Conversations?over students using artificial intelligence to cheat in their exams are masking wider?discussions?about how to improve assessment, a leading professor has argued.

Phillip Dawson, co-director of the Centre for Research in Assessment and Digital Learning at Deakin University, argued that ¡°validity matters more than cheating¡±, adding that ¡°cheating and AI have really taken over the assessment debate¡±.

Speaking at the conference of the UK¡¯s Quality Assurance Agency, he said: ¡°Cheating and all that matters. But assessing what we mean to assess is the thing that matters the most. That¡¯s really what validity is¡­We need to address it, but cheating is not necessarily the most useful frame.¡±

Dawson was speaking shortly after the publication of a survey conducted by the Higher Education Policy Institute (Hepi), which found that 88 per cent of UK undergraduates said they had used AI tools in some form when completing assessments.

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But the Hepi report argued that universities should ¡°adopt a nuanced policy which reflects the fact that student use of AI is inevitable¡±, recognising that chatbots and other tools ¡°can genuinely aid learning and productivity¡±.

Dawson agreed, arguing that ¡°assessment needs to change...in a world where AI can do the things that we used to assess¡±, he said.

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Referencing may be a good example of something that can be offloaded to AI, he said. ¡°I don¡¯t know how to do referencing by hand, and I don¡¯t care¡­We need to take that same sort of lens to what we do now and really be honest with ourselves: what¡¯s busy work? Can we allow students to use AI for their busy work to do the cognitive offloading? Let¡¯s not allow them to do it for what¡¯s intrinsic, though.¡±

It was a ¡°fantasy land¡± to introduce what he called ¡°discursive¡± measures to limit AI use, where lecturers give instructions on how AI use may or may not be permitted. Instead, he argued that ¡°structural changes¡± were needed for assessments.

¡°Discursive changes are not the way to go. You can¡¯t address this problem of AI purely through talk. You need action. You need structural changes to assessment, [and not just a] traffic light system that tells students, ¡®This is an orange task so you can use AI to edit but not to write.¡¯

Resources on AI and assessment in higher education

¡°We have no way of stopping people from using AI, if we aren¡¯t in some way supervising them; we need to accept that. We can¡¯t pretend some sort of guidance to students is going to be effective at securing assessments. Because if you aren¡¯t supervising, you can¡¯t be sure how AI was or wasn¡¯t used.¡±

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He said there were three potential outcomes for the impact on grades as AI develops: grade inflation, where people are going to be able to do ¡°so much more against our current standards so things are just going to grow and grow¡±; and norm referencing, where students are marked on how they perform?compared with other students.?

The final option, which he said was preferable, was ¡°standards inflation¡±, ¡°where we just have to keep raising the standards over time because what AI plus a student can do gets better and better¡±.

Overall, the impact of AI on assessments was fundamental, he said, adding: ¡°The times of assessing what people know are gone.¡±

juliette.rowsell@timeshighereducation.com