Latest figures from the Higher Education Funding Council England (HEFCE) suggest there have been nearly 21,000 students in the UK who left higher education in or after year one in 2011/12 and haven’t returned to higher education. Combined with the recent changes in funding, as well as duty of care for student wellbeing, making informed predictions and successfully identifying at-risk students is becoming ever more important for UK universities.
The University of London Computer Centre (ULCC) has hosted and developed Moodle for the UK education sector since 2006. It now supports over three million registered users, across 100 higher and further education institutions and has seen first-hand how interest in student analytics has grown within the edtech community.
In collaboration with Altis Consulting, an information management consultancy with a successful track-record of working with 25 universities across Australia, New Zealand and the UK, ULCC developed Bloom Thrive.
Frank Steiner, Marketing Manager at ULCC sat down with Peter Hopwood, UK Regional Manager at Altis (below) to find out more about ‘project persistence’, the pilot ULCC ran with the University of London International Academy (UoLIA), which led to the development of Bloom Thrive.
Frank Steiner: You mentioned you are headquartered in Australia and have worked with many universities ‘down under’. How does that experience translate to the UK market?
Peter Hopwood: The Australian higher education system is very similar to the UK – but they adopted the funding model we have now, several years ago. We have seen a shift in how universities have operated since and feel our insight and experience of helping Australian universities to adapt is valuable in the UK.
FS: Speaking of experience, I’ve heard about some impressive statistics from one of your Australian universities; can you elaborate?
PH: On several occasions we have developed bespoke systems that identify students most ‘at–risk’ of dropping out; based on a range of indicators such as activity, engagement progression and demographics for Australian universities. This allowed student support teams to focus their efforts on timely intervention. The University of New England produced a case study and won an award from the Australian Government for innovation in teaching and learning. The case study showed they reduced attrition from 18% to 12% in initial trials, using predictive analytics.
FS: Could you give a brief summary of what the technical teams at ULCC and Altis have been working on during the pilot with UoLIA?
PH: The teams have taken the basic concepts we used in Australia and developed a cloud version of this solution for the UK market, Bloom Thrive. It provides a standard interface for universities to share daily data, which will then be processed and analysed, looking for certain indicators which are weighted for impact and importance. This will produce a range of reports and analyses that institutions can use to spot ‘at-risk’ students. One of the key aspects of Bloom Thrive is that we will look after all the hardware, software, data integration and reporting. As long as institutions can provide data in a simple file format, we can do the rest. This will allow them to focus their efforts on using the information and insight – and interact with the ‘at-risk’ students.
FS: Learner analytics versus learning analytics – what is the difference?
PH: We prefer to describe Bloom Thrive as a ‘learner analytics’, not ‘learning analytics’ solution. We analyse the ‘learners’ to identify if and when they are starting to disengage, allowing student support teams to intervene and offer assistance.