We will present a live demonstration of the SAR and detail how the data is presented to senior leaders across the institution responsible for driving enhancement of practice in their own Faculty and Department. Using this data we will unpack the complexities of student engagement and discuss how metrics of engagement such as VLE usage, attendance and library access relate to student retention and performance. We argue that student engagement is a complex, contextually bounded and socially constructed phenomenon (Kahu, 2013) and that approaches to supporting student engagement should be driven by those who are closest to the students, rather than broad centralised engagement strategies.
Our approach to Learning Analytics involves the generation of ‘actionable intelligence’ (Clow, 2013) from a range of data sources that moves beyond demographic data gathered at the onset of the course by using educational data mining methodologies to draw data from on-course learner activity. We describe an operationalisation of the ‘Learning Analytics Cycle’ (Clow, Hall, & Keynes, 2012) that facilitates the creation of targeted interventions at the local departmental level and findings that echo recent research by Tett, Cree, & Christie (2016), which describes the transition to Higher Education and students’ subsequent engagement as an on-going longitudinal process that is more dependent on their on-course engagement rather that their incoming demographic profile.
This discussion will be firmly contextualised in the context of the TEF and how the key metrics of retention, student satisfaction and graduate employment are now gaining significant traction as proxies of practice and student support across the sector. We use our findings to argue that data is a critical component in the design of effective student support systems, but that contextualised decision-making should remain the paramount driver of excellent student support at the departmental level.
Clow, D. (2013). An overview of learning analytics. Teaching in Higher Education, 18(6), 683–696.
Clow, D., Hall, W., & Keynes, M. (2012). The Open University ’ s repository of research publications The learning analytics cycle : closing the loop effectively Conference Item The Learning Analytics Cycle : Closing the loop effectively.
Kahu, E. R. (2013). Framing student engagement in higher education. Studies in Higher Education, 38(5), 758–773.
Tett, L., Cree, V. E., & Christie, H. (2016). From further to higher education: transition as an on-going process. Higher Education, 389–406.