Data is forever in a state of flux. Nevertheless, it’s important not to make automated decisions with the data in front of us, categorising people and determining set steps, but adopting a more tailored, personalised approach. At the heart of this technology and data is people, says Rachel Maxwell, Principal Advisor, Academic, Research and Community at Solutionpath.
I’m the Principal Advisor (Academic, Research and Community) where I coach and consult client universities to help them better understand their use of student engagement data and what they want to accomplish from having this data at hand. Day-to-day, I support clients on their use and adoption of Solutionpath’s StREAM engagement analytics platform, leading our user community with a variety of webinars that explore best practice, product development and more technical sessions. I also take part in supporting pre-sales activity, speaking with potential clients on how our product could be used in their university. And lastly, I lead on research, which often comes down to the important question of what works when it comes to student support, to retaining students, and student success.
Solutionpath works primarily within the UK higher education sector. Our company aims to create and develop the solutions that enables every student to reach their full potential, which comes down to delivering personalised learning. Our journey began with Nottingham Trent University looking at supporting student retention, improving wellbeing, belonging and student success.
These, and many other use cases, continue to evolve, with the most recent articulation of these use cases wrapped into the all-encompassing requirement for universities to ‘deliver successful outcomes for all students’ (Office for Students registration condition B3). In addition to understanding how universities might benefit from having a deeper understanding of how students are participating in their learning, we also need to look at this from the student perspective and ask ourselves questions such as: what do students think engagement means and how are they engaging in their studies? What do they want from their learning and teaching in a post-Covid world?
Primarily StREAM is about identifying signs of risk to student progression and supporting any next steps activity for student success. However, universities are also using StREAM in their work to address attainment gaps. For example, some universities may have a disability attainment gap, meaning that students who are disabled are not achieving as highly as students who are not. Gaps like this can exist for a number of legally ‘protected characteristics’. In these instances, it’s vital that universities understand why those gaps exist and have a plan as to what support needs to be integrated to ensure that universities are helping every student succeed. There are multiple factors that can impact student learning and universities seek to understand how they can support student learning and success. Our role is to help them understand student engagement behaviours and then work with university staff as part of their broader work around academic and pastoral support activity.
Successful outcomes for all students are something that the university sector strives for, particularly given that the OfS have included this as a condition for university registration. Universities need to know what’s going on for each individual student and form the best way to support them – which is what, we believe, our student engagement analytics platform addresses.
As students participate in different learning activities, they passively create a digital learning footprint. StREAM takes these digital footprints– e.g., from engaging in online learning activities, borrowing a library book or accessing journal resources – and uses that data to measure engagement. If universities have a system for registering attendance to a lecture, seminar, or workshop, they can use this data as part of the wider picture of engagement. Digital footprints are useful to home in on as they can show us those incremental changes, those shifts in behaviour, that can occur if a student is struggling or faced with a challenge.
Demographic information, too, is useful in helping tutors and staff to understand who their students are and what support they need to succeed. However, StREAM doesn’t use that to quantify risk, i.e., we don’t say that your gender or race will make you more or less at risk from withdrawing from your course. Rather, demographic data is visualised within StREAM and staff users can consider its contextual relevance in discussion with students alongside the engagement scores that emerge after the engagement algorithm in StREAM has analysed students’ raw engagement data to provide universities with a range of engagement categories from very high to none.
Quantifying the engagement into six different engagement categories gives staff a well-rounded indication of risk, allowing them to make sense of quantitative data from different learning technologies so that they can focus their time and attention on who needs the most support that day. Likewise, we can look at those who are achieving and engaging more highly too, providing them with the support and encouragement to reach higher. The platform is designed for all students of all abilities and outcomes.
Data is the very start of what we can do with the StREAM platform. The universities themselves collect and supply the engagement data for us to then overlay the algorithm. What happens after this, when the insights have been generated, is where it gets particularly powerful. Student data doesn’t tell us what’s going on, only that something isn’t as expected in terms of how that student is participating in their learning. This alerts the member of staff responsible to engage in a conversation with the student to understand what factors might be inhibiting engagement with their studies; without this, there isn’t solid evidence to know when we need to reach out to specific students and what support is required. Importantly, StREAM provides end-to-end outreach functionality to support all users (staff and students), thereby ensuring that all outreach activity is satisfactorily completed and that students are not forgotten about.
The conversations themselves allow students and staff to work together on what happens next for the student, which is important as these students are adults who want some form of ownership over their learning journey. It’s these decisions that universities can be made easier with the data at hand. We help them harness the data they’ve gathered to get the most out of it, to streamline engagement insights, highlight those at risk and put the required steps in place to support (re-)engagement. We collaborate with universities to integrate StREAM as part of their practices, so these steps are well-embedded into the fabric of their processes.
Through our user community, we also share best practice and invite our clients to speak on how they’ve been using StREAM at their institution. Even though everybody is trying to engage and support their students, each is doing it in a slightly different way, so there are elements they can take from one another and apply to their own. It’s about giving staff and students – as they are encouraged to access the StREAM dashboard – the ideas about how to apply the contextual and academic knowledge to produce a refined insight for each student. That is how universities can use StREAM to really impact student outcomes and student success.
Universities have a lot of data. Some of it may be siloed or hidden, but it exists. So, what do you do with it when you’ve got the data? How do you use it and what insights do you want to get? How are you going to interrogate that data? Having a strategy for using data is very important.
It’s also important to think about such questions from a collaborative point of view, so you’re working with your stakeholder groups to fully grasp your approach, to reflect on what would be the most useful data, what you want to accomplish and what the benefits are. From the student perspective, this would involve questions around how having sight of your data can enable you to become a better student, by improving your learning and achieving your goals.
Many of the universities we work with claim that their data isn’t perfect. In all honesty, I don’t think data is ever perfect. It’s forever in a state of flux and they can work continuously with that to improve its quality. Nonetheless, it’s important not to make automated decisions with the data in front of us, categorising people and determining set steps. At the heart of all this technology and data is people – we are relational beings. There should be conversations and collaboration, to gain better understanding and explore the ways to move forward together for student success.
If you’d like to find out more about our StREAM platform, please book a call with our team.
Data is forever in a state of flux. Nevertheless, it’s important not to make automated decisions with the data in front of us, categorising people and determining set steps, but adopting a more tailored, personalised approach. At the heart of this technology and data is people, says Rachel Maxwell, Principal Advisor, Academic, Research and Community […]
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