Continuing the CEO Soapbox from last year (hopefully we’ll hit more than two a year in 2017… resolutions etc.) here I am with today’s piece:

We’re Data Rich But Information Poor…

The understanding of Student Data

I spoke last year at the future of education conference in London about data and specifically in education with regards to ensuring context behind this data. I want to elaborate a bit more on this topic as “data” something that everyone in the education space is interested in, but that’s where it starts to get noisy.

In a world where everything we do collects/ stores/ logs some sort of data, we have historically not transitioned that use of data to the education space. That, however, is starting to change. Along with the large increase of courses being online, the whole eLearning industry booming, we’re now reaching a point where we’ve gone too far the other way. We have too much data and this is where the noise comes in.

(how data is collected about us as an individual, daily, in our activities)

I was talking to a university and the words out of their mouths were, “we’re data rich, but information poor” and they’re 100{8eae1d7c55c82605346b321e0090be2e47c86d9df4359ab0b155246f7a97c78d} correct.

When you talk to schools, universities and colleges you understand that their need for data is important. It’s what they need to ensure that they understand more about their students, and yet in a lot of cases they either don’t know what they should be measuring or, which happens a lot, it’s the action that needs to take place based on the data that they have.

So for me, this is something that we need to understand in much greater detail to be able to have a greater impact on how to solve the problem for each student. Put it this way, when you browse the internet, soon enough you have adverts trying to sell you things relating to your searches, right? Whether we like it or not, it’s there and it happens. We have personal recommendations, based on our personal behaviour.

We’ve spoken before about the non-existent “average student“, and the reason I’m talking about it again is that all these things need to be considered when it comes to collection and actioning of data in the education space, too. We hear all too often “the average time a student spends doing XYZ should be ABC”, based on, one would assume, data across a sample. But that then doesn’t help us on an individual level for those students.

I’m not saying I have all the answers, or that I can change the world overnight (I’m trying, but it keeps fighting back), but when looking at analytics, one thing we should look at is how that data is captured around the individual student and measured against their historic data.  We aim to try and ensure that the data you get at the end might be “averaged” but that average is comprised of individual students’ own averages, and then normalized, rather than a generic average against the whole class/ course/ school.

Again, I would love to be able to say our company and solution changes everything, it doesn’t. What it does do though, is provide you more actionable data based on personal student activity, rather than general data. More context and trying to provide a real insight into your students and your content, is what my personal aim is to provide.

I’ve been that person standing in front of a room full of people, tasked with making sure they learnt what I was teaching them and I can tell you right now, not one of those people was the same as the other. Pace of learning, ways of explanation, type of learning style… they’re all different. Yet, we expect every student to be the same when it comes to learning content online and the data we collect about students and content doesn’t reflect the individuality of our students.

I love my work here at emotuit as I get to really dig into this subject and get on my soapbox as well as create some great products to help you guys really understand your students and your content.