The last three weeks of visualisations I have tried to put emphasis on how best to show the data in a valuable way for teachers. My feelings through this section have been of frustration for several reasons:

• What does the visualisation show?
• What value does the data gathered hold?
• Can any correlations be drawn from this data to research backed assumptions?
• A piece of text might be better at explaining the outcome of the data collection than a dashboard

Williamson (2020) explained the frustration I felt for the first two reasons:

Data and metrics set limits on what can be known and what can be knowable. They define what is rendered visible or left invisible, thereby impacting on how certain practices, objects, behaviours and so on gain value, while others are not measured or valued.

As can be seen by this statement I faced a tough choice when choosing what data to capture and to display I thought “I’m going to miss huge swathes of data that could provide context for the data I’m collecting.” I may be able to show how many times I accessed my phone or laptop, but I cannot show that between 10am and 6pm on Wednesday the reason I did not access my laptop or phone was because the electricity was out because the visualisation doesn’t allow for that. If someone has limited access to broadband for example how can that data be gathered and shown.

In ‘The Platform Society’ (van Dijck 2018) it is stated that “critics draw attention to the fact that none of the presumed benefits cited by platforms have been proven empirically.” If the benefits have yet to be proven by some form of study, the platforms and proponents of online education can make any claim they wish. This is how unregulated areas of the economy function such as the vitamin industry making claims such as a vitamin can stop a virus without any evidence or how certain treatments in the cosmetic sector can make claims like ‘this will reverse ageing.’ If we place education as one of the pillars of society, we should possibly look at some level of regulation to stop wild claims being made.

And finally, after doing six visualisations I struggle to accept that dashboards are the best way to get across information. Within every visualisation I am making personal choices about what colours and styles to utilise and this is very similar to how dashboards and the underlying software is designed. This should not be the case it should be targeted information with as mentioned above some evidence behind what it is showing. With these issues and limitations of dashboards I would believe for the moment they should not be used. I would look at some form of text recap as much information and specifically individual student details cannot be expressed in a dashboard. There is a lot of work around machine learning and text so it would still be possible to provide a version similar to a dashboard but more granular.

References

Williamson, Ben, Bayne, Sian & Shay, Suellen, 2020. The datafication of teaching in Higher Education: critical issues and perspectives. Teaching in higher education, 25(4), pp.351–365.

van Dijck, José Poell, Thomas & de Waal, Martijn, 2018. The Platform Society, Chapter 6 Oxford: Oxford University Press USA – OSO.