How are universities responding to generative AI?
What’s next for higher education as we enter a new wave of edtech innovation: AI-powered learning
Covid-19 lockdowns proved that universities can be fast and agile when they have to be — and the past 12 months have been almost as tumultuous. OpenAI’s ChatGPT burst onto the scene at the end of November 2022, registered more than one million users within five days and swiftly became a game-changer. In HE, the immediate preoccupation was academic integrity and assessment, but now the dust is settling we’re beginning to get a clearer picture of the challenges and opportunities AI will present for universities in the medium and long term.
So what does change look like for the next wave of edtech innovation in HE?
On a wintry afternoon in central London, 30 senior leaders from innovative universities and HE organisations across Europe gathered for the Jisc/Emerge edtech leadership board. Their goal: to act as the sector’s innovation radar, finding the hottest new trends and championing edtech solutions that really make a difference for educators and students.
Here is a snapshot of their discussions.
Read on for …
- The biggest problems in the sector that require innovation to solve
- How AI can help solve those problems — and which areas are ripe for innovation
- How you can get involved in our research
What are the biggest problems in HE that require innovative solutions?
“AI is a huge step change. We’ll need to navigate faster than anything in the past 100 years. The good news is that the field is innovating so fast, it’s relatively easy to catch up quickly. Startups have a role to play in pushing boundaries, but the challenge around adoption is less technical feasibility and more culture. An important part of that is educating faculty so they understand, embrace and make use of AI.”
Sven Schutt, CEO, IUBH
In a wide-ranging discussion, our HE board identified the biggest problems in the sector right now that are not being met by edtech companies or other providers, and that require innovation to solve:
- Single view of the student → Apps allowing integrated access to all aspects of student welfare and learning performance, including methods to track face-to-face and digital engagement.
- Mental wellbeing / student wellness → Tools to promote student community and belonging.
- Job readiness → Incorporating real-world problem solving, collaboration and “soft” skills as part of your degree.
- Authentic assessment → Providing personalised, adaptive learning for different learning styles at scale.
- Interoperability / data aggregation → Digital transformation and seamless integration of tools underpinned by joined-up data.
- Academic workflow management → Thinking about how tech will be used by (differentially) qualified people, and AI safety and training.
- Scaling innovative solutions in HE → providing all of the above across whole institutions, not just in pockets of best practice.
You can read more about how edtech is helping HE leaders address some of these challenges in our latest report. We believe that we are now entering a new wave of edtech innovation: AI-powered learning.
“AI vertigo”
“The challenge as a practitioner is not just the speed of innovation but also AI as a tool — we could call it ‘AI vertigo’. We are relearning and rediscovering every day, and adapting to new use cases.”
Pierre-Paul Cavalie, chief digital officer, SKEMA Business School
We asked our HE edtech leadership group how their feelings about the role of AI in education have changed in the past 12 months. Almost half (48%) felt more optimistic and another third (38%) felt about the same as they did a year ago — an overwhelming majority who have responded positively to the innovations, debates and controversies of the last year.
So how is that feeling reflected in practice? Again, a clear majority (57%) told us that they are already using AI in their research and/or teaching, and those who aren’t yet using AI expect to in the future (24%). The sole reason given for not engaging yet is simply lack of time to learn and experiment.
Zooming out, we then asked for our HE board’s impressions about how pioneering or on the back foot their institution is in relation to the wider sector when it comes to adopting AI as part of teaching and learning so far.
Most responses fell in the middle, reflecting a sense that most universities feel confident about reaching some low-hanging fruit but, beyond that, it’s hard to visualise at this stage what “pioneering” might look like.
The most common barriers cited to the adoption of AI at an institutional level were:
- Concerns around staff digital skills, confidence and anxiety about AI, especially alongside the relative absence of dedicated AI and education technologist teams who could act as ambassadors to demystify the risks and rewards of new technologies.
- A strong sense that existing infrastructure, workflows and IT services are struggling to adapt.
- There is a need to curate the various players to support universities with greater understanding of commercially viable options.
“Organisational culture is what makes it difficult. Edtech providers solve a small part of a larger problem; connection is the bigger problem. We need collaboration — we need innovators to think more about the whole problem, because solving individual elements of the problem may have no impact.”
Ian Dunn, Provost, Coventry University
Finally, we asked for our board’s reflections on the potential benefits that AI could enable for HE, as well as the risks that it could pose:
Where will AI make a big difference?
At Emerge, we have identified eight high-level trends — what we’re calling “engines of opportunity”. These eight “engines of opportunity” capture our ideas about how AI is being used to drive better practice and outcomes in HE, now and into the future.
They fall into two main categories:
- Making learning more engaging: solutions that scale high quality pedagogy at low cost.
- Making teaching more efficient: solutions that save educators and organisations time and money.
Our HE board took a deep dive into three categories that we think will be transformative for universities. Here are their thoughts.
Educator co-pilots
What are you most excited about?
- If we look at the mundane admin tasks currently being done by humans, it’s a no brainer.
What are you most wary of?
- Technology has tended to intensify work, rather than de-intensify. What changing capabilities and skills around implementation — licensing, data governance, integration etc — will be needed that almost eclipse the benefits? Do we just create new forms of drudgery?
- Quality assurance: Universities are wary of churning out material, as there’s a worry that through lowering barriers to content creation, we also lower the bar in terms of quality. By making content creation easier we are also potentially stifling innovation.
- The impact of the type of institution and subject mix in terms of how the technology can be adopted, including the costs associated with adoption. Will economic realities drive differential adoption across institutions?
Automated assessment
What are you most excited about?
- Assessment is now used in recruitment, e.g. detecting use of AI in job applications, so there is precedent for more authentic and innovative assessment formats.
- Does every assessment have to be AI proof — what does that mean? Why can’t students use AI to help them learn the basics?
What are you most wary of?
- The realities of implementation, especially across different disciplines: How do you apply a marking rubric automatically in a qualitative discipline? Do you “normalise” and lose creative/innovative answers? How would moderation/edge cases be accommodated? All these questions tie in to a fear within the sector that automating assessments would lead to a lowering of standards.
“There are big challenges around student culture, as well as academic culture. Students are all social media literate — they’re not AI/digital literate, especially when it comes to assessment. Bluntly, they say that if they can’t use AI in assessment, they don’t want it used in marking. Students are scared of this space, especially if they think there’s a risk it’s going to bring their marks down at all.”
Deborah Longworth, Pro-Vice-Chancellor for Education, University of Birmingham
Roboteacher
What are you most excited about?
- Roboteacher as Teaching Assistant, generating questions to test student understanding of concepts. There is real potential around personalisation — AI can enable learners to request things in ways that suit them. Students emit lots of data to universities about ways they’re struggling, and the big vision here is about using that. The risks are in the detail; some subjects will find it easy to incorporate this kind of tool, but other categories such as wellbeing are much more difficult.
- Roboteacher as student copilot, or “guide on the side”. Students are inundated with information, in a “tyranny of transparency” — students get so much info, they turn to a human being to curate the answers for them, but this means students ask similar questions of their lecturers a lot. Staff will need to introduce a roboteacher as part of teaching in order to cultivate trust.
What are you most wary of?
- The word “Roboteacher”! The saying goes, “Pedagogy first, digital second”. Robo-teacher fails that test.
“Teaching instigates a change that happens in a learner, when they move from knowing to doing. What teachers do is actualisation. We need a high-level conceptual model of what this learning experience is, how a teacher interacts with different phases of that experience, and then how AI can appear at different moments to facilitate that. We’re seeing endless tools but no one is linking this to a high-level conceptualisation of what exactly tools should deliver and improve. Some tools might take us into new territory that doesn’t exist in current taxonomy.”
Nick Mount, Academic Director, University of Nottingham Online
From enrolment to employability: the student journey
Over the coming months, we will explore these AI edtech categories in-depth in relation to every step in a student’s journey — from discovery and enrolment, through student experience and learning access, to assessment, graduate employability and beyond.
We will publish frequent research pieces on these topics, including market maps to plot the existing and emerging players at each step in the student journey— and we will publish case studies showcasing innovative practice at global universities. The focus might be on one part of a university, such as Novus at Tec de Monterrey in Mexico or ASU’s Learning Futures studios, or it might be a new HE provider that was born innovative, such as Minerva or LIS. In each case we’ll explore what’s working and why — and what other universities can learn from it.
We want to hear from you
- We want to draw on your expertise and contacts — which international universities would you like us to approach for case studies? Have you come across great examples you would like us to look into? Please share!
- We’d also love you to recommend exciting edtech companies that you have seen for our market maps.
- This research will underpin Edtech 20:20 vision — the list of top global emerging edtech companies that we publish every July. You can see the 2023 list here.
At Emerge, we are on the look-out for companies (existing and new) that will shape the future of learning in higher education over the coming decade.
If you are a founder building a business addressing any of these challenges in HE, we want to hear from you. Our mission is to invest in and support these entrepreneurs right from the early stage.
So if you are looking for your first cheque funding do apply to us here: https://lnkd.in/eWi_9J5U . We look at everything as we believe in democratising access to funding (just as much as we believe in democratising access to education and skills).
Emerge is a community-powered seed fund home to practical guidance for founders building the future of learning and work. Since 2014, we have invested in more than 80 companies in the space, including Unibuddy, Cadmus, Engageli and Mentor Collective.
Emerge Education welcomes inquiries from new investors and founders. For more information, visit emerge.education or email hello@emerge.education, and sign up for our newsletter here.
With special thanks to all members of the Higher Education edtech advisory board, led by Mary Curnock Cook. Read more about our work here.
Thank you for reading… I would hugely appreciate some claps 👏 and shares 🙌 so that others can find it!
Nic
