My question is both conceptual and technical, but more conceptual than technical. It's a little long and multi-pronged, but I figured the best answers would consider everything, so thanks for bearing with me. I list specific questions later.
Right now I'm research the concept of "academic mismatch" in undergraduate education, or when students attend colleges where their academic background is substantially different than the typical student (e.g., a "little fish in a big pond:" a student with low grades/scores compared to his peers, or a "big fish in a little pond:" a student with high grades/scores compared to her peers). While I'm on solid footing with outcomes analysis (do mismatched students do better/worse in school?), I want to explore the mechanisms of attending a school as a mismatch in the first place. There are a lot of reasons for this, some obvious and well explored (preferential admissions policies), others less obvious and less well explored (where I hope to contribute).
One question I want to explore, and many others (including my dissertation advisor) have found interesting, pertains to where students live and their likelihood of mismatching. The basic hypothesis is that when a student has fewer colleges to choose from within his "local college market," the more likely he is to attend a college that is less selective than he could because it's convenient. Likewise, for non-selective schools, students sometimes attend less academically appropriate colleges because they can get in, even if they're outmatched by their typical peers. There's some evidence out there in local contexts (e.g., Chicago), but very little in a national context, and almost none in rural contexts (which I/we find most fascinating).
This is the basic question I want to answer:
Does the concentration of "good-fit" colleges that are geographically near to a student associate with that students likelihood of attending a college where her academic background matches her peers?
So from this, I need to do the following:
- Create a measure of the concentration of good fit colleges. I have methods for deciding if a college is a good fit between student and college, but assessing concentration is more challenging.
- Test whether this measure is associated with students "mismatch status"
- Create maps demonstrating patterns found
Here are my questions:
- My intuition for concentration is to simply count the colleges that are a good fit within a specific distance (or a market defined by a shapefile) for each student and do appropriate analysis. What better ideas do you have?
- Are there geospatial statistical tests that are better than my plan (logistic regression analysis with outcome being match/not match, independent variable being the measure of college concentration?
- Software wise, should I bite the bullet and learn ArcGIS? I have experience as a web developer so my intuition is to run to web-based software, but I'm not sure where to start. My problem seems like it could be solved without ArcGIS, and if I can learn software I can use in web development, all the better.
As background, I have the following data:
- A student's home zip code and a number of variables on their academic background (high school gpa, SAT, etc.)
- A data file of all accredited colleges and their academic profiles (which I can assign geo-coordinates)
Everyone is in the USA.
I have time to learn, but am in proposal-writing stage, so insights in that regard are especially helpful.
As background, I have basically zero experience with GIS, but very good statistical analysis, computer programming skills, and data manipulation skills (for a social science researcher). Put another way, I'm comfortable with research design and Stata, R, Python, MySQL, but have never done anything with GIS (besides some web analytics using geolocation with IPs).