LER312:

Overview

This lesson is designed to teach you about the process of developing a research topic and hypothesis, including how to properly describe variables and relationships among variables.

Reading Assignment

• See your Course Schedule in the Syllabus

Key Terms and Concepts

• Research
• Hypotheses
• Variables
• Independent Variable (IV)
• Dependent Variable (DV)
• Scientific thinking

Activity

• Complete the Quiz 1: Critiquing an Article.

Coming Up with Research Topics (Part 1)

When you're developing a research hypothesis, or even just figuring out what it is you want to study, there are some main, basic things of which to be aware. To be perfectly and honestly simple, though, the best way to decide what you want to study is to look at the world around you and, through that observation, figure out what is the most important and interesting research question. A big part of this, though, is to also understand that the scope and depth of your question must always be limited to what you can actually do. That is, you may want to understand why people do what they do. This question, though, is incredibly broad. One might make the case that this question is the root of all of behavioral science, and so you must narrow your objective to something manageable. This process is one that comes naturally to some, but do not feel discouraged if a research question doesn't immediately come to mind.

Observing the world, in this context, includes a lot of different ways of thinking about research and hypotheses. For one, there is the simple, firsthand observation of your own life events. As this is a course in labor and human resources research, you may find that observing your own workplace may be a great way to inform your research ideas. Just looking around at work, do you notice certain things that may be useful to study through scientific research? Suppose your workplace offers one long break, but you think people would work better with a series of short breaks divided throughout the day. This is an empirical question, one that could be assessed with the scientific method.

Another great source for research ideas is your old coursework. If you took a class in something that was of particular interest to you, perhaps you can dig into a specific aspect of that course for your own scientific study. If there was a nagging question in one of your courses, one that had you scratching your head and saying, "yeah, but what if...?" this can be a great source for you to find your own, new and unique research topic. In this same vein, sometimes just reading your old textbooks, notes, and other materials may be a good way to come up with a research topic. If you have library resources available to you, you can try to find books about the topic that may give you a good, broad introduction. In the field of science, we also have scientific journals that can be excellent resources for your research. These journals are peer-reviewed, which means that someone did a study of some kind and then submitted it to the publication. This publication then found peers of the author -- other people in the field -- and asked them if they thought the article was good enough to publish. In this way, each journal sets a standard for publication, so that the work that makes it to the press has at least been through some level of informed review. These journal articles are often very specific, which can be both a blessing and a curse. If you don't have a lot of background in the topic, a journal article may be difficult to understand, but if you do have enough understanding in the topic, these articles can provide a direct resource toward understanding the phenomena of interest.

Another great way to come up with research topics is by simply talking to people. Yes, this is a step that can be done over a cup of coffee or other beverage, over lunch, or in a more formal meeting. Your coworkers, family members, friends, mentors, and professors can be a great place to start talking about research ideas. Suppose you have a very rough idea of what you want to study, and you sit down with a coworker and describe it to them. They may say that this makes them think of something slightly more specific, which may then remind you of something you learned in a prior course. You would be amazed how quickly these ideas can form and develop, when you have someone to bounce the ideas off of!

Coming Up with Research Topics (Part 2)

Sometimes, rather than starting from scratch with a brand new question and method, you can look at work that other researchers have done and then extend or change that work in your own research. Perhaps the original study only examined members of the white-collar workforce -- in this case, you could do the same study but with a blue-collar workforce. Perhaps a prior study examined productivity in terms of profits, but you think that productivity would be better measured by the amount of actual work achieved. Sometimes, too, new technology can permit a more complete view of behavior. For example, with the advent of social networking websites, it may be possible to document social behavior in a way previously not possible.

Issac Newton once said, "If I have seen a little farther, it is by standing on the shoulders of giants." What he meant by this statement is that he was able to achieve much of what he did because he benefited from the discoveries and achievements of previous thinkers. You may benefit in this same way by reading prior research and studying the work of other scientists. Since you are Penn State students studying online, you may or may not be within a reasonable distance of a Penn State library. If you are fortunate enough to be near a university library, I recommend looking in their computerized catalog for books related to your topic. Still, many college and university libraries are more than adequate for your purposes, and perhaps other libraries as well, so go ahead and do some searches for books about your topic.

On the other hand, as students of Penn State, you benefit from being able to access an enormous number of scholarly journals and publications. We will have an exercise on how to do this search, but if you want to check it out, go ahead and look for the library page on the Penn State website. When you find an article that you might want to read, it will often (if not always) be accompanied by a brief summary called an abstract. This concise summary will give you a rough idea of what the article is about, so you can decide if you want to read the actual article. In no way should the abstract be treated as a substitute for reading the article, but it is a useful tool to help decide which articles you actually want and need to read.

A very useful way to find articles is to find one article about your topic, then look at the references section of that article. Each article will typically reference at least ten other articles that are relevant to its topic, and as such you may be able to quickly find a large number of good articles for your topic. Additionally, most article search engines allow you to look at who else has cited a given article, so you can look both at what those authors cited (their references) and who has cited them.

I'd like to revisit the idea of talking to professors and instructors about your research ideas. This can be a delicate matter, as professors and instructors can be extremely busy people. Professors also make their living by being really good at thinking and coming up with ideas, so when you go to bounce ideas off of them or to help develop your own ideas, you're essentially asking them to do for free what they should be getting paid to do. As such, it is extremely important that you not expect professors to do all of your thinking for you. You should do a lot of reading and thinking before you meet with a professor or instructor about your research ideas, and then your meeting or discussion with that professor will only be about refining and perfecting your ideas, rather than about brainstorming and getting new ideas.

You need have no such anxieties, though, about meeting with fellow students and friends about your research ideas. Feel free to brainstorm with friends and peers, as long as they are willing to do so, and you may find that this experience is both rewarding and enjoyable. One extremely useful thing about discussing research and research ideas with your peers is the simplification of your language and ideas. When you talk to a professor or colleague about your work, you may be tempted to use bigger words and ideas than you would use when talking to someone who doesn't know about your field. If you can describe your ideas in simple language to someone who doesn't know about it, you can be pretty certain that you yourself actually understand that idea pretty well.

Formalizing Ideas into Hypotheses

A brief discussion of what scientific ideas are and how they are organized is in order at this point, as we will be beginning discussion of how to turn research questions into actual hypotheses. When it comes to scientific ideas, there is a hierarchy of laws, theories, and hypotheses. These categories are not the sort of thing that come from a central authority, and there can be a great deal of overlap between them, but they generally come from common use. That is, if a scientific principle is so general and universal that it can be said to hold in all (or nearly all) situations, we generally call it a law. Scientific laws are few and far between, but good examples are the Newtonian laws of motion. The next step down in the hierarchy is a theory, which is a principle that is supported by a good deal of data, but it is not yet so universal that it can be said to hold in all situations. Finally, the hypothesis is a proposed principle or set of principles that may have some support but does not yet find enough support to be called a theory. Again, these categories are somewhat nebulous, but they can be a useful way to talk about scientific principles. For example, if you were to find a type of motion that violated a Newtonian law of motion, that would indicate either that you had a major scientific finding or flawed data.

When we think about scientific principles, whether they be law, theory, or hypothesis, we must always consider two fundamental concepts: generality and parsimony. Generality refers to the range of phenomena that can be described by the principle, while parsimony refers to the simplicity of the principle. You may have heard the saying "The simplest explanation is the most likely one." This is a rewording of a medieval friar's statement: “The principle that entities should not be multiplied needlessly; the simplest of two competing theories is to be preferred.”

This saying, known commonly as Occam's Razor, after William of Occam, is saying that simple explanations are generally better than more complex ones. Often, the formulation of a scientific principle requires a tradeoff between this preference for simplicity, or parsimony, and generality. We often must make a choice between a principle that describes a great deal of behavior but is very complex, or a principle that is simpler but does not describe as much. To a great extent, the practice of statistics is built upon this very principle, but we'll get into that later in the course.

One of the most critical aspects of a scientific principle is that it must be testable, or even falsifiable. The term that describes a statement that is by its nature impossible to disprove is referred to as a tautology, or a tautological statement. If one were to state that the reason why objects in motion tend to stay in motion (Newton's law of inertia) is because an almighty deity makes it happen, this is a problematic statement for scientific inquiry. This is not to say that this is untrue, but in order to investigate whether that statement is true, one would need to be able to measure that almighty deity. This is, of course, impossible. When you formulate a hypothesis or question, you must be careful to only develop ideas that are falsifiable.

Types of Variables

This brief discussion is largely about terminology, but the reasons for discussing it are deeper than just what we call various things. Remember that experimental research refers to research in which one or more variables are changed or manipulated by the experimenter. One might even say that this variable (or these variables) are independent of other variables, such that they are changed independently of any other variables. For this reason, this manipulated variable is called the Independent Variable (IV). The variable (or variables) measured by the experimenter may or may not change as a function of what happens with the IV. In this case, one might say that this measured variable is dependent on what the manipulated variable is. For this reason, we call this variable the Dependent Variable (DV).

Now if you remember correlational research, this is the type of research in which two variables are measured and the relationship between them is investigated. The important distinction here is that neither of these two variables are manipulated or changed by the experimenter. Rather, both are merely measured. For example, if we were looking to determine whether a happy worker is a more busy worker, we would measure each worker's job satisfaction and job performance and see whether there was a tendency for one to increase while the other also increases. In this example, we are attempting to predict with one variable (job satisfaction) what the outcome of the other variable (job performance) will be. For this reason, one variable is labeled the predictor variable and the other is labeled the outcome variable. Both of these variables is measured in each and every participant in the study, and the relationship between the two is assessed using statistical analysis.

Some Other Thoughts on Scientific Thinking

The type of thinking that we do in science is in many respects different from that used in other areas of academics and society. Scientific thinking follows a deceptively simple, intuitive, and yet somehow very difficult general line of reasoning often referred to as "Hypothetico Deducto." Simply put, this principle states that we make a hypothesis, and if that hypothesis is true, the data should follow in a certain way. That is, if it is the case that {hypothesis} is true, then our results should be {data}. Of course, this seems a rather obvious point, but it never ceases to amaze me how commonly people reverse this principle. That is, people will say "These {data} mean that {hypothesis} is true." At face value, these two statements seem to be interchangeable:

1. If {hypothesis} is true, then the results should be {data}

2. These {data} mean that {hypothesis} is true.

These two statements, though, are NOT equivocal. Take for example the statement that "Consumer spending increased this quarter, as did the Gross Domestic Product, therefore the growth of the U.S. economy is due to consumer spending." Certainly, this statement may be true, but the reasoning is not sound. The Gross Domestic Product and consumer spending could as easily have both increased because of a government stimulus that gave a bunch of free cash to everyone in the country, or the two things could have increased for no common reason at all. We could propose any number of alternate hypotheses to explain the data. If instead we say "If economic growth is due to consumer spending, then we should see consumer spending and GDP increase at the same time," we can better rule out alternatives in future studies. For example, we could then ask whether GDP increases with government spending, or we could ask whether consumer spending increases with global temperature, or any number of other alternatives.

What's Next?

• Complete the Quiz 1: Critiquing an Article.