Final Project: United States SAT Map

Introduction

At present, in the United States there are two major college preparedness exams: the Scholastic Aptitude Test (SAT) and the American College Testing (ACT) exam.  Both of these standardized exams are traditionally taken by graduating high school students and are utilized by colleges to assess these prospective students in terms of mathematics, reading comprehension, and critical thinking.  The SAT, for which scores range from 600-2400, is published by the non-profit organization College Board and administered by the Educational Testing Service (College Board, 2014).  The ACT, ranging from 1-36, is developed by American College Testing, Inc. and was created in 1959 to be a competitor to the then-dominant SAT (erikthered.com, 2014).  In 2005, the ACT for the first time administered more tests than the SAT (ACT, 2014).  The SAT, however, is still widely used in the United States today and there may be state-by-state patterns of implementation of and performance on this exam by graduating high school students.

It is the goal of this project to generate a map that depicts two phenomena: 1) the percentage of graduating high school students in each state to take the SAT in 2013, including the District of Columbia, and 2) the mean SAT score of these students for each state.  This map will be visually inspected for any spatial patterns existing therein.

Methods

Both ArcMap (version 10.2) and Adobe Illustrator (version CS5.1) will be used to generate a United States map depicting SAT participation and performance.  The map will clearly show all states and the District of Columbia with appropriate labels.  The map will have an orientation baring (north arrow) and scale.  The two phenomena depicted will be easily discerned by the audience using an imbedded legend.  ArcMap will be used to first compile all the data and create a rough map.  Adobe Illustrator will be used to further visually enhance the map and tidy up the layout.

ArcMap

In ArcMap, a United States layer (from “Module 7: Choropleth Mapping”) will be added to a blank template.  Using the editor tool, I will add a new column to the attribute table for ‘Percent Participation’.  This field, which is the percentage of graduating high school students for each state that completed the SAT in 2013, will be entered using data provided by College Board and the Western Interstate Commission for Higher Education (WICHE).  A graduated color scheme symbology with manual breaks will be used to display this data – light states will have low percentage participation, dark with high.  Then, in layout mode, a legend, north arrow, and scale will be added to this map.  This file will then be exported to Adobe Illustrator (.ai) for further manipulation.

Adobe Illustrator

This program will be used to add a proportional (graduate) symbol scheme depicting the 2013 average SAT score per state of graduating high school students.  An Excel spreadsheet of the data from College Board and WICHE will be created for easy re-sorting, as well as calculation of sizes for proportional symbols.  These symbols will be simple solid red circles with a 60% transparency setting placed over the state label.

Results

State participation ranged from 2% to 100%, and state mean SAT scores ranged from 1200 to 1838.  States with lower participation rates had higher mean SAT scores than stares with high participation.

Discussion

The (presumably significant) negative correlation between participation rate and state mean SAT score suggests that mean SAT score may be a misleading representation of the average graduate student’s aptitude in a particular state.  While it appears that the Midwest states outperform the northeast and northwest states, this may not be actually true.  For example, only the ‘best and brightest’ may take the SAT in these states, while in states like Maine and Idaho all students take it, thus lowering the average.  Therefore, comparisons between states may not be valid.

The between state differences in participation itself, however, is worth speculation.  The spatial pattern of SAT participation may be a result of tradition.  For example, the universities in coastal states may preferentially request SAT scores to ACT scores and thus there are more students who complete them.  Alternatively, these coastal states may have higher graduation rates and more students who wish to continue on to college.  Regardless of the reasons, there is a real discrepancy between geographic location (e.g. inland vs. coastal) and SAT participation rate that is visually obvious in the map generated.

Week 12: Google Earth

This weeks assignment was to generate a map using Google Earth.  This required first using the Map to KML tool in ArcMap, then loading this newly created file in Google Earth.  Google Earth is an open-source GIS in which users can create and easily share maps.  Here, Google Earth was used to re-create a map that was produced in a previous lab, then use the Tour function to highlight certain points of interest. The points of interest were major areas of high population density (i.e. Cities).  I chose to use my own Data Layer from the Dot Mapping Lab.

The Tour function in Google Earth may be useful during presentations in which the speaker is presenting spatial data, or explaining spatial patterns.  The audience would be able to easily visualize the landscape.  Another useful aspect of Google Earth is the ability to share maps over the internet.  Sharing ArcGIS (.mxd) files is often a difficult, or at least time-consuming, process.  Other users are required to have the layer or FGDB files for the map to be editable in a meaningful way.  In Google Earth, editable files can be shared or even edited simultaneously, thus providing ease of use between multiple users.  However, Google Earth is limited in its spatial analysis abilities.

Module 12: Georeferenceing & ArcScene

This weeks assignment involved georeferencing an input raster layer with a vector layer providing control points.  This process is very useful and may be one of the most applied tools in ArcMap.  Selecting several control points, will allow for a more accurate georeference.  This map ultimately required a second order polynomial transformation to achieve high accuracy.  Displayed is the location of an eagle nest with two buffers.

The second part of this weeks assignment was to build and generate a 3-D map in ArcScene.

Module 11: Dot Mapping

This weeks assignment was to create a dot map representing the population distribution in South Florida.  To accomplish this, we were required to create a map in which eat dot represented a specified number of persons and to have that dot be placed at a reasonable location (i.e. one that suggests population density).

A dot map is used to display spatial phenomena in such a way that the end user can confidently determine areas of high and low density occurrence.  In the map above, it is obvious that Miami and Tampa have high population density and that central Florida has low density.  The key to placing the dots is the existence of a layer 'hidden' in the final map; this layer was a polygon of urban areas.  The dots, which represented the population of the entire county, were then only placed within these urban areas to better show the true population distribution.

Module 11: Network Analysis & Geocoding

Network analysis is the process of evaluating the interconnectedness of a system of edges and junctions.  It can be used to solve complex problems involving optimal routes or feature placement.  This week we matched addresses to a network in Lake City and mapped an emergency vehicle route in Lake County, FL (see above).  The map shows all the EMS locations in the county with one route highlighted.  By using a network analysis, this optimal route was determined following realistic traffic laws and mileage.  This is one situation in which network analysis can be applied.

Participation Assignment #2

See the Group 7: Defense and Intelligence Online Map.

I contributed the Brisbane, Queensland, Australia Flood Common Operation Picture (COP) map.  Due to an extreme flood event in Brisbane in January 2011, there was a need for current, accurate information about potential flood zones and refuge areas.  The plan for creating this was similar to that of a COP for the purposes of defense.  The COP was used by government agencies and citizens to efficiently evacuate or help in any emergency response and clean-up.