Thinking Spatially Using GIS

Thinking Spatially Using GIS is a 1:1 set of instructional materials for students that use ArcGIS Online to teach basic geography concepts found in upper elementary school and above.
Each module has both a teacher and student file.

Tornado Alley is an area of the United States that has more tornadoes than any other place on earth. Many people argue about which states are in Tornado Alley. In this lesson, you will learn how to find this area for yourself! By the time you finish this lesson, you will be able to list the states that have the most frequent tornadoes, the strongest tornadoes, and the greatest concentration of tornadoes. From your list, you will be able to identify states that are in Tornado Alley.

Tornadoes are associated with certain weather patterns, and these patterns change with the seasons. In this lesson, you will learn which regions of the United States have tornadoes at different times of the year — winter, spring, summer, and fall.

The Thinking Spatially Using GIS home is at: http://esriurl.com/TSG

All Esri GeoInquiries can be found at: http://www.esri.com/geoinquiries

The education data displayed in this theme of the Florida’s Roadmap to Living Healthy are measures utilized by the Florida Department of Education and the U.S. Department of Education to quantify educational opportunities and accountability in Florida. School grades provide an easily understandable way to measure the performance of a school. Parents and the general public can use the school grade and its components to understand how well each school is serving its students. In addition to school grades, this themed map includes Career/Technical Education Statistics, Graduation Rates, School District Grades, School Improvement Ratings, the 300 Lowest Performing Elementary Schools, Persistently Low Performing Schools, Head Start Centers, Title I Part A Program Recipients, and other education-related topics. This unique breakdown of education data can be used to better identify the specific educational needs of individual communities in Florida in relation to other social determinants that may be indicative or correlated to academic achievement and attainment.

Thinking Spatially Using GIS

Thinking Spatially Using GIS is a 1:1 set of instructional materials for students that use ArcGIS Online to teach basic geography concepts found in upper elementary school and above.
Each module has both a teacher and student file.

The zoo in your community is so popular and successful that it has decided to expand. After careful research, zookeepers have decided to add an exotic animal to the zoo population. They are holding a contest for visitors to guess what the new animal will be. You will use skills you have learned in classification and analysis to find what part of the world the new animal is from and then identify it.

To help you get started, the zoo has provided a list of possible animals. A list of clues will help you choose the correct answers. You will combine information you have in multiple layers of maps to find your answer.

The Thinking Spatially Using GIS home is at: http://esriurl.com/TSG

All Esri GeoInquiries can be found at: http://www.esri.com/geoinquiries

Thinking Spatially Using GIS

Thinking Spatially Using GIS is a 1:1 set of instructional materials for students that use ArcGIS Online to teach basic geography concepts found in upper elementary school and above.
Each module has both a teacher and student file.

Animals are a big part of our life. Animals fascinate us, whether they live with us as pets or roam wild places on our planet. One exciting way to connect with animals from beyond our back yard is to visit the zoo. Zoological parks, or zoos, are a great way to bring people closer to animals. It is a chance for people to more deeply appreciate and understand how animals live and what they are like.

Zoos have been around for a long time. Queen Hatshepsut of Egypt had one about 3,500 years ago, and the Chinese emperor Wen Wang created a large zoo named the Garden of Intelligence about 3,000 years ago. Many leaders used zoos to show power and wealth. Zoos became popular starting about 500 years ago in the 1500s, when European explorers brought animals from the New World (the Americas) back to Europe.

The Thinking Spatially Using GIS home is at: http://esriurl.com/TSG

All Esri GeoInquiries can be found at: http://www.esri.com/geoinquiries

The California School Campus Database (CSCD) is now available for all public schools and colleges/universities in California.CSCD is a GIS data set that contains detailed outlines of the lands used by public schools for educational purposes. It includes campus boundaries of schools with kindergarten through 12th grade instruction, as well as colleges, universities, and public community colleges. Each is accurately mapped at the assessor parcel level. CSCD is the first statewide database of this information and is available for use without restriction.PURPOSEWhile data is available from the California Department of Education (CDE) at a point level, the data is simplified and often inaccurate.CSCD defines the entire school campus of all public schools to allow spatial analysis, including the full extent of lands used for public education in California. CSCD is suitable for a wide range of planning, assessment, analysis, and display purposes.The lands in CSCD are defined by the parcels owned, rented, leased, or used by a public California school district for the primary purpose of educating youth. CSCD provides vetted polygons representing each public school in the state.Data is also provided for community colleges and university lands as of the 2018 release.CSCD is suitable for a wide range of planning, assessment, analysis, and display purposes. It should not be used as the basis for official regulatory, legal, or other such governmental actions unless reviewed by the user and deemed appropriate for their use. See the user manual for more information.Link to California School Campus Database.

In this tutorial, you will be introduced to the basics of the ArcGIS Online Web-based Geographic Information System (GIS) software tool. You will begin by exploring spatial data in the form of map layers that are available on the Web as well as map applications (apps). You will then use the ArcGIS Online Map Viewer to search for content, add features to a map, and save and share your completed map with others.

This dataset attempts to represent the point locations of every educational program in the state of Minnesota that is currently operational and reporting to the Minnesota Department of Education. It can be used to identify schools, various individual school programs, school districts (by office location), colleges, and libraries, among other programs. Please note that not all school programs are statutorily required to report, and many types of programs can be reported at any time of the year, so this dataset is by nature an incomplete snapshot in time.

Maintenance of these locations are a result of an ongoing project to identify current school program locations where Food and Nutrition Services Office (FNS) programs are utilized. The FNS Office is in the Minnesota Department of Education (MDE). GIS staff at MDE maintain the dataset using school program and physical addresses provided by local education authorities (LEAs) for an MDE database called "MDE ORG". MDE GIS staff track weekly changes to program locations, along with comprehensive reviews each summer. All records have been reviewed for accuracy or edited at least once since January 1, 2020.

Note that there may remain errors due to the number of program locations and inconsistency in reporting from LEAs and other organizations. In particular, some organization types (such as colleges and treatment programs) are not subject to annual reporting requirements, so some records included in this file may in fact be inactive or inaccurately located.

Note that multiple programs may occur at the same location and are represented as separate records. For example, a junior and a senior high school may be in the same building, but each has a separate record in the data layer. Users leverage the "CLASS" and "ORGTYPE" attributes to filter and sort records according to their needs. In general, records at the same physical address will be located at the same coordinates.

This data is now available in CSV format. For that format only, OBJECTID and Shape columns are removed, and the Shape column is replaced by Latitude and Longitude columns.

This map layer is a subset of the Columbus Points of Interest layer and shows education facilities in the City of Columbus. Daycares, elementary, middle, and high schools, colleges and universities, vocational schools, and other educational entities are included. This layer is maintained through a cooperative effort by multiple departments of the City of Columbus using first-hand knowledge of the area as well as a variety of authoritative data sources. While significant effort is made to ensure the data is as accurate and comprehensive as possible, some points of interest may be excluded and included points may not be immediately updated as change occurs.

School Boundaries data built from parcel database, extracted parcels based on overlay with gschools.shp. Verified site by site to add or delete based on changes since gschools created. FIELDSNAME - School NameSHORT_NAME - Short school name_DISTRICT - School District nameSTATUS - School statusADDRESS - Street number, name, and typeCITY - City nameZIP - ZipcodeMOD_DATE - Date record modified. gschools from http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?id=5681&pid=5673&topicname=United_States_Geographic_Names_Information_System_Schools

THE GIS DATA IS PROVIDED "AS IS". THE COUNTY MAKES NO WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION, ANY IMPLIED WARRANTIES OR MERCHANTABILITY AND/OR FITNESS FOR A PARTICULAR PURPOSE, REGARDING THE ACCURACY, COMPLETENESS, VALUE, QUALITY, VALIDITY, MERCHANTABILITY, SUITABILITY, AND CONDITION, OF THE GIS DATA. USER'S OF COUNTY'S GIS DATA ARE HEREBY NOTIFIED THAT CURRENT PUBLIC PRIMARY INFORMATION SOURCES SHOULD BE CONSULTED FOR VERIFICATION OF THE DATA AND INFORMATION CONTAINED HEREIN. SINCE THE GIS DATA IS DYNAMIC, IT WILL BY ITS NATURE BE INCONSISTENT WITH THE OFFICIAL COUNTY DATA. ANY USE OF COUNTY'S GIS DATA WITHOUT CONSULTING OFFICIAL PUBLIC RECORDS FOR VERIFICATION IS DONE EXCLUSIVELY AT THE RISK OF THE PARTY MAKING SUCH USE.

In successful geoinformatics education, students’ active role in the learning process, e.g. through applying self-assessment, show an increasing interest but the evidence of benefits and challenges of self-assessment are sporadic. In this article, we examine the usefulness of an online self-assessment tool developed for geoinformatics education. We gathered data in two Finnish universities on five courses (n = 11–73 students/course) between 2019 and 2021. We examined 1) how the students’ self-assessed knowledge and understanding in geoinformatics subject topics changed during a course, 2) how the competencies at the end of a course changed between the years in different courses, and 3) what was the perceived usefulness of the self-assessment approach among the students. The results indicate support for the implementation of self-assessment, both as a formative and summative assessment. However, it is crucial to ensure that the students understand the contents of the self-assessment subject topics. To increase students’ motivation to take a self-assessment, it is crucial that the teacher actively highlights how it supports their studying and learning. As the teachers of the examined courses, we discuss the benefits and challenges of the self-assessment approach and the applied tool for the future development of geoinformatics education.

Instructions for students to use aerial photos, Google Earth and QGIS to explore their fieldwork area prior to their field trip. This material was designed for first-year undergraduate Earth Sciences students, in preparation to a fieldwork in the French Alps. The fieldwork and this guide focuses on understanding the geology and geomorphology.The accompanying dataset.zip contains required gis-data, which are a DEM (SRTM) and Satellite images (Landsat). This dataset is without a topographic map (SCAN25 from IGN) due to licence constraint. For academic use, request your own licence from IGN (ign.fr) directly.

The Unpublished Digital Geologic-GIS Map of the Cave Creek School Quadrangle, Texas is composed of GIS data layers and GIS tables in a 10.1 file geodatabase (ccsc_geology.gdb), a 10.1 ArcMap (.mxd) map document (ccsc_geology.mxd), individual 10.1 layer (.lyr) files for each GIS data layer, an ancillary map information document (lyjo_geology.pdf) which contains source map unit descriptions, as well as other source map text, figures and tables, metadata in FGDC text (.txt) and FAQ (.pdf) formats, and a GIS readme file (lyjo_geology_gis_readme.pdf). Please read the lyjo_geology_gis_readme.pdf for information pertaining to the proper extraction of the file geodatabase and other map files. To request GIS data in ESRI 10.1 shapefile format contact Stephanie O'Meara (stephanie.omeara@colostate.edu; see contact information below). Presently, a GRI Google Earth KMZ/KML product doesn't exist for this map. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Texas Bureau of Economic Geology, University of Texas at Austin. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (ccsc_geology_metadata.txt or ccsc_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: http://science.nature.nps.gov/im/inventory/geology/GeologyGISDataModel.cfm). The GIS data projection is NAD83, UTM Zone 14N. The data is within the area of interest of Lyndon B. Johnson National Historical Park.

OpenStreetMap exports for use in GIS applications.

This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :

tags['amenity'] IN ('kindergarten', 'school', 'college', 'university') OR tags['building'] IN ('kindergarten', 'school', 'college', 'university')

Features may have these attributes:

• name
• name:en
• amenity
• building
• operator:type
• capacity:persons
• addr:full
• addr:city
• source
• name:id

This dataset is one of many "https://data.humdata.org/organization/hot">OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

This layer serves as the authoritative geographic data source for all school district area boundaries in California. School districts are single purpose governmental units that operate schools and provide public educational services to residents within geographically defined areas. Agencies considered school districts that do not use geographically defined service areas to determine enrollment are excluded from this data set. In order to view districts represented as point locations, please see the "California School District Offices" layer. The school districts in this layer are enriched with additional district-level attribute 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.School districts are categorized as either elementary (primary), high (secondary) or unified based on the general grade range of the schools operated by the district. Elementary school districts provide education to the lower grade/age levels and the high school districts provide education to the upper grade/age levels while unified school districts provide education to all grade/age levels in their service areas. Boundaries for the elementary, high and unified school district layers are combined into a single file. The resulting composite layer includes areas of overlapping boundaries since elementary and high school districts each serve a different grade range of students within the same territory. The 'DistrictType' field can be used to filter and display districts separately by type.Boundary lines are maintained by the California Department of Education (CDE) and are effective in the 2023-24 academic year . The CDE works collaboratively with the US Census Bureau to update and maintain boundary information as part of the federal School District Review Program (SDRP). The Census Bureau uses these school district boundaries to develop annual estimates of children in poverty to help the U.S. Department of Education determine the annual allocation of Title I funding to states and school districts. The National Center for Education Statistics (NCES) also uses the school district boundaries to develop a broad collection of district-level demographic estimates from the Census Bureau’s American Community Survey (ACS).The school district enrollment and demographic information are based on student enrollment counts collected on Fall Census Day (first Wednesday in October) in the 2023-24 academic year. These data elements 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 https://www.cde.ca.gov/ds.

Open-Source GIS plays a pivotal role in advancing GIS education, fostering research collaboration, and supporting global sustainability by enabling the sharing of data, models, and knowledge. However, the integration of big data, deep learning methods, and artificial intelligence deep learning in geospatial research presents significant challenges for GIS education. These include increasing software learning costs, higher computational power demand, and the management of fragmented information in the Web 2.0 context. Addressing these challenges while integrating emerging GIS innovations and restructuring GIS knowledge systems is crucial for the evolution of GIS Education 3.0. This study introduces a Visual Programming-based Geospatial Cyberinfrastructure (V-GCI) framework, integrated with the replicable and reproducible (R&R) framework, to enhance GIS function compatibility, learning scalability, and web GIS application interoperability. Through a case study on spatial accessibility using the generalized two-step floating catchment area method (G2SFCA), this paper demonstrates how V-GCI can reshape the GIS knowledge tree and its potential to enhance replicability and reproducibility within open-source GIS Education 3.0.

Abstract

The Master List of Schools is a record of all schools in South Africa. The data forms part of the national Education Management Information Systems (EMIS) database used to inform education policymakers and managers in the Department of Basic Education (DBE) and the Provincial education departments, as well as to provide valuable information to external stakeholders. The list is maintained by provincial departments and regularly sent to DBE for updating. A key function of the master list is to uniquely identify each school in the country through a school identifier called the EMIS number. Additionally, the list contains data on school quintiles - categories (quintiles) based on the socioeconomic status of the community in which the school is situated. Analyses comparing schools' performance often use school quintiles as control measures for socioeconomic status, to take into account the effect of, for example, poor infrastructure, shortage of materials and deprived home backgrounds on school performance. There are also other basic data fields in the school master list that could provide the means to answer some of the most frequently asked questions about learner enrolment, teachers and learner-teacher ratio of schools. It is a useful dataset for education planners and researchers and is even widely used in the private sector by those who regularly deal with schools.

Geographic coverage

The data has national coverage

Analysis unit

Individuals and institutions

Universe

The survey covers all schools (ordinary and special needs) in South Africa, both public and independent.

Kind of data

Administrative records and survey data

Mode of data collection

Other

Research instrument

Data from the SNAP survey and ANA that are used to compile the Master List of Schools is collected with a survey questionnaire and educator forms. The principle completes the survey questionnaire and each educator (both state paid and other) in each school completes an educator form. Schools record their EMIS number provided by the DBE on the questionnaire and form for identification.

Data appraisal

The 2023 series only includes data for quarter 2 and quarter 3. The GIS coordinates for schools in the Eastern Cape are incorrectly entered in the original data from the DBE. The data entered in the GIS_long variable is incorrectly entered into the GIS_lat variable. This issue only occurs for schools in the Eastern Cape (EC), all other GIS coordinates for all the other provinces is correct. Therefore, for geospatial analysis, users can swap the GIS coordiate data only for the Eastern Cape.

Do you need help in learning how to include GIS into your classroom activities? IowaView has developed a helpful guide for K-12 educators to learn what tools are available and how to integrate them into the classroom. Some of the geography content in this guide is specific to Iowa but the tools and resources are useful for anyone involved in K-12 education.

School Districts data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain three area geographic files of boundaries for elementary school districts, secondary school districts, and unifed school districts, each with associated Census and American Community Survey demographic data.

This polygon files contains 2015-2016 school-year data delineating school attendance boundaries. These data were collected and processed as part of the School Attendance Boundary Survey (SABS) project which was funded by NCES to create geography delineating school attendance boundaries. Original source information that was used to create these boundary files were collected were collected over a web-based self-reporting system, through e-mail, and mailed paper maps. The web application provided instructions and assistance to users via a user guide, a frequently asked questions document, and instructional videos. Boundaries supplied outside of the online reporting system typically fell into one of six categories: a digital geographic file, such as a shapefile or KML file; digital image files, such as jpegs and pdfs; narrative descriptions; an interactive web map; Excel or pdf address lists; and paper maps. 2015 TIGER/line features (that consist of streets, hydrography, railways, etc.) were used to digitize school attendance boundaries and was the primary source of information used to digitize analog information. This practice works well as most school attendance boundaries align with streets, railways, water bodies and similar line features included in the 2015 TIGER/line "edges" files. In those few cases in which a portion of a school attendance boundary serves both sides of a street contractor staff used Esri’s Imagery base map to estimate the property lines of parcels. The data digitized from analog maps and verbal descriptions do not conform to cadastral data (and many of the original GIS files created by school districts do not conform with cadastral or parcel data).The SABS 2015-2016 file uses the WGS 1984 Web Mercator Auxiliary Sphere coordinate system.Additional information about SABS can be found on the EDGE website.The SABS dataset is intended for research purposes only and reflects a single snapshot in time. School boundaries frequently change from year to year. To verify legal descriptions of boundaries, users must contact the school district directly.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.

Table from the American Community Survey (ACS) 5-year series on education enrollment and attainment related topics for City of Seattle Council Districts, Comprehensive Plan Growth Areas and Community Reporting Areas. Table includes B14007/B14002 School Enrollment, B15003 Educational Attainment. Data is pulled from block group tables for the most recent ACS vintage and summarized to the neighborhoods based on block group assignment.Table created for and used in the Neighborhood Profiles application.Vintages: 2023ACS Table(s): B14007, B15003, B14002Data downloaded from: Census Bureau's Explore Census Data The United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:</di