- Academics seem to overestimate the degree to which students are using generative AI in their studies
- ChatGPT and other AI tools are preferred by students as productivity tools that cover everything from producing text to improving grammar
- Mixed experience and knowledge of AI among university staff has made it more difficult to judge how students use the technology, offering an opportunity for improvement among academics
A new study has revealed the differences between students and lecturers when it comes to AI use, implying that academics think students are using generative AI too much, whereas students think they’re not using it that much.
Rating their perception of AI use, the academic staff who responded to the research recorded an average of 5.23 out of 7, whereas students recorded 3.11 on average.
The research highlights the differences in how AI is viewed among educators and students, with generative AI the focus. Common uses for the technology include producing written text and checking grammar on existing writing. It is also commonly used for research, finding answers to assignments, and other tasks where finding sources needs to be more efficient.
Understanding AI use
The research from the University of Manchester and Spain’s Universidad del Pais Vasco/Euskal Herriko Unibertsitatea took place between April and June 2024. A school of social science disciplines based at a research-intensive university was chosen for the study, which surveyed 45 academic staff and 86 students.
While the results above indicate that students believe their AI use is low, it may be subject to some underreporting. However, the researchers also add that AI use can be difficult for lecturers to spot. Staff use of AI tools was recorded, with just 14% using a paid AI tool subscription.
Whatever this research tells us about AI use in universities, it should be viewed within context of a two-year old study at a single university.
A complex reality
AI use among students has rocketed over the past few years, with the technology becoming as relevant to coursework and research as Google Docs and Wikipedia. Some educators have resigned themselves to marking work produced with AI, while others have taken more extreme measures.
“There is a tendency for the debate about AI in universities to focus on the risks of cheating or the promise of transforming education, but the reality is more complex,” noted Dr Mark Carrigan, Senior Lecturer in Education at The University of Manchester and one of the study’s authors.
Finding a response that universities can apply as a policy for learning requires greater understanding on AI use among students, Dr Carrigan says. “Our findings suggest that staff and students have quite different perceptions of how AI is being used, making it difficult for universities to develop effective responses based on assumptions rather than a clear understanding of students’ experiences.”
The solution, Carrigan adds, is to embrace AI at all levels – for students and lecturers.
“We need to move beyond a climate of suspicion and focus on how these tools can be used appropriately to support learning, while rethinking teaching and assessment for an AI-enabled world.”
