I enjoy watching a good game of Rugby Union. In recent years the introduction of a Television Match Official (TMO), slow motion replays from every angle and a body camera worn by the referee have, in general, added to the spectacle and safety of the game. These innovations have indeed ‘made visible the invisible’, but is this always a good thing?
Minor infringements of the rules, or more accurately, what can appear to be an infringement when viewed in slow motion, or from a particular angle are often reviewed by the referee and played back on screens where they can be viewed by the spectators. In some scenarios this can add exciting tension to a game, such as when it’s unclear whether the ball wall grounded and a try scored. However, in other cases tackles that appear high or late can appear much worse than they did in real time. In these circumstances it must take a strong-willed referee to ignore spectators spurred on by the on-screen images and baying for a yellow or red card to be awarded. There have been many instances where I’ve suspected that the referee has been influenced by the crowd’s reaction.
At the same time the referee’s camera provides a close up view of the ball being put into a scrum, which in my view is never straight, such that the opposing side’s hooker has almost no chance of getting a foot on the ball. This seems to have become such an accepted state of affairs that there is no crowd reaction and players are never penalised for the obvious infringement of the rules.
So what has all this got to do with Algorithmic Cultures? As Knox, J. (2014) suggests, learning analytics also ‘makes visible the invisible’’. We saw some of this in the Tweetorial analysis last week. Without analytics would we have had any idea of the gender balance between participants? Would we have known who had the most mentions?’ More importantly are either of these statistics important, or are they more likely to obfuscate and detract from more relevant statistics? Both of these stats have been at the heart of some debate amongst Tweetorial participants, both on Twitter and in blogs. Whilst there hasn’t been the equivalent of the rugby crowd baying for blood, there has been some tongue in cheek analysis and suggestions of possible ‘gaming of the system’, neither of which might have come to light without the automated analytics making the relevant statistics visible.
Is ‘making visible the invisible’ always a good thing? If it leads to healthy debate and new insights maybe it is. Where it distorts and leads to unnecessary conflict I believe it can be detrimental to our efforts as educators.
Knox, J. (2014). Abstracting Learning Analytics. Code Acts in Education ESRC seminar series blog.