Higher education institutions have grappled for decades with how best to support students, particularly those who are harder to reach or less likely to engage. What has changed is the level of expectation. Policy direction in the UK now makes clear that early identification of risk and targeted support are not optional enhancements to the student experience but an expected part of institutional practice.
The challenge for universities goes beyond whether the right support services exist to ensuring that academic and professional teams are sufficiently joined up so that students do not fall through the gaps between them.
- Why fixing student problems one by one does not work
- How to cultivate confident, creative graduates
- How unlocking data maximises student support and success
We have adopted a shared model in which academic staff and professional services at the University of Roehampton work together, using live data to identify emerging risks and tailor individualised support for students. This data-driven approach also extends to disability support and careers services.
Data dashboards that support earlier conversations
Accessible dashboards that bring together engagement, attendance, progression and employability indicators are central to this approach. These dashboards, developed by our senior data analyst, allow staff to monitor cohort-level engagement trends, identify modules with unusually low attendance, spot patterns in continuation risk, and review career confidence scores by course.
The aim is not simply to provide information but to support early conversations about student engagement before issues escalate into more serious concerns.
Critically, the dashboards are supported with data literacy skills to help staff interpret the figures. Training roadshows and individual training sessions are an essential component of the system, ensuring staff understand both what the data shows and how it can inform action.
Best practice insight: Dashboards alone do not improve outcomes; they must be interpreted and acted upon. Data only makes a difference when it sits alongside targeted early interventions, training and clear accountability.
Structured risk reviews between academic and professional teams
Alongside dashboards, Roehampton has established regular meetings between the student engagement team and deputy deans within academic schools to review live continuation and engagement data. These sessions focus not only on identifying students who may be at risk, but also on agreeing clear intervention routes and ownership.
A tiered model can underpin this process. This ensures the most complex cases receive specialist support and prevents students from falling into a grey area between services. In our system, students at the highest risk of non-continuation (such as care-leavers or students with disabilities) receive proactive support from the central student engagement team, while those at emerging or moderate risk are allocated to academic support staff within schools. While the student engagement team delivers most of the work, it is closely supported by academic guidance tutors, who mainly work with students presenting at lower risk. As academic teams can view the interventions, they can retain visibility and ownership of their student cohorts. To maintain student confidentiality, they do not have access to well-being or disability notes.
Best practice insight: Create a clear triage mechanism and document who owns each risk category. Without data, students could fall through the cracks.
Embedding disability expertise within academic schools
A similar principle of shared responsibility underpins Roehampton’s approach to supporting disabled students. Each academic school has a departmental disability coordinator (DDC), an academic role that works closely with the disability services team.
This arrangement creates a two-way flow of information between academic and professional teams. Disability services provide expertise on adjustments and entitlements, while DDCs support academic colleagues in understanding and implementing those adjustments effectively within teaching and assessment.
The collaboration means that patterns in the data – including attainment gaps or progression trends among disabled students – can be discussed jointly and addressed at course level. In doing so, disability support becomes embedded within curriculum design and delivery rather than remaining a stand-alone service.
Best practice insight: Identify academic champions with formal responsibility for inclusion and ensure they have structured links with professional teams. At Roehampton, we have multiple roles assigned to academics who work closely with support teams. This includes academic guidance tutors who support students at risk of non-continuation, DDCs who support disabled students, and employability leads who work closely with Student Futures to deliver career prep initiatives. Informal goodwill alone is rarely enough; clarity of role and governance is essential.
Using data to target employability support
Employability is integrated into the same collaborative framework. Each academic school has an employability lead who works directly with a dedicated careers consultant. Together they review data on career confidence, graduate outcomes, engagement with employability initiatives and differential outcomes across demographic groups. This shared insight allows teams to design targeted responses.
For example, outreach can be directed towards students reporting low career confidence, employability activity can be embedded more deliberately in courses where graduate outcomes are weaker, and focused interventions can be developed for under-represented student groups.
Best practice insight: Use data not only to analyse graduate outcomes retrospectively but also to identify confidence and engagement indicators during study, when meaningful intervention is still possible.
Culture matters more than tools
While dashboards and processes are important, an effective approach will ultimately rest less on technology than on culture.
Cross-team conversations about student engagement are routine and scheduled, responsibility for action is clearly allocated, and senior leaders are visibly engaged in reviewing data and discussing interventions. Over time, this has helped us develop a shared language around “risk” and “support”, ensuring academic and professional expertise are seen as complementary rather than separate.
When academic staff view data as a tool to help them support students more effectively – rather than as a measure of their performance – they are far more likely to engage with it.
For institutions looking to adopt a similar approach, the starting points are both practical and strategic:
- Formalise cross-functional risk-review meetings with named attendees and clear actions.
- Introduce a tiered intervention model to prevent both duplication and gaps in support.
- Establish clear links between academic teams and specialist services such as disability support.
- Pair school-based employability leads with careers professionals and ensure they review live data together.
- Invest in data literacy alongside dashboard development.
The technology required to bring these approaches together already exists in most universities. The real challenge is building the structures, relationships and shared accountability that allow institutions to use data collectively and translate insight into meaningful support for students.
Aleata Alstad-Calkins is director of student support and success at the University of Roehampton.
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