Posted on

Do we really need to measure everything? Week 10

It is seldom if ever that my professional life and my studies amalgamate so whole-heartedly. I don’t really know if this is a good or a bad thing because inevitably the short snippets in which my studies present surpass my professional life and leave it behind while I’m still grappling with the issues at hand.

Last week I posted about going on training on Moodle analytics. I thought this would really help me make sense of one of the courses I work on as well as contribute to my understanding of this course.

Unwieldy data, how do we manage it?

How does one make sense of a course that has over 2480 pages and 12 thousand students enrolled on it?

The Tweetorial was much easier to manage but it did make me wonder if there was any purpose to recording students’ activity in open educational spaces. How can we really know that they are engaged? What struck me in our hangout this week is that one of the participants had a different handle and gender than what I have come to recognise. Since he was not in the tutorial as himself, does that mean he didn’t participate?

I went to London and South East Learning Technologies Conference for Health Education. A lot of the discourse centred on ‘technology enhanced learning’. The first seminar I attended was on wearable technology. The speaker spoke of physiolytics, the study of the information retrieved from a device worn on one’s body such at a staff ID card and Fitbit. The doctor presenting spoke of a “smart condom” that measured one’s performance and then fed that information back to an app on a phone. I had to wonder at this point whether man’s obsession with measuring his performance has gone a step too far.

Posted on

Tweet

In one of the seminars I attended this week I heard the term physio-lytics being bandied about. This is the practise, from what I  understand as I haven’t been able to information on it, of measuring and making sense of data that is retracted from wearable technology. It is the information on your staff ID card, Fitbit or smartwatch that will be used for this kind of analysis.

Posted on

Red, amber, green: Learning analytics. Week 9

Is there any benefit to rating students’ success?

I started this week still stuck on how algorithms worked and how they might be seen to influence education. Which lead me to send my first tweet out about asking whether database results could shape research. I tweeted my question and it was in this vein of thought I went looking for any academic papers that could support what I suspected. There were a lot about  bias but I found an example which I saved on Diigo. This article focused on some of the issues around systematic reviews with regards to database searches. It prompted my thinking on how research could be adversely affected by search results but more importantly highlighted the human element of how important information literacy is for scholarly processes.

It was only during the tweetathon I finally felt like I had joined the party with regards to how data and learning analytics play a role in shaping education, but it was quite difficult making sense of what was going on. I felt I was more active than I demonstrated.

I pinned a graphic from Pinterest promising that data mining and learning analytics enhance education which was reminiscent of the instrumentalism around discourse (Bayne 2014) in Block 1.

The TED talk presented how big data can be used to build better schools and transform education by showing governments where to spend their money in education. It made me realise that, when looked at quite broadly, data can revolutionise education.

Finally, I reflected on the traffic light systems that track and rate students, something I’d like to explore further. Ironically, on the first day of week ten, while I was playing catch up in Week 9, I attended some staff training on Learning Analytics, ‘Utilizing Moodle logs and recorded interactions’, where I was shown how to analyse quantitative data to monitor students’ use and engagement.

Bayne, S. (2014). What’s the matter with ‘Technology Enhanced Learning’? Learning, Media and Technology, 40(1): pp5-20.

Posted on

Prevent (and) discrimination. Week 3

Students protesting Prevent Duty Photo: @BeMedia

I’ve been grappling with how Donna Haraway’s utopian metaphor of the cyborg relates to our relationship with technology and contemporary politics, as well as how it fits in with digital education.

If we are to live as cyborgs as Haraway’s metaphor suggests, we cannot divorce our own nature and history from that of our future selves. This seems implausible, unachievable and very much like an allegorical fairy tale from bygone times. But much like those fairy tales about power and loss, we see the dominations of ‘race’, ‘gender’, ‘sexuality’ and ‘class’, by those in positions of power, evident throughout our technological world.

There are countless examples of oppression in relation to technology. There are examples of the disparities; of how wealthy (white) companies still exploit poor (black) countries and their people for their resources without supporting the connectivity needs of those countries. Since The Cyborg Manifesto was published we have seen the gender gap in careers in technology widen. The digital divide is persistent in developed countries with regards to location and income and ethnic background; while undeveloped countries struggle to find alternative ways to access information with the lack of infrastructure.

In relation to education, Watters in her article Ed-Tech in the Time of Trump gives examples of how universities can use data to carry out surveillance on students and staff. She demonstrates how this happens through the collection of data. Using data, universities, big companies, governments and powerful individuals are able to control what we see, where we go and how we access information. This is evident in the UK with the Government’s Counter-Terrorism Strategy and how universities are tasked with monitoring extremism with the Prevent Duty agenda. Students are being monitored more than ever before.

The ‘ubiquity’ and ‘invisibility’ of the cyborg that Haraway dreams of is simply not possible because the technology and the spaces that we inhabit when online, have been taught to recognise us. Technology has been taught to read us, tasked to find out what we like, see what we look like and with whom we engage. It knows what we buy, sell, watch, read, and search for. It knows where we worship and who we love. It knows us. Most importantly technology has been taught to remember this information, this information then shapes our experiences online.

The control universities, companies and governments have over our information perpetuates the injustices and exclusions that occur in the physical world. If individuals are not aware of the information that is being collected, and of how that information is being used, they could marginalised without knowing it.

Haraway, D (1991). “A cyborg manifesto” from Bell, David; Kennedy, Barbara M (eds), The cyber cultures reader pp.34-65, London Routledge

Watters, A (2017). Ed-Tech in a time of Trump. Retrieved: 6 February 2017 http://hackeducation.com/2017/02/02/ed-tech-and-trump