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Setting Objectives & Specifications of Required Data |
  
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Setting Objectives & Specifications of Required Data |
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Setting the objectives is essential to knowing what data, software, and methodologies are required. As the process of analyzing K-12 education multi-dimensional, specific objectives can be elusive. However, there are set of data that comprise a minimal structure and an additional set of data that are typically required. The following lists are focused on the geographic objects of analysis (students, schools, etc.). The scope of subject matter for each is reviewed in more detail in subsequent sections.
Minimum Data – Level 1
Students. Test score, SES/demographic, locational, school/grade, unique student id, and related data for each student. Reference to locational data means the latitude-longitude of the student residence.
Schools (campus/building). Similar to the student data, school/building locational, name and id, and related attributes are needed for each school.
School districts. To visually depict student and school attributes, the school district boundary is required. Normally this will be a set of school districts in a region or more typically the state. Depending on the scope of analysis, summary test score and demographics might be included for each district. Minimally the school district name and codes are required. The decennial census School District Special Tabulation data are available only at the school district and county geographic levels.
Counties. Counties also need to be a part of the analysis. In many states, school district boundaries cross county boundaries. County data minimally include county boundary, name, and codes.
Places. In most cases, the places also need to be a part of the analysis. Place data minimally include place boundary, name, and codes. Places are incorporated places or census designated places and are geographic areas of population concentration whose boundaries may transcend school district and county boundaries.
Towns/County Subdivisons. For many states, particularly New York, towns need to be a part of the analysis. Town data minimally include town boundary, name, and codes. Towns are administrative subdivisions of counties, covering each county wall-to-wall, are independent of population size or concentration, and whose boundaries may transcend school district and place boundaries.
Urban Areas. In most cases, geography designated as urban area, urban areas, need to be a part of the analysis. Urban areas (UA) minimally include the UA boundary, name, and code. Urban areas are defined by the Census Bureau as contiguous census blocks that meet population size and concentration specifications. UA boundaries are independent of all other boundaries except census block.
Streets. The best quality street centerline shapefiles available are essential.
Recommended Additional Data – Level 2
Census Blocks. Census blocks, averaging 100 population, are the smallest geographic areas for which Census 2000 data are tabulated. Only complete count data (short form questionnaire) data are available for blocks. See http://proximityone.com/dp2000et.htm for a recommended set of subject matter. Census blocks are essential for the developing attendance area demographics. Census blocks do not cross school district boundaries.
Census Block Groups. Census block groups (BGs), averaging 1,000 population, are the smallest geographic areas for which Census 2000 “richer demographics” (sample based data from long form questionnaire) are tabulated. Using this level of geography permits a view of more detailed neighborhood characteristics within the district for items such as income, educational attainment, employment characteristics, housing value, etc. Generally, the DP1-DP4 demographic profile data are available and the most useful subject matter for analyses using BG geography. A significant limitation of BGs is that they will typically span school district boundaries and attendance areas.
Census Tracts. Census tracts, contiguous block groups, averaging 4,000 population, are important for several reasons. The geographic definition of the area is intended to be stable from census to census enabling longitudinal analysis. Decennial sample based data are generally more reliable for census tracts as compared to BGs. Developed in coordination with local agencies, census tracts are intended to reflect neighborhoods although this does not apply to areas changing rapidly. Population estimates and projections can also be reliably developed for census tracts provided underlying vital statistics data are available.
Tax Parcels. Tax parcels are becoming increasingly available in shapefile structures with attributes that enable analysis of land use within the school district. As tax parcel files are more widely developed, student locations can be directly associated with tax parcel. In the future, tax parcels will provide a superior basis/means of assessing alternative attendance area configurations. These files are typically developed by individual county governments.
Attendance Areas. Attendance areas (AAs) are associated with individual schools. The boundary of the attendance area encompasses all housing units assigned to a specific school. Attendance area shapefiles often do not exist for a school district. AAs must be developed for the school district. By viewing the attendance areas, in combination with block group demographics, and student SES data, it often becomes clear that schools thought to be neighborhood schools really are not.
Recommended Additional Data – Level 3
Landmark Areas (such as colleges, large government facilities, recreational areas, etc.).
Water Areas (such as lakes and larger bodies of water).
Rivers and streams.
Rail and other Non-Street Transportation Features.
Voter Registration Data.
Voting Precinct Boundaries.
Page url: http://proximityone.com/sddmi/guide/index.htm?af_reqdata.htm