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Hi everyone,
I’m looking for ways to evaluate and improve student retention at our university, and I’m particularly interested in leveraging data from Canvas Data 2 as well as other sources to identify and support struggling students.
At the moment, I’m exploring the best ways to analyze and apply data effectively to flag students who might need additional resources or interventions. We are pulling in Canvas Data on a nightly basis and are attempting to evaluate and backtest data to see what might be good indicators of measuring student success.
I’d love to learn from the experiences of other institutions:
- What metrics or indicators do you find most predictive of student struggles (e.g., low engagement, missing assignments, grades, web_logs)?
- How do you act on this data—what strategies or interventions have been successful for you?
- Do you supplement Canvas data with other tools or sources?
If you’ve found creative or effective ways to integrate and act on data to improve retention, I’d love to hear about them. Any challenges you’ve faced or lessons learned would be invaluable. Thanks in advance for sharing your insights! I’m happy to discuss further or collaborate if others are exploring similar initiatives.
We’ve used a variety of data over the years and have now settled on student activity (weblogs) and assessment data.
A couple of weeks into the semester we use activity data and contact the less active students by phone to give them a little nudge and see if they need any help. The data we use are:
After the mid-semester break we use assessment data to help us work out which students to contact. The data we use then are:
It’s just Canvas data that we use now. Previously, we also used Student Information System data to tell us things like a student’s program GPA and whether they’ve previously enrolled in a particular course but we’ve streamlined it.
Thanks so much for your input!
@a1222679 wrote:
- Course activity percentile (i.e. how the student compares to their peers within each course based on count of active days and using weblog counts as a tiebreaker when the number of active days is the same)
- % of enrollments to have accessed the course in the past week (we’re not too worried if a student hasn’t logged in to a course if none/few of their peers have either
I really like how you’re leveraging the weblogs data here. Initially, we were quite disappointed because we could only retrieve the last 30 days of weblogs data to store elsewhere, which caused a noticeable data gap in 2023. Our original plan was to use historical weblogs/requests data and backtest it in various ways, but I was always concerned about the size of the data and the many variables that came with this approach.
Following that, I considered using a technique somewhat similar to what you’ve described here—comparing students to their peers within each course—but I haven’t made much progress on that idea yet. Seeing your approach here is very helpful and I'll definitely be looking more into this in the near future. Based on other threats and posts on this site, using weblogs to compare peers on a class level appears to be the best way to use the data.
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Our university has had previous attempts at measuring and improving student-retention that mostly involved SIS data. We might end up leveraging some SIS data alongside the Canvas Data information that we pull, but I wanted to lean in pretty heavily to what's in canvas this go-around. I really like your approach here.
Once again, thanks for your input!
Hi @ChrisWolf93 , not sure if you've come across this but Instructure actually offers a boxed solution to identify students who are in need of attention and then take action by reaching out to them, their teachers (or observers) within Canvas. It's part of Intelligent Insights -- https://community.canvaslms.com/t5/Intelligent-Insights-Guides/What-data-is-available-for-Students-i...
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