Lean and ChatGPT Project Assistant

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The Mathematics and Statistics Department at the University has 5 internship opportunities for students who are working towards Mathematics or another related degree. You will support a project exploring how a combination of the proof assistant Lean and chatbots such as ChatGPT can support students with learning mathematical proof.  As a member of the project team, you will help to design interactive activities with Lean and ChatGPT that can be used in workshops with students for the academic year 2024/5.  You will also help devise evaluation methods to determine the effectiveness of these activities, tools, and strategies in supporting students with formal proof.

This role is part of the Student Campus Partnership (SCP) scheme and offers 1 day of work per week for about 6 weeks. Remote working is possible, and you will have access to offices in the Harrison Building on Streatham Campus.

Key Details

Supervisors: Gihan Marasingha, Barrie Cooper & Taro Fujita

Estimated pay: £13.45 per hour (£12.00 basic hourly rate + £1.45 holiday)

Working Hours: 8 hours a week

Application Deadline: 08/05/24

Interview Date: 15/05/24

Start Date: Flexible in June 2024

End Date: 31/07/2024

Purpose of the Role

In this role, you will work to collaboratively create workshops and evaluation strategies to support students learning mathematical proof.  The focus of these workshops will be on using the proof assistant Lean and ChatGPT to support students in conceptualising and formalising proofs.  You will work with other interns and the project leads (Gihan Marasingha, Barrie Cooper & Taro Fujita) to develop and test appropriate resources with the aim that these can be used in the academic year 2024/5.

Duties and Responsibilities 

• Co-designing activities and learning resources to support the learning of mathematical proof via the tools Lean and ChatGPT.
• Using Lean and ChatGPT to identify suitable ways in which they can be integrated into student learning of proof.
• Co-designing evaluation strategies with the aim of assessing the impact of Lean and ChatGPT on students’ understanding of proof.
• Co-drafting project outputs, such as blog posts and a report on project progress and on your own experiences.

Training and Development - What Skills and Experience will this Opportunity Provide?

• You will need to be familiar with Lean, but support will be given to develop further expertise in this. 
• Regular project meetings will be held (in-person and remotely, as appropriate) to co-develop the workshops, resources and learn from each other.  As part of this, we will be exploring and learning collaboratively how ChatGPT can assist with Lean and with learning to conceptualise and formalise proof.
• Additional training requirements can be identified and aligned with your interests and needs.

You will be asked to complete the university’s mandatory online training in: 

• Prevent Duty - Inclusive, Cohesive and Safe Universities 
• Equality and Diversity Introduction 
• Health and Safety Introduction 
• Information Governance

Support Available

• Approximately weekly meetings with the project team, and asynchronous online support via Teams.
• You will be offered 1:1 support from the Internships Team.

The Benefits

• This work can be undertaken flexibly to suit your studies and other responsibilities.  
• This is an excellent opportunity to get paid experience contributing to a research project, with the potential for a significant impact on the student and staff experience.

About You 

Degree and Attainment

• Studying towards an undergraduate or postgraduate degree in Mathematics or closely related subject.

Skills

• Good written and verbal communication skills
• Interest in education and technologies to support effective learning
• Well organised and able to work effectively to strict deadlines

Personal Qualities and Attributes

• Pro-active and confident to work independently
• Good at working with and enthusing other people
• Reliable

Knowledge

• Familiarity with the Lean proof assistant
• Good subject knowledge as a foundation for creating engaging learning resources and workshops

Prior Experience 

• Working effectively in a team
• Using the proof assistant Lean
• Experience with designing and evaluating educational resources would be useful, but is not essential
  
  

About the University Department

This project is funded by the Education Incubator and led by Gihan Marasingha, Barrie Cooper and Taro Fujita from the departments of Mathematics & Statistics, and Education.  The Education Incubator supports staff from across the University by creating spaces and funding projects in which they can explore and develop pedagogic innovations and ideas.

Further information can be found on the Handshake job listing page.