The following categories are designed to increase transparency and clarity for both staff and students. Use the categories as a guide: we are aiming for greater clarity at the course level, so consider how the categories work for you in your respective subject discipline, taking into account the needs of your students as well as the graduate attributes with which you wish to equip your students. We recognise, and embrace, that the boundary between each category and how this is interpreted will likely vary due to differences in subject discipline and the learning outcomes being assessed – there are no “right” or “wrong” answers.
It is the broad expectation that Type B will be the “new norm” for the majority of coursework for the foreseeable future, with increasing use of C in time, alongside a moderate use of Type A (for coursework).
This is to ensure that we align to our Senate-approved high-level GenAI principles in Education, existing CT principles of Assessment for Learning and Supporting the Needs of All Learners, as well as our Assessment for Learning Design Principles. Additionally, it is also pragmatic and future-focused. It is a reality that GenAI tools are increasingly ubiquitous and invisible in the tools that students – and staff – use in their work (e.g. Office365 Products and Internet Browsers). Thus, the line between using GenAI tools and not is blurred, and it will shortly be impossible to use tools such as MS Word without (intentionally or not) using GenAI. Furthermore, the evidence so far indicates that there is no simple way of detecting GenAI in student work – so-called AI Detector tools are fundamentally flawed in concept, do not work effectively, and are prone to bias against certain groups or individual characteristics. To that end, an approach which predominantly bans the use of such tools is not conducive to preparing students for a future in which GenAI will permeate all aspects of work, research and learning.