Contributed by Andy Ramsden, The University of Law 

The deployment of student engagement analytics in higher education signals a move away from a ‘one size fits all’ approach to the promise of a better, more personalized experience for students based on individual needs and with the objective of ensuring successful outcomes. In this blog, The University of Law demonstrate how universities are using this rich data insight to inform, revise and remodel their approach to student support.  

While the technology behind gathering student engagement analytics may be alien to some, the logic behind studying students’ progress and behaviours to improve their experience and performance is clear – Andy Ramsden, Director of Technology Enhanced Learning & Teaching and Learning Analytics at The University of Law.

Data should underpin everything we do in higher education, and data insights provide the lubricant for transformational change. At The University of Law, we are committed to using data to make better, informed decisions. And in my relatively new role, I aim to drive our strategic vision for the University’s student experience and academic model to the next level by providing timely, actionable insights. 

Embedding data decision-making throughout  

As part of this model, we are utilising student engagement analytics in a number of ways, including enabling a concierge type service, where a dedicated team of Student Journey Advisors (SJAs) act as the students ‘go to’ source for information, signposting, facilitation and support for all non-academic matters.. The SJAs work collaboratively with our Academic Coaches, who focus on developing the academic side of the student. All with the aim of adding value to our students learning journey and outcomes. 

We’re also using engagement analytics to provide insights on the curriculum, looking at how we can most effectively design for different modes of learning.  

Our learning and teaching model is already equipped to embrace learner analytics. The PEC Model (Prepare, Engage, Consolidate) is at the heart of our learning design approach. When deployed in a module this standardised model generates student activity within our learning systems. This provides insights to improve delivery and future redesigns. 

Collaborative partnerships are critical for transformation

Today, we’re using data to re-think our traditional delivery models. This is enabled through working closely with suppliers to provide essential support, build capacity, knowledge transfer and create beneficial partnerships.   

We started working with StREAM by Kortext when we explored the possibilities of engagement analytics. We’re using StREAM to view how students are engaged on individual, cohort, and course levels. The partnership with Kortext has helped us develop a more collaborative model between our students and teaching staff.  

The use of StREAM does not, in itself, change our intentions or responsibility to support students, but it provides an additional element of information and data which will help inform our approach to supporting students.  

Measure, monitor and manage engagement

There is such exciting potential in engagement analytics. It provides the opportunity for an earlier, more proactive and informed discussion with students regarding academic development, support and, where necessary, the provision of information regarding specialist support services. As it matures, we expect to see richer learning profiles, including more personalised information sets, action planning features and communication tools.