Investigable Questions, Predictions and Hypotheses — AC9S8I01

• Distinguish investigable questions from questions based mainly on values.
• Identify independent, dependent, controlled and confounding variables.
• Use patterns and models to make reasoned predictions.
• Write a directional hypothesis with a scientific reason.

Recall that observations describe what is detected, inferences interpret observations, and scientific models represent selected features or relationships.

Use the chain pattern or model → investigable question → variables → reasoned prediction or hypothesis → evidence. An investigable question names measurable variables and conditions. Questions such as “Should we…?” or “Is this good?” involve values and cannot be answered by experimental measurements alone.

A correlation means variables change together; causation means changing one produces a change in the other. Controlled investigations help test causation, while a confounding variable provides another possible explanation.

A prediction states an expected outcome. A hypothesis proposes a testable, directional relationship and a reason: If [independent variable changes], then [dependent variable changes], because [scientific reason].

A model may be a diagram, physical object, mathematical relationship or simulation. It can generate questions and predictions even though it simplifies reality; its predictions must still be compared with evidence.

1. Underline the two measurable variables in a question.
2. Name which variable is changed and which is measured.
3. Identify one variable that should be controlled.
4. Complete an if–then–because hypothesis using a model or known pattern.

1. Improve the question “Is fertiliser good for plants?” so it is measurable.
2. Explain why ice-cream sales and sunburn do not establish causation.
3. Write a reasoned prediction for concentration and reaction rate.
4. Identify the confounding variable if both light colour and water amount change.
5. Develop an investigable question from a plate-boundary model.
6. Explain why a hypothesis is tested rather than proved before an investigation.

Two explanations predict different outcomes when water temperature changes. Design one measurable question and hypothesis that could distinguish the explanations, then identify a confounding variable to control.

1. What makes a question investigable? Measurable evidence could answer it under stated conditions.
2. Prediction or hypothesis? A prediction states an expected result; a hypothesis proposes a testable relationship with reasoning.
3. Why control variables? To reduce alternative explanations for a change in the dependent variable.
4. Can a correlation be useful? Yes. It can reveal a pattern worth investigating, but it does not by itself prove causation.

1. Turn “Do plants like salt?” into an investigable question.
   Name salt concentration, a measurable plant response and a time or method.
2. Evaluate “More umbrellas cause more rain.”
   Identify correlation, reverse reasoning and weather as the common factor.
3. Write a hypothesis for light exposure and plant growth.
   Use if–then–because, identify both variables and qualify suitable limits.

• I write measurable questions.
• I identify all variable roles.
• I separate correlation from causation.
• I justify predictions and hypotheses with science.

Exit ticket: Why can a strong correlation still fail to show causation?

Australian Curriculum v9.0 — AC9S8I01: develop investigable questions, reasoned predictions and hypotheses to explore scientific models, identify patterns and test relationships.

Victorian Curriculum F–10 Version 2.0 — Levels 7–8, VC2S8I01: Exact.

NSW Science 7–10 Syllabus (2023) — Stage 4, SC4-WS-02: Exact — the NSW Working Scientifically outcome directly align with the core inquiry process.

Broad international closest-topic links include NGSS Practice 1, KS3 Working Scientifically, Ontario Grade 8 STEM investigation skills, New Zealand investigating in science and middle-school NCERT inquiry. These are supportive comparisons, not identical curriculum structures.

• AC9S8I02 — Planning reproducible investigations
• AC9S8I05 — Analysing patterns and anomalies

• Australian Curriculum v9.0
• Victorian Curriculum F–10 Version 2.0 Science
• NSW Science 7–10 Syllabus (2023)

Curriculum equivalents for Develop investigable questions, reasoned predictions and hypotheses to explore scientific...

Mapped skill: develop investigable questions, reasoned predictions and hypotheses to explore scientific models, identify patterns and test relationships

These references identify matching or closely related learning. Curriculum sequence, terminology and depth vary, so teachers should use the mapped skill and lesson difficulty to confirm suitability.

Australian Curriculum v9.0 is the canonical source for this SkillrHub lesson. Victoria and NSW entries name the closest published state codes or outcomes; international entries are planning references rather than claims of identical curricula.