{"id":686,"date":"2011-11-22T18:43:31","date_gmt":"2011-11-22T18:43:31","guid":{"rendered":"https:\/\/blogs.swarthmore.edu\/institutional-research\/?p=686"},"modified":"2023-09-13T15:41:15","modified_gmt":"2023-09-13T15:41:15","slug":"visualizing-survey-results-class-discussion-by-class-year","status":"publish","type":"post","link":"https:\/\/blogs.swarthmore.edu\/institutional-research\/?p=686","title":{"rendered":"Visualizing Survey Results: Class Discussion by Class Year"},"content":{"rendered":"

Jason Bryer<\/a>, a fellow IR-er at Excelsior College has a nice post (link<\/a>) about techniques for visualizing Likert-type items – those “Strongly disagree…Strongly agree” items only found on surveys. \u00a0He has even been developing an R software package called irutils<\/a> that bundles these visualization functions together with some other tools sure to be handy for anyone working with higher ed data.<\/p>\n

Jason’s post reminded me that I have been meaning to try out a “fluctuation plot<\/a>” to visualize some recent survey results. \u00a0A fluctuation plot, despite the flashy name, simply creates a representation of tabular data where rectangles are drawn proportional to the sizes of the cells of the table. \u00a0The plot below has responses to a question about how often students here participate in class discussion along the left side and class year along the bottom. \u00a0The idea behind this is to have a quick and very intuitive way to visualize how this item differs (or doesn’t differ) by class year. \u00a0In this case, it looks like fewer of our sophomores (as a percentage) report participating in class discussion “very often” than their counterparts. \u00a0This may suggest a need for further research. \u00a0For example, are there differences in the kinds of courses (seminar vs. lecture) taken by sophomores?<\/p>\n

\"\"<\/a><\/p>\n

Creating the plot<\/strong><\/p>\n

The plot itself requires only one line of code in R. \u00a0If you are not a syntax person, I recommend massaging the data as much as possible in a spreadsheet first. \u00a0You can take advantage of a default setting in R where text strings are converted to “factors<\/a>” automatically. \u00a0This default functionality usually annoys the daylights out of R programmers, but in this case, it is actually exactly what you want.<\/p>\n

All you need to do is set up your data like this:<\/p>\n

\"\"<\/a>Then you can save the file as a .csv and import it into R using my preferred method – the lazy method:<\/p>\n

mydata<-read.csv(file.choose())<\/span><\/p>\n

Nesting file.choose()<\/span> inside of the read.csv()<\/span> function brings up a GUI file chooser and you can just select your .csv file that way without having to fiddle with pathnames.<\/p>\n

Once you’ve done this, you just need to load (or install then load<\/a>) the ggplot2<\/a> package and you can plot away like this:<\/p>\n

ggfluctuation(table(mydata$Response, mydata$Year))<\/span><\/p>\n

You can add a title, axis labels, and get rid of the ugly default legend by adding some options:<\/p>\n

ggfluctuation(table(mydata$Response, mydata$Year)) + opts(title=”Participated in class discussion”, \u00a0legend.position=”none”) + xlab(“Class year”) + ylab(“”)<\/span><\/p>\n

Once you’ve done that, you’ll have just enough time left to prepare yourself for the holiday cycle of overeating-napping in front of the TV-overeating some more. \u00a0My family will be having our traditional feast of turkey AND lasagna. \u00a0If your life so far has been deprived of this combination, I suggest seeking out someone of Southern Italian heritage and inviting yourself over for dinner. \u00a0But be warned – you may be required to listen to Mario Lanza records during the meal.<\/p>\n

Happy Thanksgiving!<\/em><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Jason Bryer, a fellow IR-er at Excelsior College has a nice post (link) about techniques for visualizing Likert-type items – those “Strongly disagree…Strongly agree” items only found on surveys. \u00a0He has even been developing an R software package called irutils that bundles these visualization functions together with some other tools sure to be handy for … Continue reading Visualizing Survey Results: Class Discussion by Class Year<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=\/wp\/v2\/posts\/686"}],"collection":[{"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=686"}],"version-history":[{"count":41,"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=\/wp\/v2\/posts\/686\/revisions"}],"predecessor-version":[{"id":1568,"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=\/wp\/v2\/posts\/686\/revisions\/1568"}],"wp:attachment":[{"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=686"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=686"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.swarthmore.edu\/institutional-research\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=686"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}