I love teaching freshmen. I get excited by the opportunity to help new students navigate the unexpected characteristics of their new institution. I also get to introduce them to that institution’s approach to writing, which is often different from their previous school’s expectations. But most importantly, I love teaching students the reasons behind norms and expectations in our institution or in my field. When I taught ninth grade, I helped my students understand how a thesis statement worked and what did. We worked with a plot line until they understood what holds a story together. We diagrammed sentences (judge me if you wish) so they could see the logic behind sentence construction. Everything was designed to get them ready for what they’d have to do later.
My current school, the second-largest university in the nation by student population, presents an interesting challenge: we use a distinctive writing curriculum that differs significantly from both what is taught in most high schools and what is included on AP English exams. Students come to our classes and almost feel mentally blind-sided, especially if they took high-school courses billed as “college-prep” only to feel completely unprepared for the content of our writing program. To be fair, those college-prep courses generally help develop a greater sense of academic determination, which shouldn’t be discounted, but students focus on the easier-to-define curriculum.
The second semester of our first-year composition courses introduces students to academic research. Two major problems here: 1) different academic fields do research differently, and 2) what is called “research” in high schools is generally only half the process in college. Students need to re-calibrate their terms when they get to us, and they likely have to re-calibrate their methods when they go on to take classes in their majors. We end up facing a challenge of translation on the way in and one of compatibility on the way out. Teaching basic research in first-year composition courses requires us to help our students understand what we mean by research at the college level in a sense that is both specific enough to be actionable and general enough to transfer to each student’s major. That’s tough.
This past week, I have held individual conferences with my students, who are each beginning secondary research on a topic of their choosing. So far, they are comfortable with the research process because secondary research (finding out what other people have already said about the issue in question) is basically the only kind of action they have associated with the word research before. For now, the work of research feels familiar. But they each know that, in a few weeks, I’m going to ask them to do primary research—go into the field and learn something new that no one has ever learned before—even if that simply amounts to discovering whether an existing claim applies to their group of friends. I know of very few secondary-education classes that expect students to gather original data under the guise of creating new knowledge. It’s a significant component of the course, and an empowering expectation for students.
In effect, in a few weeks, my students will each be doing a small composition-style study. Except, as I’ve learned recently, they don’t necessarily call it that. When my students talk about their opportunity to collect new data, many use the word experiment. They say they’re going to do an experiment to learn more about their issue, and they say they’re looking for experimental results in the secondary research they collect. But this is a composition class, and people in composition generally don’t do actual experiments. We do studies. The difference is a rather significant one, and it completely changes not just how the research is done but also what the research will show. But the difference stems, as so many differences do, from the distinctions between word meanings in different contexts.
Let’s look more carefully at three important words—all nouns—to establish the context of what students do to learn more about an issue: research, experiment, and study.
As a general term, research refers to a process of curiosity and discovery leading to new knowledge. It starts with someone wondering about something, and it involves some action that clarifies or resolves the curiosity. Research of different kinds can help us find answers to each of these questions:
- How many cars pass through the major intersection near my house during rush hour?
- How does temperature affect the growth rate of yeast?
- What do people expect from the news they get from different sources?
- Why did the U.S. government shut down on October 1?
Each of these questions can be addressed (note I didn’t say “answered”…more on that in a minute) with research, but each requires a different kind of research and leads to a different kind of result. Matching the process to the question, and understanding the limitations and strengths of the potential results, is critical to doing effective research.
Researchers conduct experiments when they establish a predictable testing environment, create a control group, and measure the results. Experiments often involve changing only one variable to limit the factors that could lead to different outcomes. Students in high school conduct experiments in their science labs to see how chemicals react under different situations. Whether those experiments count as research may be debatable, as most class labs expect students to work to achieve very predictable results (which may or may not count as the new knowledge I said is a critical part of research). These experiments often follow thinking that asks, “If I do this, will it cause that to happen?” Experiments will not show us what people think or feel about something.
Such questions are very common in the physical and biological sciences and very rare in the humanities. Because experiments require a predictable, consistent testing environment, and because they’re clearest when all conditions are equal for all test subjects (be they mice or molecules), it’s difficult getting people in those situations. Experiences, knowledge, and mood can significantly change how people think and react. Good experiment design with human subjects can still happen, though. Two of my favorite examples include 1) an experiment about memory and cognitive load
involving a choice between fruit salad or chocolate cake and 2) a tremendously controversial inquiry into obedience called the Milgrim Experiments—experiments that uncovered striking and conflicting details about human behavior, left many of its participants feeling deeply uncomfortable, and changed the rules researchers have to follow when experimenting on humans.
While experiment has a fairly specific meaning, the word study is more general, often applying to any kind of research. These can include observations or detailed looks into how specific people think about a situation. For instance, if I survey people to see whether they like Coke or Pepsi better, then interview a couple people to see if they know why, I’m doing a study. I’m using methods to gain new understanding, but I’m not setting up predictable conditions or doing anything that’s reproducible or testing a hypothesis. They won’t show the effect of a variable, but they can show how people think or feel about something. It’s not an experiment, but I can still learn very interesting or valuable information.
In composition research, we rely on studies. Writing is so personal, so flexible, and so different every time we do it, that an experiment would be inappropriate. We can’t constrain writing to see how one variable affects it. But we can see how it works for different people in different circumstances and try and understand what’s happening. In composition, we use case studies to see how a small number of people function in a situation, we use ethnographic studies to see how a group of people behaves, we use observations to understand the environments in which people write, and we sometimes ask people to talk out loud while they write in an effort to “see under the hood”, if you’ll forgive the metaphor.
My Example Questions
So let’s take another look at those examples I presented above. Each one requires a different kind of research, and each will illuminate a different kind of knowledge.
How many cars pass through the major intersection near my house during rush hour?
This question needs a straightforward, numerical answer. It’s simply a measurement, not an experiment. Devices can be placed on or beside a road to count vehicles, or a researcher could sit nearby with a pencil, making tick marks on a piece of paper. Regardless of the technology used to gather the data, this is primary research (learning something new directly from the situation) but not an experiment. It is data collection, probably part of a larger research project.
How does temperature affect the growth rate of yeast?
I remember trying to answer this question when I was in grade school. My house smelled like dough for several days. In this case, the answer requires changing one condition (temperature) when other conditions (time, amount of yeast and nutrients, light, etc.) remain controlled. It is an experiment, plain and simple. If I change the temperature, what result should I expect? I record the measurements, perhaps of the volume of carbon dioxide given off by the yeast, and I report my findings.
What do people expect from the news they get from different sources?
Unlike the first two questions, this one is neither measurable nor straightforward. The answer to this question (and the methods used to get to that answer) are very messy. This will involve a study, in which I ask people—likely through interviews, but perhaps through satisfaction surveys—what they think about their news. There’s no cause/effect relationship here, and nothing I could prove, but the results would still be useful. I would better understand the goals and needs of mass media news outlets, and I’d probably better understand people and social media at the same time. My methods could be reproduced—anyone else could ask the same interview questions of groups of people—but the results would be different each time.
Why did the U.S. government shut down on October 1?
I promise not to get political here. But this question involves secondary research, but neither a study nor an experiment. To answer this question, I would need to collect information from various sources, and I would have to very carefully attend to the biases that so many people bring to such an issue. Like the study in the paragraph above, this research would get messy: I would need a lot of sources, those sources would disagree, and I would have to sort through them to understand what actually happened. But I could create a solid explanation and document where the information came from that helped me reach my conclusion.
A Note About “Proof”
You might have noticed I never talked about proving anything. I intentionally avoided discussions of proof because they’re generally inappropriate for research. (Starting research by hoping to prove something you already believe is often called “confirmation bias” and is seen as a very bad thing in academic circles.) Remember that research is a process of discovery leading to new knowledge—distinctly different from working to prove what is already believed. Notice that none of my example questions was based on an expectation or a one-sided view of a situation. The question about yeast got the closest by suggesting that there is indeed a connection between temperature and yeast growth, but by asking “how does it affect…,” I leave open the possibility that my answer may be, “It doesn’t.”
When conducting research, researchers want to learn more. If a researcher’s initial suspicions are supported through findings, great. That means the original thinking might be on the right track. But researchers must always look for other explanations, other situations, and other avenues of investigation to help better understand how our world works. That’s what makes research so fascinating.
Go learn stuff.