Instagram: The history of algorithms.

How are all these people linked to algorithms?

This was in a presentation I saw today. I wish the speaker had expanded on this and explained how all these people are linked to algorithms. #mscedc March 22, 2017 at 04:43PM


I managed to look into this a little bit after the conference. Something that struck me while looking at the picture presentation of the speaker was that all the pictures were of very old white men, except for Al-Khwarizmi, who was Arabic. I found a nice timeline with a representation of the history of algorithms. At least here they mentioned Ada Lovelace.


This post of mine didn’t particularly relate to this week’s theme but I thought it was interesting. Students training to be paramedics and working for the ambulance service are now able to train is environments that simulate real-life situations in real time. Immersive Technologies, the company that makes this possible, can provide any situation as long as it can be filmed by a camera. I thought that learning like this provides students with more learning opportunities than they would have without it and it demonstrated explicitly how technology can provide students with many more possibilities.


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.

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.