Thinking beyond student attendance as a measure of student engagement

Moving from student attendance as the sole measure of student engagement will allow universities to support those at risk of early withdrawal, says Richard Stock, Academic Registrar at the University of Essex

The use of data is a critical commitment in the University of Essex’s Education Strategy 2019-2025: ‘The responsible use of data by our skilled community will be fully embedded as a powerful tool for the development, wellbeing and success of all our students’.

The university is using data in a variety of ways to support our ambitions, and Essex was one of the first institutions to see the potential of student engagement analytics, which led to implementing a system that has enabled us to support our students to succeed more effectively and manage the risks around student continuation and student withdrawal.

A step-change approach to student engagement

Since introducing Solutionpath’s StREAM platform in 2018, we have seen a step-change in our approach to student engagement, both in our supportive processes and data analytics to support positive learning outcomes.

We have used the technology to help empower staff to target support in ways that maximise student benefit through timely review and intervention informed by engagement data. Students can track their data in real-time and actively participate in the supportive decision-making process, which has been invaluable in our drive to improve the student experience.

Moving away from student attendance as the sole measure of engagement has allowed us to identify and focus support for those students most at risk of early withdrawal. Our data show a strong correlation between student engagement and success, particularly the impact of low engagement.

The system works by drawing together data from core university systems that cover different elements of students’ engagement with their academic studies.

These data are processed through a unique engagement algorithm and classify individual students into various engagement categories, from very low to very high.

This engagement insight helps users – including students – to know when engagement is lower than expected, identify where engagement behaviour changes, and highlight where a student might benefit from a supportive conversation to help them re-engage or aim higher. The end-to-end interventions lifecycle makes it easier to signpost a student to support or refer them to an appropriate service.

Joining the dots around student support

Using data alongside contextual information about the student, their engagement with their academic programme and the university is essential in ensuring that decisions are based on as much relevant information as possible.

Joining the dots around student support at an individual level reflects an increasingly mature approach to using student engagement data within the university.

Consideration of contextual information is critical to understanding why students might be disengaging with their studies. At Essex, the use of engagement data is structured and defined through our Student Engagement Policy.

During weeks 1-5 of the autumn term, departments review student engagement weekly. At the point of the first lead indicator milestone – the end of week 6 – departments receive a breakdown of those students with shallow average concentration over that period. Previous research at the university found a strong correlation between students in that category and failure to progress at the end of the academic year.

Checkpoint data for the 2021-2022 autumn term identified 417 students within this ‘at-risk’ category. Three hundred seventy-two students have continued their studies or completed them.

Only 45 have since withdrawn or transferred to another institution. When compared over time, the data shows a continuing reduction in the percentage of students identified at risk in this way who later went on to withdraw from their studies, who failed to progress or transferred to another institution.

Through data-informed interventions, we have seen a 60% reduction in students withdrawing by the end of the academic year, where they previously averaged shallow engagement in the first term.

A tool for transforming outcomes in student attendance

We have seen an improvement in our retention rate since 2018. We are keen to continue exploring how engagement analytics can support our vision to support every student from every background to succeed. We now want to develop our use of StREAM so it becomes a tool for transforming the outcomes of all students and identifying and supporting those at risk of early withdrawal.

Student engagement analysis offers a depth of insight enabling the practical focus of support on those students who need it most. But the broader impact of this approach is more significant, and we remain ambitious.

We are gaining important insights into student engagement that enable us to understand our students’ needs and ensure we can shape the support we offer in the post-pandemic world where student expectations about how they access education have shifted.

This piece was written and provided by Richard Stock, Academic Registrar at the University of Essex.