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Learning Analytics according to Wikipedia

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As if often the case in Wikipedia, the article on Learning Analytics began as a quick summary and rapidly mushroomed into a far more extensive treatise on the subject. However - the initial definition has had few versions. It changed in the first day, then again a couple of years later, but the sentence written in 2013 is the same as the sentence which opens the article today. The difference is that in today's article this opening sentence is followed by over 4000 words of further information.

Learning analytics is the use of data and models to predict student progress and performance, and the ability to act on that information - 23rd August 2010

Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning. - 24th August 2010

Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs. - 1st September 2013

I usually like to begin my investigations about an unfamiliar subject with a read of the associated Wikipedia article. I realize that it's not a peer reviewed, 'reliable' source but it is often succinct, accessible (especially to to the non-expert) and well written with good clarity. The learning analytics article is none of these things and it reads as an article written by committee (which is, of course, exactly what it is!).

The impression that the whole article gives me is that the subject of 'Learning Analytics' is as vast, as nebulous, as complex and as multifaceted as the two words would imply. H800 challenged every internal impression and idea I had about the concept of 'learning' so I am keenly aware of how 'simple' ideas can become mosaic when investigated and the word 'analytics' gives us no expectation of a simple and easily defined concept! Put two big concepts together and the creation of a gargantuan concept seems also inevitable!

The simple sentences above describe aspects of learning analytics. My impression is not that those who change the definition claim what is stated is incorrect, but that it's incomplete and inadequate. The extra information, text, ideas and paragraphs don't detract from what has been previously written as much as adding to, augmenting and complementing it. There are a multitude of associated concepts which overlap with Learning Analytics but the edges of each concept is blurry and undefined.

I suspect a concise definition which will satisfy everyone is impossible to develop but by looking at the areas everyone agrees with we can draw some conclusions. Such commonalities include:

  • Data - the data is described as 'intelligent' and processes related to collecting, collating and analysing this data are all part of the definitions. Data is an inescapable part of Learning Analytics. It's the key ingredient and without data there can be no analytics.
  • Discover, understand - data can enable a great deal of knowledge to be amassed and that knowledge can lead to understanding of crucial patterns within learning and teaching
  • Prediction, modelling, advising and optimising - four different but overlapping ideas in this context. The way in which the data is used is part of what makes Learning Analytics what it is. The purpose of LA is, at least in part, the improvement of the learning journey for the individual and the cohort.

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Slogging and blogging

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Week 10 has been full of interesting H800 activities and full of Anna's professional and personal activities so it's been something of a busy time and I reach the first day of week 11 without having really done justice to week 10. 

I am not sure if it was intended but I feel that week 10 has been inviting us to consider the motivations of people, institutions and maybe even ourselves. 

We began by thinking about Wikipedia and how much we could rely on it given what we know, and have learned, about the politics behind the editing and writing process. Wikipedia seems, on the surface, to be benevolent and good; concerned with making as much information available to as many people as possible without charging. It is easy to understand their model - they don't pay experts to write the articles and check for accuracy - they engage experts with the overall ideal and get them to do it for free! And they do! The credentials of the 'experts' are not checked and anyone can self proclaim as an expert. Vandalism and mischief should abound surely.... and yet neither do. The project is now so big that almost all edits - both mischievous and genuine ones - are checked very quickly and Wikipedia remains remarkably accurate overall. I find myself trusting Wikipedia because all of those mischief makers can't stand against the majority of people who stand with the Wikipedia ideal and want to give the user good, accurate information. 

Of course - an analysis of Wikipedia for 'facts' (the population of nations, the height of mountains, the careers of politicians) is one thing. An analysis of Wikipedia's reporting of 'issues' (Palestine and Israel, gender politics, abortion law) may well reveal a particular worldview prevails. 

Next we looked at Stack.com (and I quickly went to similar sites such as Quora and Yahoo answers) where individuals ask questions and other individuals answer them. The questions are often very practical 'how do you....' rather than the more non specific 'should someone....' Individuals who see a question may also vote for the answer they think is best. I have found these sites very useful. Again - I am aware of the potential for mischief but if someone has asked 'how do you poach an egg?' I would not expect hundreds of people to vote for 'place the whole egg in the microwave without cracking the shell'. I rely on the desire of people to be right - and give /confirm the right information - and the desire of people to be helpful - and give / confirm the right information - over the desire of people to cause mischief or discord - and deliberately give / confirm the wrong information. Of course this benevolent assumption is rather thrown into sharp relief as we learn more about how both the EU referendum in the UK and the 2016 US Presidential election seem to have been deliberately influenced by false, inflammatory and deliberately discordant use of social media in particular and the internet in general. 

And then blogging. I felt a small smug thrill as I realized I was ahead of the curve on this! There were some very interesting articles about what happens when blogging is required (it's not good) and how students use blogging in studies (see all my former posts for a wide representation of reflection, ranting, catharsis and thought development). 

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Neutral Point of View

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The first activity of Week 10 was to do with Wikipedia. 

I love Wikipedia. I know that anyone can edit (vandalise) it, I am aware that most of its regular editors and writers are white, educated, youngish men, I would never rely on it an emergency BUT I love that the sum total of human knowledge seems to reside there! Even the plot of various books, TV shows and plays. There are long articles about fictional characters! 

A bit of directed digging this week has exposed some things about Wikipedia however. I was vaguely aware that the toxicity of 'revert wars' was akin to the nastiness of the comments section of a Daily Mail article about Brexit, however to read the environment being described as it was did alert me to the extent of the problem. I do know that I can't edit Wikipedia anymore since my teenage son went on a Wikipedia vandalizing spree and my IP address has been put on a 'naughty list' somewhere. (Which does, at least, reassure me that action is taking against deliberate vandalism and mischief). 

However - as a user I am not sure this will affect me. I wonder if it should but I don't think it will. Wikipedia not only reminds me 'where do I know that actor from?', 'is Great Gable taller than Helvellyn?, and 'where is the Sargasso sea?' (All recent Wikipedia searches) but it also acts as entry level information on academic and professional studies.

I work for a medical training company despite having no medical training! I have to proof read (for accuracy as well as spelling and grammar) questions written by doctors to test other doctors. I also write questions myself. I sit surrounded by medical text books and with NICE, Patient.co.uk and GPnotebook permanently tabbed on my screen. Sometimes I still struggle to understand though so at that point I often revert to Wikipedia. Not as a primary source - more as background reading! I learn the vocabulary and some key basics in jargon free language. I can then return to my more reliable sources with more understanding and knowledge.

In H800 I have also used Wikipedia. At the beginning terms such as 'behaviorist' were thrown about and whilst I had a vague idea of what the term meant from a sociological point of view I wasn't sure how it pertained to learning. Where did I go to catch myself up - Wikipedia! I didn't cite Wikipedia (even Wikipedia says you shouldn't do that!) but it did furnish me with some useful starter information.

The question we are now pondering is about the 'neutral point of view' which Wikipedia aims to, claims to, present. I have never seen anything which suggests there's any structural bias or systemic attempt to present a single worldview but this is not evidence that no such thing is there. Most people believe their choice of newspaper to be unbalanced and neutral whereas in reality it just matches their own worldview (including me! The Guardian is super central and moderate!)

I can see that news outlets have a ideological position. I can imagine that Wikipedia might even though I can't see it myself right now. And that got me thinking - doesn't everything get written by someone who has their own worldview? Even academic journals?

Our next activity is to do with online question sites and how much we can trust the answers that complete strangers give us, and should we trust the other complete strangers that upvote the answers. Like with Wikipedia - the question is -

How much should we trust each other?

Permalink 1 comment (latest comment by Alex Bell, Friday, 20 Apr 2018, 12:05)
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