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*This resource has been tested for appropriateness in the classroom and scrutinised for safeguarding and cybersecurity issues. However, please do carry out any due diligence processes required by your own institution before using or recommending it to others.
*This is an example of a resource that is under development and may not have been fully vetted for security, safety or ethics.  Please carry out your own safeguarding and cybersecurity due diligence before using it with students or recommending it to others.

AI-Powered Revision: Student Led Revision using AI

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Key Stage 5
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Case Study
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Chris Goodall

Head of Digital Education

In a classroom experiment, AI was employed to revamp traditional revision methods for inventory control in business. With AI serving multiple roles, students took the lead, crafting prompts and diving deep into the topic. The result? A dynamic, interactive, and productive learning experience that showcased the transformative potential of AI in education.

The integration of AI, into a revision session on inventory control in business was not just an experiment; it was an attempt towards reshaping traditional pedagogical methods. The goal was clear: to determine if students, when empowered with AI, could lead their own learning journey and potentially achieve a richer understanding of complex topics.

The session began with students divided into brainstorming groups. Each group deliberated on potential prompts they believed would provide valuable insights into the topic of inventory control. This initial stage was crucial as it fostered collaboration and encouraged students to think critically about the areas they needed clarity on.

Once a number of prompts were devised, they were projected onto the Smartboard. This visual representation allowed for a democratic approach, with students voting on their preferred starting prompts. The initial interactions with this method were somewhat tentative. Students sought foundational knowledge, such as AI's relevance in business revision and a breakdown of key terms and concepts.

However, as the session progressed, a noticeable shift occurred. As students began to grasp the depth and adaptability of AI, their queries evolved from basic to advanced. They started challenging the AI with requests for analogies that could simplify complex concepts. They asked AI to conjure real-world case studies, helping them bridge the gap between theoretical knowledge and practical application. Perhaps most impressively, they tasked the AI with creating intricate business scenarios, which they collaboratively solved, applying their knowledge of inventory control.

The transformation of the lesson from a traditional revision session to a dynamic, student-led exploration was evident. It wasn't just about recalling facts; it became an active engagement with the subject matter. By granting students the autonomy to interact with AI through the teacher, they not only revisited the topic but also explored its nuances, challenges, and real-world implications.

The scenario in this case study is genuine and based upon real events and data, however its narration has been crafted by AI to uphold a standardised and clear format for readers.

Key Learning

Students, when given autonomy, can harness AI tools in innovative ways to deepen their understanding.

AI can be more than just a supplementary tool; it can be a collaborative partner in the learning process.

Transitioning from basic to advanced prompts can significantly enhance the depth and breadth of revision.


Without proper guidance, students might initially struggle to optimise AI's potential.

Over-reliance on AI can overshadow the importance of human interaction and collaboration in learning.

Ensuring that the AI tool aligns with the educational objectives is crucial to prevent potential deviations from the curriculum.