Competing hypotheses questions present multiple scientists offering different explanations for the same observation, and your job is to understand each position well enough to compare them. These questions appear in about 25 percent of Science passages and test a specific skill: can you identify what each scientist claims, what evidence supports each claim, where the scientists agree, and where they fundamentally disagree? You do not need to decide who is right. Instead, you need to accurately represent each viewpoint and trace how specific data connects to specific arguments.
Competing hypotheses questions present multiple scientists offering different explanations for the same observation, and your job is to understand each position well enough to compare them. These questions appear in about 25 percent of Science passages and test a specific skill: can you identify what each scientist claims, what evidence supports each claim, where the scientists agree, and where they fundamentally disagree? You do not need to decide who is right. Instead, you need to accurately represent each viewpoint and trace how specific data connects to specific arguments.
These questions appear in roughly 25 percent of Science passages, making them one of the most frequently tested skills. The good news is that once you learn to spot the patterns and apply a systematic approach, these questions become some of the most predictable on the entire test. You do not need any prior science knowledge – just careful analysis and logical thinking.
Competing hypothesis passages present two to four different scientific viewpoints about the same phenomenon. Think of them as scientific debates frozen in time – each viewpoint proposes a different explanation, cites different evidence, and makes different predictions. The passage gives equal time to each perspective without telling you who is right. Your job is to analyze the evidence and arguments like a scientific jury.
About 25 percent of ACT Science questions ask you to connect specific data to the claims it supports or contradicts. A claim is a conclusion a scientist draws — 'temperature increases enzyme activity.' Evidence is the measured data — 'activity rose from 10 to 50 units as temperature climbed from 20 to 37 degrees.' Your job is to determine which evidence best supports, contradicts, or is irrelevant to a given claim. No outside knowledge is needed; the passage provides everything.
These questions appear in every passage type but are especially prominent in conflicting viewpoints passages, where multiple scientists cite different data to support competing conclusions. The skill they test is precise: can you match a specific piece of evidence to the specific claim it addresses, without being distracted by evidence that sounds relevant but belongs to a different argument?
A claim is an interpretive statement — a conclusion, hypothesis, or explanation. Claims use language like 'therefore,' 'suggests,' 'indicates,' 'is caused by,' or 'is the most effective.' They explain WHY something happens or predict what SHOULD happen. Evidence is a factual observation — a number, measurement, trend, or experimental result. Evidence uses specific values like '78 percent retention,' '3.7-fold increase,' or 'maintained above 0.65.' Evidence shows WHAT actually happened.
New findings questions test how fresh evidence affects existing scientific arguments. The ACT presents a set of hypotheses or experimental results, then introduces a new discovery and asks how it changes the picture. Does the new data strengthen one scientist's position? Does it weaken another's? Does it resolve a disagreement or create a new one? These questions appear 8 to 10 times per test, accounting for roughly 20 to 25 percent of the Science section. The skill they test is precise: you must trace how one specific piece of new evidence connects to each existing viewpoint.
These questions appear eight to ten times per test, making them absolutely crucial for your score. They account for roughly 20 to 25 percent of the Science section. The beautiful thing about science is that it evolves constantly – what we knew yesterday might be outdated tomorrow. These questions test whether you can think dynamically about how evidence reshapes our understanding.
Scientific claims compete when they propose different mechanisms for the same phenomenon, make contradictory predictions, prioritize different factors as most important, or suggest incompatible solutions. But not all competing claims are created equal. Some are mutually exclusive – if one is right, the others must be wrong. Others are partially compatible, like pieces of a puzzle that might fit together. Still others are complementary, potentially working in concert.
About 20 percent of ACT Science questions test whether a conclusion actually follows from the data. The passage presents experimental results, and the question asks whether a specific claim is supported — or whether it overstates, misinterprets, or extends beyond what the evidence shows. These questions reward careful, skeptical thinking. A conclusion might sound perfectly reasonable but use the word 'all' when the data tested only three samples, claim causation from correlational data, or predict results far outside the tested range. Your job is to catch these logical overreaches.
Sometimes conclusions sound reasonable but go beyond the evidence. A researcher might claim causation when they only showed correlation, generalize from a tiny sample to an entire population, or predict results far outside the tested range. Invalid conclusions follow five predictable patterns, and once you learn those patterns, you can spot them reliably. This chapter teaches you to apply the VALID method — a five-step framework that catches the most common logical errors in about 30 seconds.
The first and most common type is Overstatement Beyond Data – claiming 'all' when data shows 'some,' or 'always' when data shows 'usually.' These conclusions use absolute language that exceeds the evidence. If three out of four samples showed growth, an overstatement would claim ALL samples ALWAYS grow. Spot these by their love of words like never, always, all, and none.
The conflicting viewpoints passage is the most text-heavy format on the ACT Science test. It presents two to four scientists who disagree about a scientific topic, and the seven questions that follow test whether you can integrate their arguments — finding where they agree, identifying the core dispute, and synthesizing insights across multiple perspectives. This passage appears exactly once per test, but its seven questions make it worth more than any other single passage. The hardest questions ask you to combine ideas from opposing viewpoints, not just understand each one in isolation.
Out of the seven passages on ACT Science, you will face exactly one conflicting viewpoints passage worth seven questions. While other students get stuck choosing sides, you will learn to rise above the debate and see the bigger picture. The hardest questions on this passage type ask you to integrate information across multiple perspectives – finding hidden agreements, pinpointing the exact nature of disagreements, and synthesizing different ideas into new conclusions.
Common Ground questions ask what ALL scientists agree on. They use phrases like 'Both scientists would agree that' or 'All students assume that.' The trick is looking past the arguments to find shared foundations – even scientists who disagree fiercely about solutions may agree on the problem definition, the tools they use, or basic scientific principles.
Every scientific argument rests on assumptions that are never stated out loud. When a scientist concludes that a drug works because patients improved, they are assuming the improvement was not caused by the placebo effect, natural recovery, or seasonal changes. On the ACT Science test, about six questions will test your ability to identify these unstated assumptions, which accounts for roughly 15 percent of your Science score.
Assumption questions follow predictable patterns, and the assumptions themselves fall into five distinct families. Once you learn to recognize the question types by their phrasing and classify the assumption being tested, these questions become systematic rather than mysterious. This chapter teaches you to identify assumption questions by their keywords, classify the five families of hidden assumptions, and apply the UNCOVER method to expose what scientists believe but never explicitly state.
Think of hidden assumptions as five distinct families, each with its own personality and favorite hiding spots. Understanding these families lets you know exactly where to look when a question asks what a scientist is taking for granted.
Every experiment has boundaries, and every set of results can be explained in more than one way. On the ACT Science test, about two to four questions will challenge you to think like a scientific skeptic – finding the holes in experimental designs and imagining what else might explain the data. These questions make up roughly 7 percent of your Science score, but they are often the difference between a good score and a great one.
Unlike other question types that ask what the data shows, limitation and alternative explanation questions ask what the data does not show, or what else could account for the observed results. This requires a different mode of thinking: instead of absorbing information, you are actively questioning it. Think of yourself as a thoughtful critic rather than a passive reader.
Experimental Design Limitations are the most fundamental. Every experiment has boundaries set by the researcher's choices: how many subjects to test, how long to observe, what conditions to create. A study testing osmosis with five salt concentrations over 30 minutes has built-in limits on what it can reveal about the full range of concentrations or long-term effects.
Scientists are never done. Every experiment raises new questions, and every design has room for improvement. On the ACT Science test, about four to five questions will ask you to think like a researcher who is always wondering: how could we make this better? These improvement questions make up roughly 10 percent of your Science score, and the great news is that they follow predictable patterns.
Unlike questions that ask you to interpret data, improvement questions require you to evaluate the experimental design itself. You need to identify what is missing, what could be more precise, and what the next logical step in the research would be. The key principle is straightforward: good improvements address specific weaknesses in the current design without introducing new problems.
The first and most common category is Control Variables Better, which appears in about 28 percent of improvement questions. This means adding control groups, eliminating confounding variables, or standardizing conditions. If an experiment tests plant growth with different fertilizers but does not control for light exposure, adding a light-controlled environment is an improvement that eliminates a confounding variable.
Model prediction questions give you a scientific model — a graph, equation, table, or set of rules — and ask you to apply it to a new situation. If a model shows how pressure affects volume, the question might ask you to predict the volume at a pressure the model did not directly test. These questions appear about 8 to 10 times per test and reward students who can systematically read a model's rules and apply them step by step. No specialized science knowledge is needed; the model itself contains all the information. The challenge is reading the model precisely and resisting the urge to bring in outside assumptions.
The exciting part is that you do not need specialized scientific knowledge to ace these questions. Models provide all the information you need. Whether it is predicting where a graph line continues, determining what happens when you change a variable, or deciding which scientist's hypothesis best explains future results, you just need to understand relationships and apply them consistently.
If/Then Predictions are the most straightforward. The question presents a condition and asks for the consequence: 'If temperature increases by 10 degrees C, then the reaction rate will...' The model provides the relationship, and your job is to apply it to the new condition. These make up about 28 percent of prediction questions.