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A final note on H817

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I completed my EMA about social learning analytics with full weeks to spare. (2 of them to be precise!). It came together gratifyingly nicely and I enjoyed it. Of course it's possible that my tutor will disagree and give me a dreadful mark (not due until December!).

But I had mere weeks off from studies and have now begun H818 - The Networked Practitioner. I want to get MAODE done and dusted by the end of 2020 so can't afford to rest on my laurels!

Watch this space for my H818 adventures!

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Is Big Brother Listening? Social Learning Analytics

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The opening paragraph of this paper by Dawson et al. neatly summarises a major weakness with learning analytics - that the data gathered is gathered incidentally rather than with pedagogical intent.

The obvious question to ask is 'what data would be more useful?' and then 'how can we collect that data?'

Social Learning Analytics is based on the premise that the answer to the first question is 'information about the interactions between learners' based on the observation that knowledge is increasingly distributed and learning has become less about learning knowledge from a 'wise sage' and more about connections and collectively held knowledge.

The second question - how can we collect that data? - presents a problem. It is not difficult to track forum contributions or similar within an institutions VLE. The interactions can be automatically tracked and the length, time of and words within those posts can be classified and codified but the assessing the quality of engagement requires human input. This is merely the first issue: most interactions between students don't happen within the VLE. However slick an institutions VLE is it is unlikely to be as intuitive, familiar and easy as platforms like Facebook and WhatsApp. Students will opt for easy for them over helpful for the institution.

The idea of any institution monitoring and analysing my Facebook and WhatsApp conversations is creepy!




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An introduction to Social Learning Analytics

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