Tweet! My photography learning for my chosen MOOC and #MSCEDC are coming together

#MSCEDC is represented by some of the books I have read over my studies.

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.

MSCDE has changed me, for the better.

Tweet! Chatting with Myles

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.

A summary of my tweetorial

Tweet! Respecting IFTTT

It’s no secret that I’ve fought a long battle with IFTTT.com in order to get it to act the way I want and do the things I expect of it. This week I chose to look at it from outside the setting of my course blog and look at the tool in its “natural” habitat and I was actually a bit impressed. It can do some really useful things to help make life a bit easier, like send a text to my wife to let her know I’ve left work, or send a text when I am at a certain point on the journey home. This one is handy for knowing when to put the tea on but I found another use for it.  I thought it would be a great piece of data to use to show that algorithmic data can easily be misinterpreted and how different people might interpret it differently.

I set this up to publish a post to my blog to let the world know every time my phone GPS picked up that I was at Moray House, School of Education. My thinking that as a student of Moray House, this would be seen as significant and could be interpreted that I was there to visit the library of for studies. The fact that the algorithm should kick off twice every day, once in the morning and once at around 5:15 pm, I thought might imply that I as arriving and leaving for my day’s studies.

My intention of this play around with the algorithm was to see what conclusions my classmates drew from the minimal data:

  1. Eli is a student of Moray House School of Education
  2. Eli’s GPS from her phone is showing as at Moray House School of Education each morning at the same time and
  3. each evening at the same time.

It’s not a lot of information to go on and therefore involved “interpreting” what this information means. This was exactly the point I wanted to make, that with learning analytics, we are interpreting data, when we may not actually have enough of the picture to fully understand that data in context. As Yeung( 2017) stated of algorithmic use, in her paper concerning the use of data to affect behaviours,

Big Data ’ s extensive harvesting of personal digital data is troubling, not only due to its implications for privacy, but also due to the particular way in which that data are being utilised to shape individual decision-making…

Unfortunately, my experiment didn’t happen as, yes you guessed it, the IFTTT algorithm didn’t work, not even once. So instead of having a minimal amount of data to interpret to represent our possible failures of learning analytics, we have an algorithm that doesn’t fire at all and returns no data. I guess this gives us a whole different learning experience and another algorithmic potential to be critical of.

References

Yeung, K., 2017. “Hypernudge”: Big Data as a mode of regulation by design. Information, Communication and Society, 20(1), pp.118–136.

Tweet!

Helen’s tweet about the lecture this week raised a smile as I was feeling just as excited abut the opportunity to participate in a lecture. Even though I know there is a raging debate about the benefits and drawbacks of our lecture based education system and how effective it may be, I thrive when there is an opportunity to listen instead of reading. Something that there has not been a lot of opportunities for in the ODL offerings I’ve experienced and so I was gleeful.

I wondered if Helen’s joy at a lecture was because it felt more like being an on-campus student and therefore a stronger connection to our assumptions about what it would be like to study at university, or if her joy was because like me she found listening or watching a better tool for her learning.

Whether or not you think learning styles are a real thing (which is a whole different educational conversation), people do have different strengths and weaknesses, different habits and different abilities. Reading and writing are such core values of the education system that they are the backbone of almost every course.

I raise this as an opportunity, with my classmates studying Digital Education with the intention of moving into a career in an educational setting, or indeed who already work in an individual setting – a chance to ask you to think about your course design and how it brings out the best in your students and gives them the best opportunity to learn and I wonder, how will a student with reading difficulties fair in your course? Is there an opportunity to use digital tools in a way that flips traditional teaching on its head, a way to level the opportunity to for all the student on your course?

If you were designing a new course for the Digital Education programme, how would you do it? What tools would you use? What would you keep from your experiences and what would you change?

Just some random food for thought.