Yesterday we introduced Education Sector’s new Higher Ed Data Central, a new analytical tool for higher education. We’ll be highlighting several of the capabilities of this new tool over the next few days, including ways to answer more common questions in higher education like “How much has tuition increased over the years?” to exploring under-examined data, and more.
Today we’ll look at custom groupings, which allow us to tailor our investigation as widely or narrowly as desired. For example, yesterday we examined tuition and the distribution of Pell grants. But suppose we were only interested in changes in tuition for California. Here we see California’s public universities have generally been successful at holding tuition increases low (and after accounting for inflation, even decreasing tuition – e.g. from 1993-1994 to 2002-2003), but that when they are not successful in doing so, they are spectacularly unsuccessful – so much so that average tuition and fees at public, four-year universities in California are now higher than the national average.
But states are only one of the many variables that can be used to create custom groupings. Just about any variable could be used—an off-the-wall example would be latitude. The charts below show the distribution of all colleges and universities by the percent of their students receiving Pell grants for those above and below the mean latitude of U.S. colleges.
What we see from these charts is that higher education south of the 38.91 parallel (which, in case you’re interested, cuts north and south of Kansas City) has many more institutions with very high percentages of Pell recipients than is the case north of the line. While that little factoid may or may not have any policy implications, the point of the example is that this tool can slice and dice the data to look at as narrowly tailored groupings of colleges as is desired.
Tomorrow, we will examine the third capability of Higher Ed Data Central; the investigation of Under-Examined Data.