Category Archives: Institutional Research

IPEDS data in Access

I just learned that IPEDS data is now available in an Access file format. I plan on looking at this data more over the next few weeks since it appears that it contains all data rather than needing to locate and download various subsets to get what you need. It appears there is a single file for separate years (2011-), but I’m thinking I have a way of combining the files that shouldn’t be too difficult. I’ll know more once I have a chance to examine things in more detail. Here’s a link to where the data is available:

http://nces.ed.gov/ipeds/Section/accessdatabase/

THECB Data in a (more) Usable Format

If you’ve read through some of my previous posts, you know that I tend to use Accountability data from THECB for several of the things I try in Tableau. One challenge has always been the way data is formatted by the Accountability system. It outputs data with one row per institution and separate columns for each measure and year. And of course, sub-levels of each variable are part of the measure names. Needless to say this format doesn’t work very well when trying to use the data in Tableau, or pretty much any program.

My early way of dealing with this was to simply pivot the columns into rows. This created a somewhat usable version of the data with fields for institution, year, name of the measure, and the value. Of course this came with it’s own set of problems. It was possible to compare various institutions on the same measure, but it never worked as well as I would like. Also, it was easy to accidentally include values from multiple measures in an analysis because all values were stored in the same field and you had to use filters to narrow things down to the specific values you were after.

Over Spring Break (week before last), I decided to sit down with my Excel macro and try a new approach to reformatting the data. Long story short, I was able to create a format for the Accountability data that, so far, has been significantly more user-friendly. I’ll be making use of this reformatted data in some of the Tableau examples I’ll be posting over the next couple of weeks. For those that might find it useful here’s the Excel file:

Reformatted Accountability Data (~45 MB)

Now, I should mention that this data is just for public universities and not all institutions in the state. I haven’t spent a lot of time verifying all of the data, so if you need “official” data, you should probably use the Accountability System, or at the very least double check the values you get from this spreadsheet against it. The first few columns include the name of the institution, FICE code, period/year, category, and sub-category. After that are the primary measures from each area of the Accountability system. If time permits, I might get around to providing better documentation for it, but hopefully it’ll make sense to you if you’ve used the Accountability system before.

US lags behind other countries in education (nothing new here)

An interesting read about the state of higher education in America. In a nut shell, having a degree in higher ed does give you more skills (ie higher reading and numerical literacy), but as a country we still fall behind other countries. Honestly, the finding that the US is behind other countries in terms of education is nothing new. The reason this study is getting attention is that it actually shows that education does actually teach people some useful skills. Sadly, up until now, this has largely been a belief without much empirical evidence behind it, especially on a global scale. So, although it is something that most people will look at and go “no surprise there”, it is useful to have the data to back up the claim.

What’s not mentioned in the article, but included in the report itself, is that we also fall behind in those skills at the High School level. To me this raises an interesting question given the debate over providing “free” college to everyone at either the 2 or 4 year level. My thought is that rather than everyone needing the college degree what we really need is to be doing a better job at teaching these skills in the K-12 arena. Let me be clear that I do not fault teachers for this problem. There are many issues that go into the quality of a K-12 education that are to a large degree beyond the control of teachers, and unfortunately that control often ends up in the hands of politicians. Having national standards is an attempt to raise the standard across all schools, but unfortunately those standards are often seen as a goal to reach rather than a minimum to maintain. If things were really working as they should in education the fear over whether a school is able to reach that minimum level of skills on some arbitrary standardized test would be a non-issue. Reaching the minimum should be a given. If it were, we could then focus on raising the bar for our students. But again, there are several other factors that come into play, so I’ll leave that discussion for another post.

Americans with bachelor degrees lag behind other nations in labor skills
http://www.pbs.org/newshour/rundown/americans-with-bachelor-degrees-lag-behind-other-nations-in-labor-skills/

Showing Change with a Scatterplot in Tableau

Recently the VizWiz blog had a post showing how to create a 45-degree reference/trend line in a scatterplot. The original purpose was comparing countries based on literacy rates for females and males. Those above the line were countries where females had higher literacy rates and below were countries where males had the higher literacy rate. From there the post went on to talk about change in a couple of other datasets. But, there was an issue in producing the correct color coding to represent the change from year to year in those other datasets. This got me thinking that I wanted to see if I could figure out why the color coding of change wasn’t working as expected in those examples. (NOTE: Description of how to get the 45-degree line and fix the issue he encountered are at the end of this post.) Of course, trying to tie things to higher education, I decided to use my standby of accountability data from the Texas Higher Education Coordinating Board (THECB) which I’ve used previously.
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Likelihood of graduating as a criteria for admittance

Although I haven’t seen it phrased that way before, colleges do admit students they feel will be the most successsful. The better they are at making that prediction, the higher their retention and graduation rates will be. The question then is whether you want to use retention and graduation rates as criteria for judging a school since it encourages schools to be more selective rather than more inclusive. What would be nice is a measure of how successful a school is with students they expect to fail. This is why sub-group analysis is important.

Graduation Rates by Selectivity: Freshmen, 2007 http://highereddatastories.blogspot.com/2016/02/graduation-rates-by-selectivity.html

(And yes, this is a post from the blog I posted about a few weeks ago.)

THECB Accountability Comparisons

As I mentioned in a previous post, I spend a fair amount of time working with data in the Accountability System produced by the Texas Higher Education Coordinating Board (THECB). One of the things I always found missing in this tool is a way to compare one institution to another or to a set of other institutions. For example, at Texas State we often compare ourselves to the other emerging research universities (ERUs) in the state. Although the accountability system allows us to pull the data on the institutions, we then have to reformat the data and make comparisons manually. So, in an attempt to simplify this process I put together the following Tableau visualization of the data. It doesn’t include all of the measures from the accountability system (being able to download all the data is another of its limitations), but I did include many of the variables that are commonly used with a focus on undergraduates.
Continue reading THECB Accountability Comparisons

Institutional Research Tools in Tableau

After a year of playing around and developing things in Tableau, we have finally been approved to release the new tools we’ve developed at work. Of course, by “we” I really mean “me”. To be fair, other people in the office have been responsible for gathering most of the data up to this point, and a few offered comments and suggestions on layout and colors. Still, it feels like I’ve been the lead on getting these tools developed in Tableau up to this point.

One thing I should mention is that Tableau is really designed as a way to visualize data (hence the term data visualization). In these cases we are actually using it as a tool to develop an interface to university data. The goal with many of these tools, especially the University Enrollment Explorer, is to allow people to find the information they are after, and at the same time provide ways of drilling down to answer additional questions once they have that information at hand. So far Tableau has proven to be very useful for doing this and considerably more user friendly than the pivot tables in MS Excel that we were using. One nice feature is that with Tableau you can export the data behind the tables, graphs, charts, etc. to create a pivot table if someone wants to do more with the data than the visualization allows. Anyway, here’s a link to the “Self-Service Tools” on our website.

IR Self-Service Tools

I should also mention that we’ve moved our “Facts and Highlights” into Tableau as well. It doesn’t allow for the interactivity provided by the other tools, but it’s more convenient than creating all the graphs and charts in Excel or Powerpoint like we were doing. That section of our website can be found here:

Texas State University Facts and Highlights

UPDATE 3/10/2016 – Coming soon there will be a link from the “Facts and Highlights” pages which will take you to the appropriate self-service tool in case you want to drill down and explore the data further. Well, most of them will have the link since we don’t have tools that deal with everything.

Higher Ed Data Stories

Rather than posting another tip and trick about using Tableau, I decided that this week I would take a moment to acknowledge one of the sites that I try to visit on at least a semi-regular basis. The site in question is:

Higher Ed Data Stories

As the name suggests, this blog tells stories about Higher Education using data. Although I don’t always agree with some of the conclusions when the leap is made from the data to underlying causes or meanings, I do find the site useful and informative. He is also a big user of Tableau (which is actually how I found the site). I encourage you to go check it out.

 

University Demographics in Texas

One of the many things I find myself doing at work is looking at enrollment trends at colleges and universities in Texas. Most of this data is pulled from the Accountability System produced by the Texas Higher Education Coordinating Board. Anyone has used that system knows that it isn’t the most user-friendly tool. So, one of the first things I did with Tableau was put together a visualization looking at demographic characteristics of students in the state over the past several years. It’s pretty basic, but it does show a picture of how things have changed as enrollment has increased. By default it shows total enrollment at all colleges and universities, but you do have the option of drilling down to an individual institution. The visualization appears after the break…
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