We look at some of the key takeaways from the first fully online Data Matters conference and learn more about how to harness the power of data.
Context is king
Data can tell us ‘what’, but not ‘why’. This is the message presented by Prof Bart Rienties, professor of learning analytics at The Open University (OU). In his keynote address at Jisc’s Data Matters conference 2021, Bart explained that using evidence-based research, using data, can help shape narrative. He said:
“In the good old days before COVID-19, when people could physically meet in the same room, we would bring teachers together with other members of staff across the organisation. We would sit down and look at data dashboards on screen together. We’d talk through patterns we noticed, discuss what was working and what wasn’t going so well.”
Understanding what data is useful to improve services and inform decision-making was important, says Bart, but having the opportunity to discuss the context was key.
The current global context is also essential when interpreting data, said John Pritchard, director of strategic planning at Durham University, during his session. When faced with the COVID-19 pandemic, traditional planning assumptions and techniques were “blown out of the water” said John. He added that making sure to use current data is key, given the pace of change, and that it’s important that quantitative data should be complemented by qualitative insights into possible behaviours and events. When thinking about the future the hope of data certainty has always been “a pipe dream,” he added.
“In the context of the current pandemic the quest for data certainty can be dangerous. We have to live with uncertainty and good enough is good enough.”
It’s not all about learning analytics
Although learning analytics is a popular use for data, it isn’t the only one. In her session ‘data-led quality assurance and enhancement’, Ramita Tejpal, director of academic quality at BPP University Limited, talked about how data and learning analytics can also serve as an important tool for quality assurance and business operations within an education institution. Quality assurance is about establishing a baseline and maintaining that standard, explained Ramita. And to set that baseline, data is required.
A data strategy also helped BPP deliver key principles and support a four-step quality assurance process of ‘define, embed, create and predict’. Ramita explained:
“We made business decisions by mapping our data to QAA expectations for quality and standards and Office for Students (OfS) regulatory framework.”
Richard Prowse, deputy director of service design at the University of Bath, also discussed how the university uses data analytics in his keynote session ‘using data to co-design digital products and services that work'. He said:
“Recently, the university’s hospitality service found that regularly updating menus embedded in web pages was taking a lot of work and so they wanted to go back to using pdfs. But before making this change, we needed to understand what the impact would be on users. In this instance, data gave us a starting point for our investigation. It provided the groundwork for understanding what the issue was and helped us ask the right questions of users to be able to solve the problem.”
Data can break down barriers
Coming together as an organisation and using data to better all aspects of an institution is difficult when capabilities are so varied, said Gunter Saunders, associate director, digital engagement at the University of Westminster. He used his Data Matters session to discuss how digital capability underpins the running of the organisation, and how data has helped drive change “beyond the individual level”. Gunter said:
“New demands for different data to support digital teaching, particularly as a consequence of the COVID-19 crisis, are emerging, and these new data requirements are, in themselves, linked to digital capability development.”
Peter Francis, deputy vice-chancellor, and Dr James Newham, senior research fellow at Northumbria University, talked about how they are using analytics to help institutions identify what data should be prioritised when trying to provide proactive mental health support for students. In their session ‘student mental health and data analytics’, they talked about the emergence and development of the university’s mental health analytics project, and how working with sector and technology partners, drawing together existing data on students in an innovative analytics framework, meant the university was able to identify those individuals who may be at risk.
They also described how the project is working towards identifying students who may be in need of support services and ‘nudge’ them towards the resources available, while also enabling coordinated methods of engagement from the university. This is important, they said, because less than 50% of students with a mental health condition disclose this information, so being able to make accessing support as easy as possible is paramount, and data is a key indicator in this process.