{"id":77222,"date":"2025-06-12T00:46:29","date_gmt":"2025-06-12T04:46:29","guid":{"rendered":"https:\/\/world.edu\/?p=77222"},"modified":"2025-06-12T00:46:29","modified_gmt":"2025-06-12T04:46:29","slug":"assessment-in-the-age-of-ai-unis-must-do-more-than-tell-students-what-not-to-do","status":"publish","type":"post","link":"https:\/\/world.edu\/assessment-in-the-age-of-ai-unis-must-do-more-than-tell-students-what-not-to-do\/","title":{"rendered":"Assessment in the age of AI \u2013 unis must do more than tell students what not to do"},"content":{"rendered":"

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In less than three years, artificial intelligence technology has radically changed the assessment landscape. In this time, universities have taken various approaches, from outright banning the use of generative AI, to allowing it in some circumstances, to allowing AI by default.<\/p>\n

But some university teachers and students\u00a0have reported<\/a>\u00a0they remain confused and anxious, unsure about what counts as \u201cappropriate use\u201d of AI. This has been accompanied by concerns AI is facilitating a\u00a0rise in cheating<\/a>.<\/p>\n

There is also a broader question about the\u00a0value of university degrees<\/a>\u00a0today if AI is used in student assessments.<\/p>\n

In a\u00a0new journal article<\/a>, we examine current approaches to AI and assessment and ask: how should universities assess students in the age of AI?<\/p>\n

Why \u2018assessment validity\u2019 matters<\/strong><\/h4>\n

Universities have responded to the emergence of generative AI with various policies aimed at clarifying what is allowed and what is not.<\/p>\n

For example, the United Kingdom\u2019s University of Leeds set up a \u201ctraffic light<\/a>\u201d framework of when AI tools can be used in assessment: red means no AI, orange allows limited use, green encourages it.<\/p>\n

For example, a \u201cred\u201d light on a traditional essay would indicate to students it should be written without any AI assistance at all. An \u201camber\u201d marked essay would perhaps allow AI use for \u201cidea generation\u201d but not for writing elements. A \u201cgreen\u201d light would permit students to use AI in any way they choose.<\/p>\n

In order to help ensure students comply with these rules, many institutions, such as the\u00a0University of Melbourne<\/a>, require students to declare their use of AI in a statement attached to submitted assessments.<\/p>\n

The aim in these and similar cases is to preserve \u201cassessment validity<\/a>\u201d. This refers to whether the assessment is measuring what we think it is measuring. Is it assessing students\u2019 actual capabilities or learning? Or how well they use the AI? Or how much they paid to use it?<\/p>\n

But we argue setting clear rules is not enough to maintain assessment validity.<\/p>\n

Our paper<\/strong><\/h4>\n

In a\u00a0new peer-reviewed paper<\/a>, we present a conceptual argument for how universities and schools can better approach AI in assessments.<\/p>\n

We begin by making the distinction between two approaches to AI and assessment:<\/p>\n