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The question is no longer whether students will use AI after graduation but to what extent. So, how can universities best ensure that students are workforce-ready?

How playful exercises in an intersession course can improve judgement, foster probabilistic thinking and help students stand out in an uncertain job market

How to build evidence of your academic career successes when the expectations keep changing? Here are two approaches

We find out how one US institution has led the way in embedding AI across all its majors and what has been learned in the process

LinkedIn can help researchers build international collaborations, but only when it is treated as a professional community, not just a digital CV. Follow these tips to grow your profile

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