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Ignition Learning — Activity Sheet

Asking scientific questions & forming hypotheses

Science · Year 8

Name: ______________________Date: ____________

Good scientific investigations start with a genuinely investigable question — one specific and testable enough to actually gather data on, rather than a vague or unanswerable one ("Does more sunlight help plants grow taller?" versus "Is nature good?"). From a question, you form a hypothesis: a reasoned, testable prediction based on existing knowledge, usually structured as "if... then..." — not a random guess, but an educated one you can genuinely test and potentially prove wrong. Spotting patterns in prior observations, or noticing something unexpected, is often what sparks a good investigable question in the first place.

Example

Noticing that plants near a window seem to grow taller than those in a dim corner might lead to the investigable question "does more sunlight increase plant height?" and the hypothesis "if a plant receives more sunlight, then it will grow taller, because sunlight is needed for photosynthesis and energy production."

Key terms

Investigable question:
A specific, testable question that can be answered by gathering data.
Hypothesis:
A reasoned, testable prediction, often structured as "if... then..."

Questions

  1. 1. An investigable question is:

    • Specific and testable enough to gather data on
    • Vague and impossible to answer
    • Never based on prior observation
    • Always about opinions, not evidence
  2. 2. A hypothesis is:

    • A reasoned, testable prediction
    • A random guess with no reasoning
    • A definite, proven fact
    • Something that can never be tested
  3. 3. Hypotheses are often structured as:

    • "If... then..."
    • "Maybe... possibly..."
    • A single word
    • A question with no prediction
  4. 4. "Is nature good?" is a poor investigable question because it is:

    • Too vague and not testable with data
    • Perfectly specific and testable
    • The best possible scientific question
    • Already answered by all scientists
  5. 5. A hypothesis should be based on:

    • Existing knowledge and reasoning
    • Pure random chance
    • No prior information at all
    • Guessing with no explanation
  6. 6. Noticing an unexpected pattern can:

    • Spark a good investigable question
    • Never lead to a scientific question
    • Only happen by accident with no value
    • Prevent forming a hypothesis
  7. 7. A good hypothesis should be:

    • Testable and potentially provable wrong
    • Impossible to test under any circumstances
    • Always assumed to be true with no testing
    • A vague feeling with no structure
  8. 8. Why is "does more sunlight increase plant height?" a better investigable question than "is nature good?"

    • It is specific and can be tested by measuring plant height under different sunlight conditions
    • Both questions are equally testable
    • "Is nature good?" is more specific and scientific
    • Investigable questions should never be measurable
  9. 9. Why must a hypothesis be potentially provable wrong (falsifiable) to be genuinely scientific?

    • If no possible result could ever disprove it, it can't be meaningfully tested by evidence
    • Hypotheses should never be capable of being proven wrong
    • Falsifiability has no connection to whether something is scientific
    • A hypothesis is only useful if it can never be tested
  10. 10. The hypothesis "if a plant receives more sunlight, then it will grow taller, because sunlight is needed for photosynthesis" includes:

    • A testable prediction with reasoning behind it
    • No reasoning at all
    • A vague, untestable guess
    • A statement with no prediction
  11. 11. Why might reviewing prior research or observations before forming a hypothesis lead to a stronger prediction?

    • Existing knowledge helps ground the prediction in reasoning rather than a blind guess
    • Prior research always makes predictions less accurate
    • Hypotheses should always ignore any existing knowledge
    • Prior observations have no useful role in forming hypotheses
  12. 12. Which of these is a testable investigable question?

    • Does adding fertiliser increase tomato plant yield?
    • Are tomatoes tasty?
    • Is gardening fun?
    • Should everyone grow tomatoes?
  13. 13. Why might a vague question like "is nature good?" be difficult to turn into a testable hypothesis?

    • "Good" is subjective and not something you can measure or test with data
    • "Good" is easily and objectively measurable with a single number
    • Vague questions are always easier to test than specific ones
    • This question requires no reasoning to answer scientifically
  14. 14. A hypothesis differs from a simple guess mainly because a hypothesis:

    • Is based on reasoning and existing knowledge, and can be tested
    • Is always correct by definition
    • Requires no evidence or reasoning at all
    • Can never be wrong once stated
  15. 15. Why might scientists sometimes revise their investigable question after initial background reading or observation?

    • Early research may reveal the original question needs narrowing, clarifying, or was based on a misunderstanding
    • Investigable questions should never be revised once first written
    • Background research never influences how a question should be framed
    • A first-draft question is always the most refined, final version
  16. 16. Why is "if... then... because..." a particularly useful hypothesis structure, compared to just "if... then..."?

    • Including "because" forces you to state the underlying reasoning, which can also be evaluated and tested
    • Adding "because" makes a hypothesis less scientific
    • Reasoning should never be included in a hypothesis
    • The "because" clause has no scientific value
  17. 17. Why might two scientists studying the same phenomenon propose different hypotheses to test?

    • Different existing knowledge, reasoning or observations can lead to different plausible, testable predictions
    • Only one correct hypothesis can ever exist for any given phenomenon
    • Hypotheses are always identical regardless of the scientist's reasoning
    • Different hypotheses about the same topic are always evidence of an error
  18. 18. A hypothesis predicts a plant will grow taller with more sunlight, but the experiment finds no difference. What should happen next?

    • The hypothesis should be reconsidered or revised in light of the unsupported prediction, not the data ignored
    • The data should be ignored to preserve the original hypothesis
    • This result proves the entire scientific method doesn't work
    • A hypothesis being unsupported means the experiment was worthless
  19. 19. Why might turning a broad area of curiosity (e.g. "I wonder about plant growth") into a specific investigable question be one of the hardest, most important steps of an investigation?

    • A well-framed question focuses the entire investigation and determines what data can actually be meaningfully collected
    • Broad curiosity is always just as useful as a specific question for planning an investigation
    • The framing of a question has no effect on how an investigation proceeds
    • Specific questions are always easier to think of than broad areas of interest
  20. 20. A student's hypothesis is "sunlight is good for plants." Why is this weaker than "if a plant receives more sunlight, then it will grow taller, because sunlight is needed for photosynthesis"?

    • The first is vague and hard to test directly, while the second makes a specific, measurable, falsifiable prediction with reasoning
    • Both hypotheses are equally specific and testable
    • A hypothesis should never include reasoning about why it might be true
    • "Good for plants" is precise enough to design a fair experiment around
  21. 21. Understanding how to form investigable questions and testable hypotheses mainly helps you to:

    • Structure a scientific investigation so it can genuinely be tested and potentially prove an idea wrong
    • Assume every question is equally scientific regardless of how it is phrased
    • Avoid ever using reasoning when making a prediction
    • Treat guesses and hypotheses as exactly the same thing

Answer key (parent copy)

  1. 1. Specific and testable enough to gather data on
  2. 2. A reasoned, testable prediction
  3. 3. "If... then..."
  4. 4. Too vague and not testable with data
  5. 5. Existing knowledge and reasoning
  6. 6. Spark a good investigable question
  7. 7. Testable and potentially provable wrong
  8. 8. It is specific and can be tested by measuring plant height under different sunlight conditions
  9. 9. If no possible result could ever disprove it, it can't be meaningfully tested by evidence
  10. 10. A testable prediction with reasoning behind it
  11. 11. Existing knowledge helps ground the prediction in reasoning rather than a blind guess
  12. 12. Does adding fertiliser increase tomato plant yield?
  13. 13. "Good" is subjective and not something you can measure or test with data
  14. 14. Is based on reasoning and existing knowledge, and can be tested
  15. 15. Early research may reveal the original question needs narrowing, clarifying, or was based on a misunderstanding
  16. 16. Including "because" forces you to state the underlying reasoning, which can also be evaluated and tested
  17. 17. Different existing knowledge, reasoning or observations can lead to different plausible, testable predictions
  18. 18. The hypothesis should be reconsidered or revised in light of the unsupported prediction, not the data ignored
  19. 19. A well-framed question focuses the entire investigation and determines what data can actually be meaningfully collected
  20. 20. The first is vague and hard to test directly, while the second makes a specific, measurable, falsifiable prediction with reasoning
  21. 21. Structure a scientific investigation so it can genuinely be tested and potentially prove an idea wrong