Scientific Reasoning & Conflicting Viewpoints - Complete Interactive Lesson
Part 1: Scientific Method
🔬 Science Reasoning
Part 1 of 7 — The Scientific Method and the Language of Experiments
The ACT Science Section at a Glance
On the Enhanced ACT, Science is an optional section: 40 questions in 40 minutes, each with 4 answer choices. It is scored on its own and is not part of the composite score, which averages English, Math, and Reading. Some colleges and programs, especially in science and engineering, may ask for or consider it, so check the requirements of the schools you are applying to.
ACT Science is a reasoning test, not a memory test. Questions come in sets attached to short passages, and the passages appear in three formats:
| Passage format | What you see | What the questions stress |
|---|---|---|
| Data representation | One or more tables or graphs with a short introduction | Reading values, trends, interpolation |
| Research summaries | One or more experiments described step by step, with results | Variables, controls, design, conclusions |
| Conflicting viewpoints | Two or more scientists or students explaining the same thing differently | Comparing claims, predictions, and evidence |
Almost everything you need is printed in the passage. What the passage does not print is the vocabulary of experiments, and that is what this part teaches.
The Scientific Method
| Step | What it is | Example (fizzing tablet) |
|---|---|---|
| Observation | Something noticed | A fizzing tablet seems to disappear faster in a warm glass of water. |
| Question | What you want to know | Does water temperature affect how long the tablet takes to dissolve? |
| Hypothesis | A testable prediction about how variables are related | If the water is warmer, the tablet will dissolve in less time. |
| Experiment | A test that changes one factor and measures another | Time identical tablets dissolving in 200 mL of water at 10°C, 25°C, and 40°C. |
| Analysis | Organizing and reading the data | 62 s at 10°C, 41 s at 25°C, 25 s at 40°C. |
| Conclusion | What the data say about the hypothesis | Dissolving time decreased as water temperature increased. |
The method is iterative: a conclusion usually raises a new question ("Does crushing the tablet matter too?"), which starts the cycle again. A study that ends by proposing a follow-up experiment is showing exactly this.
What Makes a Good Hypothesis
A hypothesis must be testable (you can measure the variables) and falsifiable (some possible result would prove it wrong).
| Statement | Good hypothesis? | Why |
|---|---|---|
| Seeds soaked overnight will sprout sooner than dry seeds. | Yes | Sprouting time can be measured, and dry seeds sprouting first would disprove it. |
| Soaked seeds are happier. | No | "Happier" cannot be measured. |
| Soaking may or may not affect seeds somehow. | No | Every possible result fits, so nothing could disprove it. |
| Seeds sprout best in the nicest soil. | No | "Nicest" has no measurable meaning. |
Hypothesis, Law, and Theory
| Term | Meaning | Example |
|---|---|---|
| Hypothesis | A testable prediction for one situation | Warmer water dissolves sugar faster. |
| Law | A description of a pattern that holds consistently, often as a rule or equation; it does not explain why | A gas's pressure doubles when its volume is halved at constant temperature. |
| Theory | A well-supported explanation of why things happen, backed by many lines of evidence | Gases are made of moving particles that strike container walls. |
A theory never "graduates" into a law; they do different jobs. A law describes, and a theory explains.
The Variables in Every Experiment
| Term | Also called | Role |
|---|---|---|
| Independent variable | Manipulated variable | The factor the researcher deliberately changes |
| Dependent variable | Responding or measured variable | The result that is measured |
| Controlled variables | Constants | Factors kept the same in every trial so they cannot explain differences |
| Control group | Baseline | A trial with no treatment (or the standard condition) used for comparison |
ACT shortcut: In a table, the independent variable is usually the first column or the x-axis, and the dependent variable is the column or axis that shows the results.
Worked Examples
<details> <summary><b>Example 1: Name every variable in a study</b></summary>Study: A student released identical toy cars from heights of 10 cm, 20 cm, 30 cm, and 40 cm on the same ramp. Each car rolled off the ramp onto the same strip of carpet. She ran three trials at each height and recorded the average distance each car rolled across the carpet.
Question: Identify the independent variable, the dependent variable, and two controlled variables.
Solution:
- What did she change on purpose? The release height. That is the independent variable.
- What did she measure? The distance rolled across the carpet. That is the dependent variable.
- What stayed the same? The type of car and the carpet surface (also the ramp). Those are controlled variables. Because every car rolled on the same carpet, the carpet cannot explain why some cars went farther.
- What is NOT a controlled variable? Anything the passage never mentions, such as the humidity in the room. You cannot assume it was held constant.
Answer: Independent = release height; dependent = distance rolled; controlled = car type and carpet surface. ✓
</details> <details> <summary><b>Example 2: Classify the statements in a lab report</b></summary>Report excerpt:
- "Our bean plants on the windowsill leaned toward the glass."
- "If a plant receives light from only one side, its stem will bend toward that side."
- "Five of the six plants lit from the left bent left by 10° to 25°."
- "Light from one direction caused the stems to bend toward it."
Question: Which statement is the hypothesis, and which is the conclusion?
Solution:
- Statement 1 is something noticed before any test: an observation.
- Statement 2 is an "if... then" prediction that a test could prove wrong: the hypothesis.
- Statement 3 reports measured results: data.
- Statement 4 interprets the data: the conclusion.
Answer: Hypothesis = statement 2; conclusion = statement 4. ✓
Skill: Data are numbers and measurements; a conclusion says what those numbers mean.
</details>Practice: Steps, Statements, and Hypotheses 🎯
Name the Variables 🔍
A class tested whether the amount of baking soda affects how high a homemade foam rises. Each group used the same bottle, 100 mL of the same vinegar, and the same room. Groups added 0 g, 5 g, 10 g, or 15 g of baking soda and measured the foam height in centimeters. The 0 g bottle was included for comparison.
Practice: Variables, Controls, and the Cycle of Science 📋
Study 1: A student grew radish seedlings in four trays. Every tray held the same potting soil, received 50 mL of water per day, and sat under the same lamp. Each tray was watered with a different salt concentration: 0 g/L, 2 g/L, 4 g/L, or 6 g/L. After 10 days she measured the average seedling height in each tray.
ACT-Style Practice
On the real section you have about one minute per question, so naming the variables should take seconds.
A student wanted to know whether the temperature of a rubber band affects how far it stretches. She cooled four identical rubber bands to 5°C, 15°C, 25°C, and 35°C, hung the same 200 g mass from each, and measured the stretched length.
Question: Which factor was held constant so that it could not explain differences in stretched length?
<details> <summary><b>Show answer</b></summary>The mass hung from each rubber band (200 g). Temperature is the independent variable (she changed it), and stretched length is the dependent variable (she measured it). The bands were also identical, which is a second controlled variable. The air pressure in the room is never mentioned, so you cannot claim it was controlled.
</details>Key Takeaways
- ACT Science (Enhanced ACT) is optional, has 40 questions in 40 minutes with 4 choices, and is not in the composite.
- The method runs observation → question → hypothesis → experiment → analysis → conclusion, and it is iterative.
- A hypothesis must be testable and falsifiable; vague words ("happier," "may or may not") fail.
- A law describes a consistent pattern; a theory explains why. Neither turns into the other.
- Independent = changed on purpose; dependent = measured; controlled = kept the same; control group = baseline for comparison.
- Data are measurements; a conclusion says what the measurements mean.
Part 2: Hypothesis Testing
🧪 Hypothesis Testing
Part 2 of 7 — Predictions, Support, and Data That Contradict a Claim
Many ACT Science questions hand you a hypothesis and a set of results and ask one thing: do the results support it? Answering well takes three steps.
Step 1: Turn the Hypothesis into a Prediction
Before you look at the data, say what the hypothesis expects to see.
| Hypothesis wording | What it predicts |
|---|---|
| "As X increases, Y increases." | Higher X values go with higher Y values (a direct relationship). |
| "As X increases, Y decreases." | Higher X values go with lower Y values (an inverse relationship). |
| "X has no effect on Y." | Y stays about the same no matter how X changes. |
| "Y depends only on X." | Whenever X is the same, Y is the same, even if other factors change. |
| "Condition A produces more Y than condition B." | The A trials show larger Y values than the B trials. |
Notice the direction. In "As light increases, oxygen production increases," light is the factor that changes and oxygen production is the response. Reversing them changes the claim.
Step 2: Compare the Prediction with the Data
Every result does one of three things to a hypothesis:
| Verdict | When it applies |
|---|---|
| Supports (is consistent with) | The data show the predicted pattern. |
| Weakens (contradicts) | The data show a different or opposite pattern. |
| Neither | The data are about a variable the hypothesis never mentions. |
Read the measure in the right direction. If a table reports "days to germinate" or "seconds to dissolve," a larger number means slower. If a hypothesis says seeds sprout faster in the dark, the dark seeds need fewer days, not more.
ACT answer choices often take the form "Yes, because..." / "No, because...". Both halves must be right: decide yes or no first, then pick the reason that cites the data that actually matter.
Step 3: State the Verdict Carefully
Supported is not proven. Data that agree with a hypothesis support it, but a future test could still contradict it. No number of agreeing trials makes a hypothesis "proven," and agreeing trials do not turn it into a law.
Contradicted means revise or reject. When results disagree with a prediction, scientists revise or reject the hypothesis. They never discard data simply because the data disagree with what they expected.
Is the Difference Real? Variation and Sample Size
Individual measurements vary. A difference between two group averages is convincing only when it is large compared with the variation inside each group.
| Group | Growth of each fish in 4 weeks (mm) | Mean |
|---|---|---|
| Food A | 14, 20, 17 | 17.0 |
| Food B | 19, 15, 18 | 17.3 |
The means differ by only 0.3 mm, while fish within each group differ by up to 6 mm. With three fish per group, that small gap could easily be chance, so these data show no clear effect. More trials and larger differences make a result more convincing; that is why researchers repeat trials and average them.
"Only" and "All" Hypotheses
A hypothesis that says Y depends only on X can be broken by a single result: two trials with the same X but different Y. That shows something else matters. Trials where X differs and Y differs are consistent with the hypothesis, because it already says X matters.
ACT Tip: To find a result that weakens a hypothesis, write its prediction in a few words, then look for the choice that shows the opposite or shows the "only" factor held fixed while the result changed.
Worked Examples
<details> <summary><b>Example 1: A "Yes, because / No, because" question</b></summary>Study: A student hypothesized, "The activity of Enzyme K increases as temperature increases." She measured activity (in units) at five temperatures.
| Temperature (°C) | 20 | 30 | 40 | 50 | 60 |
|---|---|---|---|---|---|
| Activity (units) | 14 | 26 | 38 | 22 | 6 |
Question: Do the results support her hypothesis?
- A. Yes, because activity rose from 20°C to 40°C.
- B. Yes, because the highest activity occurred at a middle temperature.
- C. No, because activity fell at temperatures above 40°C.
- D. No, because only five temperatures were tested.
Solution:
- Prediction: activity should rise across the whole range.
- Data: it rises to 40°C, then falls to 6 units at 60°C. The prediction fails above 40°C, so the answer is No.
- Pick the reason: C names the data that contradict the claim. D is a weak reason; five temperatures are plenty to reveal the pattern. A and B start with "Yes," which is already wrong.
Answer: C ✓
</details> <details> <summary><b>Example 2: Which result would weaken an "only" hypothesis?</b></summary>Hypothesis: "The time a cup of water takes to cool from 80°C to 40°C depends only on the volume of water."
Question: Which result would contradict this hypothesis?
- A. 200 mL cooled more slowly than 100 mL in identical cups.
- B. Two 150 mL samples in identical cups cooled in the same time.
- C. 300 mL cooled more slowly than 200 mL in identical cups.
- D. Two 150 mL samples, one in a foam cup and one in a metal cup, cooled in very different times.
Solution:
- If volume is the only factor, equal volumes must cool in equal times.
- D holds volume fixed and still gets different times, so the cup material matters too. That breaks "only."
- A and C show volume mattering, which the hypothesis allows. B is exactly what the hypothesis predicts.
Answer: D ✓
</details>Practice: Does the Evidence Support the Hypothesis? 🎯
A student hypothesized: "A longer guitar string vibrates at a lower frequency." She plucked strings of the same material and tension and recorded the frequency of each.
| String length (cm) | Frequency (Hz) |
|---|---|
| 30 | 440 |
| 40 | 330 |
| 50 | 264 |
| 60 | 220 |
Support, Weaken, or Neither? ✏️
Hypothesis: "Increasing the amount of sunlight a lettuce plant gets increases the mass of its leaves."
For each finding, type support, weaken, or neither.
-
Plants given 10 hours of light per day had a greater leaf mass than plants given 6 hours.
-
Plants given 12 hours of light per day had a smaller leaf mass than plants given 8 hours.
-
Plants given 8 hours of light per day had longer roots when the soil was sandy.
Practice: Proof, Variation, and Revising a Hypothesis 📋
ACT-Style Practice
Hypothesis: "Dissolving sugar in water lowers the temperature at which the water freezes."
| Sugar added (g per L) | 0 | 100 | 200 | 300 |
|---|---|---|---|---|
| Freezing point (°C) | 0.0 | −0.5 | −1.1 | −1.6 |
Question: Do these results support the hypothesis, and what is the best reason?
<details> <summary><b>Show answer</b></summary>Yes, because the freezing point dropped each time more sugar was added. The change is small (1.6°C in total), but it is steady and in the predicted direction, which is what support means. The 0 g trial is the baseline for comparison, not a flaw. Saying the freezing point "stayed near 0°C" ignores the consistent decrease.
</details>Key Takeaways
- First turn the hypothesis into a prediction, including its direction (which variable responds to which).
- A result supports, weakens, or does neither; data about an unmentioned variable do neither.
- Read measures like "days to sprout" or "seconds to dissolve" carefully: a larger number means slower.
- In "Yes, because / No, because" choices, the verdict and the reason must both be right.
- Data support a hypothesis but never prove it; contradictory data mean revise or reject, never discard.
- A small difference between means, with large variation and few trials, may be chance.
- An "only" hypothesis is broken by the same X giving a different Y.
Part 3: Drawing Conclusions
📊 Drawing Conclusions
Part 3 of 7 — Trends, Scope, Correlation vs. Causation, and Weighing Explanations
A correct ACT conclusion says exactly what the data show: no more, no less, and in the right direction. Wrong answers usually fail in one of four ways, and this part covers each.
1. Describe the Trend Precisely
Read every data point, not just the first and last. The ACT uses a small set of trend descriptions:
| Pattern in the data | How the ACT describes it |
|---|---|
| 3, 5, 8, 12 | increases only |
| 12, 8, 5, 3 | decreases only |
| 3, 8, 12, 7 | increases, then decreases (a peak, or maximum) |
| 12, 6, 4, 9 | decreases, then increases (a minimum) |
| 3, 9, 12, 12 | increases, then levels off |
| 7, 3, 9, 5 | no consistent trend |
A data set that rises and then falls is not "increases"; checking only the endpoints (3 and 7 above) hides the peak. When you see a peak, note where it is: "Of the values tested, Y was greatest at X = 30."
2. Stay Within the Scope of the Study
A conclusion may only cover what was actually tested.
| The study tested... | A conclusion that stays in scope | A conclusion that overreaches |
|---|---|---|
| Temperatures from 20°C to 60°C | "Of the temperatures tested, activity peaked at 40°C." | "The enzyme stops working above 70°C." |
| One species of yeast | "This yeast's enzyme was most active at 40°C." | "Enzymes in all living things work best at 40°C." |
| Five tested temperatures | "The highest tested value occurred at 35°C." | "The true optimum is exactly 35°C." |
The last row matters: if the peak was measured at 35°C with neighbors at 30°C and 40°C, the real maximum could sit at 33°C or 37°C. You only know the best tested value.
3. Correlation Is Not Causation
| Kind of study | What the researcher does | What it can show |
|---|---|---|
| Observational (survey, field record) | Measures variables as they already are | An association (correlation) |
| Controlled experiment | Assigns the independent variable and holds other factors constant | A cause-and-effect relationship |
If a survey finds that on days when more umbrellas are sold, a city has more traffic accidents, the two counts are associated, but the survey does not show that one causes the other. A third factor, rain, could drive both. The cause could even run backward. To test a cause, researchers randomly assign subjects to conditions so the groups differ mainly in the factor being tested.
4. Watch for Confounding Variables
In a fair experiment, only the independent variable changes. If a second factor changes along with it, that factor is confounded with the treatment, and you cannot tell which one produced the result.
Goldfish fed Food X lived in a tank with a filter; goldfish fed Food Y lived in a tank without a filter. The Food X fish grew more.
Food and filtering changed together, so cleaner water is an alternative explanation. The study cannot conclude that Food X caused the extra growth.
5. Weighing Competing Explanations
When a passage gives two explanations, decide which one a new finding favors by comparing the finding with what each explanation predicts:
| If the finding... | Then it... |
|---|---|
| matches a prediction only Explanation 1 makes | supports Explanation 1 more than Explanation 2 |
| contradicts a prediction Explanation 2 makes | weakens Explanation 2 |
| fits both predictions equally | does not help choose between them |
| concerns something neither explanation mentions | is irrelevant to both |
Part 6 builds this into a full strategy for Conflicting Viewpoints passages.
ACT Tip: Be suspicious of answer choices with proves, always, all, every, or causes when the study was a survey. Correct conclusions tend to sound measured: "is associated with," "of the values tested," "is consistent with."
Worked Examples
<details> <summary><b>Example 1: A trend with a peak</b></summary>Study: Students counted the oxygen bubbles released per minute by a sprig of pondweed in water at different temperatures.
| Temperature (°C) | 10 | 20 | 30 | 40 | 50 |
|---|---|---|---|---|---|
| Bubbles per minute | 6 | 14 | 22 | 15 | 5 |
Question: Which statement best describes the relationship, and what can be said about the best temperature?
Solution:
- Trace every point: 6 → 14 → 22 rises; 22 → 15 → 5 falls. The pattern is increases, then decreases.
- Endpoints trap: 6 and 5 are nearly equal, so looking only at the ends would wrongly suggest "no change."
- Scope: Of the temperatures tested, bubbling was fastest at 30°C. The true peak could be anywhere between 20°C and 40°C, so "exactly 30°C" goes too far.
Answer: Bubbling increased up to 30°C, then decreased; 30°C was the best tested temperature. ✓
</details> <details> <summary><b>Example 2: Association versus cause</b></summary>Study: A survey of 300 households found that homes with more houseplants reported fewer colds per person each winter.
Question: Which conclusion is best supported?
- A. Houseplants prevent colds by cleaning indoor air.
- B. Catching fewer colds makes people buy more houseplants.
- C. The number of houseplants is associated with the number of colds.
- D. Houseplants and colds are unrelated, because no cause was found.
Solution:
- Kind of study: a survey, so it can show an association but not a cause.
- A claims a cause and adds a mechanism (air cleaning) the survey never measured. B claims the reverse cause, also untested.
- D contradicts the data: the two counts clearly vary together.
- A third factor, such as time spent at home or household income, could explain both.
Answer: C ✓
</details>Practice: Describe the Trend and Stay in Scope 🎯
Researchers warmed or cooled individual lizards of one desert species to set body temperatures and measured each lizard's top sprint speed.
| Body temperature (°C) | 20 | 25 | 30 | 35 | 40 |
|---|---|---|---|---|---|
| Sprint speed (m/s) | 0.8 | 1.4 | 1.9 | 2.1 | 1.2 |
Classify the Conclusion 🔍
Study: Researchers measured how fast one strain of bacteria multiplied at 25°C, 30°C, and 37°C. Growth was fastest at 37°C.
Classify each claim.
Practice: Correlation, Confounding, and Competing Explanations 📋
ACT-Style Practice
Researchers measured the activity of an enzyme taken from a cave-dwelling fungus at five salt concentrations: 0% salt, 8 units; 2%, 21 units; 4%, 34 units; 6%, 26 units; 8%, 11 units.
Question: A student claims, "This enzyme works best at 4% salt in every living thing." Which part of the claim goes beyond the data, and what is the in-scope version?
<details> <summary><b>Show answer</b></summary>"In every living thing" goes beyond the data, because the enzyme came from one fungus. "Works best at 4%" is also slightly too strong, since salt levels between the tested ones were never measured. The in-scope version is: "Of the salt concentrations tested, this enzyme's activity was greatest at 4%." Note also that activity rose to 4% and then fell, so it did not increase steadily across the range, and nothing is known about salt levels above 8%.
</details>Key Takeaways
- Trace every data point: increases only, decreases only, increases then decreases, decreases then increases, levels off, or no trend.
- A peak is the best tested value; the true maximum may lie between tested values.
- Keep conclusions inside the tested range, the organism or material studied, and the conditions used.
- Surveys and field records show association, not cause; random assignment in a controlled experiment can show cause.
- If a second factor changes along with the treatment, it is confounded and could explain the result.
- A finding favors the explanation whose prediction it matches.
Part 4: Applying Concepts
🔁 Applying Concepts
Part 4 of 7 — Interpolating, Extrapolating, Finding the Pattern, and Using Results in New Situations
Many ACT Science questions ask about a value the passage never measured: a point between two trials, a point beyond the last trial, or a real-world situation the experiment only models. The skill is always the same: find the pattern, then extend it honestly.
1. Interpolation: Between Tested Values
If the data change steadily, a value halfway between two trials gives a result about halfway between their results.
| Time filling (min) | 0 | 10 | 20 | 30 |
|---|---|---|---|---|
| Water depth in tank (cm) | 12 | 18 | 24 | 30 |
15 minutes falls halfway between 10 and 20 minutes, so the depth is about halfway between 18 cm and 24 cm: 21 cm. Always check the two neighbors: the answer must lie between them.
2. Extrapolation: "If the Trend Continues"
To go beyond the last trial, use the typical step size.
| Altitude (m) | 0 | 1,000 | 2,000 | 3,000 |
|---|---|---|---|---|
| Air pressure (kPa) | 101 | 90 | 79 | 70 |
The pressure falls by about 9 to 11 kPa per 1,000 m, and the drops are shrinking slightly, so at 4,000 m expect about 61 to 62 kPa. Common traps: repeating the last value (as if the trend stopped) or jumping by far more than one step.
3. Identify the Pattern Type
Not every pattern is a straight line. Test the data before you extend them.
| Pattern | Test | Example | Next value |
|---|---|---|---|
| Linear | Y changes by the same amount each equal step in X | 10, 16, 22, 28 | 34 |
| Inverse | X × Y stays the same; doubling X halves Y | X = 1, 2, 4, 5 with Y = 20, 10, 5, 4 (product 20) | X = 8 gives Y = 2.5 |
| Doubling (exponential) | Y multiplies by the same factor each step | 300, 600, 1,200, 2,400 | 4,800 |
| Peak | Y rises, then falls | 5, 12, 20, 13 | keeps falling past the peak |
The inverse pattern is the classic trap: from X = 4 to X = 5 the Y value drops by 1, but it will not keep dropping by 1 for each step in X, because the product must stay 20.
4. Applying a Result to a New Situation
Map the new situation onto the experiment's variables, then read off the answer.
| Lab finding | Same principle in everyday life |
|---|---|
| Salt water freezes at a lower temperature than fresh water | Salting icy roads, so ice melts even somewhat below 0°C |
| Water boils at a lower temperature at lower air pressure | Water boils below 100°C at high altitude, so pasta cooks more slowly |
| Dark surfaces warmed more in sunlight than light surfaces | Light-colored roofs keep houses cooler in hot climates |
| Foam-wrapped cups lost heat most slowly | Foam coolers and insulated lunch containers |
Be careful to match the mechanism, not just the topic: freezing food slows bacteria because of cold, not because of any change in freezing point.
5. Combining Two Experiments
Research summaries often vary one factor in Experiment 1 and a different factor in Experiment 2. To predict a combination neither experiment tested:
- Start from the measured value that shares one of the conditions.
- Use the other experiment to decide whether the second condition pushes the result up or down.
If a high dose of fertilizer gave 6.0 cm of growth at 20°C, and the other experiment shows plants grow more slowly at 10°C than at 20°C, then the same high dose at 10°C should give less than 6.0 cm.
6. Placing a New Trial
Questions often ask where a new trial would fall: "between 1.9 s and 2.3 s," "greater than 3.2 s." Find the two tested values on either side and choose the range between their results, as long as the trend is steady through that region.
ACT Tip: Before computing, estimate a range. If your exact answer lands outside the two neighboring values, recheck the pattern.
Worked Examples
<details> <summary><b>Example 1: Extending an inverse pattern</b></summary>Study: Engineers timed how long identical pumps, working together, took to fill the same tank.
| Number of pumps | 1 | 2 | 3 | 4 |
|---|---|---|---|---|
| Time to fill (min) | 60 | 30 | 20 | 15 |
Question: If the pattern continues, how long would 5 pumps take?
Solution:
- Test for linear: the drops are 30, 10, 5 minutes for equal steps, so the time does not fall by a fixed amount.
- Test for inverse: 1 × 60 = 60, 2 × 30 = 60, 3 × 20 = 60, 4 × 15 = 60. The product is constant.
- Extend: time = 60 ÷ 5 = 12 min.
- Trap: continuing the last drop (5 minutes) would give 10 min, which breaks the constant product.
Answer: 12 min ✓
</details> <details> <summary><b>Example 2: Combining two experiments</b></summary>Experiment 1 (all radish plants at 20°C): 0 g of fertilizer → 3.0 cm of growth per week; 2 g → 4.5 cm; 4 g → 6.0 cm.
Experiment 2 (all plants given 2 g of fertilizer): 10°C → 2.0 cm per week; 20°C → 4.5 cm; 30°C → 3.5 cm.
Question: Predict weekly growth with 4 g of fertilizer at 10°C.
Solution:
- Start from a shared condition: 4 g of fertilizer gave 6.0 cm, measured at 20°C.
- Adjust with the other experiment: at 2 g, dropping from 20°C to 10°C cut growth from 4.5 cm to 2.0 cm. Cooler means slower.
- Combine: 4 g at 10°C should be less than 6.0 cm. Choosing "more than 6.0 cm" ignores temperature; choosing "exactly 2.0 cm" ignores the extra fertilizer.
Answer: less than 6.0 cm ✓
</details>Practice: Interpolate, Extrapolate, and Find the Pattern 🎯
Table 1: The pressure of the air inside a sealed steel can was measured at four temperatures.
| Temperature (°C) | 0 | 20 | 40 | 60 |
|---|---|---|---|---|
| Pressure (kPa) | 100 | 107 | 115 | 122 |
Extend the Pattern ✏️
Type the number only.
-
Linear: at X = 1, 2, 3, 4, Y = 7, 11, 15, 19. What is Y at X = 5?
-
Inverse: at X = 2, 4, 5, 10, Y = 10, 5, 4, 2. What is Y at X = 20?
-
Interpolate: at X = 10 and X = 20, Y = 36 and Y = 48 (the data are linear). What is Y at X = 15?
Practice: Apply the Results to New Situations 📋
ACT-Style Practice
Table 2: A student hung masses from a spring and measured the stretch: 50 g, 1.5 cm; 100 g, 3.0 cm; 200 g, 6.0 cm; 300 g, 9.0 cm.
Question 1: What stretch would a 150 g mass produce?
Question 2: If the pattern continues, what mass would stretch the spring 12.0 cm?
<details> <summary><b>Show answers</b></summary>- 4.5 cm. The stretch is 3.0 cm per 100 g (a linear pattern), and 150 g is halfway between 100 g and 200 g, so the stretch is halfway between 3.0 cm and 6.0 cm.
- 400 g. Each additional 100 g adds 3.0 cm, so 12.0 cm is one step past 9.0 cm, at 400 g. Checking the pattern first (equal differences) is what makes this extrapolation safe.
Key Takeaways
- Interpolate between the two neighboring trials; the answer must lie between their results.
- Extrapolate with the typical step size; don't freeze the last value or overshoot.
- Test the pattern: equal differences (linear), constant product (inverse), constant multiplier (doubling), or a peak.
- An inverse pattern does not fall by a fixed amount; use the constant product.
- Apply a result by matching the new situation to the experiment's variables and mechanism.
- To combine two experiments, start from a value that shares one condition and adjust up or down with the other experiment.
Part 5: Science Passage Strategy
🧭 Science Passage Strategy
Part 5 of 7 — Pacing, Previewing Figures, and Avoiding Data Traps
Timing on the Enhanced ACT
The optional Science section gives you 40 questions in 40 minutes, about one minute per question, and that minute includes reading. Questions come in sets attached to passages, so think in passages: at about a minute per question, a typical passage should take roughly 5 to 6 minutes.
| Situation | Best move |
|---|---|
| You are well past 6 minutes on one passage | Make your best guesses, mark the questions, and move on |
| A question needs a long calculation or comparison | Answer the quick questions in the set first, then return |
| Time is almost up | Fill in an answer for every remaining question |
Wrong answers cost nothing extra on the ACT, so never leave a question blank. Points from easy questions in later passages are worth exactly as much as points from the hard question that is eating your time.
The 30-Second Preview
Before reading questions, spend about half a minute on:
- The introduction: what was studied and why (one or two sentences is usually enough).
- Each table or graph: the title, the axis labels or column headers, the units, the legend or key, and the overall trend.
Do not read every value or memorize tables. You will look values up as each question needs them.
Unfamiliar Terms Are Just Labels
Passages are full of names you have never seen: "Compound J," "protein RX," "Species B." Treat them as labels. A question about a protein you have never heard of is still answerable if the table shows how it behaves. Answer choices that rely on facts the passage never gives ("RX is made in the liver," "RX works faster than every other protein of its kind") cannot be concluded from the passage, however scientific they sound.
Reading Figures Accurately
| Figure feature | What to check |
|---|---|
| Axes or column headers | Which variable is which, and in what units |
| Legend or key | Which line, bar, or symbol belongs to which condition |
| Two series side by side | Do they share a trend? Which is higher, and is it higher everywhere? |
| Scale | Do grid lines go up by 1, 5, or 10? Does an axis start at 0? |
| Rates | "per minute" vs. "per hour" vs. "per day" |
The Most Common Data Traps
| Trap | Example | Defense |
|---|---|---|
| Absolute vs. relative change | Compound L rose from 90 g to 115 g (25 g); Compound K rose from 6 g to 26 g (20 g) but more than quadrupled | Ask: "change in grams" or "how many times as much"? |
| Wrong series or column | Reading the 20°C column when the question asks about 40°C | Put a finger on the row and the column |
| Units | The table is per day; the question asks per week | Convert before choosing |
| Reversed comparison | "higher at 20°C" when every 20°C value is lower | Check one row explicitly |
| NOT / EXCEPT questions | "Which is NOT supported?" | Mark each choice true or false and pick the odd one out |
Question Types in Rough Order of Speed
| Type | What it asks |
|---|---|
| Lookup | Read one value |
| Trend | Describe how one variable changes with another |
| Comparison | Compare two series, columns, or experiments |
| Interpolate / extrapolate | Estimate an unmeasured value |
| Design | Identify a variable, a control, or the purpose of a step |
| Synthesis | Combine two figures or a figure with the text |
ACT Tip: Within a passage, lookups and trend questions are the fastest points. If a synthesis question is slowing you down, answer the rest of the set first.
Worked Examples
<details> <summary><b>Example 1: Comparing two series</b></summary>Data: Rate of gas production (mL per minute) when a catalyst is added to a peroxide solution.
| Catalyst mass (g) | At 25°C | At 35°C |
|---|---|---|
| 0.5 | 2.1 | 3.0 |
| 1.0 | 4.0 | 5.8 |
| 2.0 | 7.9 | 11.2 |
Question: Which statement is supported by the data?
- A. At both temperatures, the rate rose with catalyst mass and was higher at 25°C.
- B. At both temperatures, the rate fell with catalyst mass and was higher at 35°C.
- C. At both temperatures, the rate rose with catalyst mass and was greater at 35°C.
- D. The rate rose with catalyst mass at 25°C but fell at 35°C.
Solution:
- Trend in each column: both columns increase going down, so the rate rose with catalyst mass at both temperatures. That eliminates B and D.
- Which column is higher? In every row, the 35°C value is larger (3.0 > 2.1, 5.8 > 4.0, 11.2 > 7.9). That eliminates A.
Answer: C ✓
Skill: Split a two-part statement into its parts and test each part separately.
</details> <details> <summary><b>Example 2: Absolute versus relative change</b></summary>Data: Grams of three compounds that dissolve in 100 mL of water.
| Compound | At 10°C | At 50°C |
|---|---|---|
| J | 50 | 58 |
| K | 6 | 26 |
| L | 90 | 115 |
Question: Which compound's solubility increased by the greatest number of grams?
Solution:
- Compute each change in grams: J: 58 − 50 = 8 g; K: 26 − 6 = 20 g; L: 115 − 90 = 25 g.
- Largest absolute change: Compound L (25 g).
- Trap: Compound K more than quadrupled, the largest relative change, but the question asks about grams.
Answer: Compound L ✓
</details>Practice: Pacing and Previewing 🎯
Practice: Read the Figure Accurately 📋
Table 1: Researchers measured the average daily water loss from leaves of two plant species at four air temperatures. Species B is a newly described fern.
| Air temperature (°C) | Species A (mL per day) | Species B (mL per day) |
|---|---|---|
| 15 | 40 | 10 |
| 20 | 48 | 14 |
| 25 | 60 | 19 |
| 30 | 72 | 25 |
ACT-Style Practice
Researchers studied a newly described protein, RX, by measuring the percent of RX molecules bound to zinc at different zinc concentrations: 1 µM, 20%; 2 µM, 38%; 4 µM, 61%; 8 µM, 80%; 16 µM, 88%.
Question: A student has never heard of RX. What can she conclude from this information alone, and what can she NOT conclude?
<details> <summary><b>Show answer</b></summary>She can conclude that the percent of RX bound to zinc rose as zinc concentration rose (20% up to 88%), and that the increase slowed at higher concentrations (it was leveling off). She cannot conclude where RX is made in the body or how it compares with other proteins; the passage gives no information about either. Everything a question needs here is in the data, so never having heard of RX costs nothing.
</details>Key Takeaways
- 40 questions, 40 minutes: about a minute per question, roughly 5 to 6 minutes per passage.
- Past your time on a passage? Guess, mark, move on. Never leave a question blank.
- Preview first: the introduction, then each figure's title, axes, units, legend, and trend.
- Unfamiliar terms are just labels; answer from the data, not from facts the passage never gives.
- Watch the traps: absolute vs. relative change, wrong column, units and rates, reversed comparisons, NOT/EXCEPT.
- Split two-part statements and test each part.
Part 6: Conflicting Viewpoints
⚖️ Conflicting Viewpoints
Part 6 of 7 — Comparing Hypotheses, Predictions, Evidence, and Common Ground
What the Passage Looks Like
A Conflicting Viewpoints passage opens with a short introduction describing something that needs explaining, sometimes with a table of facts everyone accepts. Then two or more people explain it differently: "Scientist 1" and "Scientist 2," "Student 1, 2, and 3," or "Hypothesis 1 and 2." Each viewpoint gives a claim, usually a mechanism (how it works), and sometimes a prediction or a piece of evidence.
This passage type has more reading and fewer numbers than the others. The questions test whether you can keep the viewpoints straight and reason about what each one would expect.
Key rule: you are never asked which viewpoint is true in the real world. Answer from what each viewpoint says, even if one of them sounds wrong to you.
A Four-Step Strategy
- Read the introduction closely. It states the facts all viewpoints accept and defines the terms.
- Read Viewpoint 1 and map it in a few words: claim, cause, prediction. If you like, answer the questions that ask only about Viewpoint 1 before reading further.
- Read Viewpoint 2 and map it the same way, then answer its questions.
- Answer the comparison questions last: agree, differ, supports one but not the other.
| Student 1 | Student 2 | |
|---|---|---|
| Claim | Island songbirds declined because of invasive rats | Island songbirds declined because of a drought |
| Mechanism | Rats eat eggs and chicks in the nests | Less rain → fewer insects → chicks starve |
| Predicts | Removing rats lets the birds recover; nests show egg loss | Bird numbers track rainfall; chicks are underweight |
| Shared ground | The bird population fell, and fewer chicks survived to adulthood | (same) |
Question Types and How to Answer Them
| Question asks... | How to answer |
|---|---|
| What does Viewpoint X claim or assume? | Use only X's paragraph |
| Which finding supports X? | The finding matches what X predicts |
| Which finding weakens X? | The finding contradicts what X predicts or claims |
| Supports X but not Y | The finding must fit X and contradict Y (or be something Y's account cannot explain) |
| On which point do X and Y agree? | The statement must appear in, or follow from, both viewpoints |
| On which point do they differ? | The cause or mechanism where they part ways |
| What would X predict for a new situation? | Apply X's mechanism to the new case |
| How many viewpoints are consistent with a result? | Test the result against each viewpoint one at a time |
Finding Common Ground
Viewpoints often share an outcome or a middle step but disagree about the cause. If one hypothesis says a river's salmon declined because a new dam blocks adults from their upstream spawning grounds, and another says warmer river water kills many of the eggs before they hatch, both agree that fewer young salmon are being produced. A detail that appears in only one viewpoint, such as the dam or the warming, is not shared ground.
Judging Evidence
| If a finding... | Then it... |
|---|---|
| matches a prediction only Viewpoint 1 makes | supports 1 more than 2 |
| contradicts a claim of Viewpoint 2 | weakens 2 |
| fits both viewpoints equally (their shared ground) | does not help choose between them |
| concerns something neither viewpoint addresses | is irrelevant to both |
Data Inside Conflicting Viewpoints Passages
Many passages include a table in the introduction. Every viewpoint must be consistent with those shared data, so the data alone often cannot decide between them. The decisive evidence is usually a new finding described in a question. All the data skills from Parts 3 to 5 still apply: read trends carefully, keep to the tested range, and check which variable was changed.
The Most Common Traps
- Swapping viewpoints: choosing a claim that belongs to the other scientist. Recheck your map.
- "Supports both" when only one predicts it: if only one viewpoint expects the result, it favors that one.
- Outside knowledge: picking the viewpoint you believe is true instead of the one the finding supports.
- Partial agreement: a statement that matches one viewpoint and is merely not contradicted by the other is not something they both claim.
ACT Tip: For "supports X but not Y," check both halves. Many wrong choices support X but also fit Y, which makes them useless for telling the viewpoints apart.
Worked Examples
<details> <summary><b>Example 1: Agreement and decisive evidence (two students)</b></summary>Passage: The population of a songbird on a small island fell by half over 10 years.
Student 1: Rats that arrived on supply boats eat the eggs and chicks. The rats are the main cause of the decline.
Student 2: Rainfall on the island has dropped during the 10 years. With less rain, there are fewer insects, so many chicks starve before leaving the nest.
Question 1: Both students would most likely agree that:
- A. rats eat songbird eggs.
- B. fewer chicks have survived to adulthood.
- C. rainfall on the island has decreased.
- D. insects are the birds' main food.
Question 2: Which finding would support Student 1 but NOT Student 2?
- A. The bird population has fallen.
- B. Chicks in the remaining nests weigh less than chicks did 10 years ago.
- C. On a nearby island with no rats but the same drop in rainfall, the songbird population stayed steady.
- D. Rainfall dropped by 30% during the decade.
Solution:
- Q1: Both explanations end with fewer chicks surviving; they differ on why. A belongs only to Student 1; C and D belong only to Student 2. Answer: B
- Q2: Choice C shows the same drought with no rats and no decline, which fits Student 1 and contradicts Student 2. A fits both. B and D support Student 2. Answer: C ✓
Passage: A burning candle is covered with a glass jar and goes out after a few seconds.
Student 1: The flame uses up the oxygen in the jar, and it goes out when no oxygen is left. Student 2: The flame produces carbon dioxide, which builds up until it smothers the flame. Student 3: Heat trapped in the jar makes the wax melt so fast that it floods the wick.
Question: A candle in a jar kept cold in an ice bath went out after the same time as a candle in a room-temperature jar. This result is consistent with which students?
Solution:
- Student 3 says trapped heat puts the flame out, so keeping the jar cold should make the candle last longer. It did not, so the result weakens Student 3.
- Students 1 and 2 blame changes in the gases, which an ice bath would not prevent. The result fits both.
Answer: Students 1 and 2 only ✓
</details>Practice: Two Scientists 🎯
Introduction: On Mirrin Flat, a dry lake bed in a desert valley, stones weighing up to 20 kg sit at the ends of long, shallow trails in the clay, showing that the stones have moved. No one has seen a stone move during a dry period.
Scientist 1: Strong winds alone push the stones. After a heavy rain, the clay surface becomes wet and slick, and gusts above 60 km/h can slide even large stones across it.
Scientist 2: The stones are pushed by ice. After winter rain, a shallow pond covers the flat, and a thin sheet of ice forms on it overnight. When the morning sun breaks the sheet into floating panels, even a light breeze moves the panels, and the panels shove the stones along the wet clay.
Which Viewpoint Does It Support? 🔍
Hypothesis 1: Bees stopped visiting the clover in a meadow because a new pesticide used on nearby farms killed many of the local bees.
Hypothesis 2: Bees stopped visiting the clover because a new sunflower field next to the meadow draws the bees away.
Practice: Three Students and a Data Table 📋
Introduction: When a glass jar is placed over a burning candle, the flame goes out. A class recorded how long a candle burned under jars of different sizes. Each jar started with ordinary air (about 21% oxygen).
| Jar volume (mL) | 250 | 500 | 1,000 |
|---|---|---|---|
| Burn time (s) | 9 | 18 | 37 |
Student 1: The flame goes out when it has used up all the oxygen in the jar. A larger jar holds more oxygen, so the candle burns longer.
Student 2: The flame goes out when the carbon dioxide it produces builds up to a level that smothers it. In a larger jar, that level takes longer to reach.
Student 3: Heat trapped in the jar melts the wax so fast that liquid wax floods the wick. A larger jar warms more slowly, so the candle burns longer.
ACT-Style Practice
Introduction: On clear, calm nights, drops of water (dew) appear on a lawn by morning, but the concrete sidewalk next to it stays dry.
Student 1: The dew comes from inside the grass. At night, grass blades release water through their leaves, and it collects as drops.
Student 2: The dew comes from the air. Thin grass blades cool faster at night than thick concrete does, and water vapor in the air condenses on the coldest surfaces.
Question 1: On the same lawn, a mat of plastic artificial grass, which releases no water, was covered in dew by morning. Which student's explanation does this weaken?
Question 2: On what point do the two students agree?
<details> <summary><b>Show answers</b></summary>- Student 1's. If dew came from inside living grass, a plastic mat that releases no water should stay dry; dew on the mat contradicts that. Student 2's explanation fits, because thin plastic blades can cool quickly too.
- They agree that the dew forms on the grass and not on the sidewalk. That is the observation both are explaining. They disagree about where the water comes from: inside the plant (Student 1) versus water vapor in the air (Student 2).
Key Takeaways
- Read the introduction closely; it holds the facts every viewpoint accepts.
- Map each viewpoint: claim, cause or mechanism, prediction. Keep them separate.
- A finding supports a viewpoint whose prediction it matches and weakens one it contradicts.
- "Supports X but not Y" must fit X and contradict Y; a finding that fits both cannot separate them.
- Agreement means both viewpoints say it, usually a shared outcome with different causes.
- Answer from the viewpoints, never from which one you think is true.
Part 7: Integrated Practice: Mixed Passage Set
🏁 Integrated Practice
Part 7 of 7 — A Mixed Passage Set Under Enhanced ACT Science Timing
The Section in One Table
| Feature | Enhanced ACT Science |
|---|---|
| Status | Optional; scored separately, not part of the composite |
| Length | 40 questions in 40 minutes |
| Answer choices | 4 per question |
| Guessing | No penalty for wrong answers, so answer everything |
| Pace | About 1 minute per question, roughly 5 to 6 minutes per passage |
Recognize the Passage Format in Ten Seconds
| You see... | Format | Questions mostly test | Lesson parts |
|---|---|---|---|
| Tables or graphs with a short introduction, no numbered experiments | Data representation | Lookups, trends, interpolation, comparing series | 3, 4, 5 |
| "Experiment 1," "Study 2," a procedure, then results | Research summary | Variables, controls, design, predictions, combining experiments | 1, 2, 4 |
| "Scientist 1," "Student 2," "Hypothesis 1" | Conflicting viewpoints | Claims, agreement, which evidence supports or weakens which view | 3, 6 |
Designing a Fair Test
Research summaries often ask which design would best test a question, or why researchers included a step.
| Feature of a good design | Why it matters |
|---|---|
| Change only one variable at a time | Any difference can be traced to that variable |
| Hold every other factor constant | Other factors cannot explain the results |
| Include a control (no treatment or standard condition) | Gives a baseline for comparison |
| Repeat trials and average | Reduces the effect of random variation |
| Randomly assign living subjects to groups | Makes groups alike except for the treatment, so a difference can show a cause |
To pick the best design, eliminate any choice that changes two things at once (color and size, treatment and location) or that never changes the variable being tested. To test whether one factor causes another in people or animals, the strongest design randomly assigns the factor rather than surveying people who chose it themselves.
A 40-Minute Game Plan
- Preview each passage for about 30 seconds: introduction, figure titles, axes, units, trends.
- First pass: answer what you can; for a question that stalls you past a minute or so, guess, mark it, and move on.
- Checkpoints: about 10 questions done by minute 10, 20 by minute 20, 30 by minute 30.
- Order is your choice. If Conflicting Viewpoints passages are slow for you, you may save them for later, but don't spend time hunting; move through the booklet or screen efficiently.
- Final two minutes: make sure every question has an answer.
Mixed-Set Checklist
| Question type | Do this |
|---|---|
| Trend | Trace every point: increases, decreases, rises then falls |
| Interpolation | The answer lies between the two neighboring results |
| Extrapolation | Use the typical step; test for linear, inverse, or doubling |
| Variables | Changed on purpose = independent; measured = dependent; same in all trials = controlled |
| Supports / weakens | Turn the claim into a prediction, then compare |
| Viewpoints | Map each one; agreement = stated by both |
| Correlation | A survey shows association, not cause |
ACT Tip: In a mixed set, the skill matters more than the topic. A lake, a protein, and a glacier all reduce to the same few question types once you name them.
Worked Examples
<details> <summary><b>Example 1: Choosing the best experimental design</b></summary>Question: A student wants to test whether the color of a pot affects how warm the soil inside it gets in sunlight. Which design is best?
- A. Pots of different colors and different sizes, each filled with soil and placed in the sun.
- B. Identical pots in different colors, filled with the same soil, placed side by side in the sun.
- C. Identical black pots filled with the same soil, some in sun and some in shade.
- D. Pots of different colors, with the black pot indoors and the others outdoors.
Solution:
- Variable to test: pot color. It must change, and nothing else should.
- A changes size along with color; D changes location along with color. Either extra factor could explain the result.
- C never changes color, so it cannot answer the question.
- B changes only color and holds pot type, soil, and location constant.
Answer: B ✓
</details> <details> <summary><b>Example 2: Testing a cause after a correlation</b></summary>Situation: A researcher finds that students who eat breakfast earn higher morning quiz scores.
Question: Which follow-up study would best test whether eating breakfast causes higher scores?
Solution:
- The original finding is a correlation: students who eat breakfast may differ in sleep, schedules, or other habits.
- Surveying more students, or asking them whether breakfast helps, still measures only an association or an opinion.
- Randomly assigning students to eat or skip breakfast on test days makes the groups alike except for breakfast, so a difference in scores can be traced to it.
Answer: Randomly assign breakfast, then compare scores. ✓
</details>Passage I (Data Representation) 🎯
Suggested time: 4 minutes for 4 questions.
Researchers measured water temperature and dissolved oxygen at several depths in a lake in late summer (Table 1). They also set nets at each depth and counted the fish of two species caught per net (Table 2).
Table 1
| Depth (m) | 0 | 5 | 10 | 15 | 20 |
|---|---|---|---|---|---|
| Water temperature (°C) | 24 | 22 | 12 | 8 | 7 |
| Dissolved oxygen (mg/L) | 8.6 | 8.2 | 5.1 | 3.0 | 2.4 |
Table 2
| Depth (m) | 0 | 5 | 10 | 15 | 20 |
|---|---|---|---|---|---|
| Species P (fish per net) | 14 | 11 | 3 | 0 | 0 |
| Species Q (fish per net) | 2 | 5 | 9 | 6 | 3 |
Passage II (Research Summary) 📋
Suggested time: 5 minutes for 5 questions.
Students studied factors that affect how fast water evaporates. In both experiments, every dish started with 200 mL of water and sat in the same room at 22°C for 48 hours. The volume of water lost was then measured.
Experiment 1: Dishes with different surface areas were used, with no fan.
Experiment 2: Dishes with a surface area of 100 cm² were placed in front of a fan set to different speeds.
Table 1 (Experiment 1)
| Surface area (cm²) | 50 | 100 | 200 | 400 |
|---|---|---|---|---|
| Water lost (mL) | 6 | 12 | 23 | 47 |
Table 2 (Experiment 2)
| Fan setting | Off | Low | High |
|---|---|---|---|
| Water lost (mL) | 12 | 19 | 27 |
Passage III (Conflicting Viewpoints) ⚖️
Suggested time: 4 minutes for 4 questions.
Introduction: Smooth, rounded pebbles of granite are found on top of Harlow Ridge, a hill 150 m above the nearest river. The nearest granite bedrock is 40 km to the north. Two geologists explain how the pebbles got there.
Geologist 1: An ancient river once flowed across this area from the north, before the land was pushed upward. The river carried the granite south and rounded the pebbles by tumbling them along its bed. River deposits form a long, narrow band, and the pebbles in them are sorted into layers by size.
Geologist 2: A glacier moving south carried the granite here. Meltwater streams flowing beneath and in front of the ice rounded the pebbles. Glacial deposits are spread over a wide area, mix pebbles with large boulders in no particular order, and often carry parallel scratches made as the ice dragged them over bedrock.
ACT-Style Practice: Pacing Check
At minute 20 of the Science section, a student has finished 15 questions. She is halfway through a Conflicting Viewpoints passage, and the passage after it is a short data-representation passage.
Question: Is she on pace, and what should she do?
<details> <summary><b>Show answer</b></summary>She is about 5 questions behind the checkpoint of roughly 20 questions by minute 20. She should finish the current passage briskly, guessing and marking any question that takes more than about a minute, then move on to the data-representation passage, where lookup and trend questions go quickly. She should not leave blanks: if she runs short at the end, a guess on every remaining question costs nothing.
</details>Key Takeaways
- Enhanced ACT Science: optional, 40 questions in 40 minutes, 4 choices, not in the composite, no guessing penalty.
- Identify the format fast: data representation, research summary, or conflicting viewpoints, and expect its typical questions.
- A fair test changes one variable, holds the rest constant, includes a control, repeats trials, and randomly assigns living subjects when testing a cause.
- Use checkpoints (about 10 questions per 10 minutes), guess and mark when stuck, and answer every question.
- Name the question type first; the same few skills solve every topic.