As a Level 2 Professional Tweet Paladin (according to Tweetails.com), the Tweetorial was an ideal opportunity to see how else Twitter can be used in an educational context. In the past I have discussed ideas around using Twitter as a feedback tool, but the concept of a ‘Tweetorial’ was a new one to me. I generally use Twitter for the content it delivers rather than a communication tool, aimlessly scrolling down the timeline stopping once in a while to check out an appealling tidbit, usually around Music, Football, Technology or Learning. According to Tweetails, I post an average of 1.16 tweets per day supporting the idea that I mainly use Twitter as a ‘research’ tool.
I went into the first day of the Tweetorial a little apprehensive about how to approach it, how often I should tweet and who should I reply to, however, the sharing and collaboration soon began with some valuable discussions emerging from the #mscedc hashtag.
On first viewing of the Tweet Archivist results, it seems our Tweetorial made a large impression with the #mscedc hashtag appearing on timelines 142,883 times (over a 13 day period). This impact is obviously pale in comparison to the the multimillions of impressions made per day from popular hastags such as #WorldCup or #BringBackOurGirls, however our ‘Tweetorial’ still showed how even a small group conversation can have some sort of impact on a global scale when it takes place in a digital space. It was interesting to read that ‘just like Facebook, what you share on Twitter isn’t seen by all your followers’, I wonder how this affects the validity of the impression and reach?
Analysing the ‘Top Words’ and ‘Top Hashtags’ graphs, we can see that the word ‘trouble’ is mentioned quite frequently, possibly suggesting that the main talking points were around the negative connotations of algorithms rather than how they can be of benefit to us in online spaces, as well as online learning spaces.
However, on closer inspection, ‘trouble’ was mentioned in regard to Sian’s inaugural lecture on ‘The Trouble with Digital Education’, rather than suggesting algorithms are a nuisance
— Sian Bayne (@sbayne) March 2, 2015
The main body of communication and discussion during the Tweetorial took place on the 13th March according the the Tweet Archivist results. Unfortuntley I was unable to participate fully on this day and therefore felt as if I didnt get the true ‘Tweetorial’ experience. I did however contribute some tweets during the previous day, but I mainly used the Tweetorial as another method of gathering research rather than a discussion opportunity. I also wonder whether this is because I am so familiar with using Twitter in this way, rather than an active communication tool thus making me rather cautious about the process.
The benefits of conducting a Tweetorial became clearer as the conversation moved on, bringing in external commentators for further debate.
— Ben Williamson (@BenPatrickWill) March 12, 2015
This shows how discussions within open social spaces can have huge positives by bringing different opinions and ideas outside the main group of learners. There are of course risks attached to this sort of open discussion, such as flamers or sabotages, however we were fortunate enough not to have any issues around these areas.
The ‘Tweetorial’ allowed for sharing useful links and articles between participants with @ leading the way with 59 tweets using the #mscedc hashtag sharing various gems and discussing ideas around algorithms.
I came in around the middle of the group with 11 contributions during the Tweetorial, but feel as if I could have got more into the process if I was around all day on the 13th March.
The question around what can we learn from all of this data, and how would we do it differently in the future begin to emerge.
‘Learning Analytics, which is fundamentally interested in providing a view, not an image; with ‘making visible’ the realities of educational activity so that positive intervention can take place?’ (Knox 2014)
So, it is crucial to act upon the data rather than just study it. Continous analytics throughout a course life span allows tutors to tweek elements during the course rather than having to wait until it is over.
Knox, J. (2014). Abstracting Learning Analytics. Code Acts in Education ESRC seminar series blog.http://codeactsineducation.wordpress.com/2014/09/26/abstracting-learning-analytics/