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News / AI cheating surges at UK universities: Why old-school exams might be the answer
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AI cheating surges at UK universities: Why old-school exams might be the answer

Alex Carter
ByAlex Carter
AI News & Big Tech Correspondent
Alex Carter writes for Aiholics, keeping readers updated on the fast-paced world of AI and Big Tech. He breaks down important news and developments from the...
- AI News & Big Tech Correspondent
Published: July 30, 2025
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There’s no denying it: AI is changing the way students tackle university exams and assignments—and not always for the better. I recently came across some startling insights revealing that cheating involving AI tools has on average tripled over the last year at a number of UK universities. What’s even more eye-opening are the methods students are now using to lean on AI, and how little resistance there currently is from academic institutions to manage the problem.

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How students are using AI to beat exams and coursework

I found it fascinating when some students anonymously shared exactly how pervasive AI use has become. One student admitted to using AI-powered tools everywhere—from assignments to open-book exams to in-class discussions. They described effortlessly copying and pasting exam questions into ChatGPT and parroting answers back as if participating in genuine group discussions. Another hack? Snipping multiple-choice questions into the prompt and getting instant correct answers within seconds. All this with almost zero critical thinking involved.

What struck me most was the confession that by their second year, they hadn’t engaged with any readings but still managed to pull top grades—largely thanks to AI voicing up their work. This paints a worrying picture of students potentially losing the ability to think independently and engage deeply with their studies.

Experts weigh in: Can we realistically police AI misuse?

According to Dr. Edward Howell, a lecturer at the University of Oxford, simply banning AI use among students is unlikely to work. The fundamental challenge? There’s currently no reliable way to trace or verify AI use in student work. That’s why he advocates for a return to handwritten examinations, which create a level playing field and reinforce the university’s core mission of teaching critical thinking skills.

On a related note, I came across insights from Chris Cameron, CEO of Turn It In, a company that has made a career out of detecting academic misconduct. He revealed that around 20% of student essays run through their platform include significant AI-generated content, with 10% almost completely AI-written. To tackle this, their software uses a clever technique: they train AI on thousands of essays written both by humans and by large language models like ChatGPT to help distinguish authentic work from AI-generated text.

Yet, no AI detector is perfect. Turn It In admits to a very low but real false positive rate—that is, about one in 200 students might be mistakenly flagged for AI misuse. However, the good news is transparency from students can quickly settle disputes; teachers can check revision histories in Word or Google Docs to confirm whether work was produced gradually by the student or pasted wholesale from AI.

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20% of student essays submitted to detection software contain substantial AI content—showing how widespread the issue really is.

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Why the UK risks falling behind—and what universities say

Interestingly, the UK has historically been a leader in using tech to uphold academic integrity. It was among the first countries to adopt anti-plagiarism software extensively over 20 years ago. However, AI detection tools are currently in use at only about 15% of UK universities, compared with around 80% adoption in other countries. This gap represents a real missed opportunity to deter AI misuse by making students aware their work will be checked rigorously.

Universities UK acknowledges the challenge but stresses that AI itself can’t just be ignored or feared. Instead, they urge institutions to focus on supporting students to harness AI ethically and responsibly, while still enforcing penalties for misconduct. This balanced stance reflects the uneasy middle ground many universities are navigating as AI becomes embedded in academic life.

Key takeaways for students and educators

  • AI cheating is widespread and growing fast, with some students relying on it for most of their work.
  • Traditional methods like handwritten exams might help restore fairness and critical thinking development.
  • Advanced AI detection tools exist, but must be paired with transparent review processes to avoid false accusations.
  • The UK lags behind other countries in adopting AI detection tech, risking academic standards.
  • Universities recognize AI as inevitable and focus on helping students use it responsibly instead of outright bans.

Final thoughts

After digging into this issue, it’s clear that AI’s role in university cheating is much more than a passing trend—it’s a fundamental challenge disrupting how we evaluate learning itself. While some students have embraced AI as a shortcut, educators and institutions are still scrambling to catch up with effective solutions. I was particularly struck by the suggestion that going back to basics with handwritten exams could be one of the most straightforward ways to protect academic integrity and critical thinking.

At the same time, AI isn’t going away. The conversation isn’t about fearing technology but learning to navigate its impact intelligently. Supporting students in using AI ethically while enhancing detection tools and revisiting assessment formats could strike the balance we so urgently need.

As AI continues shaping education, staying informed and adaptable will be essential—for students eager to learn honestly and for universities committed to fair, meaningful assessment.

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ByAlex Carter
AI News & Big Tech Correspondent
Alex Carter writes for Aiholics, keeping readers updated on the fast-paced world of AI and Big Tech. He breaks down important news and developments from the industry's top players, including OpenAI, Google, Meta, Microsoft, and NVIDIA. His goal is to present these updates in a straightforward way that’s easy to understand and genuinely helpful. What makes Alex different is that he's focused on technology that matters to real people's lives, not just for flashy headlines. He demonstrates why each news is important, answering the most important questions for readers: "Why should I care?" From major AI models to big acquisitions and new tools, Alex examines what it means for businesses, society, and end-users. When not reporting, Alex enjoys covering the trends in AI competition, tech ethics, and what's next in digital.
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