AI, Curriculum and School Mathematics
AI is becoming increasingly part of the contemporary landscape of curriculum, pedagogy and assessment, with mathematics education very much in the frame.
Recent AI models (2025-26) have markedly greater mathematical capacity and explanatory capability than earlier systems as they can combine explanation, multi-step reasoning, symbolic and numeric tool use, code execution, and iterative checking within a single workflow.
- This raises some important questions:
- What should students know and be able to do themselves?
- What roles could AI play in mathematics classrooms?
- How could curriculum, pedagogy, and assessment respond?
- How might teachers be supported to work effectively in this context?
- What mathematical knowledge, skills, processes and proficiencies are required in an AI-enabled world?
This four-part series explores some key aspects of these questions.
PART 1: The Velocity Gap
How current can a curriculum remain when the world it serves is changing faster than the review processes designed to maintain it?
Take me there.
PART 2: Mathematical agency in an age of AI
If AI is now part of the mathematical landscape, what does it mean to learn and do mathematics at school?
Take me there.
PART 3: The evidence question – AI and assessment in mathematics
What should count as evidence of mathematical learning when AI can now generate substantial parts of mathematical work?
Take me there.
PART 4: The teaching challenge – AI and classroom practice.
How can schools use AI in ways that strengthen mathematical learning without outsourcing the thinking?
Take me there.
Alternatively, download the series in PDF format:
