Week 7 – Line Visualisation

Figure 1 – Line Visualisation

Over the last week I tracked what I did throughout the day. I only marked down a new entry when I moved to a new activity, I did not track how long I did the activities for.

Description of the Visualisation

I took inspiration from Dear Data, Week 7 Complaints, when doing this visualisation.

Each line on the left hand side of the image represent tasks done prior to 13:00 and each line on the right hand side represents tasks after 13:00. The measurements are for 5 days and each day has a different inclination, day 1 starting from the top to day 5 at the bottom.

Legend

Figure 2 – Legend

Reasoning

I wanted to show what it might be like for a teacher looking at data on a dashboard. There are a lot of lines but if there is limited training how do you know which lines are important or something that should be actioned. Even with a legend or some explanation about the graph how can a teacher understand the reasoning or the underlying logic for why something is being shown to them.

Due to limited colours I decided to use the same colours for different tasks depending on what side of 13:00 the task was. I think this brought out a good point, in that teachers are bombarded with graphs and dashboards with different lines and colours but again no training or context to what they mean. One graph could show a yellow line being something important but in another graph a yellow line could be simply an average marker.

1 thought on “Week 7 – Line Visualisation

  1. bwilliamson

    “teachers are bombarded with graphs and dashboards with different lines and colours but again no training or context to what they mean.” Yes, a very astute observation. For many, the answer to this is to train teachers with data skills so they can make better use of graphs and dashboards to inform their teaching and their understanding of students. Do you think this would be the best way forward? Even on a practical basis, how could the average school teacher with a hundred or more students to teach, or a university lecturer with a course of several hundreds, cope with this deluge of visualizations, let alone consider the complex calculative processes behind it, or the relative significance of the measures?

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