‘1 in 10 (95) [of students] have considered or have made the decision to drop out of university in the last 12 months as a direct result of a lack of money caused by the cost of living crisis.’ – Student Money & Wellbeing Report 2023, blackbullion
The impact of the cost-of-living crisis on students’ academic engagement
The cost of living crisis – particularly as it pertains to all students – is once again hitting the headlines with showing how the disparity between different student groups has been intensified as a result of the crisis. One study of 1000 UK students found that seven of every ten students surveyed have considered dropping out of higher education since starting their degree and that 69% had adjusted their spending last term due to increased living costs. The ‘negligible thought and support from the government’ in respect of how the crisis is impacting students was identified by Michelle Morgan, Dean of Students at the University of East London, in a Wonkhe article.
Morgan goes on to argue that accurate data on the immediate impact of the cost-of-living crisis for individual student engagement with their studies, for groups of students and for universities themselves is needed if an effective strategic and policy-based response is to be created and to ensure that the predicted increase in student withdrawals and intermissions is not used as a weapon in the government’s policy drive to tackle courses deemed to be of ‘poor value’.
The need for consistent real-time data to shape the response
Ultimately, Morgan’s argument is that a consistent approach to the recording of reasons for withdrawal and intermission – something she rightly acknowledges as being ‘complex [and] with no single cause’ – is essential to the provision of comparative data across the sector particularly when it comes to identifying patterns of behaviour and to provide efficient targeted support.
The challenges to using existing data such as that provided to HESA are that the listed categories are broad and basic and that there are no consistent approaches to recording attendance, sickness and holiday periods. Use of real-time data is also essential if universities are to offer support to those in need today, rather than those identified by end-of-cycle data – an approach that is imperative if responses to the current crisis are to be meaningful.
The impact of financial concerns on student health and wellbeing and on engagement
The connection between financial concerns and engagement has been explicitly identified by blackbullion in their recent Student Money and Wellbeing Report 2023. In the section on the cost of living and student attainment they report that 28% of students have avoided or considered avoiding the purchase of core books or equipment needed for their course, 19% have reduced the frequency with which they travel to campus to use campus facilities like the library and 14% have considered attending fewer in-person teaching sessions – the implication being a need to reduce travel costs.
But the interplay between financial matters and attainment is further affected by the impact that financial concerns have on student mental health and wellbeing. A survey conducted by the Office for National Statistics published on 23 November 2022, identified that 49% of students felt they had financial difficulties with around 45% of respondents reporting that their mental health and wellbeing had worsened since the start of the autumn term 2022.
Similarly, the Advance HE (AHE) Student Engagement Survey 2022, published in February 2022 identified that ‘the main reason students gave for considering leaving higher education was their mental health and emotional difficulties’ (para 7.2). Additionally, their analysis identified that students were spending more time working for pay than in recent years and predicted that a worsening of the cost-of-living crisis in 2023 needs to be factored in by universities from an advice and guidance perspective. The report also stated a need for universities to actively appreciate the circumstances that students find themselves in and to offer a blend of in-person and on-campus learning ‘to ensure students do not disengage from their course due to not being able to afford the commute or through needing to work’ (para. 7.2) – a finding clearly borne out by the blackbullion research. The TechnologyOne/Opinium study cited above also found that more than half of students have either a full or part-time job to help meet their baseline financial needs.
The correlation between student mental health and wellbeing and their ability to participate in their studies is stark:
‘Institutions often point to lower engagement with studies from students facing mental health challenges. … Students with mental health challenges may seem less interested in their course, unwilling to engage in discussions and their attendance overall may decline.
Students facing anxiety or depression may feel unable to go into lectures or seminars … Students with mental health challenges may suddenly change their levels of engagement or seem less proactive. These signs of withdrawal are typical indicators of a student facing mental health risks.’
How engagement data can inform the conversation
In our experience of working with over 25 universities within UK HE, and as the above findings show, engagement data can offer very powerful insights into which students are needing support at any given moment in time. Engagement data – the digital footprints created by students participation – or non-participation in educationally-purposeful activities – can never tell us the reasons why students have a particular engagement pattern. But what it can tell us is that there is something in the way individual students, or groups of students, are engaging – or disengaging – with their learning that would benefit from further exploration. Through identifying those students early – when those digital signs of disengagement first become apparent, universities are able to maximise the window of opportunity open to them to work in partnership with each student to ensure that the right support is put in place before the impact of the cost-of-living crisis becomes so severe that the student feels their only option is to withdraw. In this way, student engagement analytics can help universities to know some of what they do not currently know i.e. to fill the gap identified by Morgan around the need for real-time data about potential student withdrawal.
As Professor Steve West CBE, President of Universities UK and Vice-Chancellor of UWE Bristol points out:
‘We need the government to work with us and provide targeted hardship funding to protect [students] now, before their living costs become so high that they are unable to keep studying. If this were to happen it is a tragic loss of talent to the country and a personal loss which crushes hope, opportunity, potential and social mobility.’
The value of engagement data
The StREAM Data Foundry offers universities with a proof point for how student engagement data can help, using historic data unique to that university. Data Foundry identifies the degree of accuracy with which the StREAM engagement platform would be able to identify students at risk of withdrawal and the window of opportunity within which the university has time to act. Typically, StREAM can identify upwards of 80% of students who go on to withdraw between 6-8 weeks in advance of them actually doing so.
Let me be clear. In no way am I arguing that the use of student engagement analytics is the silver bullet to the predicted retention crisis. But what Kortext do have evidence for is the ability for student engagement analytics to provide universities and their students with some very powerful insights into student engagement behaviours that can enable supportive action to be taken long before a problem escalates into a crisis that results in withdrawal from studies.
While, as Morgan has identified, there is no existing standardised mechanism for the collection and comparison of data on student withdrawal and intermission, there is the opportunity now for universities to use educationally purposeful data at the individual student level to identify potential issues that impact participation in learning and to initiate early support that will enable students to remain studying and, ultimately, to contribute to the OfS Condition B3 requirement for universities to deliver ‘successful outcomes for all students’.
If you’d like to find out more, please book a call with our team.
