highered

Conversations about technology in higher education often swing between two extremes. On one side, there is immense optimism that digital tools will revolutionise teaching. On the other, there is a wary scepticism about whether technology adds any real value to the student experience. A more balanced view suggests the reality is far more nuanced: the success of digital learning is inextricably linked to the human element of education.

When we discuss Generative AI in education, the conversation often defaults to technical skills. But there is so much more to this shift than 'literacy' or tool mastery. The further we go, the clearer it becomes that the challenge is also deeply human. It gets personal, it gets messy, and for many educators, it's an upheaval that strikes at the centre of their professional identity.

Nearly three years after generative AI exploded into the mainstream, a strange quiet has settled over much of higher education. The initial, acute panic over plagiarism has faded, but it hasn't been replaced by a unified, urgent call for redesign. Instead, many institutions and their leaders seem to have adopted a posture of cautious observation. This posture suggests a view of AI as a technological shift similar to previous ones, which can be primarily addressed through incremental policy updates or technical solutions. This perspective truly misreads the moment.

A constant theme in my recent conversations with teachers, faculty teams and educational developers is the challenge of Generative AI (GenAI) and assessment. There's a palpable sense of pressure in these meetings, an anxious search for a definitive "solution." It’s a feeling I’m sure many in higher education will recognise, as institutions everywhere scramble for policy.

Looking for your next read? These eight books won't all sit comfortably together on a shelf—which is exactly the point. They range from scathing critiques of neoliberal universities to surprisingly practical guides on networked learning, instructional design, and (plot twist) no-dig gardening. Each one challenged how I think about teaching, learning, and what actually makes institutions flourish.

The discussion about AI in education often gets bogged down in practical questions: are you allowed to use it, and how do we then ensure ownership and reliability? While relevant, these questions stem from the outdated idea that technology is a neutral tool, separate from the learning process itself.

Every truly revolutionary tool on campus has a story. Not the story of its features, but of its impact: a colleague who finally perfected their dream seminar, a team that unlocked a new way to collaborate with students. These are the moments that matter. They're the sparks that make us lean in and ask a trusted peer, “How did you do that?”