Block 1. Week 3. Learning: Conceptual Space

This data visualisation aims to represent how a student’s conceptual space expands in response to provocations made via the use of a range of media. It hones in on four of many aspects to this topic: (1) The question (or theme or subject) that provokes a thought (in this case, on either learning, personalisation, or data); (2) The media though which these thoughts are provoked (either via course readings, Twitter, or our course blogs);  (3) The emotion associated with my own response in each case (interested, excited, puzzled); (4) The dimension of response (small, medium, large) to what is asked or under discussion.

This visualisation could be used to demonstrate how our learning processes are not just cognitive or social. They are also charged with emotion. Influenced by Bulger (2014:4), I took a shot at defining personalisation here. But personalisation so understood makes the learning process an almost solipsistic endeavour devoid of emotional tone. Individual preferences and competences are adapted to; social and emotional dispositions are ignored. When Jeremy misquoted me I was annoyed – an appropriate emotional response to what Peet (2015) calls interpretative injustice. The learning process is laden with emotion. Personalisation fails to accommodate this. It’s missing from what Eynon (2015) calls the quantified self.

Word count: 200 words.

7 thoughts on “Block 1. Week 3. Learning: Conceptual Space

  1. The visualisation is brilliantly artistic which really adds to the overall experience of the data and it is clear to understand but you see more as you look more closely at it.

    I’m curious about what the visualisation is trying to be. Is the idea that they are flowers or petals?

    Also I get the frustration about being misquoted. I am curious if this is something that happens more on social media. I see it a lot with people who post things, generally jokes or mean things and then someone calls them out and the answer is nearly always “that was a joke” or “you’re taking me out of context.” If there is no ability for that human element there is so much room for the wrong interpretation to be taken. If an algorithm is making a decision on the language of a student that could be rather damaging.

  2. Very good visualisation here, great to see you mirroring the ‘postcard’ format from the Dear Data project. You’ve clearly put a lot of thought into the visualisation itself, which is an excellent depiction of your course related activity this week.

    I really like the way you’ve thought about space, movement, and connection here, and you’ve managed to represent so many aspects. It is also really interesting that you’ve clustered you activity around emotional responses, rather than days of the week, for example, which is really refreshing Relating these four aspects (question, media, emotion, dimension) provides a rich insight into your week.

    I must admit that it took me a few minutes to decipher it. Not that that is necessarily a bad thing, but I wonder what you thought about the ‘readability’ of this? Often data visualisation is promoted as providing ‘straightforward’ insight, as if we don’t need to interpret anything. However, interpreting your visualisation was kind of exciting, and made it seem more worthwhile to do so – what does that say about ‘readability’ I wonder?

    It would be useful to also read more about some of you decision-making with respect to the design of this visualisation, e.g. why this particular colour? Why this shape? How do your design choices relate to the ‘readability’ of this visualisation?

  3. This looks very beautiful! Can I get the postcard, maybe?:)

    I am with you here, the learning process is so multifaceted and can hardly be captured with the help of technology to the full.

    Getting back to your experience last week, was it easy to track your own emotions? Was it helpful in terms of learning?

  4. Very intriguing visualisation, takes lots of examination to take it in, and then, I think I’ve only seen a glimpse of what’s going on.
    Were you surprised at your mapping for the week? Do you think it will have an impact on future weeks?

  5. I love your visualisations! These cards could be part of the ‘Dear Data’ book 🙂
    I find it very interesting how you recorded different layers of data, all of which give a deeper meaning to the visualisations. For me it was a challenge to track ’emotions’ for the first visualisation… I’ll try to do it this week!

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