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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.

Optimising Classroom Assessments: AI's Role in Retrieval & Analysis

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Case Study
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Chris Goodall

Head of Digital Education, Bourne Education Trust

Leveraging AI, combined with Microsoft tools, has revolutionised classroom assessments, enabling educators to save approximately 3-4 hours of manual work. This case study explores the seamless 8-step process that transforms traditional MCQ retrieval methods into differentiated tasks, all curated in just a couple of minutes.

In the modern classroom, technology has become an indispensable asset. The challenge? Efficiently creating, administering, and analysing MCQ retrieval quizzes that would traditionally require hours of manual effort.

The solution is a streamlined 8-step process:

Step 1: Initiate by designing the retrieval quiz using ChatGPT.

Step 2: Transfer the content to Word, ensuring all unnecessary formatting is removed for smoother integration in later steps.

Step 3: Using Microsoft Forms' quick import feature, effortlessly bring in the whole quiz.

Step 4: Set the quiz as an assignment for students through Microsoft Teams.

Step 5: In a real-time classroom setting, students tackle the quiz using their mobile devices, offering educators immediate access to the results.

Step 6: These results are reintroduced into ChatGPT for a thorough analysis, highlighting areas of misconception or difficulty.

Step 7: Based on the insights derived, differentiated tasks are crafted using any educational framework of preference. In this instance, Bloom's taxonomy is the chosen framework, allowing for a gradation in complexity based on individual student needs.

Step 8: Lastly, students are directed to tasks tailored to their unique misconceptions, ensuring focused and effective learning.

The results? A transformed educational environment where technology, particularly AI, optimises the teaching and learning experience.

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

Integrating AI, like ChatGPT, with other educational tools can greatly optimise classroom operations.

A structured, technology-driven approach to assessments allows for real-time insights and dynamic response.

Differentiation in classroom tasks, driven by AI insights, can foster individualised learning experiences.


Sole reliance on AI for task creation might lack the human touch required for nuanced learning.

Technical glitches, if any, can disrupt the learning process.

Misinterpretation of AI-analysed data could lead to ineffective task differentiation.