Intro to Science Question Types

Kristin Fracchia
Lesson by Kristin Fracchia
Magoosh Expert
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In this Magoosh ACT science lesson, we are gonna take a look at the different types of questions you're going to encounter on the ACT science test. Now, most students blow through the ACT science section answering question after question without really having any idea that there are distinct categories of question types that all of these questions fall into. Now, although this generally works out okay for most people, if you're serious about prepping for the ACT science test it can be really useful to know what these question type categories are so that you have a better idea of what the ACT is testing and what the test makers are looking for you to be able to do.

As you practice more and more you will also get better at identifying what types of questions you are good at and which cause you a little bit of trouble and you can make smarter decisions about what to tackle and what to skip. All right, so here they are. There are my five categories for the question types that you are going to encounter on this test.

These are not official categories or titles and other prep resources might use different names but these are really the five categories that do exist or whatever you choose to call them. I'm choosing to call them what's on your screen because after years of working with students on the ACT this is what seems to make sense. Detail questions, pattern questions, inference questions, scientific method questions and finally, compare and contrast questions.

The ACT doesn't tell you this but if you know anything about the ACT you know that it's a very repetitive test. And these are question types that you will see over and over again. Now, I know what you see on your screen might not mean much to you yet, but don't worry, I'm going to go through each of these in more specific detail in just a moment.

This is just to give you an overall sense of what you're in for. Every question on ACT can be grouped into one of these five categories. Okay, first of all, detail questions. Detail questions ask you to locate and report back on a specific datapoint from a graph, a chart, a table, a diagram, or sometimes text in a passage. For the most part, they're pretty straightforward.

These questions are just about finding the right information. If there's any trick to them at all, it's usually making sure that you are looking in the right place. Often the ACT will give you multiple figures or graphs with the same labels on the horizontal and vertical axes, but different variables or different situations being tested or there might be similar numbers in the data and so on.

When I see students miss these detail questions, the most common reason is because they didn't look in the right place or they weren't careful in following a line on the graph to a particular plane. So, the number one rule in these questions is to double check that you are looking in the right place to find your answer. Okay, so here is an example.

Let's start with this really simple chart for illustrative purposes, even though most of what you see on the ACT is going to look a little bit more complex than this. A detailed question might ask you to report to the approximate growth of plant 3 between 60 days and 90 days, for example. Which, in this case all you need to do is find the height at 60 days, 10.1 and the height at 90 days, 12.3.

So we can tell that the change in height is 2.2 inches or, since ACT more often asks for approximate values you'd probably see about 2 inches in your answer choices. However, particularly, on a more complex table, it would be really easy to make a mistake and accidentally look at the height change for plant two or plant three.

So the number one rule again? Make sure you're looking at the right column or the right line on a line graph. Here's a couple other questions that would be detail questions, just to give you a couple more examples. The highest monthly average air temperature recorded during the first six months of the study was or, according to scientist one, compared to burning biomass, burning coal creates less of which of the following?

Now, in these cases you would simply be looking up information in the data to find an answer without having to make any leaps or inferring anything. The next question type are pattern questions. Pattern questions ask you to do a little more than just find a data point or a detail in the information. They ask you to predict a trend or a relationship amongst the given data points.

You generally solve these problems by doing what's called interpolating, which is finding a point between existing data points, or what's called extrapolating. Following a trend beyond the existing data. You don't need to know these terms, and it's easier than it sounds. So, let's look at an example. Okay, here is our sample chart from our detail question example as well as a simple line graph of the same data.

If we are interpolating on this chart or graph, we are going to make predictions, perhaps about how tall a plant is going to be between the data points that we have. So, let's say for example, we have a question that asks us how tall would Plant 2 be at 45 days given constant growth between 30 days and 60 days? So our answer, if we're looking at the chart, is going to be somewhere in here. And if we're looking at the graph, make sure we're looking at Plant 2, in 30 days and 60 days, we're looking for what would be right here.

So, we can guess that the answer is likely gonna be somewhere between 6.2 and 6.8, and we can determine this from either graph. Sometimes, a question will ask us to extrapolate data, so, which means to follow it beyond existing trends. So, maybe a questions wants us to predict how tall plant 3 would be after 120 days given constant growth.

We can follow this line graph here to where 120 days would be, which would be somewhere out here. And we're looking for the right plant. Let's make sure we're looking at plant three which is this one with the triangles. so it would be somewhere out here.

So if we look at our vertical axis we can guess that maybe it might be somewhere around 14 inches if there was constant growth at 120 days. Now note, I'm keeping these examples really simple, just to illustrate, obviously there quite a few things that can influence plant growth and the ACT understands this. So, often you'll see it give you a range of values, but you don't need to get caught up in the details in a question like this.

The answer is always found simply by following the pattern of data and extending it off the chart like we've done here. The third category, inference questions. Inference questions ask you to draw conclusions from the data and the information provided. Sometimes you'll have to take information from a couple different experiments or studies and sometimes you'll have to determine how new information would affect the given experiment.

So for example, figuring out what would happen if students conducting an experiment decided to alter one of the variables in the experiment. So maybe they're testing friction by sliding a brick across the table. An inference question might ask, what would happen if they change the texture of the brick on the surface against the table? Don't worry.

In most cases, all the information you need to solve this problem is going to be given to you, but there isn't going to be any one piece of data that you can point to for the answer, and you're gonna have to draw some conclusions or inferences. Here's a couple examples of what inference questions might look like on the test. Sample one, how would the results of Experiment 1 be affected, if at all, if the syringe contents were adjusted to decrease the concentration of magnesium hydroxide?

Or, scientist 2 would most likely state that the concentration of calcium carbonates in the North Pacific rim would increase if. So, let's imagine that the passage told us that calcium carbonates are found in seashells. If we're making an inference, maybe the answer might be something having to do with the particular tide patterns that would result in accumulation of shells in the rim, thereby increasing the number of calcium carbonates.

So, as you can kind of see, on a question like this, we're going to be applying data and information from the passage. And that's what can make these questions a little bit harder than our detail and our inference questions. The fourth question type is the scientific method questions. You'll likely only see a few of these questions on the test, but they will be there.

These questions ask you to consider how experiments are designed or set up, how experimenters interpret data, how hypotheses are tested. Basically anything involved in conducting good science. So, here are a couple examples. Which of the following was an independent variable in experiment one? Or, which of the following statements best explains why in experiment two the experimenter waited five minutes before testing the temperature of the water.

You can see that you need to know a little bit of information about how science experiments are conducted. Such as knowing what an independent variable is, or a dependent variable for example. But most of what you're going to be using on these types of questions is some good common sense.

These questions are going to ask you to visualize the situation and think about high, how and why scientists or students in a science class would do something a certain way. Finally, we have the compare and contrast questions. These questions appear only on the conflicting viewpoints passage, the passage that will ask you to compare and contrast two or more different scientific opinions on a situation.

These questions ask you to compare various aspects of opposing arguments, such as how one student might feel about another's argument. Or, it might introduce additional variables and ask how they would affect the arguments presented. So here are some examples again. Scientist 2, scientist 2's views differ from Scientist 1's views in that only Scientist 2 believes that solar energy can be more effectively harnessed by.

Or, both scientists would most likely agree that the increase in radiation levels were due to, or if it determine that the asteroid broke apart prior to entering the planet's atmosphere, how would this affect the arguments of both scientists? So you can see we are comparing arguments to each other or against new information that's introduced.

Like inference questions, these questions require us to make some logical leaps, so they often tend to be a bit harder. Okay. So, now that you have those five question types, let's talk about why this all matters. Knowing the question types can help you save some time and some mental energy because you will have a better idea of what your process should be going into these questions.

If you see a pattern question, you might know that you need to be tracing a line graph off the chart for example. An inference question might clue you into the fact that you need to read some background information in the passage before a chart or graph in order to draw some appropriate conclusions. You may have guessed, based on what I've been saying, that some questions types tend to be easier and faster than others.

Although you can't say that all detail questions are necessarily easier or faster than all inference questions. I think you can roughly fit them into this order that you see on this arrow here. If you feel that you are weaker on the science section, or if you're running out of time, knowing how to identify the detail questions, the questions that you can answer more easily and more quickly rather than the harder, more time confusing inference questions can really help you out and pick up some more points.

In addition, I think that simply knowing what to expect, and knowing that there is some method to the madness here, can help you become more comfortable with this test. Feeling like you know it from the inside out can be really empowering and make the ACT science section seem a lot less intimidating.

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