Artificial Intelligence Text and Image Generation for Student Co-creativity within Higher Education

Abstract

<p>Recent advancements in Artificial Intelligence (AI) deep generative modelling for writing and image synthesis, with digital tools such as OpenAI’s GPT-3 and DALL-E-2, Midjourney, and Stable Diffusion have extraordinary implications within the cultural arts and literary domains. Reviewing the relevant literature within higher education reveals emerging concerns about the technology’s impact on student plagiarism and academic honesty while threatening pre-existing definitions and conceptions of originality and creativity. This paper aims to make a case for embracing AI text and image generation technologies in transforming the possibilities for pedagogy, curriculum, and assessments and facilitating higher-level order learning in developing future readiness competencies such as critical thinking, communication skills, mental flexibility, and digital literacy and collaboration. We illustrate the pedagogical possibilities by presenting a case study of a Creative Writing programme using text and image synthesis tools, participated by undergraduate and postgraduate students from the University of Hong Kong and the Chinese University of Hong Kong. Drawing on Jacques Ranciere’s politics of intellectual emancipation, we analyse the reflections, interviews, and creative graphic fiction generated by the students, together with teacher observations. We highlight how the co-creation process with AI deep generative modelling applications is an immersive learning process and productive in the development of future-ready graduates. The findings have implications for guiding higher education in enhancing teaching and learning by reconfiguring outdated practices and leveraging advances in big data and machine learning for student-centred and future-orientated learning.<br></p>