A visualization of Canvas course engagements

Visualization of content access
Analyzing the Access Report in Excel
Visualization using R (optional)

We sometimes get questions from faculty concerning course content access, such as

Did students tend to download or preview course files?
Did students click on the Files tab to get course files?
How often did my students check their submissions for comments?
How often did my students check their grades?

In this exercise, we will practice obtaining the Access Report data for an entire course, using the Excel Pivot Table to analyze the data, and answering the questions listed above.

You may also build a chord diagram to present student content access data in R. The sample R code is included in the exercise.

First, please install the Access Report Data userscript on your computer that is used to obtain the Access Report data for all students in a course. You may following the instructions below for a quick install, or refer to the detailed documentation if needed.

Quick Installation of the Access Report Data userscript (Please skip step 1 and 2 if you have already installed the userscript)

Install a browser add-on: Greasemonkey (Links to an external site.) for Firefox or Tampermonkey (Links to an external site.) for Chrome/Safari
Install the Access Report Data (Links to an external site.) userscript.
Login into Canvas, go to a course, navigate to the People page, Click on the 'Get User Page Views' tab, and click on 'Start' to begin data extracting process.

You may use the Excel Pivot Chart tool to analyze the data and generate graphs that make most sense to you.

Faculty and instructional designers can analyze the data from a content design perspective. For instance, if a Canvas course site contains five sections, you can use the access report data to find out what course navigation links that students accessed most. In this example shown in the video, Section 5 had the most students. Section 1 had the least number of students, but had the most clicks on the Modules links.

The technique shared in the video uses Excel pivot table to analyze the data. The following fields of the Access Report were used in the example:

User ID is the Canvas User ID.
Category includes the content the user has viewed.
Class includes classification for each Category. If the student clicked on course navigation menu, a 'null' value is emitted.
Views is the number of times the student viewed the content.
Code is a unique identifier for each piece of content.
Section Name is the name of the section the student is enrolled in.

Quick Installation of the Access Report Data userscript (Please skip 1 and 2 if you have already installed the userscript)

Install a browser add-on: Greasemonkey (Links to an external site.) for Firefox or Tampermonkey (Links to an external site.) for Chrome/Safari
Install the Access Report Data (Links to an external site.) userscript.
Login into Canvas, go to a course, navigate to the People page, Click on the 'Get User Page Views' tab, and click on 'Start' to begin data extracting process.

Please load your .csv file in the app below, and a visualization of content access will be created for you https://jing-zen-garden.shinyapps.io/CanvasAccess/:

After you have installed the user script and run it in a Canvas course, please download the Access Report data, and open the resulting CSV data file in Excel. Please use the Pivot Table tool in Excel to generate a matrix, which rows represent students/sections/groups and columns include the content being accessed (watch the video below for instructions). Copy and paste the matrix in a new sheet, and save the matrix sheet to a CSV file. To visualize the data in R, we loaded the matrix in R, and used the R circlize package to build a chord diagram that visualize student course navigation data. If you are new to R, you may watch the video to install RDownload and Install R and RStudio | R Tutorial 1.2 | MarinStatsLectures and refer to the documentation https://cran.r-project.org for questions.

If you are not able to obtain the Access Report data, you may use the sample matrix to practice drawing a chord diagram in R.

The R circlize package allows us to draw a chord diagram without much scripting. You will need to download and install circlize package in R.

install.packages(circlize) #install the circlize package
library(circlize) #open circlize

After you created a matrix using the Access Report data (or the example data) in Excel, and installed the “circlize” package in R, please follow the steps to generate a basic chord diagram:

To customize sector labels:

follow 1 to 5 steps described above
switch step 6 from ‘drawing a basic diagram’ to ‘drawing an empty track’: chordDiagram(mat,directional=1, order=order, grid.col=grid.col, direction.type=c(“diffHeight”,”arrows”),link.arr.type=”big.arrow”,annotationTrack=”grid”,preAllocateTracks=list(track.height=0.3))
go back to the first track and customize sector labels: circos.trackPlotRegion(track.index = 1, panel.fun =function(x, y) {
xlim =get.cell.meta.data(“xlim”)
ylim =get.cell.meta.data(“ylim”)
sector.name =get.cell.meta.data(“sector.index”)
circos.text(mean(xlim), ylim[1], sector.name, facing = “clockwise”, niceFacing = TRUE, adj =c(0, 0.5))
}, bg.border = NA)

A Chord Diagram is commonly used to represent relations between elements(https://cran.r-project.org/web/packages/circlize/vignettes/visualize_relations_by_chord_diagram.pdf). The data format used is a matrix. The S1 to S6 represent six groups of students, and the columns represent course content and features. The value denotes the number of clicks on a given course content by a group.

	announcement	assignments	discussions	file_previews	file_download	file_tab	gradebook	submissions	pages
S1	42	39	29	0	20	19	17	16	3
S2	80	74	60	40	28	24	22	21	5
S3	62	59	47	34	28	27	25	23	3
S4	50	46	34	0	27	25	23	22	3
S5	58	55	48	33	24	23	21	20	4
S6	67	63	50	0	36	26	23	22	8

The following chord diagram (graph 1) illustrates how much students are accessing different features in a Canvas course.

Resources:

http://jokergoo.github.io/circlize/
https://cran.r-project.org/web/packages/circlize/index.html – circlize package