More student data, but later

We need to seriously consider doing a lot less with student data right now. Stopping data logging will reduce the impact on our systems and, more importantly, on our students.

As a longstanding learning analytics researcher, I don’t say this lightly.

Computer Problems
“Waiting for Moodle to render this page is taking longer than it takes to get to the lecture theatre on the other side of campus.”

The Covid-19 coronavirus crisis is profoundly changing society, including universities. There’s been a mad dash to online teaching, and a mad dash to online assessment close behind. Those of us who’ve been enthusiasts for online learning for a long time know that this may be a huge success in some places, but that it isn’t going to go terribly well in many others. It’s easy for our eyes to light up at the thought of all that interesting data that all that online activity could generate.

But hold up. In a crisis, we need to prioritise what’s most important. Frankly, the benefit to students of most of our data gathering is not sufficient to justify it getting priority in a crisis. And our evidence of what benefit there is has improved since I wrote a rather despairing paper with Rebecca Ferguson about it, but not hugely. I do believe it’s worth pursuing. But it absolutely can wait, so it should wait.

A big turn-off

What if we just turn all that data logging off for the duration of the crisis?

We’d reduce the impact on our systems. Online learning systems are under massive strain as IT staff and suppliers struggle valiantly to deal with a completely unprecedented spike in demand. With a well-designed and well-tuned system, data logging needn’t be a huge drain on front-facing server resources. But when you’re rushing to scale up, you don’t have the time to tune it well and built a robust and separate data architecture. It will make the IT people’s life much easier if we just drop those requirements for now. It would, at least, be one less thing for them to worry about. And it might well materially improve performance, particularly on hastily-deployed systems where there hasn’t been time to optimise them.

We’d also reduce the impact on our students. Most academics are only in the student data business to make things better for students – but there are other interests at play too. Students are quite reasonably concerned about how their data is being used at the best of times. There isn’t the time to do all the engagement around data privacy that good practice requires, and that you need to properly address understandable and quite reasonable concerns. We could just steamroller them in to it. This seems to be happening a lot, and there’s even been some commentary from UK ministers about the GDPR that might be useful political cover for it. Or we could just … not do that, and give them a break. Deal with their worries about data privacy by sharply reducing the amount of data we collect. I think, given all that this cohort is putting up with, and is going to have to put up with in the near future, they badly need any break we can give them.

What can’t wait?

There will be some exceptions. Obviously, where you have a cognitive tutor setup, it would be nonsense to turn off the logging – and, not coincidentally, that’s where we have the best evidence of direct student benefit.

More widely, I’d argue for saving the last login information for each student so their tutor can see who’s been able to access the system and who hasn’t. I can’t instantly think of good papers showing this, but my strong hunch from practical experience with predictive modelling is that a huge chunk of the benefit that can come from such systems is increasing awareness among tutors of which of their students hasn’t been able to study for a while. We can do that directly with a lot less impact on students and servers.

And obviously, some data has to be recorded to operate an online learning system at all.

More later

For the avoidance of doubt, I am not for one minute arguing that learning analytics should close down and give up. I do still believe that there is huge potential from using students’ data to improve their learning, and that there’s more to be gained in future than has been done so far. I am arguing that we should be humble about what we can offer and prioritise the benefit to students. That is, after all, the whole point of learning analytics.

Learning analytics researchers and practitioners have never been in more demand in their organisations. We understand the practicalities of online learning in ways our more traditional colleagues don’t. It’s not like we’d be short of stuff to do if we spend the next months prioritising support for them and for student than our data-gathering projects.

We should do a lot more with student learning data … and we should do it later, when all this is over.

Author: dougclow

Experienced project leader, data scientist, researcher, analyst, teacher, developer, educational technologist and manager. I particularly enjoy rapidly appraising new-to-me contexts, and mediating between highly technical specialisms and others, from ordinary users to senior management. After 20 years at the OU as an academic, I am now a self-employed consultant, building on my skills and experience in working with people, technology, data science, and artificial intelligence, in the education field and beyond.