University assessment and quality assurance

If educators don’t understand the learning processes, they also miss the reasons why students cheat, writes Margault Sacré. Here, she offers an approach to motivate and benchmark progress

Leadership and critical-thinking skills are difficult to measure. Here, Jonna Lee offers case studies that test the idea of integrating large language models into assessment practices as a feedback tool to empower both students and instructors

The ability to use generative AI is akin to time management or other learning skills that students need practice to master. Here, Vincent Spezzo and Ilya Gokhman offer tips to make sure instructions land equally no matter students’ level of AI experience

Let’s embrace the benefits of AI rather than fearing its impact on academic misconduct. Dilshad Sheikh offers her tips on adopting new technology in pedagogy

Interactive workshops and user-friendly guides can unlock the potential of ChatGPT in assessment and overcome initial hesitation around its use. Here, Dianne Stratton-Maher looks at ethical and responsible use of generative AI

A new era of AI requires a balance between thoughtfully mitigating and responsibly promoting student use of new tools

If GenAI tools have ushered in an era in which institutions can no longer assure the integrity of each individual assessment, the sector must focus on assuring the integrity of awards, write Samuel Doherty and Steven Warburton

In this extract from their new book, ‘Teaching with AI: A Practical Guide to a New Era of Human Learning’, José Antonio Bowen and C. Edward Watson discuss the reliability of AI detection tools and how to combat cheating without them

With large language models to provide reports and analysis, educators can make use of generative AI to improve the process of student evaluations, writes Adnan Ajšić

Our response to ChatGPT and its successors should be one that encourages open, interdisciplinary discourse and supports research investigating AI from every angle