Where in the World is Everyone? Part Two

Part Two: From Geographic Location to Neighborhood Profile

In Part One of this two part blog post I explained how to start with a list of street addresses and, using Google’s Fusion Tables function, map those locations onto an interactive Google Map. This tool alone can be very useful and powerful in the context of institutional research and administration. However, where spatial analysis becomes significantly more powerful is when you use these known locations to find out more information about the specific communities and neighborhoods of students and alumni. Through the use of spatial analysis software, these “point” locations can be tied directly to zip codes, census tracts, block groups, Congressional districts, etc. From there, geographic data from the Census Bureau’s American Community Survey or other sources can be used to understand a great deal about where the community and neighborhood profile of students and alumni. It’s only a proxy for the individual and we always need to be aware of the Ecological fallacy, but you can gain immense and detailed understanding of a group just by learning about their spatial location.

geo_2_image_7

The following is a guide for taking individual records (including street addresses), overlaying geographic boundaries (such as tracts, zip codes, etc.), joining (or combining) the individual records with their respective geographic descriptors (e.g. Student A lives in zip code 12345), and finally, joining/combining geography-based data from the US Census’ American Community Survey to those individual records (e.g. Student A lives in zip code 12345, which has a population of 3,500, a median household income of 65,000 dollars per year, and so on).

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Post-Swarthmore Educational Outcomes- SPSS syntax & template

Since we IR folks like to track things, I would ask that if you use this & find it helpful that you let me know- either by sending me a short email (pborkow1@swarthmore.edu) or commenting below.

**Note- this is example data- it is NOT actual Swarthmore Majors

fake Major A pic for Post Swat Edu blogfake Major B pic for Post Swat Edu blog

 

We were wondering about the post- Swarthmore educational outcomes of Swarthmore graduates.

  • What percentage of Swarthmore graduates go on to graduate school?
  • What degrees do they earn, and in what subjects?
  • How quickly do alumni enroll in graduate school?
  • How many have earned two additional degrees?
  • Do all of these enrollment/graduation patterns vary by graduation major at Swarthmore?

I utilized National Student Clearinghouse data, my SPSS syntax, and my excel template (listed below) to help answer these questions.

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Where in the World is Everyone? Part One

Part One: Making Use of Mapping in Institutional Research

A good visual can be a helpful tool considering that the job of an Institutional Researcher is to keep the attention of people who have many important things to do with their time and little time to spend wading through a lot of text and long explanations. Enter mapping and spatial analysis. Maps generally make for familiar, easy to read, and aesthetically pleasing images that grab viewers’ attention and, when carefully constructed, do a very good job of communicating information. They are nice to look at, but they can also tell us relevant and important about our institution. I elaborate on a specific technique in this post (Part One) and delve more deeply into the topic in a follow-up post (Part Two). In this post I illustrate a simple but effective technique for mapping point locations. In the following post (Part Two), I discuss some of the potential deeper applications for mapping and spatial analysis in Institutional Research.

Current_Student_Home_Addresses_Continental_US_2014-15

Continue reading Where in the World is Everyone? Part One

Video and SPSS Syntax: Progression & Completion Workaround

Roundabout detor” by Cubosh is is licensed under CC BY 2.0

Since we IR folks like to track things, I would ask that if you use this & find it helpful that you let me know- either by sending me a short email (pborkow1@swarthmore.edu) or commenting below (the link to comment is a bit hidden at the end of the tags, but it is there).

If you want to run the Progression & Completion syntax from the previous post, but have found that you don’t have records for EVERYONE in your cohort in the National Student Clearinghouse return file, you are going to need to incorporate your institutional enrollment/graduation data for your students through this workaround (when you submit a cohort file to the Clearinghouse for this project, you should be submitting a begin search date that would pick up the fall term for that cohort. Therefore, everyone in your cohort should have at least one record found).

These instructions & syntax use SPSS to create enrollment/graduation information from your school for your cohort that you can then use with the transfer school information from the Clearinghouse detail return file to determine Progression & Completion.

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Progression & Completion!

P&C blog pic

Since we IR folks like to track things, I would ask that if you use this & find it helpful that you let me know- either by sending me a short email (pborkow1@swarthmore.edu) or commenting below (the link to comment is a bit hidden at the end of the tags, but it is there).

This progression & completion SPSS syntax works to track enrollment/graduation at your school and other schools (including identifying concurrent enrollment) for a cohort or, if you split your file, for sub-cohorts as well .

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The Sport of IR

football game
theunforgettablebuzz.com

I was watching the NFL season-opening  game last night.   I’m not actually a football fan, but when your husband writes a book connected to football, it’s one of the sacrifices you make.  (I have also watched DOTA tournaments with my son, and thought it made about as much sense as professional football.   What can I say, I love my guys.)   I was struck by the between-play graphics of the players and their stats, and got to wondering (it wasn’t as if the game held my attention), what kinds of pictures and stats would be shown on a highlights reel of Institutional Researchers.  (You don’t know, it could happen.) Continue reading The Sport of IR

Video and SPSS Syntax: Deleting Select Cases Using the National Student Clearinghouse Individual Detail Return File

There may be some situations where you would want to delete select records from an individual return file. For example, you may have a project where you are looking at student enrollment after graduation or transfer, and it is decided that your particular project will only include records for which a student was enrolled for more than 30 days in a fall/spring term or more than 10 days in a summer term. Or, you may have six years of records for a particular cohort, but you only want to examine records for four years. In both of these cases, you would want to delete the records that don’t fit your criteria before analyzing your data.

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Video and SPSS Syntax: Admit/Not Enroll Project Using the National Student Clearinghouse Individual Detail Return File

Irish United Nations Veterans Association house and memorial garden (Arbour Hill)” by Infomatique is licensed under CC BY-SA 2.0

I use the National Student Clearinghouse individual detail return file and SPSS syntax in this video to capture the first school attended for students who were admitted to my institution, but who did not enroll (names listed are not real applicants). In a future video, I’ll work on the same project using the aggregate report. I almost always use the individual detail return file since it provides so much information, but it does have a limitation that impacts this project.

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Decisions, Decisions

I’ve been working with data from the National Student Clearinghouse (NSC) for a while now. A lot of wonderful information can be found in the NSC data, but the detailed return file can sometimes be a bit difficult. There are so many ways the data can be sliced, and it can sometimes be challenging to determine how best to work with the data to present meaningful information to stakeholders.

Continue reading Decisions, Decisions