Starting university is a milestone event in anyone’s life. Whether fresh out of school or college, or returning to study later in life, the university years can be complex to navigate. One way in which universities support their students during their undergraduate years is through the provision of a named academic colleague – a personal tutor (academic coach, personal academic tutor etc) – who is there to look out for them, to support them as they settle into university life, coach them through their studies and beyond – into graduate employment or post-graduate study.
Personal tutoring is both proactive and reactive. Part of the ‘offer’ that universities make to students is around the proactive provision of pastoral support and the opportunity to meet with a named member of staff on a termly basis during your time as an undergraduate. These scheduled sessions can be offered on an individual basis or facilitated in groups, with an intentionally designed set of co-curricular learning activities or ‘check-in points’ that, ultimately, are about supporting post-study progression.
The other part of the job, and arguably the more demanding and unpredictable side, is reactive – supporting and responding appropriately to students who seek out their tutor (or, for that matter, any other member of staff who they are comfortable opening up to) for help and support, typically in response to an issue or series of issues that are affecting the ability of the student to engage fully in their studies.
I became increasingly conscious of the nature, level, and extent of the demands on personal tutors when working at a UK university where I was responsible for designing, developing, and then implementing a new approach to personal tutoring. Conversations with colleagues both at my institution and across the sector identified that the demand for pastoral support regularly far outstripped supply in terms of official academic staff hours allocated to this role.
In addition, being a personal tutor can be really challenging for academic staff wellbeing. Personal tutors can often be overwhelmed with the complexity of the issues that their students are facing and in knowing how best to support them.
Part of my work leading the university’s revised approach to personal tutoring included the institutional deployment of the Solutionpath StREAM student engagement analytics platform introduced to support student transition, support retention and enhance success. One of the challenges I faced when working across both these projects was how to introduce and position StREAM as a way to ease the burden of demand on personal tutors. To do this, I needed to raise awareness of how both the data-driven insights provided within StREAM, combined with an end-to-end interventions and support process would allow them to fulfil their responsibilities more effectively rather than increase the burden on their already limited time.
In the light of this very real ‘demand outstripping supply’ dilemma, I want to consider how the adoption of StREAM can ease the burden on personal tutors by providing data-driven insights that allow tutors to initiate early, proactive, personal tutoring conversations with tutees, targeted to where the need is the greatest. An early conversation, supported by an end-to-end intervention cycle can stop students falling off the radar, by helping to prevent or limit academic behavioural change resulting in a student feeling or being unable to continue with their studies.
In this blog, I’d like to share my reflections on those challenges combined with explanations of how the functionality within StREAM has been designed to support personal tutoring and to mitigate the gap between the demand on pastoral support services and the resource available for this purpose.
Students engage with their academic studies in myriad ways. Where data insights are dispersed across multiple digital systems, it can be complex and time-consuming to build a comprehensive picture of what engagement with academically purposeful activities looks like at the individual student level. Given that time is already stretched, the collation of multiple data feeds within StREAM eliminates the need to check multiple pieces of software for each student or tutee each time you meet with them.
Student engagement analytics using StREAM applies an institution-specific engagement algorithm to your data and presents in back in simple engagement categories. Reviewing which students are displaying changes in engagement behaviours or who are in the lower engagement categories means you can easily identify which students to reach out to. These insights mean you can focus your limited time on meeting with and supporting those students to succeed.
Ultimately, the provision of an excellent student academic experience is the responsibility of the entire programme team even where each student has a named contact for personal and pastoral matters. Students discuss personal and pastoral matters with their academic programme team as well as their personal tutor (which can sometimes be the same person wearing a different hat), making it important to deploy StREAM in such a way that ensures there is no wrong door to student support, but which also makes it clear who has primary responsibility as the named contact for each student.
A student-centred deployment of StREAM will therefore require upfront consideration of how to ensure that all staff with a legitimate academic or pastoral responsibility for an individual student have access to the student record in line with internal Data Privacy Impact Assessment requirements. In this way, StREAM can support whichever member of the academic team is having a conversation with a student, even if they aren’t the official named personal tutor.
Engagement behaviours normally fluctuate across the course of a week, a month and over the course of the annual academic cycle. Knowing what is ‘normal’ for each student makes it easier to identify changes to the norm. Oftentimes, those digital signals are visible long before a situation has reached the point where a student seeks out a member of the academic or pastoral team for help.
Understanding when those digital signals are out with the norm provides a data-informed basis for proactively initiating a conversation with the student. In turn, the conversation can trigger targeted outreach activity that mitigates against the issue developing into a crisis.
With multiple students to keep an eye on, the ability within StREAM to select, group and filter students according to need is a valuable way in which to manage your different responsibilities.
So, whether you want to know which students haven’t yet completed their occupational health forms prior to going on placement, keep track of specific cohorts of students, or identify whether activity to address differential student outcomes is on target, StREAM student engagement analytics can provide real-time management insights to suit.
Sometimes a conversation with a tutee may result in an agreed action on the part of the student to arrange an appointment with an academic or pastoral support service (e.g. to undertake an online tutorial on referencing, to meet with an academic librarian to develop a research strategy etc). Embedded links within StREAM that signpost students and that demonstrate the breadth of support available place enable you to share this information easily with your tutees, yet situate agency over whether to act on the conversation firmly with the student.
Depending on the situation, it may be more appropriate to refer a student to a specialist support team and ask them to proactively reach out to the student directly. Either way, what matters is that agreement on the way ahead is discussed and agreed in conjunction with the student.
Current Office for Students metrics address the entire student lifecycle, from admissions to post-study progression. The revised Condition B3, due to come into force in October 2022, stipulates a continuation indicator of 85% for undergraduate students studying their first degree. Research among StREAM users has confirmed a correlation between engagement and attainment, demonstrating that StREAM has value over and above the identification of students who may be at risk from withdrawal2.
The flexible way in which the data in StREAM is presented means that strong and sustained engagement is also clearly visible to users. As StREAM is built on principles of data transparency, personal tutors can work with their tutees to encourage them to access the platform and independently take action to address aspects of non-engagement.
Auto-acknowledgement of positive engagement can serve to nudge student behaviour to achieve individual goals and encourage students to aim higher – and succeed!
Triangulating the different data sources in StREAM provides a more holistic picture of the interplay between engagement and success, particularly where attendance and assessment information is available. Reviewing engagement across all three data types – attendance, assessment and use of online/digital resources – in collaboration with a tutee, can help pinpoint which types of engagement are proving most successful for the student.
Comparing cohort behaviours to individual behaviours can provide tutors with a data-informed route to deeper conversations at the individual student level, helping them to own their learning and proactively focus their time and energy on academic behaviours that work for them.
Reviewing engagement at cohort level, in conjunction with the outcomes of intervention activity (typically changes in student engagement scores) can further help determine ‘what works’ when it comes to evaluating the effectiveness of different interventions.
While, at its heart, personal tutoring is all about providing individual, tailored support to each student, universities organise and manage personal tutoring in different ways, influenced by institutional strategic aims and objectives and in line with organisational structures and behaviour. The introduction and adoption of StREAM within a university is primarily about digital transformation within a context – enabling universities to provide pastoral care and support to students based on data-insights that were previously unavailable or difficult to access and make sense of. Deployment is therefore more than getting to grips with the technical functionality. Rather it is about using student engagement analytics to both inform and address institutional strategy and policy requirements.
On the flip side, StREAM can act as a disrupter enabling you to do new things or do existing things in ways that were not previously possible, meaning you can refresh and revise your approach to personal tutoring!
For students, regular meetings with their Personal Tutor can be so much richer when focused around the data-insights provided by StREAM into their individual engagement behaviours. Easy to access links to relevant support services through the interventions lifecycle makes it more likely that students will click on those links and follow up on suggestions from their Tutors – especially if actioned during the meeting itself.
Personal tutors can facilitate deeper conversations that are less-directive and more coaching-focused, allowing both the data and additional contextual information provided by tutees to guide actions and responses. When used to refer or signpost students to specialist teams within the university, student engagement analytics can function as a dynamic focal point for the provision of integrated student support, combining the student, the tutor and relevant professional services colleagues.
In these days of the OfS regulation and revised TEF metrics, universities cannot afford to become complacent, but rather are expected to have a strategic response to each and every policy objective emanating from government. The flexibility in how StREAM is deployed means that it provides an evidence-base for responses to a number of these different objectives – from supporting students’ independent study, academic and pastoral support, managing retention, addressing curriculum and assessment inequalities, tackling awarding gaps to improve student outcomes.
If you would like to discuss how to operationalise some of the ideas in this blog or learn more about the value of using student engagement analytics in your institution, please get in touch.
Author – Dr Rachel Maxwell, Community Manager at Solutionpath Starting university is a milestone event in anyone’s life. Whether fresh out of school or college, or returning to study later in life, the university years can be complex to navigate. One way in which universities support their students during their undergraduate years is through […]
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