Like almost all North American schools (and many around the world), we’ve had to switch the way we teach and learn due to the Covid-19 pandemic. That means significant increases in the use of technology, and in demand for support around those technologies. In a series of posts, we will be sharing some visualizations of those changes.
For today’s end-of-week “data challenge” we give you two graphs of Quercus “usage” since the covid-changes to teaching.
In graph one, we see the percentage of users who have accessed Quercus with their mobile devices (primarily phones, but not laptops). Almost 80% of those users accessed Quercus from an iPhone. The rest from Samsungs, Pixels, Huaweis, etc.
In the second graph, we show the percentage of actual sessions (actual connections to Quercus). Again, iPhones were used for the majority of the time, but the ratio is not the same – only about 60% of sessions were from iPhones.
Why would there be this delta?
I sat and pondered this question with my colleague Bryan Ekeh, our data support analyst, and we had some possible explanations.
Said Bryan, “These observations may demonstrate various behaviours of students that are having to work remotely. Many of them may roll out of bed, check Quercus through their mobile phone’s web browser and continue a Quercus session on their laptop or desktops at home.”
My thought was that the delta in the data might mean that this behaviour is more prevalent for iPhone owners than non-iPhone owners. Does that mean that non-iPhone users are more likely to use their phones to more fully engage with Quercus than iPhone users? Is there something about the user interface of an iPhone that makes it less attractive to engage with Quercus than other types of phones?
Could the explanation be more about equity and access to resources? Are iPhone users more likely to have a phone and a another computer, and therefore, Bryan’s hypothesis holds – they do quick check-ins, but for serious work, they revert to the computer? And maybe those who have non-iPhones are also less likely to have a secondary computer (or at least a computer that is useful for doing Quercus-based work)?
All of these are just hypotheses. Now it’s your turn – what do you think accounts for the delta between the two graphs?