 |  |  |  |  |
A quick recap of another great session from USU!
Introduction:
We can learn about our students by looking at data. We can improve our students' experiences by acting on that data.
Details:
As always, USU is doing amazing work and is very generous in sharing their processes and findings. With the help of an on-staff data scientist and a vendor, Canvas data from four courses was turned into beautiful, understandable visualizations. The data focused primarily on how students chose to navigate through their courses. We were able to see both an aggregate view and an individualized view of each student's path. The main takeaways are that 1) the initial visit to the course is exploratory and 2) assignments drive navigation thereafter. Knowing that a large percentage of students skip the home page in favor of navigating directly toward their To-Do list, we can made some conclusions about what should and shouldn't live on the home page. Some materials (the syllabus) weren't prioritized in initial course visits, indicating we should consider more prominent directives. Again, mobile data isn't factored in and we haven't heard feedback from students. The inclusion of these two points will lend more insight, but we're able to deduce quite a bit with what exists in the data now.
Conclusion:
We're making great strides in understanding the relationship between analytics and course design. There's still a lot of work to be done, and we'll need data scientists to help. What I'm hearing from everyone at this year's conference is that we want Canvas to help us get clean and pertinent data. I'm guessing we'll see more than one feature request on the topic in the community.
