- By Rachel Maxwell, Principal Advisor at Kortext.
Since the adjustments to the Office for Students’ (OfS) Condition B3: Student outcomes, published continuation rates have dropped from 91.1% in 2022 to 89.5% in 2024 for full-time students on their first degree.
This drop is most evident for students in four key areas: (1) foundation year courses; (2) sub-contracted and franchised courses; (3) those with lower or unknown qualifications on entry; and (4) those studying particular subjects including Business and Management, and Computing.
Universities utilising student engagement analytics are bucking this downward trend. Yet, surprisingly, engagement analytics are not mentioned in either the evaluation report or the accompanying Theory of Change document.
Ignoring the impact of analytics is a mistake: universities with real-time actionable information on student engagement can effectively target those areas where risks to continuation are evident – whether at the programme or cohort level, or defined by protected characteristics or risks to equality of opportunity.
The [engagement analytics] data you see today is next year’s continuation data.
Dr Caroline Reid, former Associate Dean at the University of Bedfordshire
A more complete view of student learning
The digital footprints generated by students offer deep insights into their learning behaviours, enabling early interventions that maximise the opportunity for students to access the right support before any issues escalate. While data can never explain why a student is disengaging from their learning, it provides the starting point for a supportive outreach conversation. What happens thereafter would depend on what the conversation revealed – what kind of intervention would be most appropriate for the student? Examples include academic skills development, health and wellbeing support or financial help. The precise nature of the intervention would depend on the ecosystem of (typically) the professional services success and support expertise available within each institution.
Analysing engagement activity at the cohort level, alongside the consequent demand on student services teams, further enables universities to design cohort or institution-wide interventions to target increasingly stretched resources where and when they are needed most.
[With engagement analytics we have] a holistic view of student engagement … We have moved away from attendance at teaching as the sole measure of engagement and now take a broader view to enable us to target support and interventions.
Richard Stock, Academic Registrar, University of Essex
In 2018–19, 88% of students at the University of Essex identified as having low engagement at week six went on to withdraw by the end of the academic year. By 2021–22, this had reduced to approximately 20%. Staff reported more streamlined referral processes and effective targeted support thanks to engagement data.
Bucking the trend at Keele
The OfS continuation dashboard shows that the Integrated Foundation Year at Keele University sits 8% above the 80% threshold. Director of the Keele Foundation Year, Simon Rimmington, puts this down to how they are using student engagement data to support student success through early identification of risk.
The enhanced data analysis undertaken by Simon and colleagues demonstrates the importance of working with students to build the right kind of academically purposeful behaviours in those first few weeks at university.
- Withdrawal rates decreased from 21% to 9% for new students in 2023–24.
- The success rate of students repeating a year has improved by nearly 10%.
- Empowering staff and students with better engagement insights has fostered a more supportive and proactive learning environment.
Moreover, by identifying students at risk of non-continuation, Keele has protected over £100K in fee income in their foundation year alone, which has been reinvested in student support services.
Teesside University, Nottingham Trent University (NTU) and the University of the West of England (UWE) all referred explicitly to engagement analytics in their successful provider statements for TEF 2023.
The Panel Statements for all three institutions identified the ‘very high rates of continuation’ as a ‘very high quality’ feature of their submissions.
- Teesside’s learning environment was rated ‘outstanding’, based on their use of ‘a learner analytics system to make informed improvements’.
- NTU cited learning analytics as the enabler for providing targeted support to students, with reduced withdrawals due to the resulting interventions.
- UWE included ‘taking actions … to improve continuation and completion rates by proactively using learning analytics’ to evidence their approach.
The OfS continuation dashboard backs up these claims. Table 1 highlights data for areas of concern identified by the OfS. Other areas flagged as key drivers for HEIs are also included. There is no data on entry qualifications. All figures where data is available, apart from one[1], are significantly above the 80% threshold.
Table 1: Selected continuation figures (%) for OfS-identified areas of concern (taught, full-time first degree 2018–19 to 2021–22 entrants)
The Tees Valley is the second most deprived of 38 English Local Enterprise Partnership areas, with a high proportion of localities among the 10% most deprived nationally. The need to support student success within this context has strongly informed Teesside University’s Access and Participation Plan.
Engagement analytics, central to their data-led approach, ‘increases the visibility of students who need additional support with key staff members and facilitates seamless referrals and monitoring of individual student cases.’ Engagement data insights are integral to supporting students ‘on the cusp of academic failure or those with additional barriers to learning’.
The NTU student caller team reaches out to students identified by its engagement dashboard as being at risk. They acknowledge that the intervention isn’t a panacea, but the check-in calls are appreciated by most students.
Despite everything happening in the world, I wasn’t forgotten about or abandoned by the University.
NTU student
By starting with the highest risk categories, NTU has been able to focus on those most likely to benefit from additional support. And even false positives are no bad thing – better to have contact and not need it, than need it and not have it.
What can we learn from these examples?
Continuation rates are under threat across the sector resulting from a combination of missed or disrupted learning through Covid, followed by a cost-of-living crisis necessitating the prioritisation of work over study.
In this messy world, data helps universities – equally challenged by rising costs and a fall in fee income – build good practice around student success activity that supports retention and continuation. These universities can take targeted action, whether individually, at cohort level or in terms of resource allocation, because they know what their real-time engagement data is showing.
All universities cited in this blog are users of the StREAM student engagement analytics platform available from Kortext. Find out more about how your university can use StREAM to support improvements in continuation.
[1] The Teesside University Integrated Foundation Year performs above the OfS-defined institutional benchmark value of 78.9%.
