Generative AI: what does it mean for teaching, learning and assessment? - Transcript

Michael Grove:

Generative Artificial Intelligence describes algorithms that can be used to create new content, including text, computer code, images, audio. Such tools are now widely accessible and will impact our teaching, learning, assessment, and support practices in increasing ways as they rapidly develop in their sophistication.

Although Generative AI had its origins back in the 1950s and 60s, its modern rise to prominence in creating readable text and photorealistic images is still in its early stages. It is therefore important that we, as educators, understand how these systems work. For example, whilst ChatGPT has been trained using an extensive database, it is not currently connected to the internet, so it cannot train itself based upon new information or in real-time which limits its ability to accurately incorporate more recent events. Further, it relies upon a level of human training by incorporating human feedback into its training loop so it is not in itself creating or evaluating new knowledge. These are the higher-order skills in Bloom’s Taxonomy and ones upon which we, as universities, should be focusing.

The response of higher education institutions to the rise in Generative AI needs to take place as part of a much wider discussion about assessment and feedback and its role in enhancing student learning, and in helping students and institutions appraise educational gain. These technologies offer the potential to support academic staff in the creation and assessment of course material, and new opportunities to engage students in problem solving, critical thinking, analysis and communication. But staff will require support to trial, evaluate and research new pedagogic practices, and students will need guidance to help them understand the role of Generative AI in the development of their graduate attributes. There is also a need to ensure institutions have student-facing policies with clear information on expectations for disclosing where Generative AI has been used within submitted work.

Generative AI is here to stay, but teaching and learning is an area where higher education institutions can shape the international agenda for its use.