Week 10: Insights from Football Manager

Upon completing Knox, Williamson and Bayne (2020), I did a Marty McFly (see image 1) and went, “Whoa, this is heavy.” It was heavy firstly because it again felt like I’m a mechanic reading about rocket science. Nevertheless, this is one reason why I signed up – to learn about things I don’t know. The second reason why it was heavy is that the article brought up some dark thoughts.

Images were taken from Zemekis, R. (Director). (1985). Back to the Future. [Film]. Universal Pictures.

Sorry, Huw. The curriculum team has definitely saved the be(a)st for last. My posts might be more exploratory and reflective and less argumentative, insightful and entertaining. As usual, it’ll be great if you could point me in the right direction where possible. I’m keeping a reading list for the holidays (if I get out of IDEL alive).

I think the earliest exposure to datafication I had was the football management simulation video game, Football Manager (then Championship Manager). In Football Manager players are given scores (highest = 20, lowest = 1, random = 0) for their playing attributes. As seen in image 2, poor Diogo Pereira has an abysmal long throw (3), average determination (10) and poor bravery (8). According to Espen (2020), there are also hidden attributes, such as consistency, versatility and injury proneness.

Image taken from Sports Interactive. (2020). Football Manager 2020 [Video game]. Location: United Kingdom. Sega.

Football Manager reveals a few problems with datafication in education. Image if students were to be given scores for attributes such as ability in English, ability in Mathematics and motivation.

The first problem we have is latent variables. An attribute such as “long throw” is a manifest variable that can be directly measured or observed. We could measure the distances of a player’s long throw and provide an accurate measure. Similarly, it is possible to provide a fairly accurate measure of a student’s current ability in English or Mathematics. In contrast, who decided Pereira’s determination and bravery scores? These are latent variables that cannot be directly observed and need manifest variables attached to them as indicators to test whether they are present. In the same vein it is a lot harder to gauge a student’s motivation. It is possible for a student to not have the same motivation across different subjects. Motivation is also very fluid. For example, a death in the family or the common cold could severely affect even the most motivated student.

This leads us to our second problem – biased raters. I know that standardized testing has gotten a bad reputation in recent times (Delgado, 2018). But unlike a standardized test, a rater could possess various biases (e.g. attractiveness bias). As discussed in a previous post, Singapore recently decided to do away with standardized tests and examinations for primary 1 and 2 students. Student will be assessed by their teachers. It is very easy in this scenario for a teacher to confuse “responsibility” with “subservience”. Would a student who helps the teacher carry books to the staff room daily be considered responsible because he or she take the initiative to carry out a duty?

A third problem is the invasion of privacy. Who gets to view the data? I shudder at the possibility that a student’s “integrity” score could be made public. It seems like some schools in China have already started using AI and wearables in the classroom, as seen in the video below. There have been some public outrage with regards to invasion of privacy. Moreover, as seen in image 1, a comment by Yelisyeyenko (2020) highlights the possibility of this technology and datafication can also be used on teachers to show how “invested and focused they are” in education.

Video is taken from Wall Street Journal. (2019). How China is using artificial intelligence in classrooms [Video]. https://www.youtube.com/watch?v=JMLsHI8aV0g&t=84s

References

Knox, J., Williamson, B., & Bayne, S. (2019). Machine behaviourism: Future visions of ‘learnification’ and ‘datafication’ across humans and digital technologies. Learning, Media and Technology, 45(1), 31-45.

Delgado, P. (2018). The problem of standardized tests. Observatory of Educational Innovation. https://observatory.tec.mx/edu-news/the-problem-of-standardized-tests#:~:text=One%20of%20the%20most%20significant,the%20answers%20are%20multiple%20choice.