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The primary source of institutional AI proficiency must be universities themselves, not the technology companies who offer training for their platforms. Without that agency, we risk surrendering educational practice to commercial interests, write Amy Allen and David Hicks

Practical advice for universities and departments that want to begin including public work meaningfully in hiring, tenure and promotion standards

By the time they arrive at university, most students are using AI. So, with the lines between AI use and original work increasingly blurred, academia now needs to teach them how to use the tools critically

Why do institutions invest in peer writing support for students but not for staff? Anne Brubaker makes the case for a more formalised approach to faculty writing support

The advent of generative AI plus questions about the relevance of higher education call for a closer look at how critical thinking skills are taught and measured. Kate Williams offers ways to level up traditional assessment formats

Combining mentoring skills with structured guidance can help doctoral researchers build confidence and refine their focus. Here’s how

Treating work placements and co-curricular programmes as optional or supplementary misses deeper questions about whether traditional degrees prepare students for careers. Michelle Seref explains

Outreach initiatives can introduce potential students to the support that will be available on campus, develop their research skills and instil a sense of belonging before they arrive. Kealin McCabe outlines different approaches

If we continue to prioritise memorisation in an age of wall-to-wall information, we send the wrong message to our students and employers. Michelle Seref offers advice on assessment that builds critical thinking skills

Students often accept AI output without questioning it. Designing assignments where the tool fails – visibly and meaningfully – can change that, as Jan Burzlaff explains