About the Project

The mathematical sciences and operational research (MSOR) community in HE is poorly prepared to adapt to the rapid rise of AI. Whilst inperson exams remain an essential assessment mode for our subjects, take-home assignments are also an integral assessment tool. However, our current assignments are not robust against AI, and staff have no time to capture ways in which AI might be used to enhance learning.

Recent AI studies in HE tend to cover a broad range of subjects without the specific needs of mathematical sciences being properly considered. According to the QAA benchmark for MSOR, students “can sometimes be expected to provide an answer which is very close to a model answer”, whilst AI can often provide such model answers.

Project Aims

This project aims to address these issues and make suggestions, specific to MSOR subjects, on how maths assessments could be adapted to work with AI whilst still achieving excellent learning outcomes. The project team will investigate assignments in their respective departments, tackling the following questions:

1. How well can AI perform in our current assignments?
2. To what extent do our students currently use AI to help with assignments?
3. Can future assessments incorporate AI as a copilot, whilst still achieving module outcomes?

Based on our findings and further surveys of how maths assessments are changing in other universities, we will suggest how AI might be integrated in future assessments. We aim to develop concrete examples of AI-assisted take-home maths assignments.

Project Team

Leads: Siri Chongchitnan (Mathematics)

Leads: Martyn Parker (Statistics)