This practitioner paper outlines three ongoing initiatives, from the Learning, Teaching and Assessment (LTA) team at TU Dublin, responding to the ‘GenAI Teaching and Assessment Challenge’. In contrast to regulatory-focused approaches or prescriptive frameworks, these efforts emphasise agency, collaborative partnership, and developing ethical AI literacy for students and staff.

Learner Agency: The NTUTORR-funded ‘AI Driving Licence’ (AIDL) is an interactive, learner-facing resource that uses scenario-based learning to move students beyond compliance toward engaging them as partners in ethical decision-making and upholding integrity. To date, close to 1,000 learners have completed their ‘AI Driving License’, which invites them to adopt a set of 'rules of the road' designed to guide ethical decision-making in their learning and assessments.

Community practice: A SATLE Pathfinder-funded series of ‘Video Vignettes’ and podcast conversations will foreground educators’ candid reflections on redesigning assessment, and teaching practice, in an age of ubiquitous generative AI. Moving beyond polished exemplars, these peer-led case studies surface the tensions between pedagogical innovation, assessment validity, and academic integrity, offering colleagues practical reference points for their own pedagogical work.

Professional Development: A digital badge will provide TU Dublin staff with an asynchronous microlearning pathway to explore practical decision-making around generative AI and assessment. It employs a custom MS Copilot agent to scaffold, not replace, educator judgement, guide them through a decision-flow process to determine the appropriate level of AI accommodation or integration based on their specified learning outcomes, and support them in translating those decisions into clear guidance and policy statements for their learners.

Together, these ongoing initiatives contribute to an ecosystem of support at TU Dublin linking learner agency, community reflection, and professional judgment, addressing the GenAI Teaching and Assessment Challenge in ways that prioritise the human dimension and empower all involved to make ethical, evidence-informed decisions about AI in teaching and learning.