‘We shouldn’t sleepwalk into a “tech knows best” approach to university teaching’

The anxiety some lecturers experience around generative AI (GenAI) may stem from a traditional view that education is an intellectual endeavour that requires students to develop their own thinking and cultivate an academic voice. This process goes beyond having something to say; it is about fostering original thought and perspective. The fear, therefore, is that students’ excessive reliance on GenAI could lead to intellectual stagnation. 

Simply having an opinion on AI, however, is insufficient to address the realities of its prominence in higher education. Practical solutions are needed for those expected to engage with GenAI pedagogically, ensuring both staff and students become AI literate and can “capitalise on the opportunities technological breakthroughs provide for teaching and learning”, as noted by the Russell Group’s 2023 AI guidelines.

So far, UK universities’ responses to the use of GenAI and large language models remain mixed. While many embrace, or even actively encourage, the educational opportunities presented by AI, narratives continue that equate its use with cheating or worry that it may conflict with academic integrity. Some universities have banned the use of AI technology in assessed work, classifying it as academic misconduct. Nevertheless, the proportion of students using GenAI tools such as ChatGPT for assessments has risen from 53 per cent in 2023-24 to 88 per cent in 2024-25, according to research published by the Higher Education Policy Institute/KortextAI.

Instead of bans, we should focus on rethinking assessment strategies to integrate AI as a collaborative tool in academic work.

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With this in mind, we have compiled a list of activities that we have successfully used in our lectures that leverage GenAI to support teaching and learning. These activities are grounded in the constructivist approach to education, which emphasises collaborative knowledge construction. In this context, AI serves as a mediator, tool, tutor or a more knowledgeable other to facilitate the co-construction of knowledge. These four key categories of AI-enhanced learning and teaching show how AI can be used not just as a content generator, but as a tool to draw out ideas and insights from students.

AI-supported analysis and critical thinking

Incorporating AI into these three analysis and critical-thinking activities allows students to engage with complex topics in a structured manner. 

1. AI transcribes a class discussion and identifies key themes; students rank them in order of importance to the topic and use them to develop their essays.
2. Students analyse AI-generated case studies (which can be pre-programmed with intentional flaws) to identify ethical concerns and problem-solving strategies.
3. Students compare AI-generated information with academic sources, identifying biases, misinformation and credibility gaps.

AI-assisted writing and academic skills development

These activities can support students in refining their academic writing, structuring arguments and improving coherence through AI-generated exemplars and structured feedback.

1. AI generates multiple versions of good, bad and ugly examples of academic writing (such as abstracts); students identify writing aspects and group versions based on common features.
2. Students use AI-guided prompts to receive targeted feedback on academic writing, experimenting with different focus areas to refine their work and enhance self-assessment skills.
3. Students use AI to create structured task lists for dissertations/essays, breaking them down into smaller activities with downloadable checklists.

AI for creative and interactive learning

These activities engage students through interactive tasks, such as AI-generated escape rooms or AI-driven role-playing. 

1. Students participate in AI-driven simulations and role-play activities, allowing them to develop professional skills and apply theoretical knowledge in practical scenarios. 
2. Students engage with AI-powered tools such as Padlet, Google Docs or Trello to participate in discussions via blog-style posts, offering diverse ways to interact and share ideas.
3. AI generates an “escape room” activity using a given text as a source, incorporating tasks like word fill-ins, definition matching, code cracking and data analysis.

AI for fostering inclusion 

Addressing diverse learning needs, supporting accessibility and personalising learning experiences is a core part of these activities.

1. Students access AI-generated podcasts, transcripts and alternative content formats to support diverse learning needs and enhance accessibility.
2. Students use AI for text-to-speech and speech-to-text conversion, helping those with dyslexia, visual impairments or processing difficulties engage with content in their preferred mode.
3. Students use AI for real-time translation, translating key academic concepts between their native language and English.

We should move away from viewing GenAI as a tool for generating ready-made answers, and instead reframe it as a resource that helps draw out ideas and insights from students. In this way, GenAI can be seen to develop the skills educators have long aimed to nurture: critical thinking, creativity and independent thought. So, we must empower, amplify and encourage student voice through GenAI, rather than sleepwalking into a “tech knows best” approach.

Rebecca Mace is a senior lecturer at the University of Worcester. Viktoria Magne is an associate professor; Sarah Hooper is a lecturer; and Sharon Vince is a senior lecturer, all at the University of West London.

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