Data-driven approaches will play a crucial role in all aspects of higher education’s digital transformation
Universities collect masses of data, but how they manage that information and what insights they take from it can have a profound impact on their operations. While the sector has long used data to underpin research evaluation frameworks such as the Times Higher Education World University Rankings, data-driven approaches are now being deployed to enhance teaching delivery, student administration and welfare.
The shift to hybrid learning in response to the Covid-19 pandemic presented the industry with the opportunity to embrace a paradigmatic shift, says Alexandros Papaspyridis, Microsoft’s higher education director for APAC. He forecasts an increase in data-driven teaching and administrative initiatives, with data consolidation acting as a crucial first step that allows for innovation further down the line.
“The data exists, but it is very siloed,” Mr Papaspyridis says. “We have been helping the University of New South Wales (UNSW Sydney) to consolidate data, and they have 17 different customer relations management systems. Seventeen different systems, different datasets – and this affects 60,000 students. People often ask about how we can use machine learning, but the important thing is that you have a central repository of data and the governance and understanding of the different data you have.”
The advantages of a consolidated dataset can soon reap rewards on campus. Once machine learning protocols are established, universities can trust artificial intelligence (AI) to assume a crucial role in managing student welfare and well-being. Machine learning can be used to identify at-risk students, pulling insights from metrics such as attendance, library activity and other readily available data points to inform staff if intervention is necessary.
Mr Papaspyridis says innovative educators such as Dr David Kellermann, senior lecturer at UNSW Sydney’s School of Mechanical and Manufacturing Engineering, “are bringing new pedagogical methods relying on the effective use of Microsoft Teams and digital linking”. In partnership with Microsoft and Antares Solutions, Dr Kellerman’s department has rolled out an AI-equipped chatbot to respond to student queries.
Embedded within Microsoft Teams, the UNSW Sydney QBot is an example of how a technological platform such as Microsoft’s Cognitive Services can be deployed within the Teams environment to address an institution’s needs. This configurability of digital applications is vital. In the broader context of digital transformation, each university will have its own unique needs and challenges, contingent on a variety of factors, such as the size of the institution, its teaching and administrative frameworks, and its strategy.
Mr Papaspyridis says the Covid-19 pandemic highlighted how a data-driven teaching culture helps institutions respond to a fast-changing crisis. Universities, particularly those in Australia, often did not know how many of their international students would make it back to campus, or how many students could partake in digital learning and how engaged they were when they did.
Although these issues were a result of the pandemic, they are inherently related to the very notion of digital transformation. “For universities such as UNSW Sydney, it has been about digital transformation,” says Mr Papaspyridis. “They have a clear goal – the 2025 Plan – and the clear goal is to become a top 50 university, and therefore they need data to drive their mission. It is looking at how they can reinvent the student experience. A big part of this project with UNSW Sydney was making sure that whoever responds to an enquiry has all the information. We wanted to have a single point of contact to address a student’s questions. That is how we see reinvention.”
Universities need not be alone in the process. Collaboration with technology partners, government agencies and research companies will drive innovation. For a platform company such as Microsoft, insights from cross-sector thinktanks such as the Global Learning Council are invaluable in identifying the most effective methods for technological progress.
“What is important is that the pedagogy and the technology evolve harmoniously together, that they are not two separate things,” says Mr Papaspyridis. Data is at the heart of successful technological interventions, such as the Microsoft Academic Graph – which offers deep-search capabilities, allowing universities to gather research data more efficiently – or AI applications that can ease administrative burdens.
As Mr Papaspyridis describes it, data is one of the most valuable resources a modern university has. It just has to decide how to use it.
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