MEGS-KT: Getting to Grips with Learning Analytics (Jisc project)



Learning Analytics is one of the buzz phrases du jour, but what does it mean in practice? Here is the first in a series of posts on the lessons that we have learned through our Jisc Business and Community Engagement project, MEGS-KT.


About MEGS-KT

MEGS-KT has been bringing regional academia and industry together around a seminar series and social media, as one of the eleven projects funded by Jisc under the Open Innovation and Access to Resources programme.  We will also shortly be opening up a website co-designed by this community, and featuring selected Open Educational Resources made available by the project partners at Loughborough University, the University of Birmingham and the University of Nottingham.

To give a flavour of the social media side of the project, try following @GreenEnergyHero on Twitter (see profile screenshot above). And here is a capture of a recent MEGS-KT seminar from Carl Benfield, CEO of Ashby-de-la-Zouch based Prescient Power. In this talk from January 2013, Carl spoke about the opportunities, limitations and challenges of renewable energy:




What's all this about Analytics?

Our Universities have a wealth of online resources and both campus based and distance learning opportunities available, with much more to come. As we have seen from the recent surge of interest in MOOCs and the UK's FutureLearn project (see my blog post "The Perfect Storm"), there is substantial interest in open online courses both as a marketing device and potentially as credit bearing activities for Continued Professional Development.

In the MEGS-KT project we are particularly interested in exploring the distinction between formal and informal learning. Here are a few themes:

  • Can we spot when a hobby interest has become an all consuming obsession and a potential new career direction?
  • What feedback can we bring to our own teaching and research from the insights provided by a larger community of practitioners and enthusiasts?
  • How many of our community members will subsequently sign up for a short course, and work through to gain a postgraduate certificate or diploma?
  • Will they interact with our systems, services and resources in a profoundly different way to other students?
  • Can we create "critical mass" in the project timeframe, so that the community is essentially self-sustaining? (always a tricky one!)

We expect that many participants in the MEGS-KT project will engage with online material that is signposted by the MEGS-KT site, and the site will generate extensive statistics via mechanisms to submit and rate user generated content.

But, we also already have access to lots of interesting information that can be gleaned from our GreenEnergyHero Twitter account and associated LinkedIn group - and from the logs of our Virtual Learning Environments.  Let's go on a whistlestop tour - we'll come back to some of these in more detail in subsequent MEGS-KT posts.


Twitter Analytics via TAGSExplorer

Martin Hawksey's TAGSExplorer tool is particularly good at visualizing Twitter activity around a search term.  Here you can see a breakdown of the proportion of tweets to retweets and replies, and which users have particularly engaged with us:



Behind the scenes, TAGSExplorer automatically harvests Twitter activity relating to a particular search term and collates it into a Google Docs spreadsheet, as shown below:




LinkedIn Group Analytics

Now let's move on to LinkedIn, which provides some rudimentary analytics for groups, such as the breakdown shown below for our East Midlands Green Energy Heroes group:


Whilst the information provided by LinkedIn is principally of marketing rather than pedagogical interest, we are provided with some interesting statistics on our group's demographics such as where people are based, the industry they are working in, and their seniority. There is some potential for confusion here around labelling - for example, if you were a University researcher in renewables do you see yourself as working in the Renewables or Research categories?

LinkedIn also offer an extensive Application Programming Interface, but there are some significant restrictions on what we can do with this, as noted in their Terms of Use, e.g.
Excluded Uses 
The use scenarios below are not permitted under these Terms. You must never do any of the following: 
[...] 
d. Sell, lease, share, transfer, or sublicense any Content or access to any Content, directly or indirectly, to any third party, including any recruiter, data broker, salesperson, or advertising-related entity.
e. Offer API search results as aggregated search.
f. Commingle Content from the APIs with any LinkedIn data obtained directly or indirectly from another source, including data scraped from our Website or data provided by a third party. For example, you cannot supplement the Profile Data you have received via the API with other LinkedIn information obtained from scraping our Website, whether that scraping was done by you or a third party.

Moodle Analytics

Beyond this, we want to study patterns of engagement with the Virtual Learning Environment (Learning Management System for US readers ;-), and will be particularly targetting the Moodle software used at Loughborough and Nottingham.

At Loughborough we had already extended Learn (our enhanced version of the Moodle software, as shown in the screenshot below) with some bespoke reporting:



Examples of our custom Moodle reports include:
  • Activities Audit: See by department which course modules are using which Moodle activities 
  • Department Resources: A report listing learning objects per department 
  • Discussion Groups: A report listing the forums on Learn, ordered by the most to the least posts 
  • Module Instances: A list of active module instances 
  • Module Resources: A report listing each module and the total resources it has 
  • New Module Resources: A report that shows the modules which have had resources added to them today 
  • Employability Award: Student percentages by department 
  • Employability Award: Student names by department 
I should mention that the Employability Award is a local Loughborough initiative to help students demonstrate their capabilities and develop a more rounded profile through participation in activities outside of the degree programme, such as work experience.

For the MEGS-KT project we are building upon this prior experience and starting to take a deeper look at patterns of engagement and resource usage. For example: Can we predict which VLE resources in the renewables area are going to be of particular interest to our community members based on student usage patterns from our courses?


More on Learning Analytics

If you are new to Learning Analytics, then a useful starting point is the Society for Learning Analytics Research website. The presentations from LAK12 and the SoLAR Flare UK event in November 2012 are likely to be of particular interest. A very helpful resource has also just been published by JISC CETIS:  Infrastructure and Tools for Analytics, by David Sherlock and Wilbert Kran.