First Learning Analytics Working Group Session
Now that some of the dust from the VLE transition to Learn Ultra is starting to settle, many of us in EDE have caught our collective breath and have a few minutes to look more deeply into other aspects of our VLE and its associated learning tools and platforms.
The transition to Learn Ultra is part of the VLE Excellence programme, which, as you might be able to tell from its name, is focussed on excellence in the University’s VLE platform and the corresponding digital student experience. Accordingly, we’re seeing a surge of new projects focussed on assessment, feedback, portfolios and learning analytics.
Some of these projects are still in the planning stage, but the project around learning analytics has already begun. Learning Analytics in UltRA (LAURA) aims to:
- identify and develop guidance and training around the learning analytics information already available to staff and students in the Learn VLE and its integrated tools,
- review our current Learning Analytics Policy, and
- network and share learning analytics practice with other higher education institutions.
On the project LAURA team, we’re currently in the information gathering stage. One thing that has become very clear to me during this stage is just how much information there is out there about learning analytics…and just how much clear, effective guidance could help us all make the best, practical use of that data in our actual learning and teaching.
I’ve often found networking and discussion are a great way to help distill an abundance of information. It’s also a great way to see new perspectives, anticipate problems you hadn’t thought about, and encounter bits of information that you didn’t come across on your own. That’s one of the reasons networking, discussing and collaborating around learning analytics is one of the goals of project LAURA.
Data and Networking, by C Romans with Canva AI, Creative Commons CC BY SA
On March 21st, a small team from EDE, in collaboration with staff from Liverpool John Moores University (LMJU), led the first learning analytics working group online session. Our session was focussed on collaboration, networking and discussion about learning analytics in higher education. The main idea was to share our institutional journeys with the practical application of learning analytics so far, look at challenges and successes, ask questions and share ideas.
Twenty-three people from 13 different UK universities joined the online session. Along with LMJU and UoE, colleagues from the University of Northampton and Swansea University gave short talks about their learning analytics journeys.
The discussion was interesting and lively, covering topics like policy and frameworks, training and CPD micro-credentials for staff, engagement and attendance analytics, how staff can use analytics to support students, dashboard experiences, data protection and how compliance monitoring might (not) dovetail with learning analytics for learning and teaching.
It was very interesting to see the wide range of perspectives higher education institutions in the UK take on learning and learner analytics. Depending on their context, different universities obviously had different concerns and foci, some of which centred around how to define engagement, attendance monitoring for compliance, and technical information about particular software.
But for the most part, people found a lot of common ground in what they want to achieve with their learning analytics programme (a better learning experience for students) and what their current challenges and opportunities are.
Each institution is taking its own journey with regard to learning analytics, and that journey is taking place in a world where the sheer amount of available data (and the demand for it) is ever-increasing. Add to this the different types of learning analytics, the question of data quality, and the skills needed by staff and students to make good use of all that information.
I’m optimistic that hearing other perspectives and ideas will help our team figure out how all the pieces of the puzzle might fit together into a learning analytics approach that is coherent, elegant and usable for improving student learning experiences.
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