Where will generative AI take university learning?
Generative AI will no doubt transform higher education. The sector must understand how these changes will affect educators and learners
Words by Juliet Andrews, director in people services at EY Australia
Generative AI can and will revolutionise university learning – both the design and delivery of learning and the way students consume and understand content. AI that can quickly create consumer-grade digital learning content is already being developed. But this is just the start.
The ability of large language models (LLMs) to create hyper-personalised content in real time, coach students and constantly improve curricula signals the beginning of a new era of teaching for higher education.
Quality digital learning will become entry level
EY 2023 research, conducted with 3,030 students from eight countries, made it clear that in-person, mass lectures must give way to a model where asynchronous digital learning supports synchronous, interactive engagement. Quality digital content will allow students to learn at their own pace and style outside of class. Then they will work with faculty in interactive activities and discussions during class time, whether online or in person, to gain a deeper understanding of the content.
Contemporary AI tools can help faculty develop content through language, imagery, audio and visual design to create more engaging study materials. As a result, rather than suffering through old-fashioned, text-based online learning, students can have a choice of videos, games, podcasts, reflection questions and interactive micro-assessments. All these assets should come with digital learning science principles built in – and with a consistent, quality look and feel.
Using these new AI tools, faculty with limited digital expertise can convert entire portfolios in a fraction of the time it would take to manually create digital content.
Hyper-personalisation will support student success
AI-created content can give students a choice of different learning pathways. If someone studying from written text can’t answer a question, the system could offer them an alternative route such as a video or practical activity. Currently, these options have to be manually built, which can be expensive, and not all of them will necessarily end up being used.
As AI improves, pre-built pathways will become less relevant. Instead, LLMs will be able to respond in real-time with a personalised alternative based on what learning style has worked previously with the student and their level of understanding. LLMs will also identify areas of weakness or strength so they can focus on concepts where the individual is struggling – or offer fertile minds extension opportunities.
AI tutors will keep students on track
In some countries, schools are already using AI tutors to help pupils in real time, responding to questions, giving hints and providing extra questions to consolidate their understanding.
Universities will also use AI tutors to provide students with instant feedback on assignments, quizzes and practice problems. Integrated with learning platforms and calendars, AI tutors will remind students of upcoming deadlines, help them prioritise tasks, set realistic deadlines based on previous completion times and allocate time slots for assignments.
Learning data will give rise to a living curriculum
As well as being updated to reflect advances in knowledge, technology and industry trends, the data from learning platforms will enable curricula to be constantly refreshed and updated. Activities with low engagement scores or poor test results can be updated with more effective teaching methods based on insights from an ever-expanding cohort of learners.
In all of this, the role of academics and learning designers will be paramount. Freed of the need to create digital content, their remit will be to assure quality and rigour while learning the art of the possible when generative AI transforms university teaching.
