https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.
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.
https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario
Data from the Ministry of Colleges and Universities' College Enrolment Statistical Reporting system.
Provides aggregated key enrolment data for college students, such as:
To protect privacy, numbers are suppressed in categories with less than 10 students.
https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
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.
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
Colleges and UniversitiesThis feature layer, utilizing data from the National Center for Education Statistics (NCES), displays colleges and universities in the U.S. and its territories. NCES uses the Integrated Postsecondary Education Data System (IPEDS) as the "primary source for information on U.S. colleges, universities, and technical and vocational institutions." According to NCES, this layer "contains directory information for every institution in the 2021-22 IPEDS universe. Includes name, address, city, state, zip code and various URL links to the institution's home page, admissions, financial aid offices and the net price calculator. Identifies institutions as currently active, institutions that participate in Title IV federal financial aid programs for which IPEDS is mandatory. It also includes variables derived from the 2021-22 Institutional Characteristics survey, such as control and level of institution, highest level and highest degree offered and Carnegie classifications."Gallaudet UniversityData currency: 2021Data source: IPEDS Complete Data FilesData modification: Removed fields with coded values and replaced with descriptionsFor more information: Integrated Postsecondary Education Data SystemSupport documentation: IPEDS Complete Data Files > Directory Information > DictionaryFor feedback, please contact: ArcGIScomNationalMaps@esri.comU.S. Department of Education (ED)Per ED, "ED's mission is to promote student achievement and preparation for global competitiveness by fostering educational excellence and ensuring equal access.ED was created in 1980 by combining offices from several federal agencies." ED's employees and budget "are dedicated to:Establishing policies on federal financial aid for education, and distributing as well as monitoring those funds.Collecting data on America's schools and disseminating research.Focusing national attention on key educational issues.Prohibiting discrimination and ensuring equal access to education."
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Context
The dataset tabulates the College Park population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of College Park across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.
Key observations
In 2023, the population of College Park was 34,187, a 0% increase year-by-year from 2022. Previously, in 2022, College Park population was 34,186, a decline of 0.92% compared to a population of 34,502 in 2021. Over the last 20 plus years, between 2000 and 2023, population of College Park increased by 9,502. In this period, the peak population was 34,698 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).
When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).
Data Coverage:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for College Park Population by Year. You can refer the same here
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License information was derived automatically
Context
The dataset tabulates the College Corner population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for College Corner. The dataset can be utilized to understand the population distribution of College Corner by age. For example, using this dataset, we can identify the largest age group in College Corner.
Key observations
The largest age group in College Corner, OH was for the group of age 30 to 34 years years with a population of 37 (11.31%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in College Corner, OH was the 80 to 84 years years with a population of 2 (0.61%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for College Corner Population by Age. You can refer the same here
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Context
The dataset tabulates the College Corner population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of College Corner.
The dataset constitues the following two datasets across these two themes
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
The National Center for Education Statistics' (NCES) Education Demographic and Geographic Estimates (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 2022-2023 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 M Indicates 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.
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Context
The dataset tabulates the College Place population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for College Place. The dataset can be utilized to understand the population distribution of College Place by age. For example, using this dataset, we can identify the largest age group in College Place.
Key observations
The largest age group in College Place, WA was for the group of age 20 to 24 years years with a population of 1,306 (13.29%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in College Place, WA was the 80 to 84 years years with a population of 134 (1.36%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates
Age groups:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for College Place Population by Age. You can refer the same here
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License information was derived automatically
The data file (SPSS file) contains data compiled from Peterson's Guide in spring 2014 about college applications, including college name, number of applicants (male and female), acceptance rate, the college's national ranking, and the college's student body size. The dataset is part of a project on gender and competition.
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
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School enrollment data are used to assess the socioeconomic condition of school-age children. Government agencies also require these data for funding allocations and program planning and implementation.
Data on school enrollment and grade or level attending were derived from answers to Question 10 in the 2015 American Community Survey (ACS). People were classified as enrolled in school if they were attending a public or private school or college at any time during the 3 months prior to the time of interview. The question included instructions to “include only nursery or preschool, kindergarten, elementary school, home school, and schooling which leads to a high school diploma, or a college degree.” Respondents who did not answer the enrollment question were assigned the enrollment status and type of school of a person with the same age, sex, race, and Hispanic or Latino origin whose residence was in the same or nearby area.
School enrollment is only recorded if the schooling advances a person toward an elementary school certificate, a high school diploma, or a college, university, or professional school (such as law or medicine) degree. Tutoring or correspondence schools are included if credit can be obtained from a public or private school or college. People enrolled in “vocational, technical, or business school” such as post secondary vocational, trade, hospital school, and on job training were not reported as enrolled in school. Field interviewers were instructed to classify individuals who were home schooled as enrolled in private school. The guide sent out with the mail questionnaire includes instructions for how to classify home schoolers.
Enrolled in Public and Private School – Includes people who attended school in the reference period and indicated they were enrolled by marking one of the questionnaire categories for “public school, public college,” or “private school, private college, home school.” The instruction guide defines a public school as “any school or college controlled and supported primarily by a local, county, state, or federal government.” Private schools are defined as schools supported and controlled primarily by religious organizations or other private groups. Home schools are defined as “parental-guided education outside of public or private school for grades 1-12.” Respondents who marked both the “public” and “private” boxes are edited to the first entry, “public.”
Grade in Which Enrolled – From 1999-2007, in the ACS, people reported to be enrolled in “public school, public college” or “private school, private college” were classified by grade or level according to responses to Question 10b, “What grade or level was this person attending?” Seven levels were identified: “nursery school, preschool;” “kindergarten;” elementary “grade 1 to grade 4” or “grade 5 to grade 8;” high school “grade 9 to grade 12;” “college undergraduate years (freshman to senior);” and “graduate or professional school (for example: medical, dental, or law school).”
In 2008, the school enrollment questions had several changes. “Home school” was explicitly included in the “private school, private college” category. For question 10b the categories changed to the following “Nursery school, preschool,” “Kindergarten,” “Grade 1 through grade 12,” “College undergraduate years (freshman to senior),” “Graduate or professional school beyond a bachelor’s degree (for example: MA or PhD program, or medical or law school).” The survey question allowed a write-in for the grades enrolled from 1-12.
Question/Concept History – Since 1999, the ACS enrollment status question (Question 10a) refers to “regular school or college,” while the 1996-1998 ACS did not restrict reporting to “regular” school, and contained an additional category for the “vocational, technical or business school.” The 1996-1998 ACS used the educational attainment question to estimate level of enrollment for those reported to be enrolled in school, and had a single year write-in for the attainment of grades 1 through 11. Grade levels estimated using the attainment question were not consistent with other estimates, so a new question specifically asking grade or level of enrollment was added starting with the 1999 ACS questionnaire.
Limitation of the Data – Beginning in 2006, the population universe in the ACS includes people living in group quarters. Data users may see slight differences in levels of school enrollment in any given geographic area due to the inclusion of this population. The extent of this difference, if any, depends on the type of group quarters present and whether the group quarters population makes up a large proportion of the total population. For example, in areas that are home to several colleges and universities, the percent of individuals 18 to 24 who were enrolled in college or graduate school would increase, as people living in college dormitories are now included in the universe.
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When the COVID-19 pandemic began, U.S. college students reported increased anxiety and depression. This study examines mental health among U.S college students during the subsequent 2020–2021 academic year by surveying students at the end of the fall 2020 and the spring 2021 semesters. Our data provide cross-sectional snapshots and longitudinal changes. Both surveys included the PSS, GAD-7, PHQ-8, questions about students’ academic experiences and sense of belonging in online, in-person, and hybrid classes, and additional questions regarding behaviors, living circumstances, and demographics. The spring 2021 study included a larger, stratified sample of eight demographic groups, and we added scales to examine relationships between mental health and students’ perceptions of their universities’ COVID-19 policies. Our results show higher-than-normal frequencies of mental health struggles throughout the 2020–2021 academic year, and these were substantially higher for female college students, but by spring 2021, the levels did not vary substantially by race/ethnicity, living circumstances, vaccination status, or perceptions of university COVID-19 policies. Mental health struggles inversely correlated with scales of academic and non-academic experiences, but the struggles positively correlated with time on social media. In both semesters, students reported more positive experiences with in-person classes, though all class types were rated higher in the spring semester, indicating improvements in college students’ course experiences as the pandemic continued. Furthermore, our longitudinal data indicate the persistence of mental health struggles across semesters. Overall, these studies show factors that contributed to mental health challenges among college students as the pandemic continued.
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Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce.While researchers and practitioners have developed data systems to track detailed occupational skills, such as those established by the U.S. Department of Labor (DOL), much less effort has been made to document which of these skills are being developed in higher education at a similar granularity.Here, we fill this gap by presenting Course-Skill Atlas -- a longitudinal dataset of skills inferred from over three million course syllabi taught at nearly three thousand U.S. higher education institutions. To construct Course-Skill Atlas, we apply natural language processing to quantify the alignment between course syllabi and detailed workplace activities (DWAs) used by the DOL to describe occupations. We then aggregate these alignment scores to create skill profiles for institutions and academic majors. Our dataset offers a large-scale representation of college education's role in preparing students for the labor market.Overall, Course-Skill Atlas can enable new research on the source of skills in the context of workforce development and provide actionable insights for shaping the future of higher education to meet evolving labor demands, especially in the face of new technologies.
This dataset contains yearly certified enrollment for all public school districts (with physical boundaries) in Wisconsin for the 2023-2024 school year. This data is also available in the WISEdash Public Portal. This dataset is derived from publicly available files on the WISEdash Download Page. Enrollment Count is the number of students enrolled on specific dates as determined by school enrollment/exit dates that cover those dates. Percent Enrollment by Student Group is a percent of the enrollment count for all student groups combined. Reporting Disability is indicated in the pupil’s individualized education program (IEP) or individualized service plan (ISP). A person's race or ethnicity is the racial and/or ethnic group to which the person belongs or with which he or she most identifies. Ethnicity is self-reported as either Hispanic/Not Hispanic. Race is self-reported as any of the following 5 categories: Asian, American Indian or Alaskan Native, Black or African American, Native Hawaiian or other Pacific Islander, or White. The data displayed reflects the race/ethnicity that is reported by school districts to DPI.An economically disadvantaged student is one who is identified by Direct Certification (only if participating in the National School Lunch Program) OR a member of a household that meets the income eligibility guidelines for free or reduced-price meals (less than or equal to 185 percent of Federal Poverty Guidelines) under the National School Lunch Program (NSLP) OR identified by an alternate mechanism, such as the alternate household income form.English Learner status is any student whose first language, or whose parents' or guardians' first language, is not English and whose level of English proficiency requires specially designed instruction, either in English or in the first language or both, in order for the student to fully benefit from classroom instruction and to be successful in attaining the state's high academic standards expected of all students at their grade level.A child is eligible for the Migrant Education Program (MEP) (and thereby eligible to receive MEP services) if the child: meets the definition of “migratory child” in section 1309(3) of the ESEA,[1] and is an “eligible child” as the term is used in section 1115(c)(1)(A) of the ESEA and 34 C.F.R. § 200.103; and has the basis for the State’s determination that the child is a “migratory child” properly recorded on the national Certificate of Eligibility (COE). Eligibility determination is made by a Wisconsin state migrant recruiter during a face-to-face family interview.
https://en.wikipedia.org/wiki/Public_domainhttps://en.wikipedia.org/wiki/Public_domain
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.
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This layer serves as the authoritative geographic data source for California's K-12 public school locations during the 2023-24 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 2023 to coincide with the official 2023-24 student enrollment counts collected on Fall Census Day in 2023 (first Wednesday in October). This layer also excludes nonpublic nonsectarian schools and district office schools.
The CDE's California School Directory provides 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 & Statistics web 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.
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The Colleges and Universities feature class/shapefile is composed of all Post Secondary Education facilities as defined by the Integrated Post Secondary Education System (IPEDS, http://nces.ed.gov/ipeds/), National Center for Education Statistics (NCES, https://nces.ed.gov/), US Department of Education for the 2018-2019 school year. Included are Doctoral/Research Universities, Masters Colleges and Universities, Baccalaureate Colleges, Associates Colleges, Theological seminaries, Medical Schools and other health care professions, Schools of engineering and technology, business and management, art, music, design, Law schools, Teachers colleges, Tribal colleges, and other specialized institutions. Overall, this data layer covers all 50 states, as well as Puerto Rico and other assorted U.S. territories. This feature class contains all MEDS/MEDS+ as approved by the National Geospatial-Intelligence Agency (NGA) Homeland Security Infrastructure Program (HSIP) Team. Complete field and attribute information is available in the ”Entities and Attributes” metadata section. Geographical coverage is depicted in the thumbnail above and detailed in the "Place Keyword" section of the metadata. This feature class does not have a relationship class but is related to Supplemental Colleges. Colleges and Universities that are not included in the NCES IPEDS data are added to the Supplemental Colleges feature class when found. This release includes the addition of 175 new records, the removal of 468 no longer reported by NCES, and modifications to the spatial location and/or attribution of 6682 records.