Student AI Toolkit

Staff Involvement:

• x2 project co-leads (10% workload from January-July)
  • Project was busiest during Feb-March, and again in June
• Responsible for:
  • Writing and gaining ethical approval
  • Organising focus groups
  • Arranging rooms and catering
  • Collatings results from focus groups
• x2 supporting colleagues (approx 90% of workload when involved)
  • Build sitebuilder structure and design of toolkit
  • Uploading and organisation of information

Students:

Initially it was intended that students would be employed to help write large parts, if not all, of the toolkit alongside staff and help inform the design and layout. However, due to time constraints this was not possible. However, the project was able to run focus groups:

• Student focus groups (12 students)
  • x2 focus groups ran across (NEED DATE)
  • Had hoped to do an additional focus group to get initial feedback on the toolkit before further iterations
  • Asked students to consider:
    • What sections they would find helpful
    • Key themes within AI they would want addressing
    • Naming convention
    • General feedback on what a resource like this could address
  • Remuneration: £25 thank you voucher
  • Recruitment: worked with student comms team around marketing and sharing with students
• Launch event feedback:
  • In lieu of original plans around co-creation and further focus groups, the team were able to invite student participants to a launch event, and used QR code to get additional feedback once the toolkit was built

Overview

Initially the project was going to look at NSS results, which highlighted assessment and feedback. However, as a result of the recent uptake in AI it was recognised that what assessment and feedback may look like could be very different, and so it evolved into an AI toolkit which could help support assessment and feedback (amongst other things).

Key Objectives

• Build a central AI toolkit that consolidates scattered information across Warwick
• Understand staff and student perspectives to identify gaps, misunderstandings, and different expectations around AI usage
• Foster AI literacy, confidence, and responsible use for both students and staff
• Strengthen communication between staff and students in an area where understanding and expectations often diverge
• Create a space that could grow and evolve with new content, shared practice, and future contributions

Key Outcomes

Due to timing constraints (ethics delays, exam periods, short funding window), student contributions were smaller than originally planned. However, through student focus groups and work with individuals the team were able to:

• Produce an AI Toolkit
  • Students strongly shape the thematic structure and informed tone, look, and priorities for the toolkit
• Get a greater understanding of staff vs students perspective on AI:
  • Students had a very strong emphasis on AI and the impact (and use) from an employability lens than staff did
  • Students and staff were both concerned around ethics, but students were a lot more expansive on ethical assessment concerns such as the impact around deep fakes, dark areas of the web etc where staff were focused on the more 'expected' elements of ethics such as Academic integrity
  • Both staff and students raised the topic of explicit content in AI
• Highlight the need for ongoing cross‑disciplinary dialogue and more consistent AI messaging across departments

Unintended outcomes & benefits

• A business school student produced an AI Talkies podcast episodeLink opens in a new window, funded through this project
• Student production of an AI poster: Me, Myself and I: Who's really in charge?Link opens in a new window
• In this case project delays could be fortunate, as it has been flagged as a potential opportunity to be absorbed into the new Education HQ proposal
• Reduced student input and staff time encouraged more efficient working, making strategic use of existing resources, revealing that much of what was needed already existed and could be surfaced and signposted rather than recreated

Lessons learnt

• Consider time constraints within funding streams- the funding came from the Education fund, and a such had to be used within the financial year
• Build in time for ethical approval- initial ethical approval didn't account for the webpages being public facing which then delayed the process significantly, subsequently limiting what was feasible funding wise in the remaining time
• Identify ownership and home for project- there was a significant lag due to discussions around where the resource would live within the web infrastructure (and who would therefore be responsible for maintenance) once the initial project was finished which delayed the start date
• Try to plan co‑creation phases around the academic cycle- by the time there was enough information from students to produce the start of a resource it had hit Term 3, reducing the ability for student contribution/further input as well as adding constraints to staff time
• Student contributions may need shifting depending on capacity- student planned roles and involvement could not progress due to insufficient work being available for students to complete, further exacerbated by compressed timelines and staff capacity
  • However, this did not mean the end of the project, but just meant flexibility of approach, and looking at what still could be included from a student voice perspective
• Decide up front how to navigate conflict between staff and student needs- whilst all routes cannot always be considered, conversations early on in the project to address what to do when consensus-building may not be possible
• Identify technical partners as early as possible- early collaboration with Digital Education, WIHEA Learning circle, Computer Science and technical colleagues would streamline the build process and help shape realistic timelines for toolkit production