Some time ago I was thinking about how Twitter’s character limitations for tweets imposed brevity and concision on tweet authors. Nonetheless, in spite of those restrictions, when you begin to disassemble a tweet, a rich and complex ensemble is revealed. More recently I’ve been revisiting those actors and trying to think about them in terms of what they ‘do’ when enacting different practices teachers associate with professional development. The thing which most struck me was that different actors play a more or less significant role depending on the practice in which they’re involved. For example, the ‘Follow’ button is clearly significant in the activity teachers call ‘connecting with others,’ but is (arguably) less important when ‘discussing issues.’ I then began to consider how it might be possible to map the significance of different tweet actors as participants in different professional development activities. These ponderings produced the following vis:

The intensity of the colour provides a sense of the intensity of contribution towards the PD activity. I decided on just three levels of gradation and no colour indicating no involvement. Why not two or four levels? Well, three seemed manageable; most intense colour suggests a strong involvement, least intense only weakly involved, with a mid point for actors which contributed somewhere between the two. Could I have gone for strong, weak and not at all? Sure. I make no apology for this being a highly subjective process and acknowledge that not only could someone else assign different levels of intensity, there would be some actors I included that they might not see as relevant, and vice versa. Therein lies the real issue. Producing this vis reminded me that PD activities, tweets and the tweet actors involved in the learning assemblage will be done differently by different teachers. ‘Sharing resources’ is not a single activity but is enacted differently by those involved in that assemblage. The above vis provides a sense of what that is like when I’m participating, but for you, it’s likely to be completely different.

The above matrix is far from complete. Not only are there many other activities and practices which sometimes contribute towards Twitter PD, but listing these particular actors from this snapshot of a tweet necessarily omits other actors with whom they are entangled. A URL for example is completely entwined with the textual characters which compose it, the location which it references, and the infrastructure which enables the connection to be made when it is clicked/tapped. Bringing to the fore some actors whilst backgrounding others becomes a necessary strategy for at least two reasons. Firstly to follow one particular actor, the tweet, which seems fundamental within Twitter PD practices, whilst recognising that the tweet itself is an assemblage. Secondly, making a cut is needed simply to avoid overload and analytical paralysis which would be inevitable when you know one actor-network is part of another which is part of another and …

The visualisation as presented here is less important than the process through which it was composed. The issues, the reflections, the decisions that arose when attempting to summarise my thinking on this, iteratively shifted that thinking.

Once more I’d argue this illustrates how visualising is at least as much about analysis as it is about summary and presentation.


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