Digital Worlds and Data | Ngā Ao Matihiko

Build and critique digital systems and data

Every chart and every screen is a design choice — code and interfaces shape what counts as evidence.

Wero — the big question

How do we design, build, and critically evaluate digital systems and the data they produce?

What you will investigate

Curriculum strands

Technology strands

1 termSupport level: Teacher support when you need it

An algorithm is a recipe a computer follows — if the recipe is wrong, every graph built from it is wrong too.

Science depends on trustworthy code — students who can design, test, and debug algorithms strengthen every sensor inquiry on the platform.

You will design, code, test, and visualise science data — documenting each step so others can trust your process.

A brilliant dataset fails if nobody can read the screen — design choices include or exclude people.

Science platforms only serve communities when interfaces are readable, accessible, and honest about data limits.

You will audit, prototype, test, and revise a simple interface — arguing for accessibility with evidence.

Maker pathways connect your evidence to a real prototype or build.

Arduino data logger scaffoldArduino
Prototype timed captures tied to reliability evidence
If jitter or sampling gaps blurred your inference, scripted intervals target that gap.
Data story packageData product
Pair charts with explicit limitations sourced from inquiry logs
Lets peers see which rows of evidence carry the headline takeaway.