Teaching in a World of AI-Generated Solutions: Lessons from Computing Education

Generative AI is changing what students can do with technology, raising important questions about what we teach, how students learn, and how we assess their understanding. For computing education, where AI now generates solutions to traditional introductory programming tasks, these questions have become particularly urgent. But the challenges are not unique to computing. Across disciplines, educators are grappling with how to help students develop meaningful skills when AI can readily produce answers.  This talk explores how we might respond to these challenges. Rather than starting with what AI can do, we should ask which existing skills remain important, what new capabilities students need to develop, and what learning experiences can best support them.  Drawing on recent research and practical examples from introductory programming courses, I will share some of the lessons we have learned, and invite you to consider how these might apply in your own classrooms.

Clare Nelson is currently Deputy Principal at Sir Edmund Hillary Collegiate Senior School in Ōtara. Across her work at Edgewater College, Tangaroa College and now SEHC, she has been actively involved in leading and developing Mathematics and Statistics curriculum, teaching and assessment. Clare has taught Mathematics, Statistics and Business across a range of year levels, but has a particular passion for teaching senior Statistics. Alongside her school roles, she contributes to Mathematics and Statistics education through her work with NZAMT, AMA (Auckland Maths Association), NZQA, Ako Mātātupu and other education organisations. She particularly enjoys opportunities to work alongside other teachers, share ideas and learn from what others are doing in their classrooms.

But What Does It Actually Mean? Making Statistics tangible

What do we do when students can follow the process, but don’t really understand the Statistics underneath? This keynote explores how we can strip statistical ideas back to their core purpose, then turn abstract concepts into something students can see, touch, experience and talk about. We’ll unpack the thinking behind creating tangible learning experiences – starting with what students are struggling to make sense of and working backwards to what we actually need them to understand. Expect practical ideas and an approach you could use to think about how statistical concepts are explored in your own classroom.