It’s July 2015 which means two things. First, Semester 2 is about to get underway and thankfully (though it’s a two-edged sword) EDU8117, Networked and Global Learning (netgl) is running again. Second, it’s summer in the northern hemisphere which seems to coincide with another round of xMOOCs running out of the US. Time to combine them both.
Week 1 of netgl includes a task that asks the participants to write a blog post about “Me as learner”. The idea is that during the first section of the course the students should head out into the digital world and try to learn something using netgl. Doing so is meant to provide a focus for what they are reading and doing around netgl. What follows is “me as learner” this time around.
What would you like to learn? Why?
Many, many things, but in this case I’m going to try and focus on educational data mining. i.e. the specific algorithms, approaches and software that can be harnessed to analyse and understand the mountain of data generated through the online courses I teach. There are perhaps three main reasons why I want to learn more about this
- Inform research.
I’ve written and given presentations about learning analytics for sometime now. However, the focus of these have tended to be at the organisational or implementation level. Not at the level of actually applying learning analytics to data and revealing something. I need to do this for the reasons below and because I think it is useful research method and that there may be some limitations about how it’s currently being applied. A major barrier in doing this is that while I’m fairly competent from a technical perspective, I’m not strong on “data science”.
Beyond specific learning analytics research, completing an edX MOOC (I’m assuming designed more as a xMOOC, than a cMOOC) while participating in netgl will also provide some interesting insights into the different perspectives that inform different approaches to netgl. Especially if I actually follow through and actively participate in the course both within and outside the MOOC specific space.
- Improve practice.
The majority of my students are online. All of my courses are taught heavily online. Being able to harness educational data mining will help understand what’s going on within these courses and inform future re-designs. But I also think that appropriate application of educational data mining can help with the actual teaching (orchestration). In particular, I think it’s an avenue that can enhance student learning, but also address some of the huge holes that exist in the e-learning infrastructure that I’m currently lumbered with.
Especially because the learning objectives for the MOOC I’ll attempt includes
How to use methods to answer practical educational questions
Observing how and experiencing the design of the MOOC may also reveal some “good practice” tips to adopt. After all, this is a large American organisation drawing on lots of resources and lots of smart people. Surely this poor Australian has something to learn from their experience and use of the e-learning literature?
- Actually complete a MOOC (of any breed).
I’m also hoping that by combining this with EDU8117 that I might actually complete a MOOC. Not something I’ve done previously, and to be honest probably not something I’ll do this time. The week 3 material of the MOOC I intend to undertake has just been released. If this were an Australian university, I wouldn’t be allowed to enrol. It’s already past the week 2 cut-off.
The MOOC I’m going to try and complete is Big Data in Education.
Why have I gone with a formal task?
I had seriously thought about using this as an opportunity to recapture my high school music experience and learn more about playing my birthday present this year (see the image to the right). This is more the type of “learning” I had in mind when designing the “me as learner” task for netgl. The idea was to move beyond more formal learning topics. Some previous participants have taken this approach and tried to learn about topics as diverse as baking bread or playing a particular bluegrass “fiddle” song/approach.
There are two reasons why I didn’t go down this route:
Learning via netgl means (at least for me) making your learning public. Not the end product, but the struggles, small wins, steps backward, and all the other dirty embarrassing missteps that are part and parcel of learning. It’s by making these public that you increase the chances of connections between you, others, and other perspectives and ideas. It’s by making these public that you open up the possibility of netgl really helping enhance your learning. In terms of learning the saxophone that might mean joining Soundcloud, sharing my “performances” (and hopefully their on-going improvement), engaging with critique and learning.
Being open like that is hard. Especially if you are a novice, and trust me it’s 30+ years since I regularly played a saxophone and it shows. Not to mention if you are a middle-aged professional in a job where you’re expected to be the expert (which is just a bit of a laugh). Add in being an introvert and you get the picture.
At the same time, I’m meant to be somewhat knowledgeable about learning analytics. Sharing my learning about educational data mining will clearly indicate just how limited that knowledge is (in one aspect). This knowledge is something that is much more central to my identify as an academic, and yet I don’t feel the same sense of embarrassment about it. Even to the extent that this paragraph is being added after taking some time away from this post.
Chances are that this will sound like a cop out (covering up for the prior and real reason) and complaining about a first-world problem from an entitled, middle-aged white man (especially given experiences in higher education like this), but it’s something that I struggle with and which impacts my life. The teaching workload expected of an academic in my position, combined with the expectation to generate research output, and the horrendous mish-mash of poorly inter-connected information systems provided to complete these jobs means that my time and energy are limited. To meet part this semester I’ll need to teach the two courses I’m directly involved with, keep an eye on another, work on the Moodle “open” book project, most likely take on some other tasks within the School, produce at least one journal paper, and that’s leaving out a range of other tasks (including have a life outside of university).
Focusing on educational data mining allows me to kill at least two (maybe three) birds with one stone.
And perhaps there is an aspect here that I’d like to keep my personal pursuits (playing the saxophone) separate from work.
It’s suitability to netgl? Benefits and barriers?
Well, my participation with the MOOC is only made possible through the use of digital technologies/the network. It’s apparently designed to use the affordances of those technologies by very intelligent folk.
The topic of the course – big analytics – is largely made possible by the increasing amount of e-learning like this MOOC. It’s learning within digital environments that is generating the “big data” that is the focus of the course. Consequently, it’s not surprise that the learning analytics and data mining communities have quite a presence online. I even follow a few members of that community on twitter and via their blogs.
I also have colleagues with whom I’m working on learning analytics related work. Most of that work is being done via digital technologies. Hence, I already have some knowledge and experience working in and with netgl.
In terms of barriers, I do wonder whether the nature of the MOOC platform will cause any issues with being more open. I doubt it, but I’m trying to find some disadvantages.
What is learning?
Ahh, this old chestnut. Wonder if there’s any value in including this, especially if the other participants react to it like I do. Perhaps I should get over myself (I’m not big on definitions).
Let’s paraphrase/extend a Google search result
Learning is the acquisition and application of knowledge and skills
I’ve added “application” and removed “through study, experience, or being taught”. Those changes perhaps don’t enhance the definition.
Wikipedia appears to add the additional clarification of “acquiring new, or modifying and reinforcing, existing knowledge, behaviour, skills, values, or preferences”
That’s enough, time to get started on the MOOC.