Unit Synthesis + Working Scientifically Depth Study
In 2019, CSIRO scientists ran more than 500 controlled plant-growth experiments — each one changing just one variable at a time — and confirmed that sunlight increases duckweed growth by up to 400%.
Printable Worksheets
Print or save as PDF — or build a custom worksheet from any module's questions.
Q1 · Without looking back, write everything you can remember about MRS GREN, cells, ecosystems and biodiversity in 2 minutes. Just a brain dump — don't worry about being neat.
Q2 · A student claims plants grow taller with classical music playing. What's WRONG with that statement as a starting point for a science experiment? List two problems.
● Know
- The big ideas of Unit 1: MRS GREN, cells, ecosystems, biodiversity, conservation
- The six steps of a scientific investigation: Q → H → M → R → D → C
- The three types of variable (independent, dependent, controlled)
● Understand
- Why a fair test changes only one variable at a time
- Why replicates and controls make results trustworthy
- How to write a testable hypothesis using "If… then…"
● Can do
- Identify IV, DV and controlled variables in an investigation
- Write a testable hypothesis
- Plan your own simple investigation using the Q-H-M-R-D-C structure
- Hypothesis
- Independent variable
- Dependent variable
- Controlled variable
- Replicate
- A repeat of the same condition
- The one thing you deliberately change
- A testable prediction ("If… then…")
- Something kept the same across all groups
- What you measure to see the effect
Picture a single duckweed plant floating on the surface of a pond: it is alive (MRS GREN), made of cells, part of a food web, and shaped by adaptations to its watery environment — every idea from this unit visible in one tiny floating leaf. Here's the big map.
| Idea | Where it sat in the unit | How it links forward |
|---|---|---|
| MRS GREN — seven signs of life | L01, L05 | Underpins the definition of biodiversity (only living things count) and tells us why ecosystems collapse without their living parts. |
| Cells — smallest unit of life | L06–L10 | Cells specialise → tissues → organs → systems → organism → population → ecosystem. Same building blocks; bigger scales. |
| Ecosystems — biotic + abiotic, food webs, energy | L11–L15 | Each organism has a role, supported by adaptations. Damage one link, the whole web wobbles. |
| Adaptations — structural/behavioural/physiological | L16 | Adaptations let species occupy ecosystem roles. Lose habitat and the adaptations no longer fit. |
| Biodiversity — genetic/species/ecosystem | L17 | The variety of life that ecosystems depend on for resilience. |
| Threats and conservation | L18–L19 | What humans do to biodiversity, and how we fight back. |
A single example to tie it all: a koala is a multicellular organism that meets all seven MRS GREN criteria. It has adaptations (gripping paws — structural; eating gum leaves at night — behavioural; tolerating gum-leaf toxins — physiological). It lives in eucalypt ecosystems where it's a primary consumer. Habitat loss and fire (threats) have made many koala populations endangered, so conservation (national parks, corridors, captive treatment for chlamydia) is now essential. Every Unit 1 idea shows up in one animal.
Every formal science investigation in NSW uses the same backbone. Memorise the six letters.
| Letter | Step | What you do |
|---|---|---|
| Q | Question | A clear, testable scientific question. Usually starts "How does …?" or "What is the effect of …?" |
| H | Hypothesis | A predicted answer in "If … then … because …" form. |
| M | Method | The steps anyone could follow to repeat your experiment. Include variables, equipment, replicates and safety. |
| R | Results | Tables and graphs of what you measured. Numbers, not feelings. |
| D | Discussion | What patterns do the results show? Were there any errors? Compare with the hypothesis. |
| C | Conclusion | One or two sentences answering the original question, based on the results. |
This structure isn't a school invention — published scientific papers use the same skeleton.
A formal investigation runs Q (Question), , , , Discussion, Conclusion. The independent variable is the one thing you ; the dependent variable is what you .
You can't run a fair test until you know your variables. There are three jobs to label.
- Independent variable (IV) — the ONE thing you deliberately change. Usually goes on the x-axis of a graph.
- Dependent variable (DV) — the thing you measure. Usually goes on the y-axis.
- Controlled variables — everything else, kept the same. Often called the "controls" of the experiment.
The fair-test rule: change one IV, keep everything else the same, and measure the DV. If you changed two things at once, you wouldn't know which one caused the result.
Example to ground it. "Does light intensity affect how fast duckweed grows in a pond microcosm?" → IV = light intensity (lux). DV = number of new leaves per week. Controlled: water type, water volume, container size, temperature, starting number of duckweed, time of day measured.
- Light intensity (lux)
- New leaves per week
- Water temperature
- Volume of water in each cup
- Container size
- Controlled variable
- Independent variable
- Controlled variable
- Dependent variable
- Controlled variable
Let's walk through a full investigation using the Q-H-M-R-D-C structure on a real pond plant.
| Step | What it looks like |
|---|---|
| Q (Question) | "How does light intensity affect the growth of duckweed in a pond microcosm?" |
| H (Hypothesis) | "If light intensity increases, then the rate of duckweed leaf growth will increase, because duckweed is a green plant and uses light for photosynthesis." |
| M (Method) | (1) Fill 12 clear cups with the SAME 300 mL of pond water. (2) Add exactly 10 starting duckweed plants to each cup. (3) Place 3 cups in each of 4 light conditions: dark cupboard, low (one weak lamp), medium (room window), high (under bright lamp). (4) Keep temperature, water volume, water source, container size and time the same. (5) Count new leaves every 3 days for 3 weeks. |
| R (Results) | Table of leaf counts at each light level, averaged across 3 replicates. Bar graph: Light level (x-axis) vs Average new leaves per week (y-axis). |
| D (Discussion) | Duckweed in higher light grew faster, supporting the hypothesis. Possible sources of error: leaves stuck together, some cups slightly warmer. Replicates reduce the impact of one stray cup. |
| C (Conclusion) | "As light intensity increased, duckweed leaf growth increased. The data supports the hypothesis that photosynthesis-driven growth depends on light intensity." |
Notice the three things that make this a fair test: one IV (light), measured DV (new leaves), and everything else controlled. The three replicates per condition are what make the conclusion trustworthy.
Wrong: "My hypothesis is: plants are amazing." Not testable — there's no way to measure "amazing", and no way to prove the statement wrong.
Right: A hypothesis must be testable and falsifiable. Use the "If … then … because …" form.
Wrong: "I changed the amount of light AND the temperature, so the plants grew differently because of one of those." If you change two variables, you can't tell which caused the effect.
Right: Change ONLY one IV at a time. Keep all other variables constant.
Wrong: "I tested it once and got a result, so it's proved." One trial could be a fluke. You need replicates and ideally repeats across different days.
Right: Use multiple replicates per condition and report an average. More repeats = more trust in the result.
In the duckweed investigation, what do you predict will happen at VERY high light (e.g. directly under a strong lamp 24 hours a day) compared to high but normal light? Will growth keep increasing forever? Explain in 1–2 sentences, then reveal.
How close was your prediction?
Excellent — you grasped that biological responses usually plateau.
Good — the "upside-down U" is one of biology's most important patterns.
At the start of the lesson you were asked how you would actually prove that plants grow better in sunlight — what would you change and what would you keep the same?
Now that you've worked through the full scientific method, revisit your original idea. Did you include a control? Did you think about repeating the experiment? Write your improved experimental design.
Q1. Name the six steps of a scientific investigation (Q-H-M-R-D-C) and briefly describe what each step does. (3 marks)
Q2. A student asks: "Does water temperature affect how many mosquito larvae hatch?" Write a testable hypothesis, then identify the IV, DV, and three controlled variables. (4 marks)
Q3. Choose ONE concept from Unit 1 (MRS GREN, cells, ecosystems, adaptations, biodiversity, or conservation). Explain how it links to the other concepts in the unit, using a real Australian example. Show that you understand the unit as a connected system, not isolated topics. (4 marks)
Answers
▾MCQ 1
B — The IV is what the experimenter deliberately changes. A describes the DV. C describes controlled variables.
MCQ 2
C — Only the "If light intensity increases, then duckweed growth will increase" option is testable and falsifiable. The others are vague feelings or simple facts, not predictions.
MCQ 3
A — Number of new leaves per week is what's being measured (the DV). Light intensity is the IV; the others are controlled.
MCQ 4
D — Three cups at each light level are replicates. Running multiple replicates lets you average and trust the result.
MCQ 5
B — Cells → organisms → ecosystems → biodiversity → conservation is the unit's main story arc. The other options miss that connection.
Short Answer 1
Model answer: Q = Question (a clear, testable scientific question). H = Hypothesis (a predicted answer in "If … then … because …" form). M = Method (the repeatable steps you'll follow, including variables and replicates). R = Results (your measured data in tables and graphs). D = Discussion (interpret the patterns, mention errors and compare with hypothesis). C = Conclusion (one or two sentences answering the original question using your results).
Short Answer 2
Model answer: Hypothesis: "If water temperature increases from 10 °C to 30 °C, then the number of mosquito larvae hatching from a fixed batch of eggs will increase, because warmer water speeds up the embryo's development." IV = water temperature. DV = number of larvae hatched per 100 eggs in 48 hours. Controlled = type of water (rainwater), volume of water in each container (200 mL), number of eggs per container (100), light conditions, container size. Run 3 replicates at each temperature and graph average hatch rate vs temperature.
Short Answer 3
Model answer (biodiversity): Biodiversity is the variety of life and connects every Unit 1 idea. It is built on living organisms (which all meet MRS GREN — Lesson 1), and every organism is made of cells (Lessons 6–10). Each species has adaptations (Lesson 16) that suit its role in an ecosystem (Lessons 11–15), and species depend on each other through food webs (Lesson 12). Threats like habitat loss and invasive species (Lesson 18) reduce biodiversity, and conservation strategies like Tasmanian devil insurance populations (Lesson 19) try to restore it. Take a Tasmanian devil: it shows MRS GREN, is made of cells, has structural and behavioural adaptations, plays a top-scavenger role in its ecosystem, is part of Australia's high mammal biodiversity, was hit by disease (a threat), and is now supported by captive breeding. Every concept from the unit shows up in one species.