The motivation of the research question is threefold:
- The need to tailor and adapt guidelines to specific creative disciplines
- The need to communicate clear expectations to students for the use of AI in advance of assessments.
- The need for technical programming skills creates barriers for learners to be AI-literate.
Research question
How can we create practical guidelines on the use of AI coding tools for BSc Data Science and AI students at the Creative Computing Institute, to reduce the barrier to AI literacy in a technical programming context?
Actions Plan
- A GenAI Checklist tailored from the UAL Student Guide to Generative AI. It aims to provide guidelines on the responsible use of AI coding assistants, including more detailed instructions on:
- How to use AI coding tools in an academic context,
- How to keep track of code generation/editing done by AI,
- How to add the “Generative AI Disclosure” in coding.
- A “Rubber Duck” Chat Mode will be implemented in GitHub Copilot (the AI coding tool integrated into the software used by CCI students) and provided to students in the unit. Chat Mode is a set of “pre-task instructions” for Copilot, to tailor its behaviours by setting the overall goal. I hope this can better support learners, and potentially help students identify what knowledge/skills are needed.
Project Plan
The BSc Mathematics and Statistics for Data Science (Math&Stats) unit runs from Sep 2025 to Jan 2026.
- GenAI Checklist: To be finalised by 10-Oct
- The “Rubber Duck” Chat Mode: To be finalised by 10-Oct
- Data collection plan: Mid-Oct
- Prepare the Miro board, workshop activities: Mid-Oct
- GenAI workshop with students: Week 5 (31-Oct) Week 7 (14-Nov)
- Students’ feedback & reflection, debrief: Week 11 (12-Dec)
- Data analysis: Week 12 (18-Dec)
- Reflection, write-up: 5-Jan