Teaching & Learning

Prof. Peter Nelson is an Associate Professor of fine art, media studies, computer games, and creative technology, with a career as a practising artist spanning over 20 years. His first book Computer Games as Landscape Art (Palgrave Macmillan 2023) considers how first-person shooter computer games can be understood through the art historical lens of landscape, and his recent papers examine questions such as realism in the age of computer-simulated images, and the role of AI in digital creative processes. Nelson’s technical areas of expertise are drawing, 3D modelling, animation, digital fabrication, and interactivity, and he exhibits art and creative technology works ranging from robotically assisted ink paintings, animations, and performance collaborations. At the Academy of Visual Arts at Hong Kong Baptist University, Nelson is the Associate Director of Teaching and Learning and co-director of the MetaCreativity Lab.

This team is recognised for their collaborative work on the GE course, “GTCU/GTSU/GTSC2805 Critical AI Literacies: Embracing AI for Social Good”.

The Panel is impressed by the alignment between the course’s pedagogies and assessments. The course is guided by a clear pedagogical framework—understand, apply, and create—which provides a robust structure to equip students with the integrated literacies essential to the AI era and drives them toward an ethical use of AI. This thoughtful design ensures that every teaching and learning activity and assessment directly supports the core goal: fostering not just technical skills, but critical judgement and social responsibility.

A key factor in this recommendation is the team’s innovative, transdisciplinary course structure. The members’ distinct areas of expertise in computer science, visual arts, communication, and business provide a comprehensive and synergistic foundation for the course. This blend of perspectives prepares students for real-world problem-solving by challenging them to analyse AI from multiple critical angles. Demonstrating remarkable foresight, the team has also developed a manual to ensure the course’s quality and to facilitate its expansion with new teaching members in the future.

The Panel also notes the team’s deep commitment to active learning, particularly their “create → critique → refine” methodology. This methodology is brought to life through a hands-on format centered on discussion and critique, made possible by a flipped classroom model. Furthermore, to address the challenge of AI-generated assignments, the team has incorporated live debates that require students to think on their feet, ensuring genuine understanding and engagement.

In recognition of their exceptional course design, innovative pedagogy, and impactful transdisciplinary collaboration, the Panel recommends the team for the GE Teaching Award (Team Teaching) to honour their excellent performance.