We propose to initiate a workshop series entitled "Co-designing Encounters with AI in Education for Sustainable Development". This series will co-design, with students, colleagues and faculty, an innovative educational experience that combines generative AI and education for sustainable development (ESD). The project will be divided into three phases: 1) co-design with multidisciplinary faculty to develop effective draft teaching and learning resources and additional co-design activities for the students; 2) two co-design workshops with undergraduate students to test and further refine the teaching and learning resources; and 3) evaluation and dissemination of our results to share our findings and support faculty to make use of the project’s outputs.  

 Given the profound effects that AI and sustainability are likely to have for our students and future generations, calls have been independently made for both to be embedded into student learning. However, on the one hand, according to the King’s ESD mapping1, ESD exists at the margins within our programmes, such that most ESD examples are extra-curricular. On the other hand, generative AI presents new opportunities and challenges for sustainable development and education, but with limited empirical evidence on its impact in these areas to date, students must gain (but often lack) the skills to critically assess AI's value, potential, risks, and consequences. This project seeks, through a co-design approach, to allow students to engage with both these issues. 

In phase 1, we will work with faculty from different disciplines to co-design draft teaching and learning resources that focus on one or two specific ESD themes, such as climate change, preparing co-design activities using the new Responsible AI Education Framework.2 This framework emphasises social justice, equity, dialogue, and inquiry-based learning. It encourages critical discussions, problem-framing skills, and awareness of diverse ethical standpoints related to AI's societal impact. Whilst it is well-suited for ESD and generative AI exploration, it has not been empirically tested in educational settings, which we will do through action research with faculty. 

 In phase 2, we involve students in further co-design of the workshops. The project team will assess the pilot workshops using mixed methods, including student participation in focus groups to explore their learning experiences and to give feedback on how the workshops could be integrated within their respective programmes. Additionally, the team will analyse the content and quality of student work during the workshops, leading to refinements in workshop design and delivery.  

 In phase 3, workshop outcomes will be analysed to generate key findings and finalise learning materials. The project team will review action research findings to create a set of core curriculum integration recommendations, and formulate a strategy to encourage faculty members to use our project outputs. We will also compile a comprehensive report, which will be summarised in a blog post as well as being disseminated through social media channels for broader outreach and engagement.