Since the launch of the chatbot ChatGPT in late 2022, educators have been grappling with how to harness artificial intelligence to enhance learning while minimizing risks to educational outcomes and the fairness of assessments.
No lectures, exams, essays: inside a twenty-first-century university
AI use among students is now the norm. In February, a survey1 of more than 1,000 full-time UK undergraduates found that 92% use AI in some form, up from 66% in 2024. And 88% of students reported relying on generative AI (a form of AI that can create text, images and code from vast data sets) to support their academic coursework, compared with 53% in 2024.
As AI continues to outperform humans in basic tasks such as reading comprehension and computer programming2, concerns have been mounting about its impact on learning and academic integrity. For example, the value of conventional essays and other written assessments is increasingly in doubt, given that AI can now produce writing that often surpasses the quality of most student work.
Other concerns include an over-reliance on chatbots leading to superficial learning3, reduced opportunities for self-reflection4 and a loss of student agency5, with students becoming passive users of technology rather than active learners.
Universities have responded by using tools to try to detect student use of generative AI. But these have proven to be unreliable6. This has led to short-term fixes such as ‘stress-testing’ written assessments1 and replacing them with oral examinations, handwritten tests or reflective formats (portfolios and journals; see go.nature.com/43btcxf), as well as clearer guidelines on when AI can and cannot be used. Although these measures help, their effectiveness is limited.
Instead, a fundamental rethink of learning and assessment is needed. Here, we highlight three promising approaches to examination that adapt existing methods — such as conversation-based assessments — to the AI era. These strategies aim to foster genuine intellectual development while ensuring that evaluations accurately reflect students’ understanding and skills.
Use other types of assessment
One of the cornerstones of modern education is that ‘writing is thinking’7. Writing is a non-linear process8 that requires authentic engagement, critical thinking and problem-solving. All of these activities stimulate human intellectual development.
When AI assists with or generates student texts, however, it becomes nearly impossible to know how much of the final work reflects the student’s own understanding and critical thinking (see go.nature.com/47tjv93). This uncertainty undermines the use of writing as evidence of learning.
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