In this assessment, students are immersed in theoretical concepts and practical applications of designing with generative AI tools. Through practice, students familiarise themselves with generative AI tools, enhancing their comprehension of the terminology, potential advantages, challenges, and broader impact on design and beyond.

Many theoretical units benefit from students programming the concepts taught in class as a learning aid. Translating these abstract theoretical concepts to practical implementations via a coding exercise reinforces understanding, often requiring extended abstract reasoning. However, code generation tools can make these coding task trivial, and removes this opportunity. The examples below make suggestions around ways to work with genAI tools, but still retain the benefits of learning through coding.

Utilising ChatGPT to create contextualised lesson plans serves as a valuable foundation for novice teachers, offering a basis for comparison and critique as they engage in the process of learning about effective lesson planning.

Critical analysis of AI-generated responses and the application of knowledge. Students are tasked with designing a drug that can be used to treat ageing. Students are requested to use generative AI to develop ideas that can be empirically tested. Learning develops as students ‘curate’ AI responses for factual accuracy, efficacy, and practicality.