Comments on: Week 1 Summary (Halfway through week 2!)

By: Martyn

Martyn — Tue, 27 Jan 2015 02:52:48 +0000

I completely agree Katherine, the heuristics here enforce the status quo, when we should be looking towards "liminality". I remember reading about "liminality" in the IDEL course, a threshold space where learners are coming to grips with new skills/knowledge and they are displaced from their original states. I thought it was a great way to express what we should be encouraging learners with and echoed Vygotsky and his zones of proximal development. It's worrying that we could get stuck in a heuristic bubble!

By: Jeremy Knox

Jeremy Knox — Mon, 26 Jan 2015 16:42:33 +0000

Good to see this example of the NetFlix algorithm at work Martyn! We’ll definitely get back to this in block 3, when we have a go at playing with some algorithms: http://edc15.education.ed.ac.uk/block-3-cyborg-learners/week-8-algorithmic-cultures-in-education/

Good to hear that the lifestream in working for you, and that you are pulling in some different content and generating some excellent discussion. As we move into week 3, it might be a good idea to continue adding new feeds, perhaps experimenting with YouTube or social bookmarking, such as Delicious or Diigo. This will allow you to comment further on the specific items that are entering your feed in your lifestream summary. It might also be a good idea to add a brief comment to the items that are currently going in (you can do this by simply adding text to the post in WordPress), saying why that particular tweet or article was interesting. This will give you the pointers for more elaboration in the end of week lifestream summary.

As we move towards the end of block 3, it would also be good to bring your explorations back to educational concerns, to try and sum this section up. How have these cultural assumptions about humans and their tools influenced the ways we might understand educational technology?

By: Katherine

Katherine — Mon, 26 Jan 2015 02:21:48 +0000

Yes! A filter bubble is itself a heuristic, so a new one could take us further, to a series of new bubbles!

By: jdarling

jdarling — Sun, 25 Jan 2015 15:25:14 +0000

So a good heuristic would take us outside of our individual ‘filter bubble’ and expose us to ideas / concepts / information that expand our thinking? It sounds a little like what we are trying to achieve with HE?

(You have probably already watched it, but if you haven’t then this TED talk is relevant here: http://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles?language=en)

By: Katherine

Katherine — Sun, 25 Jan 2015 07:40:21 +0000

I finally looked up ‘heuristic’ for some other reading I was doing, and what you say here gives me a chance to use it in context!
A heuristic is a good-enough method of problem solving or learning. Rules-of-thumb, educated guesses, assumptions and stereotypes are all heuristic techniques, as are many computer algorithms. Heuristic techniques are useful for speeding-up decision making, but can be problematic if not based on sufficient objective and theoretical research.
Basically, our problem is that our data feeds allow computers to guess about us, but it’s not a very good guess yet… and more importantly, the best teachers don’t just respond to our preferences and current behaviours, but they model, suggest and inspire ways of being that don’t just mirror past clicks, but suggest whole new modes of knowing.

By: Martyn

Martyn — Sat, 24 Jan 2015 15:12:45 +0000

Thanks Mihael. The idea of a personalised digital tutor is interesting, when we look at gamification in learning and applications like Duolingo I think that’s definitely the way we are going. Also, I think anything that can give you feedback on your learning process is going to push you more and more towards learner autonomy, which can only be a good thing.

By: mkiseloski

mkiseloski — Fri, 23 Jan 2015 15:52:39 +0000

Nice post, Martyn!

In my opinion the algorithms used by Google, Amazon or Netflix – most of which are based on machine learning – are ushering in a new era of personalisation. I see two main problems with this – on the one hand, as you mention, one gets easily creeped out by the feeling that the machines are able to know an awful lot about your preferences by analysing and connecting different datasets. It can become a scary thought, but then again in the end I don’t necessarily have a problem with that (as long as I am aware of what it is I am sharing). Netflix just wants to make money and by better knowing my viewing habits, I am getting to view things I like and they keep me as a customer – a fair tradeoff. The more problematic issue I believe is when my environment on the net is personalised in a way that I remain in my own bubble of preferences. Google already skews search results based on your views. The problem with this is that what you think is the objective reality out there is actually a representation of reality Google thinks you would like. Differing political views might get pushed into the background potentially prohibiting debate and broadening one’s horizon.

The biggest advantages I see in this increasing personalisation, however, is in the field of education. The more we know about a student’s learning progress and mental state the better we can tailor education to their specific learning needs. Perhaps one day every person will have their own personal digital tutor optimising the learning experience in a way that might even surpass the pedagogic ability of even the best personal human tutors out there giving you their undivided attention.