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AI in higher education assessment

Practical support for universities rethinking assessment and feedback in the context of generative AI, staff workload, student expectations, and complex digital ecosystems.

What is changing

AI is changing assessment in multiple ways at once. It affects assessment design, academic integrity questions, feedback practice, staff confidence, marking workflows, and institutional guidance. It also raises implementation questions that sit far beyond policy wording alone.


That is why institutions need more than a high-level AI strategy. They need practical work that helps connect policy, academic practice, assessment design, process, and staff adoption.

How I help

My work in this area focuses on practical change. That can include reviewing assessment and feedback practice, identifying where workflows or guidance are breaking down, supporting platform and process decisions, and helping institutions design workable next steps for implementation.


The goal is to help institutions respond with clarity rather than panic: protecting standards, supporting staff, and making assessment practice more workable in the AI era.

Discuss your project

If your institution is rethinking assessment and feedback in the context of AI, I’d be glad to hear more.

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