Big Data Learning Analytics

Big Data, Learning Analytics, and the Learners

Big Data is the new buzzword. It’s not ‘big’ enough to topple MOOC from the lips of educatros, but it is becoming a topic that is being talked about more and more.

Firstly, what’s the difference between Big Data and Learning Analytics (if there is one)?

Learning Analytics, as defined by the 2013 Horizon Report is “big data applied to education”. There, that helped yes? No?

Then what is Big data? According to Lisa Arthur it is confusing in that it isn’t just one thing or the other, it is “a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis”. Ed Dumbill says that Big Data is “data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the strictures of your database architectures. To gain value from this data, you must choose an alternative way to process it.

Data, big or not, is something that is captured and stored from our exposure and interaction with external sources. Offline data could include things like purchases, (credit cards, etc.) and travel (petrol pumps, airlines, trains, etc.) where as online data that is captured include searches, browsing history, accesses, and habits,

How is this pertinent to education and educators? Think about your phone or tablet. If you use it on campus, and have at any time logged into the (free?) wifi then the odds are that it will still connect to the network next time you are in range. The system can track where on campus you are from the node you access or connect to. Also tracked (actively or not) is your activity through the network – websites, systems, movement/locations, etc. All before you actively use the device.

The other (positive?) aspect of Big Data and Learning Analytics are those associated with online behaviour in a specific system … the VLE maybe? Once the student logs in it is possible to track each click, every keystroke, every interaction, and more besides. The idea is to ‘learn’ the profile of the student through their behaviour in order to track unusual activity and, possibly, be alerted to anything out of the ordinary – students lagging behind or finding particular subjects or topics difficult.

Learning Analytics, then, is all about finding patterns and clues in the volume of ‘big data’ sets and numbers, and using them to help students.

Big Data Learning Analytics

In 2011 Cailean Hargrave presented at the FOTE conference the ‘Student Analytics for Success’. It was not received well at the time, not least as it was based on predictive crime (remember Minority Report anyone?) purporting to predict behaviour based on assumptions made about the student and his/her background. I felt worried that a student who was busy and might have let a milestone slip might be flagged as ‘in-need’ unnecessarily, and that a student who was struggling personally (not academically) would be by-passed in the system as they were getting everything handed in on time and attending all lectures.

Data can be manipulated according to the need of the analysis, and I would not want the ‘individual’ taken out of the data – the system can be programmed to look for certain traits or behaviours, but that needs some far reaching assumptions to be made, assumptions that need carefully defining.

Diana Laurillard writes in The Guardian that “Big data could improve teaching, but not without educators taking control of this extraordinary methodological gift. At present the field is being driven almost entirely by technology professionals who are not educators and have never taught online. Instead, we could be recruiting all lecturers everywhere to collaborate and generate their own large-scale data collection and analysis. Then big data could really make a difference.”

Blackboard, of course, has the Learning Analytics dashboard that takes a students’ progress through a set of defined goals as a mark of learning and achievement, but the one thing it doesn’t do is measure ‘learning’. But how do you measure learning … by looking at participation in a self-assessed multiple choice test? By taking a percentage pass rate in the test or in progress through the course materials? That doesn’t show anything other than a click rate.

I was present during a presentation at the 2014 Blackboard T&L Conference in Dublin  where Blackboard introduced the Blackboard Store where I was told (in relation to students buying the core text through the system, therefore tracking could be applied to the purchase) that I would be able to easily see the students who weren’t engaged with my course as they hadn’t bought the book! I do hope that isn’t what Blackboard really think … ??

In 2012 an Austrian student, Max Schrems, launched a legal case against Facebook over the use of his personal data. The premise, by Facebook, is that is collects only the data it needs in order to keep the network running (The Independent, 20 Oct, 2012).

Schrems knew Facebook kept large amounts of information on its users, but the sheer volume of his file still amazed him, he said. Pictures uploaded from smartphones included precise global positioning system coordinates, the identities of anyone tagged in the photos and the moment — down to the second — when the shutter clicked. Information that users thought they had deleted survived in Facebook files.

So, we have data, we have ‘big’ data, and we have (limited) knowledge or control over how that information is stored, used, massaged, accessed, or even sold.

Doesn’t that scare you? It does me. And yet I continue to take photos on my iPhone (geo-tagged), share photos (Facebook, Twitter, Dropbox, Flickr), and much more, and each interaction with my phone and an internet connection (wifi or cellular) results in a wealth of information about me, my habits, my actions, etc. is shared with … well, ultimately I don’t know who with. One thing I do know is that there may not be much value in this data now, but in a few years it could be worth so much to governments, advertisers, brands, corporations …

Reflection: Does anyone else remember the album from Billy Idol: Cyberpunk in 1993? No? It must be me then. If you do you’ll remember the reading on the first track, adapted from Gareth Branwyn’s “Is There a Cyberpunk Movement?”. Here’s the bit that matters (remember, this is 1993 – before Google!!):

“Mega-corporations are the new governments;
Computer-generated info domains are the new frontiers.
And though there is better living through science and chemistry,
We are all becoming cyborgs.
The computer is the new cool tool.
And though they say all information should be free,
It is not.
Information is power and currency in the virtual world we inhabit,”

The cyberpunk movement gave us a fore-warning of Facebook, Google, Apple, etc. … “Mega-corporations are the new governments … though they say all information [data] should be free, It is not. Information [data] is power and currency in the virtual world we inhabit”.

Image source: JD Hancock (CC BY 2.0)