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Marrying data and delivery to provide student support

14 September, 2020 | by Heather Russell and David Rimmer

Ensuring higher education students have access to support touchpoints throughout their time at university is paramount to their success.

There are many reasons that students may not be reaching their full potential when undertaking study. These include challenging personal circumstances, competing pressures from work or family, as well as demographic influences such as being the first in family to attend university.

Online Education Services has always been focused on initiatives which support student’s successful transition into an online learning environment. We have found that by providing opportunities for students to connect online with peers and tutors in a highly supported, interactive and responsive learning environment they are more likely to attain their study goals.

In addition, the provision of on demand student support via phone, live chat and email and the opportunity to access coaching to address goal setting, time management and motivation challenges, has resulted in increased student persistence and progression.

However, many of these services rely on the students reaching out for support and we wanted to address a gap that identified students who were at risk of not succeeding with their studies and were not accessing the support services available.  We also wanted to ensure that they were receiving targeted support relevant to their discipline and stage of study.

Delving into data to understand and interpret student behaviours

In 2019, we saw an opportunity to create an innovative engagement tool that would give us insights into when and why a student may not be achieving their study goals.

Through the collation, aggregation and modelling of student behaviour online we identified patterns that correlated with success outcomes.  We were able to successfully identify where students were, or in many cases were not showing behaviours that were likely to lead to success in their chosen subject.

Augmenting this data from the learning management system alongside data from previous teaching periods, and demographic information collected through enrolment stages, we developed a dashboard of engagement and risk which can be delivered to students’ online tutors in real time.

Delivering just in time support

Through the timely delivery of a data summary which identifies students according to risk, online tutors are able to offer support to those students who otherwise may have fallen through the cracks. The team tested a variety of communication methods and approaches relevant to different student circumstances, to ensure students were receiving the best fit in terms of support.

For example, for student who has a critical deadline approaching and has shown a reduction in engagement, through the simple act of placing a phone call, the online tutor is able to have a personal discussion to understand the students’ unique circumstances and needs. Serving a dual purpose, the phone call not only helps a student at the moment that it’s needed, but also provides an ongoing sense of connection and belonging for students.

Early evaluation of the initiative suggests the additional contact contributed to an overall uplift in student pass rates. Student feedback indicated they appreciate the support and the lift in  confidence it gives them.

By marrying data and interventions, we have been able to best identify at risk students and provide just-in-time support to ensure that each and every student is given the opportunity to achieve their study goals.