For University Mental Health Day, we’re discussing how data technology and student analytics could help with students’ mental health and wellbeing. University provides most students with more than academic development. It provides personal and social growth, creates long-term wellbeing foundations, and also sets the trajectory for the next stage of life.
In October, Jisc published an evaluation of a three-year mental health analytics pilot project at Northumbria University. Funded by the Office for Students and running from 2019 to 2022, the project aimed to improve student mental health outcomes. The report emphasised the importance of using high-quality data to identify, support and correctly allocate resource to helping improve the wellbeing of students.
The right data tool can be invaluable for universities’ wellbeing and mental health support programmes. By leveraging data, universities can operate more strategically and efficiently with something as personal as mental health, making sure no student is left behind.
Early identification
Learning analytics can help identify students who may be at risk of mental health problems by analysing patterns in their academic performance, attendance, and engagement. A sudden change or significantly lower engagement than a cohort can signal something isn’t right and that a student might be struggling, and may benefit from support.
Although this can seem complex and costly there are manageable ways to begin using data to support students these are summarised in Good, Better, Best – how small steps can drive higher education analytics success . A first step could be Jisc’s attendance monitoring module. This can be seamlessly upgraded to full learning analytics when the time is right.
Personalised support
With mental health, a one-size-fits-all approach won’t work. Students are individuals with differing circumstances and stress factors from inside and outside the university that can be particularly acute at points of transition.
By understanding individual student needs through data, institutions can provide tailored support. This allows for proactive interventions to be provided earlier, with a lighter touch.
The newly updated learning analytics platform can improve the personalisation of support by providing a secure and confidential place to log interactions, history and information for every student. Utilising the comprehensive student biography and interactions functionality within the platform to deliver the vital information you choose, gives staff a holistic understanding of each student’s needs, while also protecting what is shared. The platform uses a best-in-class data protection toolset allowing the right staff to access the right information when they need it to deliver student success.
Resource allocation
Learning analytics can help institutions manage their finite support resources by identifying the appropriate intervention method and channel to use for each student.
Learning analytics can help institutions manage their finite support resources by identifying the appropriate intervention method and channel to use for each student. This data-driven allocation of resources not only enhances student satisfaction but also boosts retention and graduation rates.
By utilising data tools educational institutions can create a more supportive and responsive environment that promotes student well-being, mental health, and academic success.
Student analytics done well brings human experience to the forefront and helps ensure the valuable but finite resource of student support services can be made sustainable. For further reading, you can access Jisc report, Student analytics – A core specification for engagement and wellbeing analytics here, where higher education student support champion, Edward Peck, outlines his vision for efficient and scalable student services through better data governance and predictive student analytics.
Future updates to Jisc learning analytics platform will be steered by the sector’s needs, including a focus on student wellbeing. For more information see learning analytics on the Jisc website.
