three datasets for this study: A school-level dataset that includes information collected about the 59 schools in the study. School-level information was collected from the 2017-2018 Common Core of Data provided by the National Center of Education Statistics, the 2017-2018 Civil Rights Data Collection provided by the Office of Civil Rights, and school-level reading achievement data during the 2017-2018 school year, provided by state education departments. To maintain anonymity of schools, we excluded any publicly available data about school characteristics from the dataset. In Table 3 in the study report, which compares the study schools to public elementary schools nationally, the national sample includes all public, regular elementary schools serving students in any of Grades K, 1, 2, or 3 that are not charter, magnet or virtual schools. A teacher-level dataset that includes teachers in the analysis sample (i.e. teachers in Grades K-1 in the 2017-2018 school year, expanding to Grades K-3 in the 2020-2021 school year). This dataset includes responses to the two teacher surveys administered in 2019 and 2021, information about teacher usage of the A2i platform, and the number of PD events attended by each teacher in 2019-2020 and 2020-2021. A student-level dataset that includes all information used for the student-level analysis, including student demographic from district records and student achievement data from A2i assessments, Gates-MacGinitie Reading Tests administered in the spring of 2019, and state/district reading tests administered in the spring of 2021.

There were approximately 18.58 million college students in the U.S. in 2022, with around 13.49 million enrolled in public colleges and a further 5.09 million students enrolled in private colleges. The figures are projected to remain relatively constant over the next few years.

What is the most expensive college in the U.S.? The overall number of higher education institutions in the U.S. totals around 4,000, and California is the state with the most. One important factor that students – and their parents – must consider before choosing a college is cost. With annual expenses totaling almost 78,000 U.S. dollars, Harvey Mudd College in California was the most expensive college for the 2021-2022 academic year. There are three major costs of college: tuition, room, and board. The difference in on-campus and off-campus accommodation costs is often negligible, but they can change greatly depending on the college town.

The differences between public and private colleges Public colleges, also called state colleges, are mostly funded by state governments. Private colleges, on the other hand, are not funded by the government but by private donors and endowments. Typically, private institutions are  much more expensive. Public colleges tend to offer different tuition fees for students based on whether they live in-state or out-of-state, while private colleges have the same tuition cost for every student.