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The ACT science section is optional on national registrations and does not affect your composite score. If you are deciding whether to take it, read Should You Take ACT Science? first. This article is a skill lesson: read the tables, answer the questions, and review the rationales.
What ACT science actually tests
ACT describes the section as a test of interpretation, analysis, evaluation, reasoning, and problem solving. In plain language, that means you will read short passages with tables, graphs, or experimental summaries and answer questions about them.
The three skills that show up again and again are:
- Data interpretation: read values, compare numbers, and identify trends from tables and graphs.
- Experimental design: identify variables, controls, and what a result supports or weakens.
- Evaluating competing explanations: read two or more viewpoints and decide which evidence supports or contradicts each one.
No question on the real ACT requires science facts you learned in school. If a term appears, the passage either defines it or gives you enough context to answer without knowing it in advance. Science is optional and does not affect your composite score; ACT reports a STEM score only if you take the science section.
Reading graphs and tables fast
Most ACT science tables have row labels, column headers, and units. Your first move is not to memorize the numbers; it is to note what each axis or column measures and in what units. Then treat each question as a lookup task: find the right row and column, read the value, and compare it to the answer choices.
For trend questions, trace one variable as the other increases. Ask: when X goes up, does Y go up, go down, or stay about the same? The relationship may be nearly linear, but it does not have to be perfect. Pick the description that matches the overall pattern in the data.
Understanding an experiment's design
An experiment changes one or more variables and measures an outcome. The variable the researcher deliberately changes is the independent variable. The outcome measured is the dependent variable. A control condition is a baseline used to check that the effect being measured comes from the variables being tested, not from the setup itself.
When an experiment has two independent variables, look at one variable at a time while holding the other constant. That is how you isolate cause and effect in a table.
Conflicting-viewpoints passages
In a conflicting-viewpoints passage, two people offer different explanations for the same observation. Your job is to keep the two arguments straight. Before answering, note each person's main claim and the evidence they would predict. Then test each answer choice against those predictions.
Wrong answers often sound like science vocabulary but contradict the passage, or they support the other scientist's view. Always tie your choice back to the specific viewpoint in the passage.
Practice set
The three original data sets below are invented for practice. Answer all eight questions before checking the rationales.
Data Set 1: Ball rolling down a sloped tunnel
A student rolls the same ball down tunnels built at different heights and with different surface materials. She releases the ball from rest and measures the time it takes to roll 100 cm.
| Trial | Drop height (cm) | Surface material | Time to roll 100 cm (s) |
|---|---|---|---|
| Control | 0 | smooth plastic | no roll |
| 1 | 10 | smooth plastic | 4.8 |
| 2 | 10 | rough sandpaper | 6.2 |
| 3 | 10 | carpet | 8.5 |
| 4 | 30 | smooth plastic | 2.5 |
| 5 | 30 | rough sandpaper | 3.4 |
| 6 | 30 | carpet | 4.7 |
| 7 | 50 | smooth plastic | 1.7 |
| 8 | 50 | rough sandpaper | 2.3 |
| 9 | 50 | carpet | 3.1 |
Question 1. In this experiment, which two variables were deliberately changed?
- A. ball mass and tunnel length
- B. drop height and surface material
- C. rolling time and drop height
- D. surface material and ball mass
Answer: B. The table shows three drop heights (0, 10, 30, and 50 cm) and three surface materials (smooth plastic, rough sandpaper, carpet). Those are the two independent variables. A is wrong because the ball and tunnel length are kept the same. C is wrong because rolling time is the measured outcome, not a variable the student changed. D is wrong because ball mass is unchanged.
Question 2. According to Table 1, about how many seconds did the ball take to roll 100 cm on carpet with a 30-cm drop?
- A. 2.5 s
- B. 3.4 s
- C. 4.7 s
- D. 8.5 s
Answer: C. Find the row with 30-cm drop and carpet: Trial 6 shows 4.7 s. A is the time for smooth plastic at 30 cm. B is rough sandpaper at 30 cm. D is carpet at 10 cm.
Question 3. Based on Table 1, as drop height increased from 10 cm to 50 cm, the time to roll 100 cm generally:
- A. increased only when the surface was carpet.
- B. decreased for all three surface materials.
- C. stayed the same for all three surface materials.
- D. increased for smooth plastic but decreased for carpet.
Answer: B. For every surface, the times drop as height increases: smooth plastic goes 4.8 → 2.5 → 1.7; rough sandpaper goes 6.2 → 3.4 → 2.3; carpet goes 8.5 → 4.7 → 3.1. A and C contradict the data. D reverses the actual pattern.
Question 4. What was the purpose of the control trial on a level surface (0-cm drop)?
- A. to find the fastest surface material
- B. to show that the ball does not roll without a slope
- C. to compare carpet to smooth plastic directly
- D. to measure the effect of drop height on rolling time
Answer: B. The control trial has no drop height, so the ball does not roll. Its purpose is to establish that any movement in the other trials is caused by the slope, not by the ball or the track. A, C, and D all describe comparisons that require drop height to be greater than zero.
Data Set 2: Soil moisture sensor calibration
A student calibrates a soil moisture sensor by measuring the sensor voltage at known moisture percentages.
| Sensor voltage (V) | Soil moisture (%) |
|---|---|
| 0.5 | 10 |
| 1.0 | 22 |
| 1.5 | 35 |
| 2.0 | 48 |
| 2.5 | 60 |
| 3.0 | 75 |
Question 5. According to Table 2, what soil moisture percentage corresponds to a sensor reading of 2.0 V?
- A. 22%
- B. 35%
- C. 48%
- D. 60%
Answer: C. The row for 2.0 V shows 48% soil moisture. A is the value for 1.0 V, B is for 1.5 V, and D is for 2.5 V.
Question 6. Based on Table 2, which statement best describes the relationship between sensor voltage and soil moisture?
- A. As voltage increases, soil moisture decreases.
- B. As voltage increases, soil moisture increases.
- C. Soil moisture is highest at the lowest voltage.
- D. There is no clear relationship between voltage and soil moisture.
Answer: B. Moisture rises from 10% at 0.5 V to 75% at 3.0 V, so the overall trend is increasing. A and C describe the opposite trend. D ignores the clear upward pattern.
Question 7. A sensor in a garden reads 2.25 V. Based on the trend in Table 2, the soil moisture percentage is most likely closest to:
- A. 35%
- B. 48%
- C. 54%
- D. 75%
Answer: C. A reading of 2.25 V falls halfway between 2.0 V (48%) and 2.5 V (60%). The midpoint is 54%, which matches the increasing trend. A is too low, B is the value at 2.0 V, and D is the value at 3.0 V.
Data Set 3: Conflicting viewpoints on summer algae
Lake Vega has more algae in summer than in winter. Two scientists offer different explanations.
Scientist 1: Algae growth in Lake Vega is limited mainly by sunlight. In summer, days are longer and sunlight is stronger, so algae grow more. Temperature plays only a small role because the lake already stays warm enough for growth.
Scientist 2: Algae growth in Lake Vega is limited mainly by water temperature. In summer, the water is warmer, so algae grow faster. Sunlight changes are less important because even in winter the lake receives enough light for growth.
Question 8. Which finding, if true, would most support Scientist 2's viewpoint?
- A. Lake Beta receives more summer sunlight than Lake Vega but has cooler water and fewer algae.
- B. Lake Delta has the same water temperature as Lake Vega but receives less sunlight and has fewer algae.
- C. Lake Gamma has warmer water and more sunlight than Lake Vega and also has more algae.
- D. Lake Epsilon receives the same amount of sunlight as Lake Vega and has the same algae count even though its water is cooler.
Answer: A. Scientist 2 claims temperature, not sunlight, is the main factor. Lake Beta has more sunlight — which Scientist 1 would predict should produce more algae — but it has fewer algae because its water is cooler. That pattern points to temperature. B supports Scientist 1 because lower sunlight matches fewer algae. C supports both scientists because both variables differ. D weakens Scientist 2 because cooler water does not lead to fewer algae.
Question 9. Which prediction follows from Scientist 1's viewpoint?
- A. If summer sunlight on Lake Vega were reduced while water temperature stayed the same, algae growth would decrease.
- B. If summer water temperature in Lake Vega were increased while sunlight stayed the same, algae growth would decrease.
- C. Algae growth would be the same in winter and summer if water temperature were held constant.
- D. Warmer water alone would cause algae growth to decrease.
Answer: A. Scientist 1 says sunlight is the main limit, so less sunlight should mean less growth. B contradicts Scientist 1; it would fit Scientist 2. C is wrong because Scientist 1 would still expect more algae in summer due to longer days. D is not a prediction Scientist 1 would make.
After finishing, review any question where your reasoning did not match the rationale. The goal is not to learn science facts but to build a repeatable habit: read the labels, find the evidence, and check every answer against the passage or table.
How to fit this into your ACT prep
Use this practice set as a quick skills check, not a full-length section. For a timed rehearsal, use one of the official enhanced-format practice tests from ACT with its matching scoring key. For section pacing and a full study calendar, see the ACT study plan. The broader format and scoring rules are covered in the Enhanced ACT guide.
All facts in this article were verified against ACT's official publications on October 1–2, 2026.
References
- [1] ACT, Inc. (2026). The ACT Test — Test Overview. act.org. act.org
- [2] ACT, Inc. (2026). Design Framework for the ACT Enhancements (R2519). act.org. act.org
- [3] ACT, Inc. (2026). Free ACT Practice Tests and Test Prep. act.org. act.org
- [4] ACT, Inc. (2026). ACT Science Test Information. act.org. act.org
Frequently asked questions
No. ACT science tests how well you interpret data, read experiments, and evaluate competing explanations. Any specialized term you need is defined or given enough context in the passage.
The section has 40 questions in 40 minutes. Of those, 34 are scored and 6 are unscored field-test items you cannot identify, so answer every question.
Yes for national test-takers, and it does not affect your composite score. For school-day testing, whether science is included is decided by your school or district's contract with ACT. See <a href="/blog/act-science-optional">Should You Take ACT Science?</a> for a decision checklist.
Quick gains usually come from two changes: reading the table labels and units before the questions, and skipping passages that look dense until you know what the question is asking. Last-minute improvement depends on your starting point and the quality of your review.
Practice under the real 40-minute limit so you learn your natural pace. If you are behind, look for the easiest questions first — read-off and trend questions are usually faster than conflicting-viewpoints questions — and make sure you answer every question, since there is no penalty for guessing.
ACT publishes free enhanced-format practice tests with matching scoring keys on its test-preparation site. Use those for full-length timed practice and use this article for targeted skill review.
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