Pushing data boundaries to make a positive change

Some people have asked if Learning Analytics breeches the privacy of the student. The simple answer is no, but let me explain why…

The internet can be a terrible echo chamber, especially on perceived contentious points, so I write this with some trepidation. However, I would like to state from the outset that my opinion has been formed by students and users of Learning Analytics solutions and not formed by those that sit on the outside looking in.

Scaremongering of a Big Brother state, poorly conceived initiatives and fool hardy experiments by corporations has made many in society sceptical about the use of data.

Some people have asked if Learning Analytics breeches the privacy of the student. The simple answer is no, but let me explain why…

Our Learning Analytics tool StREAM only uses the information and data already owned by a university. By using existing data, whether historical or as the data as it is created, the software uses algorithms to map a successful student, and a student who may be at risk.

 

Intelligent information

Using centralised data points to collect behavioural information (attendance, system logs, door access records, library use, VLE/LMS data), StREAM analyses the individual’s digital interactions with the University. Similarly, it then performs the same process with a student who has failed or left the university early.

StREAM then builds intelligence around its findings and calculates the likelihood of success and failure, modifying the students risk status with each interaction. By monitoring these patterns of behaviour and making existing data more readily accessible to the organisation, StREAM identifies these student behaviours that may lead an individual to terminate their time at University much earlier than current methods and so giving institutions the time to react and modify student behaviours.

And the information StREAM exposes is purely objective, not subjective, based on a single persons view, based on a few interactions. Inaccurate judgements about an individual or demographical biased information such as gender, ethnicity, family income etc becomes a thing of the past and since rational and forecast are applied, the learning process is enhanced. Essentially, StREAM uses data to make a positive, not negative, changes.

 

Opinions matter

From the perspective of the student, most people in the Internet age have a wildly different view on the value of data and are prepared to share it more easily as they often disclose information for access to services or resources.

A recent survey posed the following question to a group of learners; “If there was a problem, would you want to know?” A staggering 93% said yes they would.

Many students simply don’t know what a good learner looks like and providing them with a tool that allows them to track their own daily progress is invaluable in making them independent self-determined learners. Through access to the StREAM app, students gain an understanding of their development and a demonstration of negative activity is often the motivator needed to trigger a positive change in their behaviour.

 

Enhanced delivery of education

From an internal personnel point of view, in many cases the technology chimes with tutor intuition and presents them with the opportunity to improve learning outcomes and student engagement. If a learner ceases to participate with the University, the tutor is notified and can then begin to foster a positive conversation, offering support, advice and guidance. Moreover, this objective ‘evidence’ ensures that tutors can be very specific with their guidance on how a student could improve making the value of every tutor/student interaction valuable, whether saving the tutor time or by ensuring the time is spent on the conversation and not the research of ‘how are they doing’.

Ultimately, it’s not about trying to find out how long someone has spent in the Student Union bar; it’s a tool to recognise when a student needs help.

 

Support when it’s needed the most

If negative activity is exposed, it’s up to the University to decide if a support intervention needs to be made. And interventions aren’t designed to penalise, they’re designed to offer encouragement and reassurance -making the experience better, not punitive.

The beauty of StREAM is that it doesn’t just focus on the students who stand out at either end of the success spectrum. Instead, it seeks to help all, including those in the middle, who are often overlooked, achieve the best they can. For that reason, if you take into account the positive value StREAM can deliver, the privacy argument almost becomes obsolete.

 

Some people have asked if Learning Analytics breeches the privacy of the student. The simple answer is no, but let me explain why… The internet can be a terrible echo chamber, especially on perceived contentious points, so I write this with some trepidation. However, I would like to state from the outset that my opinion […]

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