What could be more normal that heading to the university library, swiping your card and logging in to a computer?
Most students wouldn’t think twice about it. But what they may not realise is that this mundane series of events leaves a unique data pattern that can be recorded, logged and reviewed, in a practice known as “learning analytics”. And now data analysts are using this information to predict whether students will struggle with their courses, or drop out.

“We’re trying to use data to improve our understanding of how students learn,” says Dr Bart Rienties, director of the learning analytics programme at the Open University. “We want to understand the story behind that data.”

Such techniques look set to become an integral part of university life in the future, much to the delight of advocates. “Learning analytics can provide a more personal learning experience, rather than a one-size-fits-all solution,” Rienties says. He was part of a new study – which analysed data from more than 113,000 students at the Open University – looking at drop-out rates and how usage patterns of online learning resources can be an early indicator of academic performance.

At Aston University, experts are using learning analytics to try to lower the number of drop-outs. But the university’s achievement enhancement adviser, James Moran, is keen to emphasise that the programme is coming “firmly from a position of providing support and pastoral care, rather than tracking students”.

He says: “If a student had been expected to come to a library session, meet a personal tutor or a career adviser, and they hadn’t appeared, that might send a flag to the personal tutor saying it might be worth giving them a ring.”

The university’s deputy vice-chancellor, Helen Higson, explains that the move came from practical considerations. “We have a big student database where we collect everything about them, from enrolment to when they leave,” she says. “We started monitoring VLE [virtual learning environment] data because the visa requirements for overseas students mean that we have to demonstrate every two weeks that a student is engaging.”

The long view

But Nick Hillman, director of the Higher Education Policy Institute, warns that it’s too early to say what effect this approach will have in the long run.

“I think it has a lot of potential, but you have to be very careful. You don’t want a massive security breach, or for the data to be used in a way that some students think is inappropriate.”

Dr Richard Tynan, a technologist at Privacy International, has other concerns. “All data has the potential to betray you,” he warns. “We need much more honesty, about what data is being collected and about the inferences that they’re going to make about people. We need to be able to ask the university ‘What do you think you know about me?’”

Tynan argues that legislation should be updated to reflect changing approaches to the collection of personal data. “The problem with data protection law is that it was from an era when people went to technology,” he says. “Now, technology is coming to the individual, whether they like it or not.”

The Data Protection Act distinguishes between “anonymous data” and data that identifies an individual. But Tynan points out that seemingly anonymous data can be pieced together to identify individuals behind the numbers.

Students can make a subject access request (Sar) for the data their university holds about them – but this doesn’t necessarily allow students to find out what conclusions have been drawn from it.

Meanwhile, the data collected by universities can be shared with third parties, meaning that students have little idea how far information about them could be travelling.

“Data is incredibly valuable, and many systems pay for themselves just in the data they collect,” Tynan says . “What happens when the student leaves – is the system going to retain this data forever? How are they protecting it? Students need to know what the consequences are now and in the future.”

Ultimately it should be for the student to decide whether or not they are tracked, he says. “Sometimes data tracking is good, sometimes it’s bad. But students need to be able to opt out.”

Emotional data

The next frontier for learning analytics is feelings. Research is already probing therole of emotions in a student’s university experience, and analysts are developing theories about how this “emotional data” can be captured.

Mobile phones can be used to monitor eye movements and body pose, for example, and this data could be used to tailor individual educational programmes based on the teaching methods that elicit the greatest positive emotional response.

But it could, of course, be seen as a massive invasion of privacy. The Open University has consulted 100 students about its use of analytics, which Rienties says generated mixed responses.

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