How’s your student data this morning?
Depending on how close you sit to your institutional student data systems, your answer may range from a bemused shrug to an anguished yelp.
In the most part, we remain blissfully unaware of how much work it currently takes to derive useful and actionable insights from the various data traces our students leave behind them. We’ve all seen the advertisements promising seamless systems integration and a tangible improvement in the student experience, but in most cases the reality is far different.
James Gray’s aim is to start a meaningful conversation about how we get there and what systems need to be in place to make it happen – at a sector as well as a provider level. As he says:
There is a genuine predictive value in using data to design future solutions to engage students and drive improved outcomes. We now have the technical capability to bring content, data, and context together in a way that simply has not been possible before now.”
All well and good, but just because we have the technology doesn’t mean we have the data in the right place or the right format – the problem is, as Helen O’Sullivan has already pointed out on Wonkhe, silos.
Think again about your student data.
Some of it is in your student information system (assessment performance, module choices), which may or may not link to the application tracking systems that got students on to courses in the first place. You’ll also have information about how students engage with your virtual learning environment, what books they are reading in the library, how they interact with support services, whether and how often they attend in person, and their (disclosed) underlying health conditions and specific support needs.
The value of this stuff is clear – but without a whole-institution strategic approach to data it remains just a possibility. James notes that:
We have learned that a focus on the student digital journey and institutional digital transformation means that we need to bring data silos together, both in terms of use and collection. There needs to be a coherent strategy to drive deployment and data use.
But how do we get there? From what James has seen overseas, in the big online US providers like Georgia Tech and Arizona State data is something that is managed strategically at the highest levels of university leadership. It’s perhaps a truism to suggest that if you really care about something it needs ownership at a senior level, but having that level of buy-in unlocks the resource and momentum that a big project like this needs.
We also talked about the finer-grained aspects of implementation – James felt that the way to bring students and staff on board is to clearly demonstrate the benefits, and listen (and respond) to concerns. That latter is essential because “you will annoy folks”.
Is it worth this annoyance to unlock gains in productivity and effectiveness? Ideally, we’d all be focused on getting the greatest benefit from our resources – but often processes and common practices are arranged in sub-optimal ways for historical reasons, and rewiring large parts of someone’s role is a big ask. The hope is that the new way will prove simpler and less arduous, so it absolutely makes sense to focus on potential benefits and their realisation – and bringing in staff voices at the design stage can make for gains in autonomy and job satisfaction.
The other end of the problem concerns procurement. Many providers have updated their student records systems in recent years in response to the demands of the Data Futures programme. The trend has been away from bespoke and customised solutions and towards commercial off-the-shelf (COTS) procurement: the thinking here being that updates and modifications are easier to apply consistently with a standard install.
As James outlines, providers are looking at a “buy, build, or partner” decision – and institutions with different goals (and at different stages of data maturity) may choose different options. There is though enormous value in senior leaders talking across institutions about decisions such as these. “We had to go through the same process” James outlined. “In the end we decided to focus on our existing partnership with Microsoft to build a cutting edge data warehouse, and data ingestion, hierarchy and management process leveraging Azure and MS Fabric with direct connectivity to Gen AI capabilities to support our university customers with their data, and digital transformation journey.” – there is certainly both knowledge and hard-won experience out there about the different trade-offs, but what university leader wants to tell a competitor about the time they spent thousands of pounds on a platform that didn’t communicate with the rest of their data ecosystem?
As Claire Taylor recently noted on Wonkhe there is a power in relationships and networks among senior leaders that exist to share learning for the benefit of many. It is becoming increasingly clear that higher education is a data-intensive sector – so every provider should feel empowered to make one of the most important decisions they will make in the light of a collective understanding of the landscape.
This article is published in association with Kortext. Join us at an upcoming Kortext LIVE event in London, Manchester and Edinburgh in January and February 2025 to find out more about Wonkhe and Kortext’s work on leading digital capability for learning, teaching and student success.
