Investigable questions, predictions and hypotheses

Develop feasible investigable questions, reasoned predictions and hypotheses that use scientific models, identify patterns and test relationships.

Success criteria

• I can tell whether a question is measurable, feasible and evidence-based.
• I can identify independent and dependent variables in a relationship question.
• I can distinguish a prediction from a hypothesis.
• I can use scientific knowledge or a model to justify an expected result.
• I can refine vague questions into testable ones.

1. Start with curiosity, then ask: Can evidence answer this?
2. Make the question specific and feasible: what can we change/compare and what can we measure?
3. For relationships, identify IV (changed) and DV (measured). Relevant controls belong in later planning.
4. Use prior scientific knowledge, a model or an observed pattern to make a reasoned prediction.
5. Form a hypothesis: a testable relationship or explanation. Useful scaffold: “If [IV changes], then [DV will…], because [scientific reason].”

From vague idea to testable inquiry

Vague: “Do plants like music?”

Investigable: “How does 2 hours per day of recorded music affect average seedling height over 21 days compared with no music?”

Prediction: “Seedlings exposed to music may show a different average height than controls.”

Hypothesis: if a mechanism is proposed, state it clearly and make sure evidence could challenge it.

Teacher prompt: “Which words became measurable? What is IV? What is DV? What would count as evidence against the hypothesis?”

• Particle model: suggests a question about temperature and gas volume.
• Food-web model: suggests a question about prey abundance and predator feeding/population patterns.
• Earth–Moon–Sun model: suggests a question about tide height across the lunar cycle.
• Place-based ecological observations: can suggest testable seasonal pattern questions when used with appropriate source, context and attribution.

• “A hypothesis is just a guess.” False — it is testable and reasoned.
• “A prediction is written after the result.” False — it should be recorded before evidence is collected.
• “Any question is investigable.” False — opinions, unsafe questions or questions beyond available resources may need refinement.
• “Models give the answer.” False — models help generate testable questions and predictions; real evidence is still required.

1. Turn “Is warm water better?” into an investigable question.
2. In “How does ramp height affect trolley travel time?”, identify IV and DV.
3. Write a reasoned prediction for a larger parachute.
4. Explain one difference between a prediction and a hypothesis.

Give students three everyday curiosities. For each, they must decide whether it is investigable as written, refine it if needed, identify variables or measurable patterns, and write a reasoned prediction or hypothesis. Require one example based on a scientific model and one based on observational data.