How I learned to stop worrying and love the data

People are scared of data.

After watching Scott Galloway’s great TED Talk on how large tech companies manipulate our emotions, my colleagues lamented how easily their personal data was forfeited. When I returned home for Christmas, my parents sagely advised me to use DuckDuckGo as my search engine, as it didn’t track your activity like Google. And with articles detailing how much personal information tech companies scrape about us being published at the same time as reports of how they mishandled said data, it’s understandable people are worried about who knows what about them.

Whilst it was worrying to think that Uber might have been tracking my location and to think about why my parents wanted their search history deleted, it made me realize that people don’t often hear how we can use data for good. This fear, generated by a bombardment of reports of secret tracking and hidden data breaches, is holding us back from truly harnessing the power of data.

What is it that we actually get in return for letting corporations gather all of this information about us? Well, I think the majority of it can be summed up in a word: convenience. We can buy apps using our fingerprint, find the perfect movie for a Friday night in, or even get personalised discounts on our favourite groceries—if we’re willing to let these companies get to know us. Companies are also using this information for social good too. Anyone with an iPhone will see know that if they a– travelling at a certain speed, their phone asks them whether they are driving before they can open it. Apple is using your location data to try and prevent road accidents.

At a macro level, there are great examples of social good that could be achieved with big data sets –sets that can only be generated if we add our own personal data to the pot. Google Flu Trends attempted to track the location of searches about common symptoms to predict outbreaks of the flu. Whilst it didn’t work out as planned, Google’s efforts showed there were new ways to think about how we make use of large collections of people’s data.

In education, we’re only just starting to explore the potential of using data to improve learning outcomes. Gradebook tools found in most LMSs, already offer visualization of student scores, to show teachers areas of difficulty in an instant. Adaptive learning platforms present different content to students, based on memory of how they’ve performed.

But what if we could combine data about a student’s interests, gathered from other websites, with their education? Each student could learn from activities that had been automatically rewritten around topics that they genuinely engage with. What if we combined the scores of students taking the same course all around the world? If a learner is struggling with a particular topic, teachers could be sent recommendations of how to help them, based on what helped thousands of other students who have suffered with the same topic.

Collecting personal information about students is a rightfully delicate topic however, especially in the cases of younger learners. But to move closer to effectively utilising data in education, on the kind of scale consumer tech companies make recommendations about our everyday lives, we need to remove some of the fears and myths surrounding use of data.

I think there would be benefit in aggregating general preference personal data with explicitly educational data. It is arguably a social good to share your data in education if it can contribute to better learning outcomes for others (as well as yourself), which is far less worrying than simply making yourself a better target for advertising.

 

Author: Harry Cunningham
Partnerships and Innovation Manager at Oxford University Press

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