Tuesday, June 23, 2020

eLearning stats

Here are our stats for our eLearning period from April 1 to June 12:
50 teaching days.
1,484,152 minutes in Zoom (JS).
495 hours in Zoom per day (JS).
56,036 Seesaw posts from students and teachers (JK-4).
27,6681 Seesaw comments (JK-4).
4652 Google Classroom posts (5-7).
We had four days of pro-d from March 26 to March 31 but I tried not to include those. For the 50 teaching days I just used an online calculator to take away the weekends and holidays. The last 10 of those days were actually a combination of our Home Learning and On-Campus Blended Learning.

The Zoom stats are very misleading. The raw stats outputted from the Zoom dashboard seem to multiply the number of meeting minutes. We don't require (or suggest) students to create Zoom accounts but faculty must have a registered account so it's easy to just pull out faculty stats and filter for just the Junior School (JK-Grade 7). However, Zoom seems to include participants into meeting minute totals but it's quite inconsistent. So a teacher hosting a meeting for 10 minutes with two participants may end up with a meeting total of 30 minutes!

I'm a little surprised that Chromebooks are not represented higher in the OS breakdown. This might be because this chart comes from client information so only tracks participants using the packaged Zoom app. I still strongly recommend Chromebooks in our BYOD years and we have maybe 25% representation in the school so I would have expected a greater percentage here.

The Seesaw stats were pulled from the admin dashboard and needed a bit of calculation. Total posts were found by subtracting our June 12 total from the April 1 total. Seesaw also provides a "weekly item" analytic but it's confusing. It would imply that each week thousands of posts were being added which would greatly skew our "total posts" analytic. I suspect this "weekly item" total also includes comments and attachments:

Google Classroom stats were pulled from the GSuite Admin dashboard. There are ways to pull this data out using the GSuite API or tools like GAM or littleSIS and I'd like to dig a little deeper into this in the fall. One such use of this data is to pull post titles or rubric info out of assignments so teachers have an easy way of tracking assessable student content.