why do you think research is important brainly

2.1 Why Is Research Important?

Learning objectives.

By the end of this section, you will be able to:

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( Figure 2.2 ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Use of Research Information

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the explosion in our use of technology has led researchers to question whether this ultimately helps or hinders us. The use and implementation of technology in educational settings has become widespread over the last few decades. Researchers are coming to different conclusions regarding the use of technology. To illustrate this point, a study investigating a smartphone app targeting surgery residents (graduate students in surgery training) found that the use of this app can increase student engagement and raise test scores (Shaw & Tan, 2015). Conversely, another study found that the use of technology in undergraduate student populations had negative impacts on sleep, communication, and time management skills (Massimini & Peterson, 2009). Until sufficient amounts of research have been conducted, there will be no clear consensus on the effects that technology has on a student's acquisition of knowledge, study skills, and mental health.

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding early intervention programs. These programs are designed to help children who come from low-income backgrounds, have special needs, or face other disadvantages. These programs may involve providing a wide variety of services to maximize the children's development and position them for optimal levels of success in school and later in life (Blann, 2005). While such programs sound appealing, you would want to be sure that they also proved effective before investing additional money in these programs. Fortunately, psychologists and other scientists have conducted vast amounts of research on such programs and, in general, the programs are found to be effective (Neil & Christensen, 2009; Peters-Scheffer, Didden, Korzilius, & Sturmey, 2011). While not all programs are equally effective, and the short-term effects of many such programs are more pronounced, there is reason to believe that many of these programs produce long-term benefits for participants (Barnett, 2011). If you are committed to being a good steward of taxpayer money, you would want to look at research. Which programs are most effective? What characteristics of these programs make them effective? Which programs promote the best outcomes? After examining the research, you would be best equipped to make decisions about which programs to fund.

Link to Learning

Watch this video about early childhood program effectiveness to learn how scientists evaluate effectiveness and how best to invest money into programs that are most effective.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine that your sister, Maria, expresses concern about her two-year-old child, Umberto. Umberto does not speak as much or as clearly as the other children in his daycare or others in the family. Umberto's pediatrician undertakes some screening and recommends an evaluation by a speech pathologist, but does not refer Maria to any other specialists. Maria is concerned that Umberto's speech delays are signs of a developmental disorder, but Umberto's pediatrician does not; she sees indications of differences in Umberto's jaw and facial muscles. Hearing this, you do some internet searches, but you are overwhelmed by the breadth of information and the wide array of sources. You see blog posts, top-ten lists, advertisements from healthcare providers, and recommendations from several advocacy organizations. Why are there so many sites? Which are based in research, and which are not?

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

NOTABLE RESEARCHERS

Psychological research has a long history involving important figures from diverse backgrounds. While the introductory chapter discussed several researchers who made significant contributions to the discipline, there are many more individuals who deserve attention in considering how psychology has advanced as a science through their work ( Figure 2.3 ). For instance, Margaret Floy Washburn (1871–1939) was the first woman to earn a PhD in psychology. Her research focused on animal behavior and cognition (Margaret Floy Washburn, PhD, n.d.). Mary Whiton Calkins (1863–1930) was a preeminent first-generation American psychologist who opposed the behaviorist movement, conducted significant research into memory, and established one of the earliest experimental psychology labs in the United States (Mary Whiton Calkins, n.d.).

Francis Sumner (1895–1954) was the first African American to receive a PhD in psychology in 1920. His dissertation focused on issues related to psychoanalysis. Sumner also had research interests in racial bias and educational justice. Sumner was one of the founders of Howard University’s department of psychology, and because of his accomplishments, he is sometimes referred to as the “Father of Black Psychology.” Thirteen years later, Inez Beverly Prosser (1895–1934) became the first African American woman to receive a PhD in psychology. Prosser’s research highlighted issues related to education in segregated versus integrated schools, and ultimately, her work was very influential in the hallmark Brown v. Board of Education Supreme Court ruling that segregation of public schools was unconstitutional (Ethnicity and Health in America Series: Featured Psychologists, n.d.).

Although the establishment of psychology’s scientific roots occurred first in Europe and the United States, it did not take much time until researchers from around the world began to establish their own laboratories and research programs. For example, some of the first experimental psychology laboratories in South America were founded by Horatio Piñero (1869–1919) at two institutions in Buenos Aires, Argentina (Godoy & Brussino, 2010). In India, Gunamudian David Boaz (1908–1965) and Narendra Nath Sen Gupta (1889–1944) established the first independent departments of psychology at the University of Madras and the University of Calcutta, respectively. These developments provided an opportunity for Indian researchers to make important contributions to the field (Gunamudian David Boaz, n.d.; Narendra Nath Sen Gupta, n.d.).

When the American Psychological Association (APA) was first founded in 1892, all of the members were White males (Women and Minorities in Psychology, n.d.). However, by 1905, Mary Whiton Calkins was elected as the first female president of the APA, and by 1946, nearly one-quarter of American psychologists were female. Psychology became a popular degree option for students enrolled in the nation’s historically Black higher education institutions, increasing the number of Black Americans who went on to become psychologists. Given demographic shifts occurring in the United States and increased access to higher educational opportunities among historically underrepresented populations, there is reason to hope that the diversity of the field will increasingly match the larger population, and that the research contributions made by the psychologists of the future will better serve people of all backgrounds (Women and Minorities in Psychology, n.d.).

The Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested in the real world; in inductive reasoning , real-world observations lead to new ideas ( Figure 2.4 ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests Figure 2.5 .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( Figure 2.6 ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

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What Is Research, and Why Do People Do It?

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

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Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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The Importance of Research in the Advancement of Society

Thanks to the internet and other technologies, life moves at a very fast pace. We’re constantly adapting and learning new ways to do things–as well as expecting and even demanding innovation from our scientists, executives, and leaders.

Without research, our demands would go completely unanswered!

Curiosity leads to research

Research is what propels humanity forward. It’s fueled by curiosity: we get curious, ask questions, and immerse ourselves in discovering everything there is to know. Learning is thriving. Without curiosity and research, progress would slow to a halt, and our lives as we know them would be completely different.

What would happen without research?

If early civilizations hadn’t been curious about the dark sky, we wouldn’t know anything about space. Decades of research have led us to where we are today: a civilized society with the knowledge and tools to move forward.

If that research slowed to a standstill, what would happen?

We’d become ignorant and unaware. We wouldn’t understand or go forward. Without research, we couldn’t say we were close to finding the cure for cancer or find the most eco-friendly way to light up our homes and offices. We wouldn’t know that, even though bees are not our favorites, they do a job that help us all.

Without research, we could not possibly have survived as long as we have.

And there are still millions of things that have yet to be discovered: diseases to cure, waters to explore, species to discover. All of that is possible with research.

The future of research

Thankfully, schools are becoming more concerned with science and technology, and research is finding its place in the minds of today’s students. Students are eager to make discoveries, create solutions to the world’s problems, and invent the next big thing. We’re going places, one research project at a time.

How do we enable researchers to spend their time on, well, research (instead of filling out forms)? Thankfully, there’s cloud-based software to make that easier. Researchers and research administrators can find funding faster , apply for it more easily, manage their funding once they get it, meet federal and local requirements for documentation, stay in compliance if research involves humans or animals, and make sure research facilities are safe .

All of that means they’re one step closer to tomorrow’s big discoveries.

Adapted from an essay by Cali Simboli

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2.8: Why Is Research Important?

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Learning outcomes

By the end of this section, you will be able to:

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( Figure ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is  empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

USE OF RESEARCH INFORMATION

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the hypothesized link between exposure to media violence and subsequent aggression has been debated in the scientific community for roughly 60 years. Even today, we will find detractors, but a consensus is building. Several professional organizations view media violence exposure as a risk factor for actual violence, including the American Medical Association, the American Psychiatric Association, and the American Psychological Association (American Academy of Pediatrics, American Academy of Child & Adolescent Psychiatry, American Psychological Association, American Medical Association, American Academy of Family Physicians, American Psychiatric Association, 2000).

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding the  D.A.R.E.  (Drug Abuse Resistance Education) program in public schools ( Figure ). This program typically involves police officers coming into the classroom to educate students about the dangers of becoming involved with alcohol and other drugs. According to the D.A.R.E. website (www.dare.org), this program has been very popular since its inception in 1983, and it is currently operating in 75% of school districts in the United States and in more than 40 countries worldwide. Sounds like an easy decision, right? However, on closer review, you discover that the vast majority of research into this program consistently suggests that participation has little, if any, effect on whether or not someone uses alcohol or other drugs (Clayton, Cattarello, & Johnstone, 1996; Ennett, Tobler, Ringwalt, & Flewelling, 1994; Lynam et al., 1999; Ringwalt, Ennett, & Holt, 1991). If you are committed to being a good steward of taxpayer money, will you fund this particular program, or will you try to find other programs that research has consistently demonstrated to be effective?

Watch this  news report  to learn more about some of the controversial issues surrounding the D.A.R.E. program.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine you just found out that a close friend has breast cancer or that one of your young relatives has recently been diagnosed with autism. In either case, you want to know which treatment options are most successful with the fewest side effects. How would you find that out? You would probably talk with your doctor and personally review the research that has been done on various treatment options—always with a critical eye to ensure that you are as informed as possible.

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

THE PROCESS OF SCIENTIFIC RESEARCH

Scientific knowledge is advanced through a process known as the  scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning, ideas are tested against the empirical world; in inductive reasoning, empirical observations lead to new ideas ( Figure ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

Play this  “Deal Me In” interactive card game  to practice using inductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests  Figure .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable, or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund  Freud  had lots of interesting ideas to explain various human behaviors ( Figure ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

Visit this  website  to apply the scientific method and practice its steps by using them to solve a murder mystery, determine why a student is in trouble, and design an experiment to test house paint.

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. In this way, research enables scientists to separate fact from simple opinion. Having good information generated from research aids in making wise decisions both in public policy and in our personal lives.

Review Questions

Scientific hypotheses are ________ and falsifiable.

________ are defined as observable realities.

Scientific knowledge is ________.

A major criticism of Freud’s early theories involves the fact that his theories ________.

• were too limited in scope
• were too outrageous
• were too broad
• were not testable

Critical Thinking Questions

In this section, the D.A.R.E. program was described as an incredibly popular program in schools across the United States despite the fact that research consistently suggests that this program is largely ineffective. How might one explain this discrepancy?

The scientific method is often described as self-correcting and cyclical. Briefly describe your understanding of the scientific method with regard to these concepts.

Personal Application Questions

Healthcare professionals cite an enormous number of health problems related to obesity, and many people have an understandable desire to attain a healthy weight. There are many diet programs, services, and products on the market to aid those who wish to lose weight. If a close friend was considering purchasing or participating in one of these products, programs, or services, how would you make sure your friend was fully aware of the potential consequences of this decision? What sort of information would you want to review before making such an investment or lifestyle change yourself?

[glossary-page] [glossary-term]deductive reasoning:[/glossary-term] [glossary-definition]results are predicted based on a general premise[/glossary-definition]

[glossary-term]empirical:[/glossary-term] [glossary-definition]grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing[/glossary-definition]

[glossary-term]fact:[/glossary-term] [glossary-definition]objective and verifiable observation, established using evidence collected through empirical research[/glossary-definition]

[glossary-term]falsifiable:[/glossary-term] [glossary-definition]able to be disproven by experimental results[/glossary-definition]

[glossary-term]hypothesis:[/glossary-term] [glossary-definition](plural: hypotheses) tentative and testable statement about the relationship between two or more variables[/glossary-definition]

[glossary-term]inductive reasoning:[/glossary-term] [glossary-definition]conclusions are drawn from observations[/glossary-definition]

[glossary-term]opinion:[/glossary-term] [glossary-definition]personal judgements, conclusions, or attitudes that may or may not be accurate[/glossary-definition]

[glossary-term]theory:[/glossary-term] [glossary-definition]well-developed set of ideas that propose an explanation for observed phenomena[/glossary-definition] [/glossary-page]

• Why Is Research Important?. Provided by : OpenStax CNX. Located at : https://cnx.org/contents/[email protected]:Hp5zMFYB@3/Why-Is-Research-Important . License : CC BY-SA: Attribution-ShareAlike

The Why: Explaining the significance of your research

In the first four articles of this series, we examined The What: Defining a research project , The Where: Constructing an effective writing environment , The When: Setting realistic timeframes for your research , and The Who: Finding key sources in the existing literature . In this article, we will explore the fifth, and final, W of academic writing, The Why: Explaining the significance of your research.

Q1: When considering the significance of your research, what is the general contribution you make?

According to the Unite for Sight online module titled “ The Importance of Research ”:

“The purpose of research is to inform action. Thus, your study should seek to contextualize its findings within the larger body of research. Research must always be of high quality in order to produce knowledge that is applicable outside of the research setting. Furthermore, the results of your study may have implications for policy and future project implementation.”

In response to this TweetChat question, Twitter user @aemidr shared that the “dissemination of the research outcomes” is their contribution. Petra Boynton expressed a contribution of “easy to follow resources other people can use to help improve their health/wellbeing”.

Eric Schmieder said, “In general, I try to expand the application of technology to improve the efficiency of business processes through my research and personal use and development of technology solutions.” While Janet Salmons offered the response, “ I am a metaresearcher , that is, I research emerging qualitative methods & write about them. I hope contribution helps student & experienced researchers try new approaches.”

Despite the different contributions each of these participants noted as the significance of their individual research efforts, there is a significance to each. In addition to the importance stated through the above examples, Leann Zarah offered 7 Reasons Why Research Is Important , as follows:

• A Tool for Building Knowledge and for Facilitating Learning
• Means to Understand Various Issues and Increase Public Awareness
• An Aid to Business Success
• A Way to Prove Lies and to Support Truths
• Means to Find, Gauge, and Seize Opportunities
• A Seed to Love Reading, Writing, Analyzing, and Sharing Valuable Information
• Nourishment and Exercise for the Mind

Q1a: What is the specific significance of your research to yourself or other individuals?

The first of “ 3 Important Things to Consider When Selecting Your Research Topic ”, as written by Stephen Fiedler is to “choose something that interests you”. By doing so, you are more likely to stay motivated and persevere through inevitable challenges.

As mentioned earlier, for Salmons her interests lie in emerging methods and new approaches to research. As Salmons pointed out in the TweetChat, “Conventional methods may not be adequate in a globally-connected world – using online methods expands potential participation.”

For @aemidr, “specific significance of my research is on health and safety from the environment and lifestyle”. In contrast, Schmieder said “my ongoing research allows me to be a better educator, to be more efficient in my own business practices, and to feel comfortable engaging with new technology”.

Regardless of discipline, a personal statement can help identify for yourself and others your suitability for specific research. Some things to include in the statement are:

• Your reasons for choosing your topic of research
• The aspects of your topic of research that interest you most
• Any work experience, placement or voluntary work you have undertaken, particularly if it is relevant to your subject. Include the skills and abilities you have gained from these activities
• How your choice of research fits in with your future career plans

Q2: Why is it important to communicate the value of your research?

According to Salmons, “If you research and no one knows about it or can use what you discover, it is just an intellectual exercise. If we want the public to support & fund research, we must show why it’s important!” She has written for the SAGE MethodSpace blog on the subject Write with Purpose, Publish for Impact building a collection of articles from both the MethodSpace blog and TAA’s blog, Abstract .

Peter J. Stogios shares with us benefits to both the scientist and the public in his article, “ Why Sharing Your Research with the Public is as Necessary as Doing the Research Itself ”. Unsure where to start? Stogios states, “There are many ways scientists can communicate more directly with the public. These include writing a personal blog, updating their lab’s or personal website to be less technical and more accessible to non-scientists, popular science forums and message boards, and engaging with your institution’s research communication office. Most organizations publish newsletters or create websites showcasing the work being done, and act as intermediaries between the researchers and the media. Scientists can and should interact more with these communicators.”

Schmieder stated during the TweetChat that the importance of communicating the value of your research is “primarily to help others understand why you do what you do, but also for funding purposes, application of your results by others, and increased personal value and validation”.

In her article, “ Explaining Your Research to the Public: Why It Matters, How to Do It! ”, Sharon Page-Medrich conveys the importance, stating “UC Berkeley’s 30,000+ undergraduate and 11,000+ graduate students generate or contribute to diverse research in the natural and physical sciences, social sciences and humanities, and many professional fields. Such research and its applications are fundamental to saving lives, restoring healthy environments, making art and preserving culture, and raising standards of living. Yet the average person-in-the-street may not see the connection between students’ investigations and these larger outcomes.”

Q2a: To whom is it most difficult to explain that value?

Although important, it’s not always easy to share our research efforts with others. Erin Bedford sets the scene as she tells us “ How to (Not) Talk about Your Research ”. “It’s happened to the best of us. First, the question: ‘so, what is your research on?’ Then, the blank stare as you try to explain. And finally, the uninterested but polite nod and smile.”

Schmieder acknowledges that these polite people who care enough to ask, but often are the hardest to explain things to are “family and friends who don’t share the same interests or understanding of the subject matter.” It’s not that they don’t care about the efforts, it’s that the level to which a researcher’s investment and understanding is different from those asking about their work.

When faced with less-than-supportive reactions from friends, Noelle Sterne shares some ways to retain your perspective and friendship in her TAA blog article, “ Friends – How to deal with their negative responses to your academic projects ”.

Q3: What methods have you used to explain your research to others (both inside and outside of your discipline)?

Schmieder stated, “I have done webinars, professional development seminars, blog articles, and online courses” in an effort to communicate research to others. The Edinburg Napier University LibGuides guide to Sharing Your Research includes some of these in their list of resources as well adding considerations of online presence, saving time / online efficiency, copyright, and compliance to the discussion.

Michaela Panter states in her article, “ Sharing Your Findings with a General Audience ”, that “tips and guidelines for conveying your research to a general audience are increasingly widespread, yet scientists remain wary of doing so.” She notes, however, that “effectively sharing your research with a general audience can positively affect funding for your work” and “engaging the general public can further the impact of your research”.

If these are affects you desire, consider CES’s “ Six ways to share your research findings ”, as follows:

• Know your audience and define your goal
• Collaborate with others
• Make a plan
• Embrace plain language writing
• Layer and link, and
• Evaluate your work

Q4: What are some places you can share your research and its significance beyond your writing?

Beyond traditional journal article publication efforts, there are many opportunities to share your research with a larger community. Schmieder listed several options during the TweetChat event, specifically, “conference presentations, social media, blogs, professional networks and organizations, podcasts, and online courses”.

Elsevier’s resource, “ Sharing and promoting your article ” provides advice on sharing your article in the following ten places:

• At a conference
• For classroom teaching purposes
• For grant applications
• With my colleagues
• On a preprint server
• On my personal blog or website
• On my institutional repository
• On a subject repository (or other non-commercial repository)
• On Scholarly Communication Network (SCN), such as Mendeley or Scholar Universe
• Social Media, such as Facebook, LinkedIn, Twitter

Nature Publishing Group’s “ tips for promoting your research ” include nine ways to get started:

• Share your work with your social networks
• Update your professional profile
• Utilize research-sharing platforms
• Create a Google Scholar profile – or review and enhance your existing one
• Highlight key and topical points in a blog post
• Make your research outputs shareable and discoverable
• Register for a unique ORCID author identifier
• Encourage readership within your institution

Finally, Sheffield Solutions produced a top ten list of actions you can take to help share and disseminate your work more widely online, as follows:

• Create an ORCID ID
• Upload to Sheffield’s MyPublications system
• Make your work Open Access
• Create a Google Scholar profile
• Join an academic social network
• Connect through Twitter
• Blog about your research
• Upload to Slideshare or ORDA
• Track your research

Q5: How is the significance of your study conveyed in your writing efforts?

Schmieder stated, “Significance is conveyed through the introduction, the structure of the study, and the implications for further research sections of articles”. According to The Writing Center at University of North Carolina at Chapel Hill, “A thesis statement tells the reader how you will interpret the significance of the subject matter under discussion”.

In their online Tips & Tools resource on Thesis Statements , they share the following six questions to ask to help determine if your thesis is strong:

• Do I answer the question?
• Have I taken a position that others might challenge or oppose?
• Is my thesis statement specific enough?
• Does my thesis pass the “So what?” test?
• Does my essay support my thesis specifically and without wandering?
• Does my thesis pass the “how and why?” test?

Some journals, such as Elsevier’s Acta Biomaterialia, now require a statement of significance with manuscript submissions. According to the announcement linked above, “these statements will address the novelty aspect and the significance of the work with respect to the existing literature and more generally to the society.” and “by highlighting the scientific merit of your research, these statements will help make your work more visible to our readership.”

Q5a: How does the significance influence the structure of your writing?

According to Jeff Hume-Pratuch in the Academic Coaching & Writing (ACW) article, “ Using APA Style in Academic Writing: Precision and Clarity ”, “The need for precision and clarity of expression is one of the distinguishing marks of academic writing.” As a result, Hume-Pratuch advises that you “choose your words wisely so that they do not come between your idea and the audience.” To do so, he suggests avoiding ambiguous expressions, approximate language, and euphemisms and jargon in your writing.

Schmieder shared in the TweetChat that “the impact of the writing is affected by the target audience for the research and can influence word choice, organization of ideas, and elements included in the narrative”.

Discussing the organization of ideas, Patrick A. Regoniel offers “ Two Tips in Writing the Significance of the Study ” claiming that by referring to the statement of the problem and writing from general to specific contribution, you can “prevent your mind from wandering wildly or aimlessly as you explore the significance of your study”.

Q6: What are some ways you can improve your ability to explain your research to others?

For both Schmieder and Salmons, practice is key. Schmieder suggested, “Practice simplifying the concepts. Focus on why rather than what. Share research in areas where they are active and comfortable”. Salmons added, “answer ‘so what’ and ‘who cares’ questions. Practice creating a sentence. For my study of the collaborative process: ‘Learning to collaborate is important for team success in professional life’ works better than ‘a phenomenological study of instructors’ perceptions’”.

In a guest blog post for Scientific American titled “ Effective Communication, Better Science ”, Mónica I. Feliú-Mójer claimed “to be a successful scientist, you must be an effective communicator.” In support of the goal of being an effective communicator, a list of training opportunities and other resources are included in the article.

Along the same lines, The University of Melbourne shared the following list of resources, workshops, and programs in their online resource on academic writing and communication skills :

• Speaking and Presenting : Resources for presenting your research, using PowerPoint to your advantage, presenting at conferences and helpful videos on presenting effectively
• Research Impact Library Advisory Service  (RILAS): Helps you to determine the impact of your publications and other research outputs for academic promotions and grant applications
• Three Minute Thesis Competition  (3MT): Research communication competition that requires you to deliver a compelling oration on your thesis topic and its significance in just three minutes or less.
• Visualise your Thesis Competition : A dynamic and engaging audio-visual “elevator pitch” (e-Poster) to communicate your research to a broad non-specialist audience in 60 seconds.

As we complete this series exploration of the five W’s of academic writing, we hope that you are adequately prepared to apply them to your own research efforts of defining a research project, constructing an effective writing environment, setting realistic timeframes for your research, finding key sources in the existing literature, and last, but not least, explaining the significance of your research.

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Simple Answers to Scientific Questions

Importance Of Research In Daily Life

Whether we are students, professionals, or stay-at-home parents, we all need to do research on a daily basis.

The reason?

Research helps us make informed decisions.

It allows us to learn about new things, and it teaches us how to think critically.

There is an importance of research in daily life.

Let’s discuss the importance of research in our daily lives and how it can help us achieve our goals!

6 ways research plays an important role in our daily lives.

• It leads to new discoveries and innovations that improve our lives. Many of the technologies we rely on today are the result of research in fields like medicine, computer science, engineering, etc. Things like smartphones, wifi, GPS, and medical treatments were made possible by research.
• It informs policy making. Research provides data and evidence that allows policymakers to make more informed decisions on issues that impact society, whether it’s related to health, education, the economy, or other areas. Research gives insights into problems.
• It spreads knowledge and awareness. The research contributes new information and facts to various fields and disciplines. The sharing of research educates people on new topics, ideas, social issues, etc. It provides context for understanding the world.
• It drives progress and change. Research challenges existing notions, tests new theories and hypotheses, and pushes boundaries of what’s known. Pushing the frontiers of knowledge through research is key for advancement. Even when research invalidates ideas, it leads to progress.
• It develops critical thinking skills. The research process itself – asking questions, collecting data, analyzing results, drawing conclusions – builds logic, problem-solving, and cognitive skills that benefit individuals in their professional and personal lives.
• It fuels innovation and the economy. Research leads to the development of new products and services that create jobs and improve productivity in the marketplace. Private sector research drives economic growth.

So while not always visible, research underlies much of our technological, social, economic, and human progress. It’s a building block for society.

Conducting quality research and using it to maximum benefit is key.

Research is important in everyday life because it allows us to make informed decisions about the things that matter most to us.

Whether we’re researching a new car before making a purchase, studying for an important test, or looking into different treatment options for a health issue, research allows us to get the facts and make the best choices for ourselves and our families.

• In today’s world, there’s so much information available at our fingertips, and research is more accessible than ever.
• The internet has made it possible for anyone with an interest in doing research to access vast amounts of information in a short amount of time.

This is both a blessing and a curse; while it’s great that we have so much information available to us, it can be overwhelming to try to sort through everything and find the most reliable sources.

What is the importance of research in our daily life?

Research is essential to our daily lives.

• It helps us to make informed decisions about everything from the food we eat to the medicines we take.
• It also allows us to better understand the world around us and find solutions to problems.

In short, research is essential for our health, safety, and well-being. Without it, we would be living in a world of ignorance and misinformation.

What is the importance of research in our daily lives as a student?

As a student, research plays an important role in our daily life. It helps us to gain knowledge and understanding of the world around us.

• It also allows us to develop new skills and perspectives.
• In addition, research helps us to innovate and create new things. 
• Research is essential for students because it helps us to learn about the world around us. Without research, we would be limited to our own personal experiences and observations.
• Research allows us to go beyond our personal bubble and explore new ideas and concepts.
• It also gives us the opportunity to develop new skills and perspectives. 
• In addition, research is important because it helps us to innovate and create new things. When we conduct research , we are constantly learning new information that can be used to create something new.

This could be anything from a new product or service to a new way of doing things.

Research is essential for students because it allows us to be innovative and create new things that can make a difference in the world.

Consequently, while each person’s daily life routine might differ based on their unique circumstances, the role that research plays in our lives as students is an integral one nonetheless.

Different though our routines might be, the value of research in our lives shines through brightly regardless.  And that importance cannot be overstated .

How does research affect your daily life?

Every day, we benefit from the countless hours of research that have been conducted by scientists and scholars around the world.

• From the moment we wake up in the morning to the time we go to bed at night, we rely on research to improve our lives in a variety of ways.
• For instance, many of the items we use every day, such as our phones and laptops, are the result of years of research and development.
• And when we see a news story about a new medical breakthrough or a natural disaster, it is often the result of research that has been conducted over a long period of time.

In short, research affects our daily lives in countless ways, both big and small. Without it, we would be living in a very different world.

What are the purposes of research?

The word “research” is used in a variety of ways. In its broadest sense, research includes any gathering of data, information, and facts for the advancement of knowledge.

Whether you are looking for a new recipe or trying to find a cure for cancer, the process of research is the same.

You start with a question or an area of interest and then use different sources to find information that will help you answer that question or learn more about that topic.

“The purpose of research is to find answers to questions, solve problems, or develop new knowledge.”

It is an essential tool in business , education, science, and many other fields. By conducting research, we can learn about the world around us and make it a better place.

How to do effective research 

Research is a process of uncovering facts and information about a subject.

It is usually done when preparing for an assignment or project and can be either primary research, which involves collecting data yourself, or secondary research, which involves finding existing data.

Regardless of the type of research you do, there are some effective strategies that will help you get the most out of your efforts:

• First, start by clearly defining your topic and what you hope to learn. This will help you to focus your search and find relevant information more quickly.
• Once you know what you’re looking for, try using keyword searches to find websites, articles, and other resources that are relevant to your topic.
• When evaluating each source, be sure to consider its reliability and biases.
• Finally, take good notes as you read, and make sure to keep track of where each piece of information came from so that you can easily cite it later.

By following these steps, you can ensure that your research is both thorough and accurate.

How to use research to achieve your goals.

Achieving your goals requires careful planning and a lot of hard work.

But even the best-laid plans can sometimes go awry.

That’s where research comes in.

By taking the time to do your homework, you can increase your chances of success while also learning more about your topic of interest.

When it comes to goal-setting, research can help you to identify realistic targets and develop a roadmap for achieving them.

It can also provide valuable insights into potential obstacles and how to overcome them.

In short, research is an essential tool for anyone who wants to achieve their goals.

So if you’re serious about reaching your target, be sure to do your homework first.

So the next time you are faced with a decision, don’t forget to do your research!

It could very well be the most important thing you do all day.

Jacks of Science sources the most authoritative, trustworthy, and highly recognized institutions for our article research. Learn more about our Editorial Teams process and diligence in verifying the accuracy of every article we publish.

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The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

National Institute of Environmental Health Sciences

Your environment. your health., what is ethics in research & why is it important, by david b. resnik, j.d., ph.d..

December 23, 2020

The ideas and opinions expressed in this essay are the author’s own and do not necessarily represent those of the NIH, NIEHS, or US government.

When most people think of ethics (or morals), they think of rules for distinguishing between right and wrong, such as the Golden Rule ("Do unto others as you would have them do unto you"), a code of professional conduct like the Hippocratic Oath ("First of all, do no harm"), a religious creed like the Ten Commandments ("Thou Shalt not kill..."), or a wise aphorisms like the sayings of Confucius. This is the most common way of defining "ethics": norms for conduct that distinguish between acceptable and unacceptable behavior.

Most people learn ethical norms at home, at school, in church, or in other social settings. Although most people acquire their sense of right and wrong during childhood, moral development occurs throughout life and human beings pass through different stages of growth as they mature. Ethical norms are so ubiquitous that one might be tempted to regard them as simple commonsense. On the other hand, if morality were nothing more than commonsense, then why are there so many ethical disputes and issues in our society?

Alternatives to Animal Testing

Alternative test methods are methods that replace, reduce, or refine animal use in research and testing

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One plausible explanation of these disagreements is that all people recognize some common ethical norms but interpret, apply, and balance them in different ways in light of their own values and life experiences. For example, two people could agree that murder is wrong but disagree about the morality of abortion because they have different understandings of what it means to be a human being.

Most societies also have legal rules that govern behavior, but ethical norms tend to be broader and more informal than laws. Although most societies use laws to enforce widely accepted moral standards and ethical and legal rules use similar concepts, ethics and law are not the same. An action may be legal but unethical or illegal but ethical. We can also use ethical concepts and principles to criticize, evaluate, propose, or interpret laws. Indeed, in the last century, many social reformers have urged citizens to disobey laws they regarded as immoral or unjust laws. Peaceful civil disobedience is an ethical way of protesting laws or expressing political viewpoints.

Another way of defining 'ethics' focuses on the disciplines that study standards of conduct, such as philosophy, theology, law, psychology, or sociology. For example, a "medical ethicist" is someone who studies ethical standards in medicine. One may also define ethics as a method, procedure, or perspective for deciding how to act and for analyzing complex problems and issues. For instance, in considering a complex issue like global warming , one may take an economic, ecological, political, or ethical perspective on the problem. While an economist might examine the cost and benefits of various policies related to global warming, an environmental ethicist could examine the ethical values and principles at stake.

See ethics in practice at NIEHS

Read latest updates in our monthly  Global Environmental Health Newsletter

Many different disciplines, institutions , and professions have standards for behavior that suit their particular aims and goals. These standards also help members of the discipline to coordinate their actions or activities and to establish the public's trust of the discipline. For instance, ethical standards govern conduct in medicine, law, engineering, and business. Ethical norms also serve the aims or goals of research and apply to people who conduct scientific research or other scholarly or creative activities. There is even a specialized discipline, research ethics, which studies these norms. See Glossary of Commonly Used Terms in Research Ethics and Research Ethics Timeline .

There are several reasons why it is important to adhere to ethical norms in research. First, norms promote the aims of research , such as knowledge, truth, and avoidance of error. For example, prohibitions against fabricating , falsifying, or misrepresenting research data promote the truth and minimize error.

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See how we put research Ethics to practice.

Visit Joinastudy.niehs.nih.gov to see the various studies NIEHS perform.

Second, since research often involves a great deal of cooperation and coordination among many different people in different disciplines and institutions, ethical standards promote the values that are essential to collaborative work , such as trust, accountability, mutual respect, and fairness. For example, many ethical norms in research, such as guidelines for authorship , copyright and patenting policies , data sharing policies, and confidentiality rules in peer review, are designed to protect intellectual property interests while encouraging collaboration. Most researchers want to receive credit for their contributions and do not want to have their ideas stolen or disclosed prematurely.

Third, many of the ethical norms help to ensure that researchers can be held accountable to the public . For instance, federal policies on research misconduct, conflicts of interest, the human subjects protections, and animal care and use are necessary in order to make sure that researchers who are funded by public money can be held accountable to the public.

Fourth, ethical norms in research also help to build public support for research. People are more likely to fund a research project if they can trust the quality and integrity of research.

Finally, many of the norms of research promote a variety of other important moral and social values , such as social responsibility, human rights, animal welfare, compliance with the law, and public health and safety. Ethical lapses in research can significantly harm human and animal subjects, students, and the public. For example, a researcher who fabricates data in a clinical trial may harm or even kill patients, and a researcher who fails to abide by regulations and guidelines relating to radiation or biological safety may jeopardize his health and safety or the health and safety of staff and students.

Codes and Policies for Research Ethics

Given the importance of ethics for the conduct of research, it should come as no surprise that many different professional associations, government agencies, and universities have adopted specific codes, rules, and policies relating to research ethics. Many government agencies have ethics rules for funded researchers.

• National Institutes of Health (NIH)
• National Science Foundation (NSF)
• Food and Drug Administration (FDA)
• Environmental Protection Agency (EPA)
• US Department of Agriculture (USDA)
• Singapore Statement on Research Integrity
• American Chemical Society, The Chemist Professional’s Code of Conduct
• Code of Ethics (American Society for Clinical Laboratory Science)
• American Psychological Association, Ethical Principles of Psychologists and Code of Conduct
• Statement on Professional Ethics (American Association of University Professors)
• Nuremberg Code
• World Medical Association's Declaration of Helsinki

Ethical Principles

The following is a rough and general summary of some ethical principles that various codes address*:

Strive for honesty in all scientific communications. Honestly report data, results, methods and procedures, and publication status. Do not fabricate, falsify, or misrepresent data. Do not deceive colleagues, research sponsors, or the public.

Objectivity

Strive to avoid bias in experimental design, data analysis, data interpretation, peer review, personnel decisions, grant writing, expert testimony, and other aspects of research where objectivity is expected or required. Avoid or minimize bias or self-deception. Disclose personal or financial interests that may affect research.

Keep your promises and agreements; act with sincerity; strive for consistency of thought and action.

Carefulness

Avoid careless errors and negligence; carefully and critically examine your own work and the work of your peers. Keep good records of research activities, such as data collection, research design, and correspondence with agencies or journals.

Share data, results, ideas, tools, resources. Be open to criticism and new ideas.

Transparency

Disclose methods, materials, assumptions, analyses, and other information needed to evaluate your research.

Accountability

Take responsibility for your part in research and be prepared to give an account (i.e. an explanation or justification) of what you did on a research project and why.

Intellectual Property

Honor patents, copyrights, and other forms of intellectual property. Do not use unpublished data, methods, or results without permission. Give proper acknowledgement or credit for all contributions to research. Never plagiarize.

Confidentiality

Protect confidential communications, such as papers or grants submitted for publication, personnel records, trade or military secrets, and patient records.

Responsible Publication

Publish in order to advance research and scholarship, not to advance just your own career. Avoid wasteful and duplicative publication.

Responsible Mentoring

Help to educate, mentor, and advise students. Promote their welfare and allow them to make their own decisions.

Respect for Colleagues

Respect your colleagues and treat them fairly.

Social Responsibility

Strive to promote social good and prevent or mitigate social harms through research, public education, and advocacy.

Non-Discrimination

Avoid discrimination against colleagues or students on the basis of sex, race, ethnicity, or other factors not related to scientific competence and integrity.

Maintain and improve your own professional competence and expertise through lifelong education and learning; take steps to promote competence in science as a whole.

Know and obey relevant laws and institutional and governmental policies.

Animal Care

Show proper respect and care for animals when using them in research. Do not conduct unnecessary or poorly designed animal experiments.

Human Subjects protection

When conducting research on human subjects, minimize harms and risks and maximize benefits; respect human dignity, privacy, and autonomy; take special precautions with vulnerable populations; and strive to distribute the benefits and burdens of research fairly.

* Adapted from Shamoo A and Resnik D. 2015. Responsible Conduct of Research, 3rd ed. (New York: Oxford University Press).

Ethical Decision Making in Research

Although codes, policies, and principles are very important and useful, like any set of rules, they do not cover every situation, they often conflict, and they require interpretation. It is therefore important for researchers to learn how to interpret, assess, and apply various research rules and how to make decisions and act ethically in various situations. The vast majority of decisions involve the straightforward application of ethical rules. For example, consider the following case:

The research protocol for a study of a drug on hypertension requires the administration of the drug at different doses to 50 laboratory mice, with chemical and behavioral tests to determine toxic effects. Tom has almost finished the experiment for Dr. Q. He has only 5 mice left to test. However, he really wants to finish his work in time to go to Florida on spring break with his friends, who are leaving tonight. He has injected the drug in all 50 mice but has not completed all of the tests. He therefore decides to extrapolate from the 45 completed results to produce the 5 additional results.

Many different research ethics policies would hold that Tom has acted unethically by fabricating data. If this study were sponsored by a federal agency, such as the NIH, his actions would constitute a form of research misconduct , which the government defines as "fabrication, falsification, or plagiarism" (or FFP). Actions that nearly all researchers classify as unethical are viewed as misconduct. It is important to remember, however, that misconduct occurs only when researchers intend to deceive : honest errors related to sloppiness, poor record keeping, miscalculations, bias, self-deception, and even negligence do not constitute misconduct. Also, reasonable disagreements about research methods, procedures, and interpretations do not constitute research misconduct. Consider the following case:

Dr. T has just discovered a mathematical error in his paper that has been accepted for publication in a journal. The error does not affect the overall results of his research, but it is potentially misleading. The journal has just gone to press, so it is too late to catch the error before it appears in print. In order to avoid embarrassment, Dr. T decides to ignore the error.

Dr. T's error is not misconduct nor is his decision to take no action to correct the error. Most researchers, as well as many different policies and codes would say that Dr. T should tell the journal (and any coauthors) about the error and consider publishing a correction or errata. Failing to publish a correction would be unethical because it would violate norms relating to honesty and objectivity in research.

There are many other activities that the government does not define as "misconduct" but which are still regarded by most researchers as unethical. These are sometimes referred to as " other deviations " from acceptable research practices and include:

• Publishing the same paper in two different journals without telling the editors
• Submitting the same paper to different journals without telling the editors
• Not informing a collaborator of your intent to file a patent in order to make sure that you are the sole inventor
• Including a colleague as an author on a paper in return for a favor even though the colleague did not make a serious contribution to the paper
• Discussing with your colleagues confidential data from a paper that you are reviewing for a journal
• Using data, ideas, or methods you learn about while reviewing a grant or a papers without permission
• Trimming outliers from a data set without discussing your reasons in paper
• Using an inappropriate statistical technique in order to enhance the significance of your research
• Bypassing the peer review process and announcing your results through a press conference without giving peers adequate information to review your work
• Conducting a review of the literature that fails to acknowledge the contributions of other people in the field or relevant prior work
• Stretching the truth on a grant application in order to convince reviewers that your project will make a significant contribution to the field
• Stretching the truth on a job application or curriculum vita
• Giving the same research project to two graduate students in order to see who can do it the fastest
• Overworking, neglecting, or exploiting graduate or post-doctoral students
• Failing to keep good research records
• Failing to maintain research data for a reasonable period of time
• Making derogatory comments and personal attacks in your review of author's submission
• Promising a student a better grade for sexual favors
• Using a racist epithet in the laboratory
• Making significant deviations from the research protocol approved by your institution's Animal Care and Use Committee or Institutional Review Board for Human Subjects Research without telling the committee or the board
• Not reporting an adverse event in a human research experiment
• Wasting animals in research
• Exposing students and staff to biological risks in violation of your institution's biosafety rules
• Sabotaging someone's work
• Stealing supplies, books, or data
• Rigging an experiment so you know how it will turn out
• Making unauthorized copies of data, papers, or computer programs
• Owning over $10,000 in stock in a company that sponsors your research and not disclosing this financial interest
• Deliberately overestimating the clinical significance of a new drug in order to obtain economic benefits

These actions would be regarded as unethical by most scientists and some might even be illegal in some cases. Most of these would also violate different professional ethics codes or institutional policies. However, they do not fall into the narrow category of actions that the government classifies as research misconduct. Indeed, there has been considerable debate about the definition of "research misconduct" and many researchers and policy makers are not satisfied with the government's narrow definition that focuses on FFP. However, given the huge list of potential offenses that might fall into the category "other serious deviations," and the practical problems with defining and policing these other deviations, it is understandable why government officials have chosen to limit their focus.

Finally, situations frequently arise in research in which different people disagree about the proper course of action and there is no broad consensus about what should be done. In these situations, there may be good arguments on both sides of the issue and different ethical principles may conflict. These situations create difficult decisions for research known as ethical or moral dilemmas . Consider the following case:

Dr. Wexford is the principal investigator of a large, epidemiological study on the health of 10,000 agricultural workers. She has an impressive dataset that includes information on demographics, environmental exposures, diet, genetics, and various disease outcomes such as cancer, Parkinson’s disease (PD), and ALS. She has just published a paper on the relationship between pesticide exposure and PD in a prestigious journal. She is planning to publish many other papers from her dataset. She receives a request from another research team that wants access to her complete dataset. They are interested in examining the relationship between pesticide exposures and skin cancer. Dr. Wexford was planning to conduct a study on this topic.

Dr. Wexford faces a difficult choice. On the one hand, the ethical norm of openness obliges her to share data with the other research team. Her funding agency may also have rules that obligate her to share data. On the other hand, if she shares data with the other team, they may publish results that she was planning to publish, thus depriving her (and her team) of recognition and priority. It seems that there are good arguments on both sides of this issue and Dr. Wexford needs to take some time to think about what she should do. One possible option is to share data, provided that the investigators sign a data use agreement. The agreement could define allowable uses of the data, publication plans, authorship, etc. Another option would be to offer to collaborate with the researchers.

The following are some step that researchers, such as Dr. Wexford, can take to deal with ethical dilemmas in research:

What is the problem or issue?

It is always important to get a clear statement of the problem. In this case, the issue is whether to share information with the other research team.

What is the relevant information?

Many bad decisions are made as a result of poor information. To know what to do, Dr. Wexford needs to have more information concerning such matters as university or funding agency or journal policies that may apply to this situation, the team's intellectual property interests, the possibility of negotiating some kind of agreement with the other team, whether the other team also has some information it is willing to share, the impact of the potential publications, etc.

What are the different options?

People may fail to see different options due to a limited imagination, bias, ignorance, or fear. In this case, there may be other choices besides 'share' or 'don't share,' such as 'negotiate an agreement' or 'offer to collaborate with the researchers.'

How do ethical codes or policies as well as legal rules apply to these different options?

The university or funding agency may have policies on data management that apply to this case. Broader ethical rules, such as openness and respect for credit and intellectual property, may also apply to this case. Laws relating to intellectual property may be relevant.

Are there any people who can offer ethical advice?

It may be useful to seek advice from a colleague, a senior researcher, your department chair, an ethics or compliance officer, or anyone else you can trust. In the case, Dr. Wexford might want to talk to her supervisor and research team before making a decision.

After considering these questions, a person facing an ethical dilemma may decide to ask more questions, gather more information, explore different options, or consider other ethical rules. However, at some point he or she will have to make a decision and then take action. Ideally, a person who makes a decision in an ethical dilemma should be able to justify his or her decision to himself or herself, as well as colleagues, administrators, and other people who might be affected by the decision. He or she should be able to articulate reasons for his or her conduct and should consider the following questions in order to explain how he or she arrived at his or her decision:

• Which choice will probably have the best overall consequences for science and society?
• Which choice could stand up to further publicity and scrutiny?
• Which choice could you not live with?
• Think of the wisest person you know. What would he or she do in this situation?
• Which choice would be the most just, fair, or responsible?

After considering all of these questions, one still might find it difficult to decide what to do. If this is the case, then it may be appropriate to consider others ways of making the decision, such as going with a gut feeling or intuition, seeking guidance through prayer or meditation, or even flipping a coin. Endorsing these methods in this context need not imply that ethical decisions are irrational, however. The main point is that human reasoning plays a pivotal role in ethical decision-making but there are limits to its ability to solve all ethical dilemmas in a finite amount of time.

Promoting Ethical Conduct in Science

Do U.S. research institutions meet or exceed federal mandates for instruction in responsible conduct of research? A national survey

 Read about U.S. research instutuins follow federal manadates for ethics in research 

Learn more about NIEHS Research

Most academic institutions in the US require undergraduate, graduate, or postgraduate students to have some education in the responsible conduct of research (RCR) . The NIH and NSF have both mandated training in research ethics for students and trainees. Many academic institutions outside of the US have also developed educational curricula in research ethics

Those of you who are taking or have taken courses in research ethics may be wondering why you are required to have education in research ethics. You may believe that you are highly ethical and know the difference between right and wrong. You would never fabricate or falsify data or plagiarize. Indeed, you also may believe that most of your colleagues are highly ethical and that there is no ethics problem in research..

If you feel this way, relax. No one is accusing you of acting unethically. Indeed, the evidence produced so far shows that misconduct is a very rare occurrence in research, although there is considerable variation among various estimates. The rate of misconduct has been estimated to be as low as 0.01% of researchers per year (based on confirmed cases of misconduct in federally funded research) to as high as 1% of researchers per year (based on self-reports of misconduct on anonymous surveys). See Shamoo and Resnik (2015), cited above.

Clearly, it would be useful to have more data on this topic, but so far there is no evidence that science has become ethically corrupt, despite some highly publicized scandals. Even if misconduct is only a rare occurrence, it can still have a tremendous impact on science and society because it can compromise the integrity of research, erode the public’s trust in science, and waste time and resources. Will education in research ethics help reduce the rate of misconduct in science? It is too early to tell. The answer to this question depends, in part, on how one understands the causes of misconduct. There are two main theories about why researchers commit misconduct. According to the "bad apple" theory, most scientists are highly ethical. Only researchers who are morally corrupt, economically desperate, or psychologically disturbed commit misconduct. Moreover, only a fool would commit misconduct because science's peer review system and self-correcting mechanisms will eventually catch those who try to cheat the system. In any case, a course in research ethics will have little impact on "bad apples," one might argue.

According to the "stressful" or "imperfect" environment theory, misconduct occurs because various institutional pressures, incentives, and constraints encourage people to commit misconduct, such as pressures to publish or obtain grants or contracts, career ambitions, the pursuit of profit or fame, poor supervision of students and trainees, and poor oversight of researchers (see Shamoo and Resnik 2015). Moreover, defenders of the stressful environment theory point out that science's peer review system is far from perfect and that it is relatively easy to cheat the system. Erroneous or fraudulent research often enters the public record without being detected for years. Misconduct probably results from environmental and individual causes, i.e. when people who are morally weak, ignorant, or insensitive are placed in stressful or imperfect environments. In any case, a course in research ethics can be useful in helping to prevent deviations from norms even if it does not prevent misconduct. Education in research ethics is can help people get a better understanding of ethical standards, policies, and issues and improve ethical judgment and decision making. Many of the deviations that occur in research may occur because researchers simply do not know or have never thought seriously about some of the ethical norms of research. For example, some unethical authorship practices probably reflect traditions and practices that have not been questioned seriously until recently. If the director of a lab is named as an author on every paper that comes from his lab, even if he does not make a significant contribution, what could be wrong with that? That's just the way it's done, one might argue. Another example where there may be some ignorance or mistaken traditions is conflicts of interest in research. A researcher may think that a "normal" or "traditional" financial relationship, such as accepting stock or a consulting fee from a drug company that sponsors her research, raises no serious ethical issues. Or perhaps a university administrator sees no ethical problem in taking a large gift with strings attached from a pharmaceutical company. Maybe a physician thinks that it is perfectly appropriate to receive a $300 finder’s fee for referring patients into a clinical trial.

If "deviations" from ethical conduct occur in research as a result of ignorance or a failure to reflect critically on problematic traditions, then a course in research ethics may help reduce the rate of serious deviations by improving the researcher's understanding of ethics and by sensitizing him or her to the issues.

Finally, education in research ethics should be able to help researchers grapple with the ethical dilemmas they are likely to encounter by introducing them to important concepts, tools, principles, and methods that can be useful in resolving these dilemmas. Scientists must deal with a number of different controversial topics, such as human embryonic stem cell research, cloning, genetic engineering, and research involving animal or human subjects, which require ethical reflection and deliberation.

The importance of research and its impact on education

Tertiary education is indeed a big investment, so looking for the right university takes time, patience, and dedication. In case you hadn’t noticed, most universities tend to highlight research as one of their most distinguished and competitive strengths. But the question here is why ?

From an individual point of view, the advantages of research extend beyond having an impressive degree certificate. Through detailed research, students develop critical thinking expertise, as well as effective analytical, research, and communication skills that are globally sought-after and incredibly beneficial. Ultimately, research is essential to economic and social development of our globalised society, forming the foundations governmental policies around the world.

“Knowledge generated by research is the basis of sustainable development, which requires that knowledge be placed at the service of development, be converted into applications, and be shared to ensure widespread benefits,” says Mary-Louise Kearney, Director of the UNESCO Forum on Higher Education, Research and Knowledge.

One institution which understands this is the University of Skovde . Though the university is actually much younger than most, its education and internationally-competitive research are highly respected, particularly within the School of Bioscience . The university has a well-developed collaboration between education, research, the business community, and society on both a national and international level.

The school has three divisions : – The Division for Bioinformatics and Ecology, The Division for Cognitive Neuroscience and Philosophy, and The Division for Molecular Biology; offering a total of 13 academic programs at the undergraduate and advanced levels. Besides providing an impressive array of courses, the school has its own research centre known as the Systems Biology Research Center , where research is conducted in the following areas:- Infection Biology , Bioinformatics , Biotechnology , Cognitive Neuroscience and Philosophy and Ecological Modeling . Here are some examples of what Skovde’s experienced research teams have been working on:

Infection Biology

Research from the Infection Biology Group focuses on the development of mathematical and statistical models as well as experimental methodology used to help understand the complex systems that make up infection biology. The Group’s current funded projects focus on:

• Identifying new biomarkers to help diagnose sepsis patients at an early stage
• Identifying biomarker profiles for immunosuppressive drugs
• Developing new methods for the detection of plant pathogens

Bioinformatics

Formed by computer science researchers, this area of investigation focuses on the development and application of algorithms for the analysis of biological data. Skovde’s research has incorporated the development of algorithms, software and databases, as well as solving biological research problems with these tools. As part of the research team, students get to work with other researchers such as stem cell and tumour biologists from other groups within the university , industrial partners and other establishments.

Cognitive neuroscience and philosophy

Research in cognitive neuroscience seeks to increase knowledge and understanding of human abilities, reflected in the form of cerebral activity. One of the main goals of the research is to increase our understanding of human consciousness, as well as to study methods that might increase human wellbeing.

Biotechnology

Defined as the application of biological organisms, systems, or processes by various industries, stakeholders and researchers, Biotechnology encompasses science and life, improving the value of materials and organisms through pharmaceuticals, crops, livestock and the environment. While research in plant biotechnology seeks to identify specific genes to eliminate various forms of arsenic contamination, Skovde’s research projects in microbial biotechnology can also be used to develop microbial bioreactors. The mussel research project that is run together with ecologists includes development of molecular markers that will enable scientists to identify different mussel species.

Skovde’s high-impact research also extends far beyond the laboratory, where the school collaborates with  Life Science companies, public organisations and other universities to strengthen its research. Through these partnerships, the school has access to specific expertise, highly advanced laboratories and equipment, as well as PhD studies.

Additionally, the university works with business partners like AstraZeneca , Abbott Diagnostics AB and EnviroPlanning to teach industrial PhD students, and also conduct research in the interest of the company. Students who register for an industrial PhD will be employed by these companies, and receive PhD training at the School of Bioscience – a great career experience that enhances their CV tremendously.

In short, studying at a university with a reputable research foundation not only gives you a firm platform on which you can continue learning, but the skills you master also provide a real advantage over others in the real-world.

Click here to view Skovde’s recent research publications

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All images courtesy of University of Skovde

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Psychological Research

Why is research important, learning objectives.

By the end of this section, you will be able to:

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( [link] ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

Some of our ancestors, across the world and over the centuries, believed that trephination—the practice of making a hole in the skull, as shown here—allowed evil spirits to leave the body, thus curing mental illness and other disorders. (credit: “taiproject”/Flickr)

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

USE OF RESEARCH INFORMATION

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the hypothesized link between exposure to media violence and subsequent aggression has been debated in the scientific community for roughly 60 years. Even today, we will find detractors, but a consensus is building. Several professional organizations view media violence exposure as a risk factor for actual violence, including the American Medical Association, the American Psychiatric Association, and the American Psychological Association (American Academy of Pediatrics, American Academy of Child & Adolescent Psychiatry, American Psychological Association, American Medical Association, American Academy of Family Physicians, American Psychiatric Association, 2000).

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding the D.A.R.E. (Drug Abuse Resistance Education) program in public schools ( [link] ). This program typically involves police officers coming into the classroom to educate students about the dangers of becoming involved with alcohol and other drugs. According to the D.A.R.E. website (www.dare.org), this program has been very popular since its inception in 1983, and it is currently operating in 75% of school districts in the United States and in more than 40 countries worldwide. Sounds like an easy decision, right? However, on closer review, you discover that the vast majority of research into this program consistently suggests that participation has little, if any, effect on whether or not someone uses alcohol or other drugs (Clayton, Cattarello, & Johnstone, 1996; Ennett, Tobler, Ringwalt, & Flewelling, 1994; Lynam et al., 1999; Ringwalt, Ennett, & Holt, 1991). If you are committed to being a good steward of taxpayer money, will you fund this particular program, or will you try to find other programs that research has consistently demonstrated to be effective?

The D.A.R.E. program continues to be popular in schools around the world despite research suggesting that it is ineffective.

Link to Learning

Watch this news report to learn more about some of the controversial issues surrounding the D.A.R.E. program.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine you just found out that a close friend has breast cancer or that one of your young relatives has recently been diagnosed with autism. In either case, you want to know which treatment options are most successful with the fewest side effects. How would you find that out? You would probably talk with your doctor and personally review the research that has been done on various treatment options—always with a critical eye to ensure that you are as informed as possible.

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

THE PROCESS OF SCIENTIFIC RESEARCH

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested against the empirical world; in inductive reasoning , empirical observations lead to new ideas ( [link] ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

Psychological research relies on both inductive and deductive reasoning.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests [link] .

The scientific method of research includes proposing hypotheses, conducting research, and creating or modifying theories based on results.

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( [link] ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

Many of the specifics of (a) Freud’s theories, such as (b) his division of the mind into id, ego, and superego, have fallen out of favor in recent decades because they are not falsifiable. In broader strokes, his views set the stage for much of psychological thinking today, such as the unconscious nature of the majority of psychological processes.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

Visit this website to apply the scientific method and practice its steps by using them to solve a murder mystery, determine why a student is in trouble, and design an experiment to test house paint.

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. In this way, research enables scientists to separate fact from simple opinion. Having good information generated from research aids in making wise decisions both in public policy and in our personal lives.

Self Check Questions

Critical thinking questions.

1. In this section, the D.A.R.E. program was described as an incredibly popular program in schools across the United States despite the fact that research consistently suggests that this program is largely ineffective. How might one explain this discrepancy?

2. The scientific method is often described as self-correcting and cyclical. Briefly describe your understanding of the scientific method with regard to these concepts.

Personal Application Questions

3. Healthcare professionals cite an enormous number of health problems related to obesity, and many people have an understandable desire to attain a healthy weight. There are many diet programs, services, and products on the market to aid those who wish to lose weight. If a close friend was considering purchasing or participating in one of these products, programs, or services, how would you make sure your friend was fully aware of the potential consequences of this decision? What sort of information would you want to review before making such an investment or lifestyle change yourself?

1. There is probably tremendous political pressure to appear to be hard on drugs. Therefore, even though D.A.R.E. might be ineffective, it is a well-known program with which voters are familiar.

2. This cyclical, self-correcting process is primarily a function of the empirical nature of science. Theories are generated as explanations of real-world phenomena. From theories, specific hypotheses are developed and tested. As a function of this testing, theories will be revisited and modified or refined to generate new hypotheses that are again tested. This cyclical process ultimately allows for more and more precise (and presumably accurate) information to be collected.

• Psychology. Authored by : OpenStax College. Located at : http://cnx.org/contents/[email protected]:1/Psychology . License : CC BY: Attribution . License Terms : Download for free at http://cnx.org/content/col11629/latest/.

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Business Analytics: What It Is & Why It's Important

• 16 Jul 2019

Business analytics is a powerful tool in today’s marketplace that can be used to make decisions and craft business strategies. Across industries, organizations generate vast amounts of data which, in turn, has heightened the need for professionals who are data literate and know how to interpret and analyze that information.

According to a study by MicroStrategy , companies worldwide are using data to:

• Improve efficiency and productivity (64 percent)
• Achieve more effective decision-making (56 percent)
• Drive better financial performance (51 percent)

The research also shows that 65 percent of global enterprises plan to increase analytics spending.

In light of these market trends, gaining an in-depth understanding of business analytics can be a way to advance your career and make better decisions in the workplace.

“Using data analytics is a very effective way to have influence in an organization,” said Harvard Business School Professor Jan Hammond, who teaches the online course Business Analytics , in a previous interview . “If you’re able to go into a meeting and other people have opinions, but you have data to support your arguments and your recommendations, you’re going to be influential.”

Before diving into the benefits of data analysis, it’s important to understand what the term “business analytics” means.

Check out our video on business analytics below, and subscribe to our YouTube channel for more explainer content!

What Is Business Analytics?

Business analytics is the process of using quantitative methods to derive meaning from data to make informed business decisions.

There are four primary methods of business analysis:

• Descriptive : The interpretation of historical data to identify trends and patterns
• Diagnostic : The interpretation of historical data to determine why something has happened
• Predictive : The use of statistics to forecast future outcomes
• Prescriptive : The application of testing and other techniques to determine which outcome will yield the best result in a given scenario

These four types of business analytics methods can be used individually or in tandem to analyze past efforts and improve future business performance.

Business Analytics vs. Data Science

To understand what business analytics is, it’s also important to distinguish it from data science. While both processes analyze data to solve business problems, the difference between business analytics and data science lies in how data is used.

Business analytics is concerned with extracting meaningful insights from and visualizing data to facilitate the decision-making process , whereas data science is focused on making sense of raw data using algorithms, statistical models, and computer programming. Despite their differences, both business analytics and data science glean insights from data to inform business decisions.

To better understand how data insights can drive organizational performance, here are some of the ways firms have benefitted from using business analytics.

The Benefits of Business Analytics

1. more informed decision-making.

Business analytics can be a valuable resource when approaching an important strategic decision.

When ride-hailing company Uber upgraded its Customer Obsession Ticket Assistant (COTA) in early 2018—a tool that uses machine learning and natural language processing to help agents improve speed and accuracy when responding to support tickets—it used prescriptive analytics to examine whether the product’s new iteration would be more effective than its initial version.

Through A/B testing —a method of comparing the outcomes of two different choices—the company determined that the updated product led to faster service, more accurate resolution recommendations, and higher customer satisfaction scores. These insights not only streamlined Uber’s ticket resolution process, but saved the company millions of dollars.

2. Greater Revenue

Companies that embrace data and analytics initiatives can experience significant financial returns.

Research by McKinsey shows organizations that invest in big data yield a six percent average increase in profits, which jumps to nine percent for investments spanning five years.

Echoing this trend, a recent study by BARC found that businesses able to quantify their gains from analyzing data report an average eight percent increase in revenues and a 10 percent reduction in costs.

These findings illustrate the clear financial payoff that can come from a robust business analysis strategy—one that many firms can stand to benefit from as the big data and analytics market grows.

Related: 5 Business Analytics Skills for Professionals

3. Improved Operational Efficiency

Beyond financial gains, analytics can be used to fine-tune business processes and operations.

In a recent KPMG report on emerging trends in infrastructure, it was found that many firms now use predictive analytics to anticipate maintenance and operational issues before they become larger problems.

A mobile network operator surveyed noted that it leverages data to foresee outages seven days before they occur. Armed with this information, the firm can prevent outages by more effectively timing maintenance, enabling it to not only save on operational costs, but ensure it keeps assets at optimal performance levels.

Why Study Business Analytics?

Taking a data-driven approach to business can come with tremendous upside, but many companies report that the number of skilled employees in analytics roles are in short supply .

LinkedIn lists business analysis as one of the skills companies need most in 2020 , and the Bureau of Labor Statistics projects operations research analyst jobs to grow by 23 percent through 2031—a rate much faster than the average for all occupations.

“A lot of people can crunch numbers, but I think they’ll be in very limited positions unless they can help interpret those analyses in the context in which the business is competing,” said Hammond in a previous interview .

Skills Business Analysts Need

Success as a business analyst goes beyond knowing how to crunch numbers. In addition to collecting data and using statistics to analyze it, it’s crucial to have critical thinking skills to interpret the results. Strong communication skills are also necessary for effectively relaying insights to those who aren’t familiar with advanced analytics. An effective data analyst has both the technical and soft skills to ensure an organization is making the best use of its data.

Improving Your Business Analytics Skills

If you’re interested in capitalizing on the need for data-minded professionals, taking an online business analytics course is one way to broaden your analytical skill set and take your career to the next level

Through learning how to recognize trends, test hypotheses , and draw conclusions from population samples, you can build an analytical framework that can be applied in your everyday decision-making and help your organization thrive.

“If you don’t use the data, you’re going to fall behind,” Hammond said . “People that have those capabilities—as well as an understanding of business contexts—are going to be the ones that will add the most value and have the greatest impact.”

Do you want to leverage the power of data within your organization? Explore our eight-week online course Business Analytics to learn how to use data analysis to solve business problems.

This post was updated on November 14, 2022. It was originally published on July 16, 2019.

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The 10 Most Important Qualities of a Good Teacher, According to Real Educators

This is what it takes to succeed in this challenging career.

It’s a standard teacher interview question : “What do you think is the most important quality of a good teacher?” While everyone has a different answer, there are some that come up more often than others. We asked a group of experienced educators and administrators to share their thoughts on the key qualities of a good teacher. Here’s what they had to say.

1. Patience

This was far and away the most commonly mentioned characteristic by educators in our survey. “Patience can be used in virtually every situation,” says high school ELA teacher Ann Cox. “If a teacher is able to remain calm, consider others’ point of view, and think through scenarios, they will be able to navigate just about anything that comes their way.”

She continues: “Patience helps teachers not to react in the moment when students are off task, disrespectful, etc. It’s also helpful when dealing with angry parents so you don’t say or do something you might regret later. And patience is definitely needed when sitting through meetings and professional development sessions!”

For ELA teacher Kenly CG, patience means “paying attention to each student’s needs and showing that you care about your students’ learning.” UK special school teacher Sarah Brown also advises “remaining calm, listening and observing students’ needs, repeating instructions, and modelling again when necessary.”

Learn more: 7 Ways To Cultivate Patience at Calm

2. Empathy and Compassion

These two traits were a close second behind patience when we asked about the qualities of a good teacher. “They have to know you care before they can learn from you,” explains middle school teacher Samantha Wheeler. As a special ed teacher from New York notes: “You have to teach the child before you can teach the curriculum.”

“Empathy is a constant exercise in stepping outside of yourself and your perspective to see the children you teach for who they are,” notes Indiana preschool teacher Maile C. Quinton. “Contact talks. Get down on the same level as a child, listen to what they say, and emphasize their shared feelings by validating them. Don’t try to silver lining everything—you can validate a situation, a moment, an emotion without condoning a behavior or a problem. Empathy isn’t sympathy.”

Learn more: Cultivating Empathy at American Psychological Association

3. Flexibility and Adaptability

Being open-minded to change is critical in this field. So many of the educators we surveyed agree with this North Carolina ESL teacher: “There is nothing constant in teaching. Good teachers have to be able to adapt to the changing needs of students, to new administrators, new curricula, new colleagues, and new technology.”

“With so many different needs from students and parents, teachers need to be flexible to accommodate and meet students where they are at,” says elementary school counselor Lisa K, while high school English teacher Nicole P. adds, “There are often times where you need to think on your feet, so being flexible is important to go with the flow in different situations.”

Elementary special ed teacher Brianna Vuori sums it up like this: “We can only begin to predict what the future will hold and with that what we need to prepare students for, so adaptability is critical to being able to survive and thrive in this ever-changing profession.”

Learn more: Teachers, To Succeed, It’s Important To Be Flexible at EdWeek

Teaching can be a tough gig, and you’ll need to be dedicated and passionate in order to thrive. “Passion is what drives us forward and what sees us through rough times,” emphasizes ELS department head Katerina T. “It is the driving force behind every lesson plan or decision we make and what lies at the foundation of life-changing relationships with our students.”

“Teachers that have passion will always find a way to meet the demands of the job,” says Florida teacher Jamie Cabaniss. “Teachers can lean on their passions when feeling frustrated and burnt out. Passions are what reignite us to get back in the classroom to teach our hearts out.”

Preschool teacher Christina H. couldn’t agree more. “You have to have a love and passion for what you are doing,” she declares. “Teaching isn’t just ‘teaching.’ It is also being a second mom (or dad), a counselor, a referee, a nurse, and so much more. To wear these many hats, you need to love what you are doing. You also need to love your students to help them succeed. Loving them on their best and worst days is what will make you successful.”

Learn more: 5 Ways Educators Can Grow and Sustain a Passion for Teaching at NSHSS

5. Kindness

Over and over again, educators emphasized kindness as one of the most important qualities of a good teacher. “We are in the business of teaching human beings. We must teach them to be good people,” stresses Adam Peterson, Illinois music teacher and tutor.

Tina Jones agrees: “Teachers need to be kind, caring, compassionate and understanding. In our world today, with kids getting so much information and misinformation via social media, children need examples of those qualities more than ever.”

Learn more: The Case for Professional Kindness in Teaching at Teacher magazine

6. Collaboration

“Good teachers need to be able to give ideas, ask for help, share, and communicate with coworkers and families,” advises one Washington second grade teacher. “Be able to take suggestions, offer help, and not take things personally.”

Teachers regularly have to work collaboratively, and not just with their fellow colleagues and administrators. Developing strong, collaborative relationships with parents and families is vital. To succeed in this field, you need to learn to work well as part of a team.

Learn more: The Importance of Teacher Collaboration at American University School of Education

7. Professionalism

It probably feels like professionalism should be a given in any job, but it’s one of the most important qualities of a good teacher because you need to gain and maintain the respect of students, families, and administration. “Some days are going to be frustrating, discouraging, and stressful,” warns an Ohio 7th grade science teacher, “but you need to remain professional by staying calm and encouraging and being a good mentor for your students.”

Learn more: The Five P’s of Professionalism in Teaching at Grand Canyon University

8. Sense of Humor

There’s no doubt about it, teachers do best when they have a sense of humor. “Laughing at yourself is a great relief, and laughing with children builds trust with them,” says Maile C. Quinton. Find ways to bring humor into your classroom, and you’ll find that students relax and learn a little more easily. (Plus, it’s much easier to deal with the small daily annoyances of teaching when you learn to laugh them off!)

Learn more: Engaging Students With Humor at Association for Psychological Science

9. Open-Mindedness

“Be open to learning from more (and even less) experienced teachers, and open to trying out new teaching and classroom management methods,” recommends middle school ELA teacher Abigail Perry.

“We are building relationships with a diverse student population,” notes Cheryl Rizzo, a middle school ELA teacher. “This can be a source of stress or create divide. However, with an open mind, it can create new opportunities or a chance to grow. Teachers are open-minded when they allow students to have a voice and take an active part in their education.”

Part of being open-minded means demonstrating a willingness to grow and a dedication to growth mindset. According to a literacy coach from North Carolina: “This job requires constant reflection, learning, and growth.”

Learn more: How To Be Open-Minded and Why It Matters at Very Well Mind

10. Resilience

Marilyn Weber, a retired principal from Massachusetts, names this as the quality she looked for in a good teacher. “In order to navigate the world of education with all its related constituencies and responsibilities, an educator needs to be knowledgeable, flexible, an impeccable communicator, and should be able to withstand all the highs and lows of what comes their way and needs to be accomplished,” she states. She added that educators must be able to “do so without allowing any of that to shake their confidence and resolve in order to do what’s best for their students.”

That’s a tall order! Fortunately, Andrea Perry, a certified coach for educator well-being, has some advice. “Develop emotional intelligence. It’s critical for keeping our calm and being proactive, not reactive. This supports the teacher not only in serving their students well but also helps them remain joyfully in the profession as well.”

Learn more: How To Be Resilient at Work at Positive Psychology

More Qualities of a Good Teacher To Consider

These qualities of a good teacher didn’t make the top 10, but they’re definitely worthwhile attributes for every educator to cultivate:

• Inclusive mindset: “There is such a huge stigma against disabilities and it is often hushed away, which creates shame. All children are general education first and receive special education services second. Build a classroom community with respect by explaining differences to students and celebrating everyone’s strengths. True inclusivity helps all students grow, not just the students in a special education classroom. True inclusivity should help you as a teacher grow.” —Katie M., Functional Life Skills Teacher
• Love for all children: “A good teacher must truly like kids, even the naughty ones. Too often teachers only seem to like the ‘good’ kids or the ones from ‘good’ families. They attribute the student’s behavior to something personal or bad about them. Instead, those are the kids in whom we need to diligently look for the good.” —Kathryn Roe, retired educator and administrator
• Love of learning
• Problem-solving skills
• Hopefulness
• Imagination
• Reliability
• Knowledge of content and pedagogy
• High expectations

What do you feel are the most important qualities of a good teacher? Come share your thoughts in the We Are Teachers HELPLINE group on Facebook .

Plus, the complete guide to becoming a teacher, from choosing a college to landing a job ..

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8 Why Is Research Important?

[latexpage]

Learning Objectives

By the end of this section, you will be able to:

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( [link] ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

USE OF RESEARCH INFORMATION

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the hypothesized link between exposure to media violence and subsequent aggression has been debated in the scientific community for roughly 60 years. Even today, we will find detractors, but a consensus is building. Several professional organizations view media violence exposure as a risk factor for actual violence, including the American Medical Association, the American Psychiatric Association, and the American Psychological Association (American Academy of Pediatrics, American Academy of Child & Adolescent Psychiatry, American Psychological Association, American Medical Association, American Academy of Family Physicians, American Psychiatric Association, 2000).

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding the D.A.R.E. (Drug Abuse Resistance Education) program in public schools ( [link] ). This program typically involves police officers coming into the classroom to educate students about the dangers of becoming involved with alcohol and other drugs. According to the D.A.R.E. website (www.dare.org), this program has been very popular since its inception in 1983, and it is currently operating in 75% of school districts in the United States and in more than 40 countries worldwide. Sounds like an easy decision, right? However, on closer review, you discover that the vast majority of research into this program consistently suggests that participation has little, if any, effect on whether or not someone uses alcohol or other drugs (Clayton, Cattarello, & Johnstone, 1996; Ennett, Tobler, Ringwalt, & Flewelling, 1994; Lynam et al., 1999; Ringwalt, Ennett, & Holt, 1991). If you are committed to being a good steward of taxpayer money, will you fund this particular program, or will you try to find other programs that research has consistently demonstrated to be effective?

Watch this news report to learn more about some of the controversial issues surrounding the D.A.R.E. program.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine you just found out that a close friend has breast cancer or that one of your young relatives has recently been diagnosed with autism. In either case, you want to know which treatment options are most successful with the fewest side effects. How would you find that out? You would probably talk with your doctor and personally review the research that has been done on various treatment options—always with a critical eye to ensure that you are as informed as possible.

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

THE PROCESS OF SCIENTIFIC RESEARCH

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested against the empirical world; in inductive reasoning , empirical observations lead to new ideas ( [link] ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

Play this “Deal Me In” interactive card game to practice using inductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests [link] .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( [link] ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

Visit this website to apply the scientific method and practice its steps by using them to solve a murder mystery, determine why a student is in trouble, and design an experiment to test house paint.

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. In this way, research enables scientists to separate fact from simple opinion. Having good information generated from research aids in making wise decisions both in public policy and in our personal lives.

Review Questions

Scientific hypotheses are ________ and falsifiable.

________ are defined as observable realities.

Scientific knowledge is ________.

A major criticism of Freud’s early theories involves the fact that his theories ________.

• were too limited in scope
• were too outrageous
• were too broad
• were not testable

Critical Thinking Questions

In this section, the D.A.R.E. program was described as an incredibly popular program in schools across the United States despite the fact that research consistently suggests that this program is largely ineffective. How might one explain this discrepancy?

There is probably tremendous political pressure to appear to be hard on drugs. Therefore, even though D.A.R.E. might be ineffective, it is a well-known program with which voters are familiar.

The scientific method is often described as self-correcting and cyclical. Briefly describe your understanding of the scientific method with regard to these concepts.

This cyclical, self-correcting process is primarily a function of the empirical nature of science. Theories are generated as explanations of real-world phenomena. From theories, specific hypotheses are developed and tested. As a function of this testing, theories will be revisited and modified or refined to generate new hypotheses that are again tested. This cyclical process ultimately allows for more and more precise (and presumably accurate) information to be collected.

Personal Application Questions

Healthcare professionals cite an enormous number of health problems related to obesity, and many people have an understandable desire to attain a healthy weight. There are many diet programs, services, and products on the market to aid those who wish to lose weight. If a close friend was considering purchasing or participating in one of these products, programs, or services, how would you make sure your friend was fully aware of the potential consequences of this decision? What sort of information would you want to review before making such an investment or lifestyle change yourself?

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Americans’ Dismal Views of the Nation’s Politics

1. the biggest problems and greatest strengths of the u.s. political system, table of contents.

• The impact of partisan polarization
• Persistent concerns over money in politics
• Views of the parties and possible changes to the two-party system
• Other important findings
• Explore chapters of this report
• In their own words: Americans on the political system’s biggest problems
• In their own words: Americans on the political system’s biggest strengths
• Are there clear solutions to the nation’s problems?
• Evaluations of the political system
• Trust in the federal government
• Feelings toward the federal government
• The relationship between the federal and state governments
• Americans’ ratings of their House member, governor and local officials
• Party favorability ratings
• Most characterize their party positively
• Quality of the parties’ ideas
• Influence in congressional decision-making
• Views on limiting the role of money in politics
• Views on what kinds of activities can change the country for the better
• How much can voting affect the future direction of the country?
• Views of members of Congress
• In their own words: Americans’ views of the major problems with today’s elected officials
• How much do elected officials care about people like me?
• What motivates people to run for office?
• Quality of recent political candidates
• In elections, is there usually at least one candidate who shares your views?
• What the public sees as most important in political candidates
• Impressions of the people who will be running for president in 2024
• Views about presidential campaigns
• How much of an impact does who is president have on your life?
• Whose priorities should the president focus on?
• How different are the Republican and Democratic parties?
• Views of how well the parties represent people’s interests
• What if there were more political parties?
• Would more parties make solving problems easier or harder?
• How likely is it that an independent candidate will become president?
• Americans who feel unrepresented by the parties have highly negative views of the political system
• Views of the Electoral College
• Should the size of the U.S. House of Representatives change?
• Senate seats and population size
• Younger adults more supportive of structural changes
• Politics in a single word or phrase: An outpouring of negative sentiments
• Negative emotions prevail when Americans think about politics
• Americans say the tone of political debate in the country has worsened
• Which political topics get too much – and too little – attention?
• Majority of Americans find it stressful to talk politics with people they disagree with
• Acknowledgments

The public sees a number of specific problems with American politics. Partisan fighting, the high cost of political campaigns, and the outsize influence of special interests and lobbyists are each seen as characteristic of the U.S. political system by at least 84% of Americans.

Yet 63% also say that “ordinary Americans care about making the political system work well” is a good description of U.S. politics today. Still, when asked to describe a strength of the political system in their own words, more than half either say “nothing” (22%) or decline to give an answer (34%).

Americans view negative statements as better descriptions of the political system than positive ones

More than eight-in-ten adults say that each of the following is at least a somewhat good description of the U.S. political system today:

• Republicans and Democrats are more focused on fighting each other than on solving problems (86%);
• The cost of political campaigns makes it hard for good people to run for office (85%);
• Special interest groups and lobbyists have too much say in what happens in politics (84%).

About six-in-ten (63%) think ordinary Americans want to make the political system work well. This is the rare positive sentiment that a majority views as a good descriptor of the political system.

Fewer than half of adults hold the view that the government deserves more credit than it gets: Majorities say that “the federal government does more for ordinary Americans than people give it credit for” (59%) and “Congress accomplishes more than people give it credit for” (65%) are both bad descriptions of the political system.

Nearly seven-in-ten adults express frustration with the availability of unbiased information about politics: 68% say the statement “it is easy to find unbiased information about what is happening in politics” is not a good description of the political system.

And just 22% of Americans say that political leaders facing consequences for acting unethically is a good description of the political system. They are more than three times as likely to say that this is a bad description (76% say this).

Many critiques of the political system are bipartisan

Partisans have similar views of many of the descriptions of the political system included in the survey.

Overwhelming majorities in both parties think there is too much partisan fighting, campaigns cost too much, and lobbyists and special interests have too much say in politics. And just 24% of Democrats and Democratic-leaning independents and 20% of Republicans and Republican leaners say that political leaders face consequences if they act unethically.

The widest partisan gap is over a description of the federal government. Democrats are roughly twice as likely as Republicans to say “the federal government does more for ordinary Americans than people give it credit for” (54% vs. 26%).

There is a narrower gap in views of Congress’ accomplishments: 37% of Democrats and 28% of Republicans say it accomplishes more than people give it credit for.

Democrats are also more likely to say, “It is easy to find unbiased information about what is happening in politics” (36% of Democrats and 25% of Republicans say this is a good description of the political system today), while Republicans are slightly more likely than Democrats to view ordinary Americans as wanting to make the political system work well (67% of Republicans and 61% of Democrats say this is a good description).

When asked to describe in their own words the biggest problem with the political system in the U.S. today, Americans point to a wide range of factors.

Negative characteristics attributed to politicians and political leaders are a common complaint: 31% of U.S. adults say politicians are the biggest problem with the system, including 15% who point to greed or corruption and 7% who cite dishonesty or a lack of trustworthiness.

The biggest problem, according to one woman in her 50s, is that politicians are “hiding the truth and fulfilling their own agendas.” Similarly, a man in his 30s says, “They don’t work for the people. They are too corrupt and busy filling their pockets.”

Explore more voices: The political system’s biggest problems

What do you see as the biggest problem with the political system in the U.S. today?

“An almost total lack of credibility and trust. Coupled with a media that’s so biased, that they’ve lost all objectivity.” –Man, 70s

“Lying about intentions or not following through with what elected officials said they would do.” –Woman, 20s

“Blind faith in political figures.” –Woman, 50s

“Our elected officials would rather play political games than serve the needs of their constituents.” –Woman, 50s

“Same politicians in office too long.” –Woman, 30s

“Extremism on both sides exploited by the mainstream media for ratings. It is making it impossible for both parties to work together.” –Man, 30s

“It has become too polarized. No one is willing to compromise or be moderate.” –Woman, 40s

“Too much money in politics coming from large corporations and special interest.” –Man, 30s

“The people have no say in important matters, we have NO representation at all. Our lawmakers are isolated and could care less what we want.” –Man, 60s

About two-in-ten adults cite deep divisions between the parties as the biggest problem with the U.S. political system, with respondents describing a lack of cooperation between the parties or among elected leaders in Washington.

“Both of the political parties are so busy trying to stop the other party, they are wasting their opportunities to solve the problems faced by our nation,” in the view of one man in his 70s.

Even as some blame polarization, others (10% of respondents) identify the other party as the system’s biggest problem. Some Republicans say that the biggest problem is “Democrats” while some Democrats simply say “Republicans.”

Smaller but substantial shares of adults name the media and political discourse (9%), the influence of money in politics (7%), government’s perceived failures (6%), specific policy areas and issues (6%) or problems with elections and voting (4%) as the biggest problem with the political system today.

Far fewer adults name a specific strength of the political system today when asked to describe the system’s biggest strength in their own words. More than half either say that the system lacks a biggest strength (22%) or decline to answer (34%). As one woman in her 60s writes, “I’m not seeing any strengths!”

Among those who do identify strengths of the U.S. political system, the structure of political institutions and the principles that define the constitutional order are named most frequently (by 12% of respondents). Many respondents specifically point to the Constitution itself or refer to the separation of powers or the checks and balances created by the Constitution.

A man in his 20s believes that the “separation of powers and federalism work pretty well,” while one in his 30s writes that the system’s greatest strength is “the checks and balances to make sure that monumental changes aren’t made unilaterally.”

Explore more voices: The political system’s biggest strengths

What do you see as the biggest strength of the U.S. political system today?

“Everyone getting a say; democracy.” –Woman, 40s

“The right to have your opinions heard.” –Man, 60s

“In spite of our differences, we are still a democracy, and I believe there are people within our government who still care and are interested in the betterment of our country.” –Woman, 50s

“The freedom of speech and religion” –Woman, 50s

“If we have fair, honest elections we can vote out the corruption and/or incompetent politicians.” –Man, 70s

“The Constitution.” –Man, 50s

“The checks and balances to control the power of any office. The voice of the people and the options to remove an official from office.” –Man, 60s

“New, younger voices in government.” –Woman, 40s

“If we can’t get more bipartisanship we’ll become weaker. Our biggest strength is our working together.” –Woman, 60s

“The way that every two years the people get to make their voice heard.” –Man, 30s

About one-in-ten (9%) refer to individual freedoms and related democratic values, while a similar share (8%) discuss the right to vote and the existence of free elections. A woman in her 70s echoes many similar comments when she points to “the possibility of change in upcoming elections.”

However, even some of the descriptions of positive characteristics of the system are couched in respondents’ doubts about the way the system is working today. One woman in her 50s adds a qualification to what she views as the system’s biggest strength, saying, “Theoretically every voter has a say.”

Smaller shares of the public point to the positive characteristics of some politicians (4%) or the positive characteristics of the American people (4%) as reasons for optimism.

The public remains roughly evenly split over whether there are clear solutions to the biggest issues facing the country. Half of Americans today say there are clear solutions to most of the big issues facing the country, while about as many (48%) say most big issues don’t have clear solutions.

There are relatively modest demographic and political differences in perceptions of whether the solutions to the nations’ problems are clear or not.

While both men and women are relatively divided on this question, women are 6 percentage points more likely to think the big issues facing the country don’t have clear solutions.

Race and ethnicity

While 43% of Hispanic adults and about half of Black (50%) and White (48%) adults say there aren’t clear solutions for most big issues, that rises to 62% among Asian adults.

Age differences on this question are modest, but those under 30 are slightly more likely than those 30 and older to say most big issues have clear solutions.

Partisanship and political engagement

Both Republicans and Democrats are relatively split on this question, though Republicans are slightly more likely to say there are clear solutions to most big issues.

Those with higher levels of political engagement are more likely to say there are clear solutions to most big issues facing the country.

About six-in-ten adults with high levels of political engagement (61%) say there are clear solutions to big issues today, compared with half of those with medium levels of engagement and 41% of those with lower engagement.

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