Use the pathway to build a clear mental model. Open each node and answer the check question.
Start with a scientific question, e.g., "How does exercise affect heart rate?" Then form a hypothesis - a prediction based on your knowledge. Example: "I predict that exercise will increase heart rate because muscles need more oxygen."
Check: What is a hypothesis and why do we need one?
Independent variable: what you change (e.g., amount of exercise). Dependent variable: what you measure (e.g., heart rate). Control variables: what you keep the same to make it fair (e.g., same person, same room temperature, same method of measuring).
Check: What are the three types of variables in an investigation?
Write a method listing each step. Measure resting heart rate first. Do the exercise (e.g., 30 star jumps). Measure heart rate immediately after. Repeat for reliability. Record all data in a table.
Check: Why is it important to repeat measurements?
Look for patterns in your data. Calculate averages if you repeated measurements. Draw a bar chart or line graph. Write a conclusion explaining whether your results support your hypothesis. Suggest improvements.
Check: How do you know if your hypothesis was correct?
A scientific investigation is a structured way of testing ideas to find out how the world works. In this chapter, you'll learn how to plan and conduct your own investigation into factors that affect heart rate.
Good scientific questions can be tested by experiment. For heart rate, you might ask:
A hypothesis is a prediction you can test. It should explain WHY you expect that result. Example: "I predict exercise will increase heart rate because muscles need more oxygen, so the heart must pump blood faster."
A fair test changes only ONE thing at a time:
Write a clear method that someone else could follow:
Record data in a table with columns for Trial, Resting HR, HR After Exercise.
The scientific method is how we find out the truth about the world. By planning careful investigations, controlling variables, and analysing data, you can discover real patterns and relationships. These skills apply to all areas of science and to solving problems in everyday life.
Question: Does more intense exercise cause a greater increase in heart rate?
Method: Compare heart rate after 10 star jumps, 20 star jumps, and 30 star jumps. Measure resting HR first, then HR after each level of exercise (with 5-minute rest between).
Variables: Independent = number of star jumps. Dependent = heart rate. Control = same person, same pace, same recovery time.
Question: How long does it take for heart rate to return to normal after exercise?
Method: Do 30 star jumps, then measure heart rate immediately, after 1 minute, 2 minutes, 3 minutes, etc., until it returns to resting rate.
Variables: Independent = time after exercise. Dependent = heart rate. Control = same person, same exercise, same conditions.
Question: Do different types of exercise affect heart rate differently?
Method: Compare heart rate after 1 minute of star jumps vs. 1 minute of running on the spot vs. 1 minute of squats. Allow 5-minute recovery between each.
Variables: Independent = type of exercise. Dependent = heart rate. Control = same duration, same person, same starting conditions.
Sports scientists at UK universities use similar methods to test athlete fitness. They measure how quickly heart rate increases during exercise and how quickly it recovers. Faster recovery indicates better cardiovascular fitness. Teams like the England football squad use these measurements to track player fitness throughout the season.
Answer all questions, then check your answers. Your quiz result is saved on this device.
Remember: Independent = what YOU change (you're IN control). Dependent = what you measure (it DEPENDS on what you changed). In a heart rate investigation, if you change exercise intensity, that's independent; the heart rate you measure depends on that choice.
If you test different people or don't allow proper rest between measurements, your results won't be reliable. A fair test changes ONLY the independent variable - everything else stays the same.
One measurement isn't reliable - you might have made an error, or something unusual might have happened. Always repeat measurements (at least 3 times) and calculate the mean average. This makes your results more trustworthy.
Your conclusion must be based on your actual results, not on what you expected. If your results don't support your hypothesis, that's still a valid finding! Say what your results actually showed and try to explain why.