Week 6 – Picnic Visualisation

Figure 1 – Picnic Visualisation

This week I focused on gathering the information I have gathered over the previous three weeks which were:

  • that of distractions (meals, tea, snacks, etc)
  • time outside
  • focus on course materials (reading, twitter, responding to posts, etc)

The reason for this was to show in one visualisation how busy any given week is.

Description of Visualisation

The visualisation is showing a picnic on a bed of grass, there is a blanket in the middle with different plates of food on it and the sun is out and shining.

The idea here is that each of the blades of grass represents a different distraction faced throughout the week. The individual rays from the sun are showing how often I have been outside in the week. On the blanket are different plates which represent different activities surrounding the module/course.

Legend

Figure 2 – Picnic Legend

Reasoning

The idea behind this was to show a teacher that in students lives there are many surrounding items that occur. The blanket which is specifically for items on the course is what the teacher can see but it is important for the teacher to be able to understand that surrounding it from all directions are items that can affect a student.

Teachers are normally very good at understanding that there are other items going on in peoples lives. As we move more towards AI teachers and algorithms making choices on students the above items do not seem to be factored in. I understand that there is discussion about wearables, but that doesn’t factor in personal issues, wearables are more focused on tracking and monitoring of the physical person not the person in a more human / personal sense.

2 thoughts on “Week 6 – Picnic Visualisation

  1. bwilliamson

    I am really enjoying the visualization of all the surrounding complexity that would normally not be made visible by a dashboard or similar software used to represent teaching and learning as data. I also like the way you have drawn on the previous weeks’ dataviz tasks, because it recognizes that different sources of data are often gathered together over temporal periods, so any analysis is inevitably partial and time-specific despite claims to being increasingly comprehensive. I think this is a really compelling way of approaching the issue of ‘learning with data’ because it highlights the contingency and partiality of data, encouraging a more sceptical orientation to the usual claims that the data provide direct ‘insights’ that may even be ‘actionable’. In this sense, it seems to fit with a more ‘critical data literacy’ perspective on teaching with data. I’m still wondering how a critical data literacy course could be designed to appeal to educators, who, it seems, are increasingly under pressure to see themselves as data-driven professionals.

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  2. mofford

    I really like the imagination you have used and how you have created a really memorable image. I particularly like the image of the blanket as the ‘target’ of our effort, one from which we are often deflected.

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