Year 1 Science · AC9S1I01
A good science question comes from something observed. A prediction uses experience or a pattern to say what might happen
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A good science question comes from something observed. A prediction uses experience or a pattern to say what might happen.
Learning routine: Observe pattern → Ask question → Use experience → Predict → Check later
I notice the large ball rolled farther. I wonder if size changes distance. I predict the large ball may roll farther again.
Observation: The large ball rolled farther. Question: Will the large ball roll farther again? Prediction: I think yes because it happened in the first try.
The prediction can be wrong later, but it should make sense before the test.
Explain your thinking: Say what each part of the model represents, then explain why the answer or conclusion follows.
Worked example Observation: The large ball rolled farther. Question: Will the large ball roll farther again? Prediction: I think yes because it happened in the first try.
Notice and wonder Observe two objects moving and write one I notice and one I wonder sentence. Model: I notice... / I wonder...
Pattern question Look at a repeated pattern and ask a question about what may happen next. Model: wet → slippery?
Reasoned prediction Make a prediction and include because. Model: I predict ___ because ___.
These curriculum examples extend the central model into varied contexts. They are learning contexts, not extra definitions to memorise.
posing questions about simple relationships between push and pull forces, such as: ‘Does a toy car go further if it is pushed harder?’
Try and explain: Turn ‘This toy rolls’ into a question that compares two push strengths.
For example, ‘Does this toy travel farther after a stronger push than after a gentle push on the same surface?’ The question identifies what to compare.
posing questions about how animals meet their needs in particular places, such as: ‘Where does it shelter? Where does it get water from?’
Try and explain: You see a bird under a bush on a wet day. Ask a question about how it meets a need.
For example, ‘Does the bird use this bush for shelter when it rains?’ Further observations could help investigate the idea.
making predictions about plant needs, such as: ‘I think a plant will die if it doesn’t get enough water’
Try and explain: A plant's soil has been dry and its leaves are drooping. Make a prediction about suitable watering, without withholding the care it needs.
For example, ‘I predict the leaves may become firmer after suitable watering because plants need water.’ Observe what happens; a prediction is not a guaranteed result.
making predictions about types of animals and plants they might observe in a particular place, such as a garden or pond
Try and explain: Where would you predict finding a frog more often: near a pond or on a dry paved path? Give a reason.
Near a pond is a reasonable prediction because water and nearby shelter may meet its needs. An actual observation is still needed.
making predictions about patterns of observable phenomena such as seasonal changes of plants or changes in temperatures across the seasons
Try and explain: Last year's records show more flowers on a particular tree in spring. Make a prediction for this spring and name the evidence.
Predict more flowers on that tree in spring, using the previous seasonal record as evidence. Check the new observations rather than assuming an exact repeat.
Ask a question about an observed pattern and give a reason for a prediction.
You notice the same toy car rolls differently on a rug and on a smooth board. What could you ask?
Watch for this mistake: A prediction is made before the test and includes a reason. An observation reports what actually happens.
Which can be investigated by observation: ‘Which surface lets this car roll farther?’ or ‘Which car is the nicest?’
Look for a result that can be compared.
The surface question. ‘Nicest’ is a preference unless a clear criterion is agreed.
Complete a prediction: I think the car will roll farther on __ because __.
Use something you have observed or experienced.
Accept a stated surface with a relevant experience-based reason; the prediction need not later be correct.
Key idea: A good science question comes from something observed. A prediction uses experience or a pattern to say what might happen.
Return to the concept model if an answer is uncertain. Use the model to explain, not just to guess.
Use the Practice Sheet for written or hands-on work, Practice for supported feedback, and Test when the student is ready to demonstrate independent mastery.
A good science question comes from something observed. A prediction uses experience or a pattern to say what might happen.
Learning routine: Observe pattern → Ask question → Use experience → Predict → Check later
AC9S1I01: pose questions to explore observed simple patterns and relationships and make predictions based on experiences
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