Recursion without mystery.
A practical guide to base cases, recursive steps, and reading recursive programs without getting lost in the stack.
Articles
8 piecesWriting on computing, education, and evidence-led practice. Subscribe via RSS .
Algorithms
Bellman–Ford, explained clearly.
A practical guide to shortest paths, negative edges, negative cycles, and a Python implementation.
Computing education
Debugging as a teachable habit.
A practical classroom habit for turning program failures into evidence — reproduce, narrow, hypothesise, and test.
Teaching computing beyond syntax.
What pupils need besides working code: structure, explanation, debugging habits, and the confidence to reason about programs.
Education and AI
Fluent answers are not understanding.
Why a correct-looking AI response is weak evidence that a learner understands the subject — and what to check instead.
LLM fluency is not reasoning.
What large language models are good at, where fluent answers mislead us, and how to evaluate claims about intelligence and understanding.
Measure before you optimise.
Why visible metrics are seductive, how wrong measures mislead improvement efforts, and what to establish before changing a system.
Productive struggle in learning.
When difficulty is worth preserving, what learners lose when help arrives too soon, and how to design tasks that keep thinking in the right place.