The Full Scientific Inquiry Process
AdvancedScientific inquiry runs a full process: pose a question from observation, write a testable hypothesis, design a fair test (one variable changed, others controlled, a control group set), collect and record data, analyse with charts, conclude and review errors; results must be repeatable. Master the process and it serves every experiment — and every judgement of information.
- The inquiry process: observe and question, hypothesise, design, collect data, analyse, conclude and review.
- A fair test changes one independent variable, controls the rest, and sets a control group.
- Large samples and repeated trials with averages reduce chance error.
文體小知識：科學探究報告按「提問、假設、設計、數據、結論」的流程組織，訓練有系統的科學思考。
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1Inquiry begins with observation. Example: a pupil notices mung beans soaked in salt water sprout more slowly than those in fresh water. From this comes a testable question: 'How does salt concentration affect how quickly mung beans sprout?' Then the hypothesis — a tentative answer: 'The higher the salt concentration, the slower the beans sprout.' A hypothesis must be testable and may prove wrong; a rejected hypothesis still advances science.
2Step two is designing a fair test. Change only one independent variable — here the salt concentration (0 per cent, 1 per cent, 3 per cent) — measure the dependent variable (days to sprout or sprouting rate), and control everything else: the same bean variety, twenty beans per group, the same room, temperature and light, the same volume of water. The 0-per-cent group is the control for comparison. Repeat each setup three times and take averages to reduce chance error.
3Step three is collecting and analysing data. Design a recording table and observe at the same time daily: how many seed coats split, how many roots emerge. Fill the table, then draw a bar or line chart so the trend shows at a glance. Face all the data honestly, including any group against expectation; consider sources of error — seed differences, evaporated water, imprecise measuring. The larger the sample and the more repetitions, the firmer the conclusion.
4Last come conclusion and communication. Conclude only on the original question and only from the data: if 3-per-cent water clearly slows sprouting, the hypothesis is supported; if results are muddled, report honestly and review the design. A report usually has four parts — aim, method, results, conclusion — so others can repeat and verify. The process also judges everyday claims: an advert says 'works for eight in ten users' — ask how large the sample was, whether there was a control group, and how 'works' was measured. Scientific thinking is the best antidote to blind belief.
1Summary 重點摘要
Scientific inquiry runs a full process: pose a question from observation, write a testable hypothesis, design a fair test (one variable changed, others controlled, a control group set), collect and record data, analyse with charts, conclude and review errors; results must be repeatable. Master the process and it serves every experiment — and every judgement of information.
2Vocabulary cards Vocabulary
The systematic process from question and hypothesis through experiment to conclusion.
A tentative answer to a question that must be testable by experiment.
A factor in an experiment that can be changed or measured.
The factor deliberately changed, such as salt concentration.
The measured result that changes with the independent variable, such as days to sprout.
Factors kept constant, such as water volume, temperature and light.
The untreated group kept for comparison, such as the fresh-water group.
A design changing only one variable while holding all others constant.
The measurements and observations collected in an experiment.
The answer to the question based on the data, going no further than the evidence.
3Step by step Steps
- Step 1: From observation to questionScientific inquiry begins with careful observation, then turns what is seen into a specific, testable question. Example: seeing slow sprouting in salt water, turn it into 'How does salt concentration affect mung-bean sprouting?' The question must be specific and testable, never vague, or no experiment can be designed; the sharper the question, the easier the variables are to control and the more likely the experiment succeeds.
- Step 2: Write a testable hypothesisA hypothesis is a tentative answer that clearly predicts a relationship between variables, so an experiment can confirm or overturn it. Example: 'The higher the salt concentration, the slower mung beans sprout' predicts a link between the variables; the experiment will judge it. A hypothesis is more than a guess — it is a statement that can be tested; even one finally overturned still advances science.
- Step 3: Design a fair testA fair test changes only one variable while every other condition stays the same, so the result can be attributed. Example: three groups of twenty same-variety beans in 0 per cent, 1 per cent and 3 per cent water; same room, temperature, light and water volume — only the concentration differs. Any extra difference would rob the result of its power; this is the heart of experimental design.
- Step 4: Set the control and repetitionsA control group gives the baseline for comparison, and repetitions cancel out chance errors; together they make conclusions reliable. Example: the fresh-water (0 per cent) group is the control; each setup repeats three times and averages — sixty beans in all — so chance cancels out. Without control and repetition, even pretty data cannot be trusted; the larger the sample and the more repetitions, the firmer the conclusion.
- Step 5: Collect the dataData must be collected on schedule, honestly and systematically, with a record sheet prepared before the experiment. Example: observe at eight each morning and record: on day one, eighteen of the control beans split, twelve of the 1-per-cent group, only five of the 3-per-cent group. Honest records have value even when the result surprises you; the group against expectation is often the very clue to a new discovery.
- Step 6: Analyse the dataData must be organised and charted before the trend appears. Example: chart the sprouting rates — control 90 per cent, 1-per-cent 60 per cent, 3-per-cent 25 per cent — and the trend leaps out. Charts let the numbers tell the story and are an essential part of any science report; while analysing, also weigh the sources of error, such as evaporated water and imprecise measuring.
- Step 7: Conclude and reviewThe conclusion answers the hypothesis and states whether the evidence supports it; reviewing errors makes the next round better. Example: write 'higher salt concentration lowers sprouting rate; the hypothesis is supported', then review errors: does evaporating salt water grow stronger? do seeds differ? how can the next round improve? Honest review is the very spirit of science; a report stating aim, method, results and conclusion lets others repeat and verify.
4Diagrams Diagrams
5Worked example Example
Example: Yan wants to study 'how water temperature affects how fast sugar dissolves'. Write the hypothesis, the independent and dependent variables, two controlled variables, and describe the steps.
- Hypothesis: the hotter the water, the faster the sugar dissolves — a clear prediction of the link between temperature and speed that the experiment can put to the test.
- Independent variable: water temperature, with three groups at 20°C, 40°C and 60°C for comparison; dependent variable: the time in seconds for the sugar to dissolve completely.
- Controlled variables: the same water volume, 100 millilitres per cup; the same sugar amount and grain size, five grams per cup, using the same kind of sugar and the same stirring.
- Steps: check each cup's temperature with a thermometer, drop an equal sugar cube in at the same moment, stir once a second at the same pace, and time with a stopwatch until the sugar vanishes; repeat each group three times, average, then compare with a bar chart.
- Answer: The hypothesis is that hotter water dissolves sugar faster; temperature is the independent variable and dissolving time the dependent; keeping volume, sugar amount and stirring constant while changing only temperature, with three repetitions per group, makes the test fair and the results easy to compare on a bar chart.
6Common mistakes Mistakes
7Quick check Quick check
Q1What is a hypothesis, and what marks it?
Q2Why may a fair test change only one variable?
Q3In the salt-sprouting experiment, what is the control group and what is it for?
Q4Why repeat trials and average them?
Q5What scientific questions can be asked of the claim 'works for eight in ten users'?
8Recap Recap
- The inquiry process: observe and question, hypothesise, design, collect data, analyse, conclude and review.
- A fair test changes one independent variable, controls the rest, and sets a control group.
- Large samples and repeated trials with averages reduce chance error.
- Record all data honestly; conclude no further than the evidence and welcome repetition.
- The same process screens daily information: ask about sample, control and measurement.