How have global academic developers and their units developed and changed over recent decades?
How has the context in which academic development works is done altered?
What have academic developers and their professional associations learnt?
I was delighted to be able to co-author the “Technologies and Academic Development” chapter with Professors Peter Hartley and Keith Smyth. Our chapter explores “what academic developers need to know and be able to do about learning technologies, considering both breadth and depth of knowledge . . . we concentrate on the functional and educational potential of current and emerging classes of technologies.”
Like a number of my peers, I see myself as a bit of a hybrid academic/educational developer. David Walker and I explored this notion last year in our Chapter on Learning Technologist as Digital Pedagogues in The Really Useful Ed Tech Book.
Our roles in universities are evolving which is good, but we do still need to fight to be heard at strategic levels too. Our chapter explores a number of models that are being used successful to bring around bottom up change and at times more top down strategic change.
I think many of could be drawn to “the middle way” describe by Peter Bryant in his recent post. I continue to support the need for academic developers to be at the heart of developments and institutional strategies relating to (digital) technology and learning and teaching. I’m sure that this book will make a significant contribution to the discourse around the evolution and impact of academic development.
(image: Jeremykemp at English Wikipedia [GFDL (http://www.gnu.org/copyleft/fdl.html) or CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0)], via Wikimedia Commons)
Warning -this is a bit of a moan post.
Last week I attended the Jisc Learning Analytics Network meeting. It was a really good day, lots of people there, lots of good sharing, moaning, asking where next-ing. One of the reasons I find these events useful is that they help focus my mind and give me a sense of relief that some of the challenges that I face are similar, if not exactly the same, as many others in the sector.
In terms of learning analytics, my experiences to date have been metaphor-tastic: (ever decreasing) circles, slopes, dead ends, stop-starts . . . I feel that it’s appropriate reflect on my journey via the well trodden Gartner hype cycle.
I’m the first to admit I enjoyed being swept up to the peak of inflated expectations. Exploring the potential of data and learning analytics was probably the last piece of innovation work I was involved in when I work with Cetis. I really enjoyed trying to figure out the practical applications and meanings for mainstream learning and teaching of the swirly twirly graphs at early LAK conferences. It was great to support the emerging UK community via early SoLAR meeting. I learnt a huge amount being involved in the Cetis Analytics Series. I always think I brought a healthy degree of scepticism to some of the hype of learning analytics, but I could (and still can) see the benefits of extracting, exploring and understanding data around learning and teaching.
From the giddy heights of the peak of inflated expectation, I knew when I moved to a “proper job” within a university I would have a bit of a slide down the slope to the trough of disillusionment. It’s getting out of the trough that I’m finding real difficulty with. Changes in senior management, have meant going through a bit of a treadmill in terms of gaining institutional support and understanding. That’s before even accessing any data.
The Jisc Effective Analytics Programme has been a bit of ray of light and hope for me. Towards the end of last year we took part in the Discovery phase of the programme. This involved a consultancy exercise, onsite for 3 days with a cross section of institutional stakeholders to assess our “readiness” for analytics. At the end of the exercise we got a report with our readiness matrix and some recommendations. You can view our report here.
At the meeting last week a number of institutions who have gone through the Discovery phase took part in a panel discussion about the experience. One common thread was the reassurance that the exercise gave to everyone in terms of being “on the right track” with things. I was pleasantly surprised that we got such good score in terms of our cultural readiness. The validation of having an external report from a nationally recognised agency such as Jisc is also incredibly useful for those of us on the ground to remind/cajole (hit people of the head – oh wait that’s only in my dreams) with in terms of what we should be doing next.
I think one of the main problems with analytics is finding a starting point. Going through the Discovery phase does give a number of starting points. My frustration just now is that my institution is now going through a major rethink of our overall data architecture. So on the one hand I think “hurrah” because that does need to be done. On the other I feel that I am almost back to square one as terms of “business needs” anything to do with learning and teaching seems to fall off the list of things that need to be done pretty quickly. It’s difficult to juggle priorities, what is more important, getting our admissions process working more efficiently or developing ways to understand what happens when students are engaging (or not) with modules and the rest of the “stuff” that happens at University? Or updating our student record system, or updating our finance systems?
Amidst all this it was good to get a day out to find out what others are up to in the sector. Thanks Jisc for providing these networking events. They really are so useful for the sector and long may they continue. UEL who hosted the event have been doing some great work over the past four years around learning analytics which has emerged from their original BI work with Jisc. The work they have been doing around module attendance (via their swipe card system and VLE data) and performance is something I hope we can do here at GCU sometime soon.
In the morning we got updates from 3 mini projects just have funded starting with the University of Greenwich and their investigations into module survey results and learning outcomes. The team explain more in this blog post. I was also very interested in the Student workload model mini project being developed at the OU. You can read more about it here.
The other mini project from the University of Edinburgh, was interesting too, but in a different way. It is more what I would term, a pure LA research project with lots of text data mining, regression modelling of (MOOC) discussion forums. Part of me is fascinated by all of this “clever stuff”, but equally part of me just thinks that I will never be able to use any of that in my day job. We don’t have huge discussion forums, in fact we are seeing (and in many ways encouraging) less use of them (even with our limited data views I know that) and more use of wikis and blogs for reflection and discussion. Maybe these techniques will work on these areas too, I hope so but sometimes thinking about that really does make my head hurt.
I hope that we can start moving on our pilot work around learning analytics soon. ’Til then, I will hang on in there and continue my slow climb up the slope, and maby one day arrive at the plateau.