Universities started realising about a decade ago that the administrative data gathered routinely as part of the teaching process might have some other potential. It was discovered that patterns in data, such as records of attendance and achievement, could reveal at an early stage when a student is struggling with their course or starting to disengage.
This might sound geeky, but in just a few years, this activity has evolved into learning analytics systems and become mainstream.
Today, many universities see the benefits of using learning analytics to inform conversations that help students to achieve their potential. But now universities have fresh challenges, particularly in the area of student mental health. Hence, there is a new kid on the block in educational analytics – the emerging field of mental health and wellbeing analytics.
It has been widely reported that the incidence of anxiety, depression and mental disorders has risen significantly in young people, which places a set of very real and sometimes frightening burdens on already stretched university support staff. This is illustrated in how the sector is dealing with an increased demand for counselling services.
And this demand is predicted to increase.
There is growing evidence that using data can help students achieve better learning outcomes, so we really are duty-bound to see how data – and technology more generally – can make a positive contribution to student mental health as well.
At Jisc, we have been working with universities to understand how we can do this. With the increased pressure on student services, counselling resources and others, institutions and sector bodies need to make it as safe and as easy as possible for students to get the help they need from these services.
Next steps for universities
Listening to student feedback, some universities we have spoken to have already noticed how data can make a difference.
Lisa Banks, director of student services at the University of Central Lancashire (UCLan), manages a proactive, centralised student support service, which works closely with academics and seeks regular feedback from students.
A stark student quote from a recent user survey carried out at the university illustrates the need for wellbeing analytics: “If it wasn’t for the fantastic team in student services who support counselling, mental health and wellbeing, I would likely be dead.”
However, for some universities, the work of support staff is currently inhibited by a patchwork of IT systems. Data about a student in crisis might be spread over a variety of separate systems and the full picture will only be revealed when these systems are joined up.
Most universities would like to move towards models where relevant information is available centrally, where and when needed.
A word of caution. Clumsy use of – or communications about – data and student wellbeing could easily make things worse rather than better. Students who perceive their university as a ‘big brother’ that cannot be trusted are probably less likely to share their problems or seek help.
Such a negative perception could even tip a vulnerable student into crisis. The law provides some guidance, but university professionals also need help from health professionals and students to understand how to make improvements in the use of data in wellbeing, while still respecting privacy.
To help the sector navigate this tricky field, we have developed a draft Code of Practice. This should be compulsory reading for anyone whose institution is preparing to use data and analytics more actively to support mental health and wellbeing services, including those who are already familiar with some of the issues from their learning analytics work.
The continued role for staff
We believe that support staff would always take the leading role in any data-informed conversations with students
And, finally, let’s clear up one misconception we have come across when talking about the role of data and technology in supporting mental health. There have been concerns around AI or machine-learning approaches such as predictive modelling and whether these technologies could essentially eliminate the human from the process. That is absolutely not what we are saying here. We believe that support staff would always take the leading role in any data-informed conversations with students.
8 Top Tips
To help universities as they face these challenges and opportunities, and working with Universities UK and other stakeholders, Jisc has come up with eight tips that can be used to help ensure its data contributes to better student support:
1. Get ready: understand data and
Is the data and information currently held on students accurate, up to date, and easy to access and use by those who need it to support students’ wellbeing?
2. Start the data conversation now
Do the right people know how to get information about students when they need it? Is data being gathered that will enable staff to focus on student support in the right way? Has the role of data in ‘triaging’ students at risk been considered?
3. Build links between data, systems
If already using student data to underpin support services or to enable learning analytics, do universities have a process in place to enable mental health and wellbeing services to become involved when a student needs that support? If there is a workflow or set of protocols to enable student data to be used for mental health and wellbeing, is it well publicised and understood by everyone?
4. Build up a richer picture of students and their support needs
While some data is being used to enable student support, what else might make things more efficient? For example, can appropriately trained staff see data about academic performance, as well as data related to wellbeing? Is other contextual
data such as attendance or finance data
in one place?
5. Enable information and data-flows across the institution
How easy is it for all those who support students to communicate with each other? For example, can teaching staff and wellbeing staff raise concerns or share information about relevant students when they need to? How streamlined are ongoing communications with students when a problem arises?
6. Build in interoperability and
How up to date are the systems and information architecture that underpin data and information in the institution? Can changes be made, when required, and do relevant systems and software link up?
7. Understand relevant legal and
Is there awareness of which areas of the law relate to using student data for mental health and wellbeing purposes? Is there a clear understanding of which data can be used and for what purposes?
8. Start to work in a wider data landscape
To what extent is the university able to work with health and other related services in its locality – for example, police – when a student is in crisis? Are there situations in which staff would like to be able to raise concerns and share information but are not able to? What can be done to start to develop partnerships, so this is easier to achieve?
Catherine Grout is head of service development at Jisc. Follow her on Twitter @CatherineGrout