Retention

A majority of institutions (11, 58%) surveyed stated retention as a key driver for the implementation of learning analytics. Retention is an important driver as it is stated by the Scottish Funding Council as a marker for progress and ambition.

Definition & background:

Retention is defined as the percentage of full-time students completing first year and remaining in higher education. In the Scottish higher education sector, there is a focus on retention rates, notably for students from deprived areas (SIMD20) or students from care backgrounds who tend to have lower retention rates than average (average retention rate: 91.8%; SIMD20: 87.4%; care background: 87.0%) (SFC statistical publication, 2016-17).

Different factors play a part in student retention, notably, social economic status and background. Consequently, fully understanding the mediating factors are essential to implementing structures and interventions to improve retention rates. This is where learning analytics can play an important role.

Institutions stating retention as a key driver:

• University of Dundee
• Edinburgh Napier University
• Heriot Watt University
• University of Highlands and Islands
• Queen Margaret University
• Royal Conservatoire of Scotland
• Scotland’s Rural College
• University of Stirling
• Open University in Scotland
• University of the West of Scotland
• Robert Gordon University

Learning analytics projects focused on retention:

• The University of Dundee’s Registry are currently running dashboards on retention and progression, by taking data from SITS and pulling it into dynamic spreadsheets.
• The University of Edinburgh was running a pilot using Civitas Learning to improve retention for distance-learning cohorts, however this project was discontinued due to the lack of significant findings. Consequently, Edinburgh is no longer looking into setting up a learning analytics tool as retention is not an urgent interest.
• Queen Margaret University are interested in a learning analytics project that is focused on retention due to students coming from a large spectrum of different backgrounds. The development of their current learning analytics project involves pulling access, inclusion and retention data.

Case study:

The University of West of Scotland implemented a learning analytics project, StREAM (using an external provider, SolutionPath) in 2016 to improve retention rates and overall student engagement. After in-depth research and interviews with academic stakeholders and students, a learning analytics dashboard for student use was developed. This dashboard, entitled My Journey, pulls library data, use of online resources and assessment marks compared to class or cohort averages. This allows staff to identify students who are at risk of withdrawing from their studies and put additional support in place to support their retention and progression. It also allows students to reflect and take control of their own learning.

(https://www.uws.ac.uk/current-students/supporting-your-studies/moodle-myday-myjourney/)

Conclusion:

Learning analytics can help understand the factors underlying retention and could ultimately lead to interventions to increase retention levels. Retention is an important aspect of higher education outcomes, as it is one of many factors stated by the Scottish Funding Council, which can influence a university’s funding status.

References:

Scottish Funding Council (2018). Scottish Funding Council Report on Widening Access 2016-17. Retrieved from (26.03.19): http://www.sfc.ac.uk/web/FILES/statisticalpublications_sfcst062018/SFCST062018_Report_on_Widening_Access_2016-17.pdf