At Bett 2024, one theme rang above the rest, AI, which dominated the talks and displays of the show. At one of the talks, the focus was all on how AI can be effectively built into higher education institutions. Hosted by Gill Ferrell, Program Director at 1EdTech Europe & Relationship Manager at EUNIS, with guest speakers Professor Perry Hobson, Director at Breda University, and Ugne Litvinaite, Research Assistant at LSE Eden Centre, the discussions highlighted best practices for bringing AI and higher education institutions into one.
Throughout the talks, two key themes emerged, the first being the importance of identifying where AI needs to be implemented in a meaningful way, and the methodology of implementation.
Meaningful AI endeavours in higher education institutions
“One question that we’re all asking ourselves is ‘Where do we actually implement technology into our operations?’” led Hobson. The go-to answer for this is always teaching and learning as the top priority, followed by research and innovation, which both sound great on paper, but if it was so simple then these talks wouldn’t need to happen. Instead, Hobson and his team at Breda University believe that there is so much more to this topic, “…operations are a key area too, and the realities of education finance cause this.” So what is the answer? For Hobson there needs to be strategy to the implementation of AI into higher education institutions, without it, it is doomed to fail.
When implementing AI, higher education institutions must consider the key areas that will see the most return on investment. These being, vision and goals, talent and development, curriculum development, AI in operations, infrastructure and resources, data governance and ethics, and research and innovation. At Breda University, Hobson and his team have begun to work on this approach and have seen growing successes.
For visions and goals, they have begun the think about the role of AI for students of the future, areas that will both impact and be impacted the most by AI, and align AI with the overall mission that Breda is trying to achieve. Within talent and development, they have set up a ‘Pioneers Team’ whose goal is to attract and generate top talent within the AI field through workshops, training, and professional development. Curriculum development has included the designing of and improvement of AI-focused courses, collaborations with industry, and constant considerations of testing and assessment methods. Within operations, cost efficiency and value are top priorities when it comes to AI, something that the Breda team strongly believes will elevate the institution, benefit staff, and enrich learning for students. AI is also allowing Breda to enhance institutional infrastructure and resources through current systems and applications evaluation and improved budget and resource allocation. AI is also being used to develop policies and procedures as well as constantly considering biases, ethical practices, and fairness that might be missed, enhancing data governance and ethics of the institution. Finally, on the research and innovation front, AI is enabling interdisciplinary collaborations as well as those with industry and has resulted in an uptick in Startups/Spinouts. Breda has also implemented a dedicated AI research centre to help pioneer all of these fronts.
For Hobson, this multifaceted approach means that almost all the key areas of the institution are feeling a positive impact from the use of AI, with none lagging behind others. It is also helping to address the skills gap that is often present when it comes to AI, as Hobson noted: “Lots of people know about AI, which is great, but very few actually understand what it is.” For these reasons, it is important that institutions hit all areas when onboarding AI and simultaneously roll out training for students and the institution alike.
How to implement AI into institutions successfully
Interestingly, one of the key considerations that need to be made when bringing AI to an institution is not with the institution itself, but rather with the students. Litvinaite, backed by research from LSE Eden Centre, found that it is just as important to communicate with students concerning AI as it is with any staff or board members, “transparency is key,” she enthused. After all, at its core, it’s the students who will be impacted the most by the new wave of emerging AI within higher education and beyond. Many of the factors that students strongly believe need to be considered do align with those of the institution but there are outliers. Most critical to this is clarity when it comes to AI, specifically with academic integrity rules and assessment. It is critical to ensure that communication takes place so that both student and teacher understand the rules when it comes to AI within education, where it can and cannot be used, when it makes sense to be used and when it doesn’t, as well as the open use of AI. Without this level of transparency, “it would be hard to keep up to date with the technology,” says Litvinaite.
Thus, these factors are essential, along with those outlined by Hobson in ensuring a successful implementation of AI into higher education institutions.