This map answers the question "What is the most common, or predominant, education level for people in this area?" The map shows predominant educational attainment in each census tract. Darker colors indicate a greater gap between the predominant group and the next largest group.The U.S. Census Bureau asks citizens to indicate how far they went in formal education. The database includes seven different columns, each representing a count of population by that education level. A simple routine in compares the seven columns of information, and finds which one has the highest value, writing that to a string field. Each tract's transparency is set by a transparency field added to the data.Predominance maps can be created in ArcGIS Online by adding two fields, calculating their values, and setting up the renderer based on those two fields. See this blog by Jim Herries for details on how to create a predominance map in ArcGIS Online from any feature layer.See this GitHub repo by Jennifer Bell for a script you can run in ArcMap as a script tool, to calculate predominance for any columns of data you have.

This web map displays the California Department of Education's (CDE) core set of geographic data layers. This content represents the authoritative source for all statewide public school site locations and school district service areas boundaries for the 2018-19 academic year. The map also includes school and district layers enriched with student demographic and performance information from the California Department of Education's data collections. These data elements add meaningful statistical and descriptive information that can be visualized and analyzed on a map and used to advance education research or inform decision making.

This map shows the schools, school districts, and Board of Education districts in Carteret County, North Carolina. The coordinate system for this data is NAD 1983 State Plane North Carolina FIPS 3200 Feet. School districts are decided by the Board of Education and Board of Education districts are decided by the Board of Commissioners. All data was digitized by the Carteret County Information Technology Department- GIS Division.

SDOT's Safe Routes to Schools - School Flashing Beacons MapWebsite: https://www.seattle.gov/transportation/srtsAt bottom - 'How Can SRTS help you?' (Expand 'Learn and Go' options)Direct Website:https://www.seattle.gov/transportation/projects-and-programs/safety-first/safe-routes-to-school/flashing-beacons-and-map

Finding Schools is now easier than ever with the College Map, the first geographic search tool published by IPEDS (Integrated Postsecondary Education Data System) providing access to over 7,000 certificate, undergraduate and graduate-level schools. This all-in-one tool enables students, parents and counselors to filter potential programs for location, major, tuition and more. Including both certificate-level programs and advanced degrees, this public application makes the often overwhelming process of school searching simple, and it’s available on mobile devices.Once the results are narrowed down, users can share their lists on social media or download in excel format. Additionally, the College Map integrates with the College Navigator, a research based search tool providing data from the complete list of IPEDS Survey indicators.

Financial overview and grant giving statistics of Map Education Inc.

Digital Map Of Education
This dataset falls under the category Traffic Generating Parameters Workplaces.
It contains the following data: Location of Public Schools in the City of Rio de Janeiro
This dataset was scouted on 2022-02-15 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://arcg.is/fy5LC0See URL for data access and license information.

This map shows schools, school districts, and population density throughout the US. Click on the map to learn more about the school districts and schools within an area. A few things you can learn within this map:How many public/private schools fall within the district?What type of population density lives within this district? Socioeconomic factors about the Census Tracts which fall within the district:School enrollment of under 19 by grade Children living below the poverty level Children with no internet at home Children without a working parentRace/ethnicity breakdown of the population within the districtFor more information about the data sources:Socioeconomic factors:The American Community Survey (ACS) helps us understand the population in the US. This app uses the 5-year estimates, and the data is updated annually when the U.S. Census Bureau releases the newest estimates. For detailed metadata, visit the links in the bullet points above. Current School Districts layer: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 single-purpose 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 NCES EDGE program collaborates with the U.S. Census Bureau’s Education Demographic, Geographic, and Economic Statistics (EDGE) Branch to develop the composite school district files. The inputs for this data layer were developed from Census TIGER/Line and represent the most current boundaries available. For more information about NCES school district boundary data, see https://nces.ed.gov/programs/edge/Geographic/DistrictBoundaries.Private Schools layer: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.Public Schools layer: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.WorldPop Populated Foorprint layer:This layer represents an estimate of the footprint of human settlement in 2020. It is intended as a fast-drawing cartographic layer to augment base maps and to focus a map reader's attention on the location of human population. This layer is not intended for analysis.This layer was derived from the 2020 slice of the WorldPop Population Density 2000-2020 100m and 1km layers. WorldPop modeled this population footprint based on imagery datasets and population data from national statistical organizations and the United Nations. Zooming in to very large scales will often show discrepancies between reality and this or any model. Like all data sources imagery and population counts are subject to many types of error, thus this gridded footprint contains errors of omission and commission. The imagery base maps available in ArcGIS Online were not used in WorldPop's model. Imagery only informs the model of characteristics that indicate a potential for settlement, and cannot intrinsically indicate whether any or how many people live in a building.

Browse the different maps showcased in the "Midwifery Education Around the World" map, namely: midwifery education institutions by country, national curriculum, direct entry programs, post-nursing programs, and masters and doctorate degrees. Map driving the Education Story Map, located here: https://directrelief.maps.arcgis.com/home/item.html?id=c89deca4b5b642e1bd35140267427a67Data focused on the education of midwives globally was collected for the 2021 State of the World's Midwifery Report by the International Confederation of Midwives, with support by Direct Relief, and can be accessed and downloaded in the Open Data Portal of the Global Midwives' Hub. Data collected on the state of midwifery leadership throughout the world for the 2021 State of the World's Midwifery Report. The data was collected via a survey that was sent to midwives' associations, who filled it out for their country and shared it with their Ministry of Health for validation. Data was collected by the International Confederation of Midwives with the support of UNFPA, WHO, and Direct Relief. This data visualization is just one of the many data products on the Global Midwives Hub, a digital resource with open data, maps, and mapping applications (among other things), to support advocacy for improved maternal and newborn services.

This map service contains boundaries for the following types of public school districts:Local School - administered by a city or town school committee.Regional Academic - administered by a regional school committee.Regional Vocational Technical - administered by a regional vocational school committee.Independent Vocational and County Agricultural - administered by a board of trustees.Independent Public, including Commonwealth Charter Schools and Horace Mann Charter SchoolsDistrict information as of December 2, 2014, was obtained from the Massachusetts Department of Elementary and Secondary Education (ESE).For full metadata see https://www.mass.gov/info-details/massgis-data-public-school-districtsMap service also available.

This dataset contains the official listing of all public educational organizations in Connecticut as of April 25, 2014. Data elements include name, organization type, organization code, address, open date, interdistrict magnet status and grades offered.

Included data are collected by the CT State Department of Education (CSDE) through the Directory Manager (DM) portal in accordance with Connecticut General Statute (C.G.S.) 10-4. This critical information is used by other data collection systems and for state and federal reporting.

For more information regarding DM, please visit http://www.csde.state.ct.us/public/directorymanager/default.asp

In 1968, Sonja Peterson conducted a study that included all students from grade 1 to grade 9 in Arvika, Sweden. That study was named: Vad vet grundskoleeleven om kartan? [What does the primary school student know about the map?] and was published in 1971 in the report series: Rapporter från Pedagogiska institutionen i Göteborg [Reports from the Department of Education in Gothenburg]. As a part of the doctoral studies Pontus Hennerdal conducted at Stockholm University, he recreated parts of the test Peterson used in her study. Together with some new questions, Hennerdals study was also carried out with students in Arvika during 2013. This time with students from grade 2 to year 9. This archive consists of answers from the 1206 completed questionnaires that were filled in during the spring term 2013 during Hennerdals Arvika study. Also the archive include some comparisons with the data Peterson collected 45 years earlier.

During the spring term of 2013, tests(see attached files) were distributed to all classes (grade 2 to 9) in Arvika, Sweden. All grades did not have all test sheets. The teachers conducted the test with each class based on the instruction:

The intention is that the questions should be self-instructing, that the only thing the students need in addition to the questions is a pen and an eraser, and that the answers to the questions should be received during an hour. But the study is not ruined by helping students to understand question they find unclear (explain the question, not the concept), let them use draft paper and their own ruler, or let someone draw a little over the time if the teacher finds it possible.

Public colleges welcome students living in their recruitment sector as a matter of priority. This area is determined by the student’s place of residence. It is therefore neither the primary school attended nor the place of professional practice of the parents that determine the sector college(s). It is the departmental council that defines the “public college school map”, i.e. the recruitment sectors of the various public colleges of the department, specifying in which public college(s) are to be educated students who live in a particular area of the department. When this promotes social diversity, the departmental council may decide that the same recruitment sector is shared by several public colleges (in this case we refer to as “multi-college sector”). Reference: Education Code, Article L213-1 (‘https://www.legifrance.gouv.fr/codes/article_lc/LEGIARTI000031104883’) The school card is taken into account by DASEN in preparing the assignment of students using the Affelnet 6e . In order to automate the reconciliation between the address of the pupils and their sector college(s), DASEN may import a school card file into Affelnet 6e, provided that this file has been previously transmitted by the departmental council in a harmonised format, defined at national level. The published dataset results from the national aggregation of departmental files used by DASEN to automatically determine the student sector college(s). For 2023, this dataset covers 90 departments (out of a total of 101), indeed: — on the one hand, 10 departments have not yet integrated their school map data into the Affelnet 6e application (Charente-Maritime, Côtes-d’Armor, Corse-du-Sud, Finistère, Guadeloupe, Haute-Corse, Haute-Marne, Martinique, Mayotte and Morbihan). However, municipalities in those departments are included in the dataset on the ground that they are covered by the sector of a college located in a neighbouring department and which has a school card file; — on the other hand, in the department of Gironde, although a school card was imported into Affelnet 6e, the automatic determination feature of the sector college was not used. Therefore, since this departmental file might not have the degree of reliability expected, it was chosen not to integrate it into the dataset.

This Public Schools feature dataset is composed of all Public elementary and secondary education in the United States as defined by the Common Core of Data, National Center for Education Statistics, US Department of Education. This includes all Kindergarten through 12th grade schools as tracked by the Common Core of Data. Included in this dataset are the military schools abroad and referenced in the city field with an APO or FPO address. Also referenced in the state field with the abbreviation AE. Please note that the APO and FPO schoolpoints are located at 0,0. This feature class contains all MEDS/MEDS+ as approved by NGA. For each field the 'Not Avaliable' and 'NULL' designations are used to indicate that the data for the particular record and field is currently unavaliable and will be populated when and if that data becomes avaliable.

Public schools give priority to students living in their recruitment sector. This sector is determined by the pupil’s place of residence. It is therefore neither the primary school attended nor the place where the parents work that determines the sector establishment(s). It is the departmental council that defines the ‘school map of public colleges’, i.e. the recruitment sectors of the various public colleges in the department, specifying in which public college(s) students who live in a given area of the department must be enrolled. Where this promotes social diversity, the departmental council may decide that the same recruitment sector is shared by several public colleges (in this case, the ‘multi-college sector’). The Regional Council shall draw up the provisional investment programme for high schools and special education establishments; it defines their location, their reception capacity and the way in which pupils are accommodated. Student recruitment districts are defined jointly by the academic authority and the regional council, taking into account the criteria of demographic, economic and social balance and ensuring social diversity. However, in case of disagreement, the delimitation of districts is decided by the academic authority. Reference https://www.education.gouv.fr/le-role-des-collectivites-territoriales-dans-le-service-public-de-l-education-8138 The published dataset results from the aggregation, at the level of the academic region, of the 13 departmental files used by the DSDENs to automatically determine the sector college(s) and high school(s) of pupils.

The map of the sectorisation of the public colleges of Hauts-de-Seine allows you to quickly know the sector college associated with a section of road.

In the Versailles Academy, the Yvelines Department and the Val d’Oise Department benefit from a comprehensive mapping solution for managing and consulting the school sectorisation of colleges. This solution, aimed at families and partners, makes it possible to disseminate very widely reliable and accessible information on the sectorisation of colleges, competence of the Departments.

For the Directorate of Education, Citizenship and Colleges (DECC), the challenge of this project was to propose a similar scheme on Hauts-de-Seine within the framework of the Unified Directorate and thus replace the current solution with a complete mapping application. A finer geographical data based on the wireline of roads/streets, a real management mesh of school sectorisation, has been created to visualise and manipulate the data as closely as possible.

The Department’s school sectorisation solution is based on two separate modules:

• A school sector management module for in-house DECC;
• A module to consult the school map of colleges for the general public.

On the basis of the official sectorisation data provided by the DECC (stopped) and the wireline of streets from the IGN topographic database (BD Topo), the SIG and Open data teams, have made the sections of streets reliable in order to assign to each of them its connecting college. They then set up a management web mapping application based on the Department’s GIS solutions. Through it, the DECC can reliable the data and refine the school map according to the evolution of the territory: new college, new neighborhood, evolution of the student population, etc.

The interactive map for the general public exploits all the data thus reliable and refined. This school map of the public colleges of Hauts-de-Seine allows families to quickly and simply know the college of attachment of their children.

Special observations

The map is provided as an indication and only the deliberation voted by the Conseil Départemental des Hauts-de-Seine is enforceable. The information presented relates to the school year 2022-2023. The school map is updated each year according to the evolution of the sectorisations of the colleges.

Related links

Link to the general public web application of the school map School map of public colleges

Related data

Link to College Dataset Public and Private Colleges

In 2001, the proportion of the population (individuals aged 15 and older) with non-university post-secondary credentials had more than doubled since 1971 to 36%. This, added to the 15% with university qualifications, meant that more than one-half (51%) of all Canadians aged 15 and over had post-secondary qualifications in 2001.

This Private Schools feature dataset is composed of all Private elementary and secondary education features in the United States as defined by the Private School Universe Survey (PSS), National Center for Education Statistics, US Department of Education. This includes all Kindergarten through 12th grade schools as tracked by the PSS. This feature class contains all MEDS/MEDS+ attributes as approved by NGA. For each field the 'Not Available' and NULL designations are used to indicate that the data for the particular record and field is currently unavailable and will be populated when and if that data becomes available.

IDA Grants for education projects (managed by Education Sector Board) from FY2002 going forward.

This interactive map uses indicators that shows how certain socioeconomic factors can influence early educational outcomes. Indicators are grouped by category, either pertaining to children, communities, families, or services, and are mapped by county for the entire state. The map uses the Weave interactive platform, which allows the user to select data variables and customize related data visualizations (charts/graphs).