Keeping students engaged on and off campus

Recent images shared of empty classrooms and lecture halls have shown that students are continuing to utilise online teaching and learning. Alex Chapman, head of technology enhanced learning at Middlesex University, believes that a one-size-fits-all approach to student engagement will no longer work for a vast portion of students who cannot, or do not, wish to spend all their time on campus. To ensure that every student is engaged and feels satisfied, universities can look to student engagement data.

Posted 19 January 2023 by Christine Horton

Around one quarter of Middlesex undergraduate UK and EU students come from deprived areas and are also the first generation from their household to enter higher education. Around 88 percent of our students fall into at least one of the categories for widening participation, and four in five of our UK students spend more than 40 minutes travelling to our campus. Consequently, we’ve seen many of our students choose online as an option which fits in with their lifestyle and other commitments better.

However, as remote learning becomes more frequent, we’ve been very mindful of its impact on student belonging and cohort identity. This needs to be considered as we look to newer models of teaching delivery, such as hybrid and blended, and as we work towards a delivery model where online learning complements on-campus activity, not replaces it.      

A centralised record of engagement

Middlesex has been focused on providing support for students in this blended model of learning as they move through their course. With the support of student engagement software Solutionpath and its StREAM platform, we have a centralised dashboard to keep record of every student’s engagement, performance, and progress.

For academic tutors, this information is vital to help them identify students potentially at risk of leaving and provides data to make decisions with the student’s wellbeing at the heart. This data will also play a key role alongside academic advising as we look to integrate aspects of hybrid learning into the curriculum, but also as we continue to ensure students feel a sense of belonging during their time with us.

These data analytics can also be used to identify different engagement patterns across specific disciplines and cohorts, showing the various ways students are engaging with their programs. This allows us to develop tailored solutions that can best support the student based on their course. Alongside things like student surveys and other formal and informal feedback mechanisms, we can get a holistic oversight on the student experience of our university programs and make improvements where the data indicates it would be beneficial.

Cohort identity and academic advising

A large part of student engagement and participation is, of course, ingrained in wellbeing. Data on student satisfaction is not a new concept, but with higher education witnessing an acceleration in the use of new technologies, there is an increased risk that students simply don’t feel like they belong in their institution. Cohort identity has been difficult to conjure with the mix of virtual and online spaces, meaning that the discussion around belonging has become embedded into the wider conversation of the university experience.

When students first arrive at Middlesex, an onboarding process and welcome programme takes place. Students are asked to complete a pre-arrival survey, before meeting with their academic advisor for the first time. The data helps academic advisors to understand the make-up of their cohort of tutees and helps to identify specific support requirements. Each student then receives an action plan for the following months.  

Academic advising plays a key role in supporting our students to achieve the best possible outcomes. It involves a mixture of group tutorials and one-to-one meetings, including 12 interactions based around the student lifecycle and embedded into the curriculum. This generates rigorous data and student feedback so that any issues are flagged earlier rather than later. The process also gives the student the opportunity to interact and connect with peers and staff members to help them integrate into the learning community.

Working best with different cohorts and disciplines

Blended learning has become increasingly prevalent in higher education since the pandemic, as universities continue to deliver education that is flexible and accessible, shifting with the ever-more fragmented landscape of student learning behaviours.  

As well as being a worthwhile indicator of engagement and wellbeing from the offset, data can also reveal the digital skillset of our students and staff. Many online resources have only been introduced since the beginning of the pandemic and therefore not everyone is comfortable or confident with this type of learning. Knowing what digital platforms and in-person approaches work best for different cohorts will define how we move forward with our teaching and learning strategy.    

It has become clear that a one-size-fits-all approach to student engagement will no longer work for a vast portion of students who cannot or do not wish to spend all their time on campus. Therefore, to ensure that every student is engaged and feels satisfied with their course, we need to analyse the wealth of data available to us.

We know that sometimes we don’t have all the answers, but as we look to move forward with our strategy, we will ensure we continue to work with students, staff and technology partners collaboratively to maximise that student experience.