Using small data to help students make big discoveries about themselves


Big data is big news.  In today’s world a growing number of services and products are delivered to us by huge organisations: large retail chains, powerful online companies, big government agencies, ever-growing universities and so on.  Interestingly, many of them are quite good at recognising our small individual needs despite their big size.  All of these institutions are interested in serving their customers better whilst at the same time benefiting from that servitude.  It’s difficult to serve someone if you don’t know them well so it’s not too surprising that they want to get to know us better.  Information about us is being collected all the time – from simple surveys to loyalty cards, from focus groups to smart meters.

Our consumer choices, our long-term aspirations, our opinions, our thoughts, our physical movements; everything is worth recording.  The data banks are already so large and complex that many organisations struggle with analysing them, hence the need for the big data tools.  And yet, despite already choking on that data, they want even more of it.  Books are replaced with e-books, face-to-face conversations turn online, anonymous cash gives way to chip cards.  We perceive these new technologies as convenient innovations, while at the same time worrying that even the tiniest of our activities are now used to learn about us.  Facts which can’t be automatically tracked are collected by specialised companies such as Facebook or Twitter who make profit by collecting and digesting information that is provided on a voluntary basis.  These seemingly fragmented data sets, small snapshots, are at some point cleverly turned into various types of profiles and timelines – personas.  By looking at our profiles patterns can be spotted, assumptions can be made.  In essence, by knowing us better it’s easier for big organisations to predict and match our short-term choices, our long-term plans, or even surreptitiously project our future desires…

It would seem that everyone is interested in benefiting from feeding their big data banks with facts about us.  But what about small data?  Could we not benefit from discovering more about ourselves?  Could we not deploy similar data collection techniques at a more intimate scale to start spotting interesting, unique patterns in our small day-to-day choices?  Instead of sharing data about ourselves and allowing others to direct us, why not reflect on it to self-direct?  Moreover – as educators – could we not take an extra step, and turn these smart business ideas around for the benefit of our students?  This time, it would be solely to improve their potential as self-directed learners.

Today I’ve been invited to make a presentation to a group of personal tutors from medicine-based subjects.  I’ll be helping them to think about ‘ways of engaging students in reflective dialogue with their personal tutors’.  The venue is a building adjacent to a big hospital complex.  I arrive at the car park on my scooter and look around.  It will take me a while to walk to the venue.  That’s good – some extra thinking time.

Hopefully, some of you can relate to those few unique moments of intensive brain activity as you’re getting ready to start talking for 60 minutes.  I always try to use those brief moments to think up fresh arguments to illustrate my points.  I believe that introducing simple analogies and examples from the real world is an essential part of good communication, especially, when I’m tasked with promoting reflective learning.  It’s a subject which can be seen by some students or tutors as slightly alien or even completely abstract.  So, here I am, heading out of the car park towards the building, while a chain of simple real-world analogies starts developing…

Take this white concrete beast of a building for example.  How can such a giant function so effectively?  It feeds on enormous quantities of data.  So again, what about us and our own ‘small data’ banks?  What about the personal tutors who need to understand their students?  And the students who need to understand themselves?  As an experiment, let’s ask students to become their own ‘small data’ gurus.  Purely for self-development purposes, let’s use the richness of such analysis to switch them into a more self-reflective mode.  Here are some quick prompts to get our tutees going:

–          Think of the amount of time it took you to prepare for an exam versus the results you obtained.  Start collecting those simple figures and reflect on (in)consistencies.

–          Using a calendar (or even Facebook or Twitter) scroll through your last month and try to identify days which you spent on intensive academic reading or writing, as opposed to days spent on just thinking or not thinking about studies at all. What does it say to you?  Has this month been unusual in any sense?  What names would you use to categorise your months?  Knowing your months, could you think of theme names for your years?

–          Based on your personal preferences at the time, can you think of your top two courses from a year ago, from the last semester and today?  Try to identify any patterns.  Can you envisage your top two in six months time? If you were your own careers adviser, would you be able to explain those course choices?

–          Use three adjectives to describe the experience of writing on an essay.  Repeat the exercise every time you writing one.  Comment on the collection (from different time perspectives).

–          Every time before receiving your assignment’s feedback try to predict positive and negative comments.  Compare them later with the marker’s feedback.  What did you predict incorrectly and why?  Are your ‘predictive skills’ improving in time?

–          Look at the university map.  Which are the places where you tend to spend most of your time and which are your favourite spots?  Are those two lists correlated?  If not, what would you have to change to make the two lists look similar?

This is just a very small range of ideas which students could use to start developing more complete pictures of themselves.  Please feel free to shoot those examples down, or maybe you can think of some better ones?  I’ll certainly keep wondering about analogies between researching patterns of customer behaviour and encouraging more objective students’ self-discoveries.  It seems to me that this topic can’t be fully exhausted in a single blog post – let alone whilst trying to find a way out of a hospital car park…!


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