We’re not data capitalists. We’re just trying to make things better.
Do we risk making students unnecessarily paranoid about how data is used in education?
Sometimes, hearing some people in the learning technologies community talk about analytics in education gives me a crushing sense of disappointment and frustration. It’s a bit like hearing Daily Mail readers talk about immigration.
I use analytics in education. And I must admit it’s been interesting, and surprising, to find myself being referred to as things such as ‘data capitalist’, ‘data thief, and ‘an oppressor in the class war’ (yes, seriously). As a lad who grew up in a deprived mining town in the north east of England under Thatcher (imagine Billy Elliot but without the dancing) I’ve always been pretty certain which side I’d be on in any class war. But apparently others know better.
You might think that using this data as part of the Open University, a champion of social justice, would help people see what we do in a positive light. Yet I’ve seen our motives questioned. More than once I’ve heard something along the lines of “I’m sure the Open University is well intentioned…” with the unsaid, but heavily inferred ‘BUT…’ looming accusingly over the conversation.
I’ve read blogs, followed social media threads, and watched presentations where people within the education sector have sounded a clarion call to fight this use of data and, along with it, fight the people who use it.
I think it’s time to challenge this narrative. Not that there aren’t genuine concerns about use of analytics. There absolutely are. But it’s important that we also recognise and champion the positives, and make students aware of these benefits, as well as the risks, so they are well informed.
They need to know that just because data is used it does not necessarily follow that the user is an oppressor, or a capitalist, or some other kind of shyster. There are plenty who are just looking to make things better.
So what does a data capitalist do?
“If the service is free then you’re the product.”
I’m sure most people have heard this maxim before. It’s often used in relation to the likes of Facebook, Twitter and other social media platforms. It refers to the idea that the service you receive, such as the ability to build a network and share content, is paid for by the platform selling access to you.
And how do they do that? Well, as an example, what the likes for Facebook do is this. They capture as much info as they can about you. They want to know what you like, what you do, who you trust, and myriad other things. They build a profile of you.
They do this for two main reasons.
The first is to sell the advertising space in front of you to other people. Facebook can offer a company who sells underwater basket weaving kits advertising space to those people who appear to have an interest in underwater basket weaving. That’s a pretty compelling proposition for advertisers. Note that it is advertising space, rather than data, that is sold. Facebook are unlikely to sell the very thing that makes them profitable.
Secondly, they use your profile to try and put content you will find interesting in front of you. They do this to make sure you keep coming back to their platform, and you spend plenty of time there when you do. Offering advertising space in front of you only really works if advertisers know you’re actually going to be there to see it.
For these platforms data is what they monetise. Your data. About you.
It’s a model some people don’t like, but others are okay with.
Additionally there are organisations that gather data about what you have shared or posted on these platforms. In these cases they offer to sell this data, or profiles they have developed, to third parties. Yeah, they’re making money off your data without offering you anything in return.
What we do.
We’re the learning systems team so we use data to help us understand how our online learning systems are being used. And it is really helpful. Particularly as we’re a distance learning institution and, unfortunately, rarely get to speak with the students.
This information helps us understand where things aren’t working so well — so we can investigate to fix or improve them — and where things are working well — so we can learn from them. We want to make sure the learning systems don’t damage the student experience. We want our systems to enhance and support that experience.
We have limited resources available to maintain and enhance our online learning systems. Data helps us make decisions about how we make best use of these limited resources. For example, it may lead to us continuing support for an older browser as we can see a marginal, but significant enough, group of students still rely on it. Without this relevant data we may have decided to withdraw support as other organisations were doing. Similarly, anecdotal evidence we receive suggests that our VLE forums are dead and the students have all migrated to social media. But our data shows that in some areas this isn’t true and forums are vibrant places of student communication and collaboration. So again, we know to continue supporting and enhancing this tool.
It’s important that we understand what users do. However, what users actually do doesn’t always align with what users remember they have done, and tell us they’ve done. This is a perfectly normal quirk of being a human being, and is one of the reasons evidence from data can be so useful.
Data has improved our ability to make decisions. This is a better situation than when all we had to base our decisions on were limited survey results, the all to infrequent user tests, anecdotes, best guesses, and gut feeling. We still use this mix of sources. But adding actual data to the mix amplifies and supports the reality present in this information. And, importantly, data challenges the biases present in assumptions.
We want to develop systems based on how students really use them, not on how we think they should use them.
The module teams, TEL designers, and other academics, also work together to monitor how the learning systems are used. They’re interested in which aspects of content work and which don’t and trying to identify if there are better ways to design learning? The data can help indicate areas of concern where further qualitative research with students will be useful. It can also be helpful in terms of identifying those students who may need more support and a helping hand.
How does this make us different?
When we use data we use it to make the online learning experience better for our students.
The data doesn’t get sold on to other people.
We don’t sell advertising space in front of our students.
The data is not monetised.
Rarely, if ever, do we link the activity to individuals.
We’re more interested in building profiles of our systems and content, than building profiles of students.
If we were to stop using data there would be no immediate financial hit. We don’t make our living from the data.
However, it’s true to say that without the data we would find it a lot harder to keep improving the learning experience for our students. That’s not good for the students, and it’s not good for us as an organisation. And that, indirectly, could lead to a financial hit in the long run if students were to leave us for a better, data informed, learning experience elsewhere.
We use data to make things better, not to make money.
So what’s my point?
It’s right that we make our students aware of how data is used by organisations. It’s right that they understand the trade-offs that are being made when they access ‘free’ services. It’s right that we help them understand the relevance, and potential impact, of their digital footprint. It’s also right — and I can’t believe that we’ve reached a point that I have to say this — that we make them aware of worse case scenarios and how authoritarian regimes could use their digital history.
On the other hand, we don’t need to make it seem like we’re already living in a dystopian nightmare. Not every click and view a student makes is bundled up and sold off to whichever machiavellian corporate monolith or scheming dictator is willing to pay the highest price. Not everyone is out there to get them.
Students have some great allies working with data to help them. Data can be used for good just as it may be used for bad. As part of developing their digital literacy students need to understand the nuances, good and bad, around how their data is gathered, held and used. This will help them come to their own informed decisions about how they make their way through the emerging digital society.
Let’s make students confident about their data. Not fearful.
If you have questions about how and why we use data feel free to ask and we’ll try and answer them. We’re reasonably friendly people.
This blog was written by Steve Parkinson (@Steve_p_uk) a senior product development manager, and part qualified accountant, in the Learning Systems team (@GoTeamLTS) at the Open University.
