Ok I’m going to explain the cheese thing which happened during the tweetorial. it seemed crazy to some of our class, but I assure you it was a genuine testing of algorithms.
During the tweetorial, there was a question raised about the amount of new followers some of us seem to have collected especially since the algorithm block of the course. This led to an experiment to find out what was catching the attention of whatever bot or algorithm which was deciding that these random people would be interested in our tweets. Hence Nigel’s play with hashtags and keyword son cheese. I had done the same on roller skates, but since I was working during the tweetorial I only managed a couple of tweets on this, so poor Nigel took the brunt for the weirdness.
I didn’t get any new followers interested in roller skates 🙁 but it was really interesting to try to reverse engineer the algorithm.
It’s a nice feeling when you see something and instantly know one of your classmates would be interested in it. It shows the community building going on, that we are getting to know each other and more importantly that the work each of us does on this course, resonates with our classmates.
This is a really interesting topic Cathy, I read about it last week and it really got me thinking about the recommendation algorithm we were all talking about in relation to recommending courses. Apart from the obvious of the authority in charge of the recommendations and their motives for the recommendations, I worried about how it could be used or abused by the person being given recommendations.
I know from working at a Uni that there are a lot of students who choose their courses based on how easy they think the assignments sound and how the course fits into what they want to do (like no group work). So I wondered about how we’d sell this recommendation, if we said, here are courses that people who took your course passed, would that influence students to choose courses because it might be an easy pass?
Yeung, K., 2017. “Hypernudge”: Big Data as a mode of regulation by design. Information, Communication and Society, 20(1), pp.118–136.
from Comments for Cathy’s Lifestream http://ift.tt/2o4cdEc
We’d noticed that we’d gain an awful lot of new twitter followers who seemed to be some how involved in advertising, media or statistical companies and we were playing with keywords and hashtag to see if we could manipulate the acquisition of new followers.
That of course became a hilarious back and forth of cheese jokes as Nigel tried to gain cheese related followers and I tried the same with roller skates.
I didn’t get any roller skate related followers though 🙁 just more statisticians.
from Comments for Matthew’s EDC blog http://ift.tt/2nIXOOx
I enjoyed the MOOC from block 2 so much that I carried on learning from it in the little bit of spare time I have (aside from work, masters study, family life, my blog, my youtube channel and sleep). This week I had an assignment of taking a self-portrait BUT I couldn’t be in the picture.
It was a really fun assignment which meant I had to do a lot of thought about what would represent me in a photograph. My usual gardening, cooking and cycling were evident, as was my brewing, but right up there was also my studies in MSCDE. The study, Moray House and now the University have all become so much an important part of who I am that I couldn’t possibly leave them out. A very big change from the very first blog post I wrote as part of IDEL where I spoke about how I didn’t feel like I was part of the university. now I find myself thinking about, using and talking about my studies as part of my job, I feel like I have a much better understanding of what I do as a learning technologist, and more importantly what I could do.
I sometimes forget that we don’t all work in a higher education institute and sometimes the actions and behaviours I experience as normal every day seem very different to those outside the H.E. circuit.
I feel that learning analytics is one of those very things, but the shoe is on the other foot. As a learning consultant for a non education establishment, my entire job was based around being able to provide data to prove the value of the training we offered. If we couldn’t prove with analytics, that the training was making a positive impact on the business then it wasn’t deemed important enough to have. There was no place for personal development or learning that didn’t directly feed into the bottom line.
I sometimes wonder now as I progress through the different courses in the MSc, how my classmates from different backgrounds and even other H.E. institutions take onboard our learning, how it relates to their work place and if they are on the same journal as me or if they are indeed taking a very different perspective on the things we learn.
I guess it’s a fantastic way to introduce the idea of interpretation to this weeks workload. We all start with the same raw data, how we interpret it will then factor into how we will use it. Something which I am sure will come up frequently as we continue our fun with algorithms and learning analytics this week.
Let’s get rid of the elephant first, this week I did a lot of tidying up as the tweetorial took over my blog. Twitter dominated and it was messy, I can’t have disorder or mess. You can now read all the tweets in one nice, neat post.
Adventuring through classmates’ blogs this week also gave me a couple of smiles, Claire and I have a TV show in common and Renee found a brilliant infographic which I stole. I also enjoyed some recommended readings which tied into an article I shared from my pocket.
Youtube fun was to be had with a video talking about algorithms in the financial sector and how they are causing physical changes to our world and there was excitement as I had a play with IFTTT to try to show the potential pitfalls of humans interpreting algorithmic data. Then disappointment as it didn’t work but still a valuable thought. I pinneda great picture of a digital footprint to talk about the information we harvest from students here at Edinburgh and how we might be using it and I joined Helen in celebrating our real lecture, like “proper” students 😉 which served nicely as a chance to challenge course design for all and not the assumption of a student.
This week has felt balanced and productive and I feel I have progressed with some of my digital choices, learning their benefits, was that the point of making me use IFTTT perhaps and I had space to contemplate and to share thoughts. A successful week.