Humans & the Ocean
Practical · Topic 5
CAPS block 2
6 investigations
Builds your Expo project
Practical 5 — Scientific Inquiry
This is the only practical in the course where doing it yourself is the assessed outcome. Every other topic's practical can be completed from supplied data, because there CAPS assesses the analysis. Here CAPS assesses the investigation — so Parts 1–3 build the skills on supplied data, and Parts 4–6 are your own project, start to finish.
What CAPS actually asks for
"Observation · Hypothesis testing · Theory and truth · Problem statement (initial inquiry) · Hypothesis (allows for predictions) · Experimental design (materials and procedure) · Data collection (observations and measurements) · Analysis and interpretation of data or results (inferences) · Drawing conclusions (answering the research question or problem) · Have we proved or disproved the hypothesis? · Extension (further inquiry — pose new questions that are related to the original question and can lead to new investigations)."
And the purpose, stated outright: "Learners must be trained in how to submit a credible research project to the annual National Sciences Exposition."
And the purpose, stated outright: "Learners must be trained in how to submit a credible research project to the annual National Sciences Exposition."
📐 What you need
Parts 1–3 and 5–6 need nothing but paper, a pencil and a ruler. Graph paper helps; the boxes on this sheet are ruled if you print it.
Part 4 is your own experiment, and three ready-to-run options are given — all built from things you already have, or from a morning at the shore. Pick one, or design your own using the same scaffold.
1
Practise on someone else's data first
CAPS: "Analysis and interpretation of data or results"
Aim
To tabulate, graph and interpret a supplied data set, applying the CAPS formatting rules — before your own marks depend on them.
The data
A Grade 10 learner measured sea-surface temperature and counted sardines in a standard net haul at the same Algoa Bay site, once a month for a year. Her raw notes are below, exactly as she wrote them — unsorted, unlabelled and unusable as they stand. That is your starting point, and it is realistic.
📊 The supplied data — her raw notebook
| Month | SST | Sardines counted |
|---|---|---|
| Jan | 22.4 | 31 |
| Feb | 23.1 | 24 |
| Mar | 22.0 | 38 |
| Apr | 20.6 | 66 |
| May | 18.9 | 112 |
| Jun | 17.2 | 187 |
| Jul | 16.4 | 243 |
| Aug | 16.8 | 229 |
| Sep | 18.1 | 141 |
| Oct | 19.7 | 88 |
| Nov | 21.2 | 19 |
| Dec | 22.8 | 27 |
Your task
- Redraw the table properly — figure number, descriptive title, labelled headings, units in the headings in brackets, numbers only in the body.
- Plot sardine count against month as a line graph, following all seven graph rules.
- Look for the trend. Then look for the one month that breaks it.
Analysis
- 5Redraw the table to the CAPS format. Marks for: figure number · descriptive title · labelled headings · units in headings only · body clean.
- 7Draw the line graph. Marks for: correct type · figure number · descriptive title · both axes labelled with units · sensible scale using most of the space · points plotted accurately · line drawn accurately.
- 3Describe the trend in your own words. State what happens to sardine numbers as SST falls.
- 3November does not fit the pattern — 19 sardines at 21.2 °C, when October managed 88 at a similar temperature. Identify it, name what it is called, and give two possible explanations that do not involve deleting it.
- 2Write an inference from this data. Then write the piece of data your inference rests on, and explain the difference between the two.
- 3This is correlation. Explain why it does not prove that lower temperature causes more sardines, and suggest one other factor that could produce the same pattern.
2
Pick the right chart — four times
CAPS: "the correct and appropriate use of Diagrams, Tables, Line graphs, Bar graphs, Histograms, Pie charts"
Aim
To choose the correct graph type for a given data set, and justify the choice.
Four data sets. Four different correct answers — one of each type. For each, name the chart and give the reason in one sentence.
| The data | Chart type | Because… |
|---|---|---|
| a) Water temperature measured every 2 m from the surface down to 30 m at one dive site | ||
| b) The number of individuals of each of five limpet species found in one rock pool | ||
| c) How the 100% of a plankton sample divides between diatoms, dinoflagellates, copepods and larvae | ||
| d) Monthly rainfall at Cape Recife across one year |
Analysis
- 8Name the correct chart for each, with a one-sentence reason. (1 mark for the chart, 1 for the reason.)
- 2Two of these are column charts. Explain the one visual difference between them and what that difference means.
- 2For (a), state which variable goes on the x-axis and which on the y-axis, and justify it.
- 2Give one reason a pie chart would be a poor choice for data set (b).
3
Aims, hypotheses and variables
CAPS: "Problem statement · Hypothesis (allows for predictions) · Define variables"
Aim
To write a correct aim and a testable hypothesis, and to identify all three variable types, for three scenarios.
Remember the difference
The aim says what you are setting out to do, using a CAPS stem: To determine… / To show that… / To investigate… / To find out… / To observe… / To measure…
The hypothesis is a testable prediction — one short sentence naming both variables and the expected direction.
| Scenario | Aim | Hypothesis | Ind. / Dep. / Controlled |
|---|---|---|---|
| A — Does light level change how fast Ulva (sea lettuce) produces oxygen bubbles? | |||
| B — Do mussels on the exposed side of a rock grow smaller than those in the sheltered gully? | |||
| C — Does salt concentration affect how quickly a potato cylinder loses mass? |
Analysis
- 6Write the aim for each scenario, using a CAPS verb stem. (2 each.)
- 6Write a testable hypothesis for each — one sentence, both variables named, direction stated. (2 each.)
- 9Identify the independent, dependent and controlled variables for each. (3 each.)
- 3For scenario B, explain why it is harder to control variables in a field study than in a lab, and name two things you could not hold constant.
- 2Explain why "Sea lettuce is affected by light" is a poor hypothesis, and rewrite it properly.
4
Run your own investigation
CAPS: "Experimental design (materials and procedure) · Data collection (observations and measurements)"
This is the assessed part, and there is no supplied-data version of it. Pick one of the three options below, or design your own using the same scaffold. All three are built from things you already have or can get in one trip.
① Salinity and buoyancy
How does the salt concentration of water affect how much of a floating object sits below the surface?
Float a pencil weighted with a bit of clay ("hydrometer") in jars of 0, 10, 20, 35 and 50 g/L salt water. Mark and measure the waterline each time.
Ind: salt concentration · Dep: depth submerged (mm) · Controlled: same pencil, same water volume, same temperature
🟢 kitchen
🟢 kitchen
② Temperature and dissolved gas
Does warmer water hold less dissolved gas? (The reason warm seas are less productive.)
Take equal volumes of fizzy water at 5, 15, 25 and 35 °C. Measure mass lost over 10 minutes as the gas escapes, or count bubbles released per minute.
Ind: temperature · Dep: mass lost (g) or bubbles/min · Controlled: same volume, same container, same starting fizz, same timing
🟢 kitchen
🟢 kitchen
③ Zonation on the shore
Do organisms change predictably as you move up a rocky shore from the water?
Lay a tape (transect) from the low-water mark up the shore. Place a quadrat every 2 m and record what is inside each one. A string square and a phone camera are enough.
Ind: distance up the shore (m) · Dep: number/type of organisms per quadrat · Controlled: same quadrat size, same shore, same tide state
🌊 shore · Cape Recife or Schoenmakerskop
🌊 shore · Cape Recife or Schoenmakerskop
⚠️ Safety — for option ③ especially
Never work a rocky shore alone, and never turn your back on the sea. Go on a falling tide, tell someone where you are, wear grippy shoes, and check the swell forecast first. Put every rock you turn back exactly as you found it — the animals underneath will die if you don't. Take nothing living home.
Your experimental design — fill this in before you start
| Problem statement (the question) | |
|---|---|
| Aim (use a CAPS stem) | |
| Hypothesis | |
| Independent variable + range | |
| Dependent variable + unit | |
| Controlled variables (at least 3) | |
| Number of repeats (min 3) | |
| Apparatus |
Method — write it so a stranger could repeat it exactly
Your results table — draw it BEFORE you collect data
This is the habit that separates organised investigators from people scribbling on the back of a hand. Headings, units in brackets, a column for each repeat and one for the mean.
| Independent variable ( ) | Trial 1 | Trial 2 | Trial 3 | Mean |
|---|---|---|---|---|
Your graph
Analysis
- 8Complete the design table in full — problem statement, aim, hypothesis, all three variable types, repeats, apparatus.
- 5Write the method as numbered steps, detailed enough to be repeated exactly.
- 5Collect your data into the table, with at least three repeats and a calculated mean.
- 7Graph your results, applying all seven graph rules.
- 4Describe the trend, and identify any outliers with a possible explanation.
- 3State whether your hypothesis was supported or not supported, and justify it from your data.
5
Write the report — all six CAPS parts
CAPS: "Produce a research report… Introduction, Hypothesis and Aim, Method, Results, Discussion, Conclusion"
The checklist
Tick each item as you complete it. The two starred parts are the ones learners most often skip entirely.
- Title — descriptive, not just "My Experiment".1
- ★ Introduction — what is already known, from your reading. Cite your sources. This is where you show the judge you did background research.5
- ★ Aim — one sentence, using a CAPS verb stem.2
- Hypothesis — one short testable sentence, both variables named.2
- Method — materials and numbered procedure; repeatable by a stranger; note any calibration.5
- Results — table and graph to the CAPS format. Data only, no interpretation.8
- Discussion — what the results mean; trends; outliers; and an honest account of flaws and inaccuracies in your procedure and where you could have improved it.6
- Conclusion — hypothesis supported or not supported, plus at least two suggested future studies.4
Analysis
- 33Submit the complete report, marked against the checklist above.
- 3In your Discussion, name three specific flaws in your own procedure and state, for each, whether it would have pushed your result too high or too low.
- 2In your Conclusion, propose two further investigations that follow from your findings. CAPS calls this "Extension — pose new questions related to the original question."
6
Build the poster and face the judges
CAPS Display Skills: "present diagrams, tables & graphs in a poster for an exposition"
The rule that catches everyone
The poster is not the report at a smaller size. Your booklet: "The poster must be a visual graphic summary of the investigation." A judge walking past should get your question, your method and your finding in about twenty seconds, mostly from the pictures.
A layout that works
| Left column | Centre (the eye lands here) | Right column |
|---|---|---|
| Title (large) Aim Hypothesis Short introduction |
Your graph, big. Your results table. A photo or diagram of the setup. |
Discussion — brief Conclusion — one clear sentence Two future studies References |
Everything on the board gets a figure number and a descriptive title — same rules as the report. Text in blocks short enough to read standing up.
Rehearse these — judges ask them every year
- "In one sentence, what were you trying to find out?"
- "Why did you choose this question?" (They are testing whether it is yours.)
- "What was your independent variable, and what did you keep constant?"
- "Talk me through this graph."
- "What went wrong, and what would you do differently?" (Say something real. "Nothing" is the worst possible answer.)
- "Your results don't support your hypothesis — how do you feel about that?" (Correct answer: it is still a result.)
- "What would you investigate next?"
Analysis
- 10Produce the poster. Marks for: visual-first layout · graph prominent and correctly formatted · figure numbers and titles throughout · aim and hypothesis visible · conclusion in one clear sentence · readable standing up.
- 7Answer all seven judge questions aloud to someone else, from memory, without reading the poster. (1 each.)
- 3Explain in your own words why a judge cares more about how you thought than about whether your hypothesis was right.
✅ Memo & marking guide — try it first
Total: 153 marks — Investigation 1: 23 · Investigation 2: 14 · Investigation 3: 26 · Investigation 4: 32 · Investigation 5: 38 · Investigation 6: 20.
Parts 1–3 are self-markable against this memo; Parts 4–6 are your own project and are rubric-marked. This memo does not print with the worksheet.
Part 1 — the supplied data
- Q1 (5): One mark each — "Fig 1" · a title of the form "Fig 1: A table showing sea-surface temperature and sardine count at [site], Algoa Bay, over one year" · headings labelled · units in headings in brackets: Month, Sea-surface temperature (°C), Sardines per standard haul · body contains numbers only.
- Q2 (7): Line graph (month is continuous) · figure number · descriptive title · x = Month, y = Sardines per haul, both labelled with units · scale using most of the grid · points accurate · line accurate.
- Q3 (3): Sardine numbers rise as SST falls, peaking in July at 243 when SST is lowest (16.4 °C), and collapsing through the warm months to a low in November. An inverse relationship.
- Q4 (3): November is the outlier (1). Two plausible explanations from: a counting or recording error; the net was set at a different depth or time of day; a storm or unusual current that week; a predator event; genuine year-to-year variability (2). Do not delete it — mark and explain.
- Q5 (2): Data = "243 sardines were counted in July at 16.4 °C". Inference = "sardines in Algoa Bay are more abundant in cooler water". The data is what was measured; the inference is what you reason from it.
- Q6 (3): Correlation is not causation — two things varying together does not show one causes the other. Both could be driven by a third factor. Accept any sensible confounder: seasonal upwelling bringing both cooler water and the plankton sardines feed on; the sardine run's migration timing; seasonal fishing pressure.
Part 2 — chart choice
- Q7 (8): (a) Line graph — depth is continuous, so the trend between readings is meaningful. (b) Bar graph — five separate species, same unit, columns separated. (c) Pie chart — the categories are proportions of one fixed whole (100% of the sample). (d) Histogram — months are continuous related ranges, so columns touch.
- Q8 (2): Bar-graph columns are separated; histogram columns touch. The gap states that the categories are discrete and unrelated; touching states they are continuous and adjacent.
- Q9 (2): Depth on the x-axis (independent — what you chose to sample), temperature on the y-axis (dependent — what you measured in response). Accept the inverted-y convention with depth on y if justified as an oceanographic profile.
- Q10 (2): The species counts are not parts of a meaningful single whole, and a pie chart hides the actual numbers — you cannot read "how many limpets" off it, only proportions.
Part 3 — aims, hypotheses, variables
- Q11 (6): Must use a CAPS stem. E.g. A: "To investigate the effect of light intensity on the rate of oxygen production in Ulva." B: "To determine whether mussels on an exposed rock face grow smaller than those in a sheltered gully." C: "To measure the effect of salt concentration on mass loss from potato cylinders."
- Q12 (6): One sentence, both variables, direction stated. E.g. A: "As light intensity increases, the rate of oxygen bubble production by Ulva will increase."
- Q13 (9): A — Ind: light intensity · Dep: bubbles per minute · Controlled: same piece/mass of Ulva, same water temperature, same CO₂ availability, same time period. B — Ind: exposure (exposed vs sheltered) · Dep: mussel shell length (mm) · Controlled: same species, same tidal height, same sample size, same measuring method. C — Ind: salt concentration · Dep: mass change (g) · Controlled: same potato, same cylinder size, same volume of solution, same time and temperature.
- Q14 (3): In the field you cannot hold conditions constant — accept any two of: wave exposure, tidal height, sunlight, predation, water temperature, age of the organisms. You manage this by sampling randomly and repeatedly rather than by control.
- Q15 (2): It is not testable and gives no direction — "affected" could mean anything, and it names no measurable dependent variable. Rewrite: "As light intensity increases, the number of oxygen bubbles produced per minute by Ulva will increase."
Part 4 — your own investigation · rubric-marked
- Q16 (8): One mark per row of the design table — problem statement · aim with a CAPS stem · hypothesis · independent variable and its range · dependent variable and its unit · at least three controlled variables · at least three repeats · apparatus. The rows must be internally consistent: the hypothesis must name the same two variables the table names.
- Q17 (5): Numbered steps a stranger could repeat exactly — quantities and units stated, how the independent variable is changed, how and when the dependent variable is measured, and how the controlled variables are kept constant.
- Q18 (5): The results table is drawn to the CAPS format, every value of the independent variable has at least three repeats, and each mean is calculated correctly. Readings are recorded as measured — an odd value is kept and marked, never quietly dropped.
- Q19 (7): One mark per graph rule, the same seven as Part 1 Q2: correct graph type · figure number · descriptive title · both axes labelled with units · scale using most of the grid · points plotted accurately · line drawn accurately.
- Q20 (4): The trend is described in words from the learner's own data, and any outlier is identified with a possible explanation rather than deleted.
- Q21 (3): The hypothesis is stated as supported or not supported — never "proved" — and the judgement is justified from the learner's own data.
Part 5 — the report · rubric-marked
- Q22 (33): Mark item by item against the checklist: title (1) · introduction (5) · aim (2) · hypothesis (2) · method (5) · results (8) · discussion (6) · conclusion (4). Introduction and Aim carry 7 of those 33 between them — the two parts most often missing entirely.
- Q23 (3): One mark per flaw, and only when it is specific to this procedure and states whether it would have pushed the result too high or too low.
- Q24 (2): One mark per further investigation, and only when it grows out of this one's findings — a new question about the original question, not an unrelated topic.
Part 6 — the poster and the judges · rubric-marked
- Q25 (10): Mark against the six criteria in the question. A poster that is the report shrunk down — dense text, a small graph — cannot score well on visual-first layout or on being readable standing up.
- Q26 (7): One mark per judge question answered from memory, without reading the poster. "Nothing went wrong" earns no mark for judge question 5; for judge question 6, the answer is that an unsupported hypothesis is still a result.
- Q27 (3): A judge is assessing the science: whether the investigation was a fair test, honestly recorded and soundly reasoned. Whether the hypothesis turned out right is not in the investigator's control.
- The standard that matters: a well-designed investigation whose results do not support its hypothesis scores full marks. A neat project with fudged data scores zero.