I continue to develop and use the software I patched together to look at correlates (or covariates) within large scalar or ordinal data sets like surveys. I have gotten requests from several institutions in and out of higher ed to do these. A couple of interesting graphs that resulted are shown below, with permission of the owners of the data, who shall remain anonymous. Both of these are HERI surveys. I have found the HERI surveys the most revealing, partly because they discriminate so well between different dimensions. Some other surveys seem to produce (in the data sets I've seen) big globs of correlated items that are hard to get meaning from.
First the CIRP Freshman Survey at a private college. It neatly divides up the survey respondents into clusters. Rich urban kids negatively correlated to working class or middle class kids, athletes, the religious, and the environmentally-conscious all show up clearly. I've labeled the optional questions with an approximation of the prompt.[Download full-sized graph]
Your First Year College Survey at a different private college. I find the link between texting in class and recommending the school to others particularly interesting. That's at the bottom. Red lines are negative correlations.[Download full-sized graph]