These prompts work with any Science Learning Hub topic. Use them after students have had a real encounter with the science — a field trip, a stream sample, a night-sky observation, a museum visit — and have read the relevant Hub article or watched the relevant Hub video.
Years 1–6
What we found vs what the Hub saysShow AI a photograph from your field experience. Ask: "What is this?" Then read what the Science Learning Hub says about the same topic. Did AI and the Hub agree? What did being there show you that neither could?
Our question to the scientistsAfter reading a Hub article, ask students: what question do you still have that the article didn't answer? Type it into AI. Does AI's answer satisfy you? What would you need to do to check it?
The local versionThe Hub explains how something works generally. Ask AI: "How does [the science concept from the Hub] work specifically in [your local river / your region / your town]?" Compare AI's local answer with what you observed in the field.
What scientists doAfter reading about a NZ scientist on the Hub, ask AI: "What does a [type of scientist] do every day? What skills do they need?" After your field experience, which of those skills did you use yourself?
Years 7–10
Field data meets Hub scienceStudents record their field observations in specific terms — species found, measurements taken, conditions noted. Ask AI to help interpret the data against the science concepts in the relevant Hub topic. Where does the field data confirm the Hub's explanation? Where does it complicate it?
The Hub article's limitsAfter reading a Hub article, ask AI: "What does this article leave out or simplify? What would a specialist in this field add?" Use AI to identify the boundaries of what the Hub covered — then decide which boundary is worth pushing further.
NZ context vs global scienceThe Hub often covers NZ-specific science. Ask AI: "How does [the phenomenon] in New Zealand compare to how it works in other countries or ecosystems?" Use your field experience as the NZ anchor for this comparison.
Uncertainty and the nature of scienceAfter reading a Hub article about an ongoing research question, ask AI: "What are scientists still uncertain about in this area? What methods are they using to find out?" Compare AI's answer with what the Hub says about the research process.
Years 11–13
Primary evidence vs Hub synthesisThe Hub synthesises science for teachers and students. Ask AI to locate the primary research papers or data sources behind a specific claim in a Hub article. Evaluate the original evidence against the Hub's summary. What did the synthesis gain and what did it lose?
The field experience as a research instrumentStudents design a formal inquiry question from their field observations. Ask AI to help identify the relevant science concepts, the appropriate methodology, and the main variables. Cross-check AI's methodology suggestions against the Hub's explanation of how scientists in this field actually work.
Contested science and the Hub's framingFor any Hub topic that involves scientific debate or uncertainty — climate change, biodiversity, conservation trade-offs — ask AI: "What are the main points of genuine scientific disagreement in this area?" Evaluate how the Hub presents that uncertainty and whether AI's account of the debate matches, extends, or complicates the Hub's framing.
Mātauranga Māori and Western scienceMany Hub topics involve phenomena that are also understood through mātauranga Māori. After a field experience in which both knowledge systems were present, ask AI: "What does Western science say about [phenomenon]? How has this been understood in mātauranga Māori?" Evaluate AI's account of mātauranga Māori carefully — then consider what sources would be more authoritative than AI for that dimension.
