My academic blogging goes back more than the eight years I have spent with my own account on WordPress – my first doctoral blog post was on 9 Nov 2015.
In it I noted, ‘I was at Dave Wield’s U500 seminar on research methodology yesterday, and remembered how crucial research journals are. Thought I’d take a break from the one for my Masters and start once again.’
I now have no memory of that Masters blog, but the research journal that I began on Blogger and then imported to the university’s installation of WordPress is still there, and I still occasionally add to it, and still make use of it.
It still has the great advantages over a physical research journal that I can search it very easily, and that it is available to me wherever I have an Internet connection.
I am one of the chairs of this learning analytics networking event that takes place next week.
Doug Clow and I took a new approach to presenting at ECTEL 2015. Our paper Moving through MOOCS: pedagogy, learning design and patterns of engagement was jointly authored with researchers from Edinburgh, Leeds and Birmingham. It combined a number of studies, involving cluster analysis of different MOOCs. An enormous amount of information to cram into a 20-minute talk.
So we produced two sets of slides. The first, available on my Slideshare account, takes viewers through the paper in detail. The MOOCs, the methods, the clusters. The second, available on Doug’s account, focuses on a simpler message – that massive open online courses vary enormously in pedagogy and in learning design. Before making grandiose claims for generalisability, we need to check whether our findings really apply widely – or if they actually only apply to MOOCs on our platform or in our subject area, or within our university. While almost all the people in our audience had visited at least one MOOC, the majority had not visited more than one MOOC platform.
You can investigate our research further, taking the detailed route via one presentation, or the route with a simpler message and better pictures via the other, or the complex but clearly mapped route by reading the paper. Or, if you have the energy, you can explore a combination of routes and find out which works best for you.
Of course, this isn’t a fair test. The presentations aren’t offered in the same way and in the same place. Nevertheless, Doug and I will be looking at the stats for each of them, and making anecdotal use of those figures for some time – so choose your route wisely.
As I type, one of the Slideshares has 636 views, 5 likes, 5 downloads, 5 LinkedIn shares, 1 Facebook share and 24 Tweets.
The other has 571 views, 3 likes, 0 downloads, 0 shares on LinkedIn or Facebook and 25 Tweets.
The paper, following the link above, has 99 downloads and 2 Tweets
I was invited to give a guest talk on Scaling up Learning Analytics at the ALT-C conference in Manchester during September 2015.
I talked about how innovation in technology-enhanced learning (TEL) always requires us to take into consideration all aspects of the ‘TEL Complex’. It’s not enough to think about just the teachers, or just the learners, or the researchers, or the technical experts, or the administrators. For an innovation to take root in an educational establisshment, it need to take all those communities into account, and their practices, and the environment in which they are working – including the funding context and the policy context.
That’s a lot of things to think about at the same time, and the Rapid Outcomes Modelling Approach (ROMA) provides a way of doing this. It starts with a vision or, more prosaically, the definition of a set of policy objectives. The next stages are to map the political context, identify key stakeholders, identify desired behaviour changes, develop an engagement strategy, analyse internal capacity to effect change and establish monitoring and learning frameworks. The process is a cycle, only coming to an end when you are clear that you have achieved your vision.
The ROMA Framework was developed by Young and Menizabal, and adapted by Macfadyen and Dawson. More detail in this paper, Setting learning analytics in context: overcoming the barriers to large-scale adoption.
On 3 September, I was invited to give a keynote talk for GMW (Gesellschaft für Medien in der Wissenschaft – Society for Media in Science) in Munich at the Interdis 2015 conference.
The promise of learning analytics is that they will enable us to understand and optimize learning and the environments in which it takes place. The intention is to develop models, algorithms, and processes that can be widely used. In order to do this, we need to move from small-scale research within our disciplines towards large-scale implementation across our institutions. This is a tough challenge, because educational institutions are stable systems, resistant to change.
To avoid failure and maximize success, implementation of learning analytics at scale requires careful consideration of the entire ‘TEL technology complex’. This complex includes the different groups of people involved, the educational beliefs and practices of those groups, the technologies they use, and the specific environments within which they operate. Providing reliable and trustworthy analytics is just one part of implementing analytics at scale. It is also important to develop a clear strategic vision, assess institutional culture critically, identify potential barriers to adoption, develop approaches that can overcome these, and put in place appropriate forms of support, training, and community building. In her keynote, Rebecca will introduce tools, resources, organisations and case studies that can be used to support the deployment of learning analytics at scale.
I just hit 10,000 views on a presentation I uploaded to Slideshare a couple of months ago.
I’m pleased, but puzzled. There’s no clear reason why ‘Learning design and learning analytics‘ should have proved to be so much more popular than my other Slideshares, which typically get 500-1500 views.