Block 1: Week 5 Visualisation

What roles do I play?

Working with many individuals and groups, I was interested to know more about the roles I played in each situation.

Methodology

Using a pre-made list of roles in groupwork (which I thought expansive enough that it might cover all situations I encountered), I recorded data about my role(s), defined as the function I believed it was intended I was to carry out in any work situation, plus other functions I thought I was carrying out as well.

Again, I kept the number of variables small to make manual recording manageable, and simplified the detail to ensure privacy.

Results and Analysis

The experience of having done this in Weeks 3 and 4 made me think about the extent to which my choice of variables to record and level of reduction was having on my visualisation. I decided this time to work against the attempt to make data simple or readable through visualisation.

I removed any indication of day/hour as it suggests it’s an important factor (to me); I have recorded in chronological order, but this to illustrate the mixture of synchronicity and asynchronicity.

What roles do I play?

Waves in water propagate, depending on the context (depth, medium), interacting (interfering) with other waves, adding together or cancelling each other out.

circular waves on water illustrating interferance
“Seattle Rain Drops and Flash” by Spappy.joneS (licensed CC BY-NC-SA 2.0.)

Activities (work, learning) can be counted as isolated events, but they propagate, influencing and being influenced by other activities and their context.

How does this relate to my learning activity?

  • Again, the visualisation uses partial data and lacks context, but so do all visualisations, no matter the amount of data gathered and for however long.
  • Again, I am controlling this data gathering. This time I am conscious of the fact that the simplicity/readability is my choice, not an accident of the data; this is data in itself, possibly the most obvious, the most persuasive, and also the most synthetic.
  • Again, considerably more data would be needed to identify trends, but who has decided that identifying trends is the object of this exercise and what effect does this have on the data gatherer, analyst and visualiser? Without understanding the full context, how would a student/teacher benefit from them? In fact, as we know that the context is always partial, are attempts to recognise/act on poorly understood trends potentially dangerous?
  • Although, some in-depth data on my effectiveness in these roles could have been collected, the actual effectiveness might not be determinable until later, and dependent on a new set of contextual data.
  • Although data might be collected as discrete items, this does not make them unrelated; displaying them as separate points can suggest that they are, yet we know learning activities overlap and interact. Imagine these fuzzy circles spreading outwards…
  • Recording my idea of the roles I undertake, does not say whether or not I carried them out (well) in the estimation of my colleagues; there may be role of which I was not conscious. Again, it is important, when automated systems may nudge a student based on their activity (as it detects it), it may be unconscious of data it cannot collect, that may be as, or more, important.

References

Group work role cards

2 Replies to “Block 1: Week 5 Visualisation”

  1. A very inventive way of tracking and representing your different roles. It’s a compelling example of how even tracking the different roles that one person assumes in their professional life can become hugely complex. Next block we will be considering the role of the teacher with data. I wonder whether we might see very different kinds of roles emerging for the teacher too–a data leader, a data challenger, a data collector, a data subject…?

    1. Thanks, Ben. Again, very much a reduction to make a visualisation possible. I am required to return data on my training courses; fortunately, I am also able to comment on the wider picture (because I don’t think the data really capture the most interesting or significant aspects of what happens.)

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