Workshop information
In three sequential in-person sessions, we step through a process to design and develop a GenAI-enabled learning activity or assessment task to implement in your subject.
As we progress through pedagogical decisions, ethical considerations and practical planning, you will collaborate with peers and learning designers. Between sessions, you will have the opportunity to revise, reflect and discuss your project with the Teaching and Learning Innovation team and peer network. Following the sessions, we will support you to evaluate and iterate, and to repeat the process to develop future activities.
This workshop series is for
Subject coordinators and educators involved in learning and assessment design, delivery and support. We encourage teaching teams to attend together to work on shared projects.
Intended learning outcomes
On completion of all three sprints, you will be able to:
- Identify where AI meaningfully supports learning and articulate its role
- Design AI supported learning prompts and ethical expectations
- Design task instructions that assure reliable evidence of learning.
Content not covered
The series does not provide a general introduction to GenAI and its use in teaching and learning. See ‘Recommended background knowledge’ in the next section to learn more about these topics.
Recommended background knowledge
Some familiarity with GenAI in teaching, such as completion of Module 1: Fundamentals of GenAI for educators in our GenAI hub. The GenAI hub has further examples and information on incorporating GenAI into teaching.
Additional information
After registering, you will receive 3 x Outlook calendar invitations for the in-person workshops. We ask participants to commit to all three sprints in order to progress through the design process.
This overview of the series shows how each sprint builds towards the development of an activity or assessment task ready for teaching.
| Sprint | Focus | Practical outcome | Outputs | Commitment |
|---|---|---|---|---|
| Sprint 1: Pedagogically aligned AI integration | Purposeful use: Where AI belongs in learning | By the end, participants will be able to Identify where AI meaningfully supports learning and articulate its role. |
1. Rationale for AI use (max 5 lines). 2. Clear description of AI’s role in the task. | AI use is intentional and pedagogically aligned. Supports, not replaces student thinking. |
| Sprint 2: Prompts that serve pedagogy | Responsible learning design: How AI supports learning | By the end, participants will be able to design AI supported learning prompts + ethical expectations. |
1. AI-integrated learning prompt. 2. Draft student-facing brief (AI use guidance, evidence of process, acknowledgement expectations). | AI use is transparent and ethically grounded. Design extends student thinking. |
| Sprint 3: Assured learning with AI | Trusted evidence: Making student learning visible and trusted | By the end, participants will be able to design the task instructions that assure trustworthy evidence of learning. |
1. Final student-facing brief (AI use guidance, evidence of process, acknowledgement expectations, non-AI alternatives). 2. Assessment rubric (evaluating thinking and judgement). 3. Drafting an evaluation plan. | Evidence of learning is credible and transparent. Standards are clear and equitable. |