My name is Andrew Dalgleish and I am Head of Digital Services at the University of South Wales library. A large part of my role involves analysing and presenting data to demonstrate the value and impact of library services and our collections. However, the exact influence that an academic library has on the success of an individual student has always been difficult to measure.
Recently, however, universities and colleges are beginning to see the potential of collecting, visualising and interpreting a whole range of indicators of a student’s engagement with their course, their progress and how the curriculum is delivered. These aggregated data are known as “Learning Analytics”. Library colleagues are making an important contribution to cross-institutional projects of this kind.
What is Learning Analytics and what are the potential benefits?
Learning Analytics is measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.
Typical kinds of learning analytics data sources include VLE activity, attendance data, and information from student registry systems such as assessment submission and grades. Library data such as visits to the library, borrowing, use of e-resources and engagement with information skills sessions all have the potential to enrich the picture of the student interacting in the learning environment. Putting all of this data together can reveal patterns of student activity and achievement that can point to improved design of courses and more fluid and effective support.
At University of South Wales, there is a strong sense that learning analytics can be the basis for better quality conversations with students about their expectations and aspirations. We have developed a model of personal academic coaching in which the live data can influence effective interventions by tutors or support staff where there are indications that students may be at risk of dropping out or might be stretched further.
How are we contributing at University of South Wales?
It is still early days, and much of this data needs careful validation and interpretation. Therefore, at USW we are working with JISC to pilot several products.
Much of the activity to date has been to populate a dashboard (“Data Explorer”) that visualises data such VLE activity, attendance and grades. There are different views of the dashboard – personal academic coaches can see data relating to their own students; course leaders can see whole groups of students.
So far, we are providing regular feeds of library borrowing data into the dashboard. This means that people can see at a glance (alongside other data) how long it has been since a student borrowed a book. Of course, borrowing of print books forms a relatively small part of student engagement with the library. In the coming year we are hoping to feed in data relating to how frequently students are accessing their online reading lists and also look at whether we can provide data on downloads of journal articles and e-books for individual students.
All of the data is stored in a JISC national hub and this means it can be used for enhanced analysis. Combined with other data, such as demographic data, this provides the capability for third party solutions to make predictions of student success.
Finally, we are keen to start using JISC’s “Study Goal” app. This is a student mobile application that enables students to see and log their own learning activity, and set themselves targets. It is a sort of Learning Fitbit. Here too, it is possible to see ways in which library activity – such as visits to the library or attending information literacy sessions, could be included as student goals on the app.
Learning Analytics Cymru
In Wales, there is huge potential for collaboration with learning analytics. The recent launch of the Learning Analytics Cymru project provides a framework to share expertise and experience of data analysis and student support interventions. In HE libraries in Wales, our shared library system and existing collaborative work on library data analytics means that the library community is well placed to learn form a community of practice and make an effective contribution to this national project.