This code was broken for a while, the .png-generation portion is still too repetitive. The code takes questionnaire results and provides a faceted (R ggplot2-like) view with an .html page that list questions with a visualization of their results for the individual, the individual's department(faculty), and the department's(faculty's) university.
Experience with Racket's path utilities over the past weeks (and today's discovery that regexp-replace works with paths!) helped to clean up the part that filters plot images.
Other work demands attention and time, but it's awful to leave code in a broken state.
If it wasn't for SJIS (or some sort of MS Windows Encoding Page) troubles, this script would probably be useful and reliable. I'm fudging the possible encoding issues by, using “key” and “value” as backups when assoc doesn't find what it should in an associative list (alist, als). Playing with Scheme/Racket gives you the confidence to deal with any problem, if some detail isn't working, just throw in an if or cond statement, and maybe the results will help you figure out where the trouble is. DrRacket is great for showing where errors are, it even produces bright red lines that trace the errors for you...
There is a pattern, where I develop the script to generate useful pages to process one data file and then adapt it to handle several files in a directory. After the script seems to work for one data file, I get all the define definitions used to transform data (not those used to make functions) from the original file, and put those definitions into a let* expression (or clause) within a procedure that is used with for-each to go through a list of data files. Some definitions remain global, but all the definitions that rely on the data file go into a let* clause.
This code is re-working of earlier code (fn:1) that, from one .csv data file generated three files: a racket data file, a browser page to print roll sheets, and a browser page to print a seating chart. To get code that will generate three useful files (a rkt data file, a roll sheet, and a seating chart) for each .csv data file in a directory, I just had to see what belongs in a let* clause of the function that is mapped (with for-each for the side-effects and the list-generation) over a list of file paths.
A typo(bug) that disturbed my flow made me appreciate first and second in place of car and cadr. I had build-path errors that confused me for a while. when I moved the define cls-als (class associative list: alist: als) into the let* clause, I forgot the a in cadr. In place of a one-key one-value associative list, I ended up with, not a string, but a long list as the value. Without the string, I could build paths for file-generation. I imagine using first and second could make it easier to spot a mistake like that. But cddr is probably still useful instead of (rest (rest ....
There is another bug, where the first seat is taken up by the keys for associative list, or what could be viewed as column headers in a table of data. If there is time I'll see where in the chart-generation process to intervene, and get rid of the header intrusion. But the bug could be a feature, it can be nice to have an open table at the front of the room for returning papers, for set-up. With the Graded Direct Method teachers haul a lot of “realia” into the classroom, and tend to need tables and seats for demonstrations...
The code needs editing, but I like this view of questionnaire data where “factor” responses of 1 and 2 are negative, 3 is seemingly neutral, and 4 and 5 are positive. It seems possible to see things with this view that might not be possible with an average/mean of the responses.
The visualization needs to be on a page with the full text for the questions, the symbols for the numbered responses, the tables for the data, and an attempt to explain the visualization.
While using questionnaire data to learn plotting, questions come to mind. Averages don't make sense for “ranked” “factors”, for numbered responses to questions about how much a person agrees or disagrees with a question. Maybe seeing the percentage and number of positive responses versus negative responses will help in the search for meaning in the data.
With Racket it is possible to transform and view the data however you like. It's nice to be able to implement a view out of curiosity. I'm hoping the stacked lines with their labels provide enough hints for people to figure out that they are combinations of responses of 4 and 5 in a positive direction, and 1 and 2 in a negative direction.
If there is time to go over the code again there must be less repetitive way to stack negative lines after stacking positive lines. Getting started on that gave me a change to use Racket's define to give the pnt-w-lbl procedure an optional argument.
Years ago with gnuplot I plotted “enthused”熱意 results against “satisified”満足 responses. Naomi Klein quoted a Harpers article by a professor that said he refused to be “cool” like a Marshall McLuhan screen.
For now though, I just want to see how Racket can replace two pages oddly scaled visualizations and averages. It's time to move into other work, after adjusting the css styles so that the generated page fits onto two A4 papers.
Here's proof that the code pasted in below worked in DrRacket:
Developing faculties for designing programs and visualization with Faculty Development Questionnaires. In the spirit of “Nothing about us without us”, ideally, students would design the questionnaires. We would view the data with Racket's help, and get started thinking about what sort of classes, what sort of universities, we need.
It was good to get that feeling that capacities/abilities/powers were growing while doing this. Racket's documentation, DrRacket, and Emacs are great for self-directed exploratory learning. With enough time to become the equivalent of a “native speaker” in Racket, developing a Graded Direct Method for learning the language could be one way of developing “effectively capable people”(I.A. Richards).
This sort of visualization may let me replace bar charts. The panel or facet approach to interleaved discrete histograms might be good for on-screen browsing, but this sort of plot might be easier on the printer and ink supply.
Discussion in Diaspora* post comments provides motivation to explore more code and presentation. (fn:1~
Now I have to see about getting these separate images aligned into one eye-span for analytical viewing.
I was feeling overwhelmed while try to label the bars in interleaved, discrete histogram plots of percentages. So I went back to the basics: lines and points.
There is probably a straightforward way to montage a series of plots together, but I haven't found it yet. Maybe series of this sort of plot panel for different results can be helpful if grouped and aligned on an .html page and seen in a browser.
DrRacket is great for checking code developed with Emacs geiser-mode. After pasting the text from and Emacs buffer and clicking the “Run” button, DrRacket reminds me of all the definitions from previous scripts and REPL experiments that never made it into the file.
This code is still clumsy, the process isn't clear enough in my mind for elegant solutions. But working through the process is great for learning. This may be a way to re-discover the faceting that R/ggplot2 makes possible. I think this is the best way to get a feel for how an individual teachers results are situated in relation to the groups: the individual's department and school.
Racket plot and scribble/html with stacked-histograms and output-xml are working well. It was fun to play with plot keywords and think about printing the data visualizations, but for quick comparisons in the browser the defaults seem better.
I imagine DrRacket will make the code below work with a Windows computer too. How would Windows users be able to find their home directory, Racket's (current-directory) and get their bowser to show “/FD201801/FD-Anketo-Results.html”... The file-separator slashes are probably different too. But that sort of detail can be overcome when a Windows user shows an interest in testing the code and visualization...
It was good training to work with associative lists, to use two a-lists to generate a new a-list. Using a-lists allows for the generation of useful titles and file names that match the data used for the visualization.
Faculty Development Questionnaires give me an opportunity to work with Racket. Until now the questionnaire data provided opportunities to learn data visualization with two other languages: gnuplot with Philip Janert's book, and R/ggplot2 with Hadley Wickham's book. But for more regular work I was using emacs-lisp with org-mode. Without weekly practice with language like gnuplot or R/ggplot2, it was always a struggle to get back into the data manipulation and visualization flow once every six months. Recently my regular work goes well with Scheme.(fn:1) Guile Scheme is more compact that org-mode and emacs-lisp for converting jpg images to png and svg images and for generating worksheets, roll-sheets, and seating charts. However, I am not yet able to graph/plot/chart with Guile. Racket's plot lets me work well with Questionnaire data.
It will be interesting to learn how to plot and label points at will, and how to adjust colors, but in the meantime racket/plot's stacked-histograms provide compact visualizations that may serve as springboards for discussion. I made the English version, to make it easier for non-Japanese readers to follow the code. Seeing two versions clearly shows the advantages of Chinese characters for compact information design.
There are eleven questions on the school's questionnaire. The first three questions attempt to gauge students feelings their participation in the class. What are their feelings about how often they `attended`出席 the class, how much they `spoke` in the class, and how much they `engaged` in the class. The next five questions gauge the students perceptions of how well they `heard` the teacher's voice, how they had `seen` the teacher's materials, how well `timed` the teacher's starting and ending of the classwas, how `responsive` the teacher was, as well as how `enthused` the teacher may have been. The last three questions are about overall perceptions of how much the student `comprehended` and `valued` the class, ending with a overall ranking of how `satisfied` the student is with the classes experienced so far. The questionnaires are usually filled out during the 13th or 14th class a 15-class semester.
