study or research

Research vs. Study

What's the difference.

Research and study are two essential components of the learning process, but they differ in their approach and purpose. Research involves a systematic investigation of a particular topic or issue, aiming to discover new knowledge or validate existing theories. It often involves collecting and analyzing data, conducting experiments, and drawing conclusions. On the other hand, study refers to the process of acquiring knowledge or understanding through reading, memorizing, and reviewing information. It is typically focused on a specific subject or discipline and aims to deepen one's understanding or mastery of that subject. While research is more exploratory and investigative, study is more focused on acquiring and retaining information. Both research and study are crucial for intellectual growth and expanding our knowledge base.

Further Detail

Introduction.

Research and study are two fundamental activities that play a crucial role in acquiring knowledge and understanding. While they share similarities, they also have distinct attributes that set them apart. In this article, we will explore the characteristics of research and study, highlighting their differences and similarities.

Definition and Purpose

Research is a systematic investigation aimed at discovering new knowledge, expanding existing knowledge, or solving specific problems. It involves gathering and analyzing data, formulating hypotheses, and drawing conclusions based on evidence. Research is often conducted in a structured and scientific manner, employing various methodologies and techniques.

On the other hand, study refers to the process of acquiring knowledge through reading, memorizing, and understanding information. It involves examining and learning from existing materials, such as textbooks, articles, or lectures. The purpose of study is to gain a comprehensive understanding of a particular subject or topic.

Approach and Methodology

Research typically follows a systematic approach, involving the formulation of research questions or hypotheses, designing experiments or surveys, collecting and analyzing data, and drawing conclusions. It often requires a rigorous methodology, including literature review, data collection, statistical analysis, and peer review. Research can be qualitative or quantitative, depending on the nature of the investigation.

Study, on the other hand, does not necessarily follow a specific methodology. It can be more flexible and personalized, allowing individuals to choose their own approach to learning. Study often involves reading and analyzing existing materials, taking notes, summarizing information, and engaging in discussions or self-reflection. While study can be structured, it is generally less formalized compared to research.

Scope and Depth

Research tends to have a broader scope and aims to contribute to the overall body of knowledge in a particular field. It often involves exploring new areas, pushing boundaries, and generating original insights. Research can be interdisciplinary, involving multiple disciplines and perspectives. The depth of research is often extensive, requiring in-depth analysis, critical thinking, and the ability to synthesize complex information.

Study, on the other hand, is usually more focused and specific. It aims to gain a comprehensive understanding of a particular subject or topic within an existing body of knowledge. Study can be deep and detailed, but it is often limited to the available resources and materials. While study may not contribute directly to the advancement of knowledge, it plays a crucial role in building a solid foundation of understanding.

Application and Output

Research is often driven by the desire to solve real-world problems or contribute to practical applications. The output of research can take various forms, including scientific papers, patents, policy recommendations, or technological advancements. Research findings are typically shared with the academic community and the public, aiming to advance knowledge and improve society.

Study, on the other hand, focuses more on personal development and learning. The application of study is often seen in academic settings, where individuals acquire knowledge to excel in their studies or careers. The output of study is usually reflected in improved understanding, enhanced critical thinking skills, and the ability to apply knowledge in practical situations.

Limitations and Challenges

Research faces several challenges, including limited resources, time constraints, ethical considerations, and the potential for bias. Conducting research requires careful planning, data collection, and analysis, which can be time-consuming and costly. Researchers must also navigate ethical guidelines and ensure the validity and reliability of their findings.

Study, on the other hand, may face challenges such as information overload, lack of motivation, or difficulty in finding reliable sources. It requires self-discipline, time management, and the ability to filter and prioritize information. Without proper guidance or structure, study can sometimes lead to superficial understanding or misconceptions.

In conclusion, research and study are both essential activities in the pursuit of knowledge and understanding. While research focuses on generating new knowledge and solving problems through a systematic approach, study aims to acquire and comprehend existing information. Research tends to be more formalized, rigorous, and contributes to the advancement of knowledge, while study is often more flexible, personalized, and focused on individual learning. Both research and study have their unique attributes and challenges, but together they form the foundation for intellectual growth and development.

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Study vs. Research — What's the Difference?

Difference Between Study and Research

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Research vs. study

The confusion about these words is that they can both be either nouns or verbs. If you ask someone, "Does 'studies' mean the same as 'researches'?" you may hear "Yes," but it is only true if they are used as verbs. As nouns, they have subtly different meanings.

"This team has done a lot of good research. I just read their latest study, which they wrote about calcium in germinating soybeans. It described several interesting experiments."

research 1. to perform a systematic investigation

1. "What kind of scientist is he? He's a botanist. He researches plants."

study 1. to perform a systematic investigation; 2. to actively learn or memorize academic material

1. "What kind of scientist is he? He's a botanist. He studies plants."

2. "Mindy studies every day. That is why she gets such excellent grades. She wants to go to college to study math."

Some authors say "research" when they mean "study." "Research," as a verb, means "to perform a study or studies," but "research" as a noun refers to the sum of many studies. "Chemical research" means the sum of all chemical studies. If you find yourself writing "a research" or "in this research," change it to "a study" or "in this study."

research The act of performing research. Also, the results of research. Note that "research" is a mass noun. It is already plural in meaning but grammatically singular. If you want to indicate more than one type, say "bodies of research" or "pieces of research," not "researches."

"Dr. Lee was a prolific scientist. She performed a great deal of research over her long career."

study A single research project or paper.

"Dr. Lee was a prolific scientist. She performed a great many studies over her long career."

The noun "study" refers to a single paper or project. You can replace "paper" with "study" in almost all cases (but not always the other way around), to the point where you can say "I wrote a study." The noun "research" means more like a whole body of research including many individual studies: The research of a field. The lifetime achievements of a scientist or research team.

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods.

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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Doing Research: A New Researcher’s Guide pp 1–15 Cite as

What Is Research, and Why Do People Do It?

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  
• Open Access
• First Online: 03 December 2022

15k Accesses

Part of the book series: Research in Mathematics Education ((RME))

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.

You have full access to this open access chapter,  Download chapter PDF

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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Research methods--quantitative, qualitative, and more: overview.

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As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

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Meaning of research in English

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• He has dedicated his life to scientific research.
• He emphasized that all the people taking part in the research were volunteers .
• The state of Michigan has endowed three institutes to do research for industry .
• I'd like to see the research that these recommendations are founded on.
• It took months of painstaking research to write the book .
• absorptive capacity
• dream something up
• modularization
• nanotechnology
• non-imitative
• operations research
• think outside the box idiom
• think something up
• uninventive
• study What do you plan on studying in college?
• major US She majored in philosophy at Harvard.
• cram She's cramming for her history exam.
• revise UK I'm revising for tomorrow's test.
• review US We're going to review for the test tomorrow night.
• research Scientists are researching possible new treatments for cancer.
• The amount of time and money being spent on researching this disease is pitiful .
• We are researching the reproduction of elephants .
• She researched a wide variety of jobs before deciding on law .
• He researches heart disease .
• The internet has reduced the amount of time it takes to research these subjects .
• adjudication
• analytically
• interpretable
• interpretive
• interpretively
• investigate
• reinvestigate
• reinvestigation
• risk assessment
• run over/through something
• run through something

You can also find related words, phrases, and synonyms in the topics:

Related word

Research | intermediate english, research | business english, examples of research, collocations with research.

These are words often used in combination with research .

Click on a collocation to see more examples of it.

Translations of research

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Research or Researches: Which is Correct? Simple English Explanations

Research or researches ? Which one is correct?!

There seems to be a lot of misinformation about this on the web, as most people (including native English speakers) get this one wrong!

We can use “research” as a noun or verb . Researches can be the third person singular of the verb “research.” Researches can also be used as a plural noun for “research,” but it is rarely used.

Meaning of Research (Verb and Noun)

By definition, “ research” (verb form) means to investigate or search carefully. It is typically related to studious inquiries or examinations.

Here are some examples with the verb “research”:

• “He researched the history of the building.”
• “She is researching how many people speak a particular language.”
• “I need to research this.”
• “We have been researching a new method.”
• “They are researching different options for the company.”
• “I researched every single product before I made my purchase.”
• You should research the pros and cons before you make a decision .
• “He is researching his family tree.”
• She has been researching her options for college.

When used as a noun, the word “research” typically refers to the activity of investigating or examining a subject in-depth with the aim of discovering new facts or information.

It can also refer to the resulting product of this activity.

Here are some examples with the noun “research”:

• “The scientists conducted research on the properties of a new material.”
• “She published her first paper on the results of her research.”
• If you want to write a paper on the dangers of smoking, you will need to do some research on the topic.
• “The research was published in a leading journal.”
• “They are funding market research.”
• “This is a new area of research for me.”
• “I need to do some research on this subject.”
• “Can you please send me your latest research?”

Research or researches?

• Research (singular noun)
• Researches (plural noun)

In a nutshell, we use research as a singular noun and researches as a plural noun, but it is very rare to say the term researches.

It is preferred to say “pieces of research,” “research studies” or “research projects” when talking about more than one.

Researches can also be used as a verb for the third person singular in the simple present tense. For example, “he researches on the internet for his school project.”

Research (simple present tense):

• I research,
• you research,
• he researches,
• she researches,
• it researches,
• we research,
• they research.

Research as a Noun

Research can be a countable and uncountable noun.

As a noun, “research” is usually used as uncountable. For example, we could say, “the research is able to determine the demand for health drinks.”

The plural countable noun researches is rarely used. It is used to distinguish between one or more sets of research.

For example, we could say “research conducted at Trinity College and University College Dublin” (we don’t know if this is a joint research project or a separate research project in both colleges).

Or we could say “researches conducted at Trinity College and University College Dublin” (separate research projects carried out at the colleges).

Is it correct to say researches ?

As you can see from our examples, it is correct to say researches.

You must be warned, however, that while we can use researches as a plural countable noun, most English speakers have never heard this and may think this is incorrect.

Native English speakers prefer to say “some research,” “research studies,” or “research projects” rather than researches nowadays.

Researches as a term is seen as archaic and old-fashioned. Therefore, it is rarely, if ever used.

Can we say a research ?

While “research” can be used as a countable and uncountable noun, it is never correct to say “a research.” However, we can say “a research student,” “much research,” or “some research.”

To make research or to do research?

We never say “make research.” Instead, you can say, “do research,” “conduct research,” “perform research,” or “carry out research.”

When do we say researches?

When using “research” as the verb, we often say researches.

It is much more common to use researches in the third person simple present (he/she/it).

For example, we could say, “he researches for his project in the library.”

Researches can also be used as a noun, as mentioned earlier.

Alternative Ways to Say Researches (noun)

• His researches prove that the disease is a genetic disorder.
• His research proves that the disease is a genetic disorder.
• His research studies prove that the disease is a genetic disorder.
• His research projects prove that the disease is a genetic disorder.
• His pieces of research prove that the disease is a genetic disorder.
• His findings prove that the disease is a genetic disorder.
• His research results prove that the disease is a genetic disorder.

How do you pronounce research ?

“Research” (verb form) is pronounced as ri-SERCH in American English but may vary across different accents.

“Research” (noun form) is pronounced as REE-serch in American English but may vary across different accents.

Therefore, you may choose to pronounce both the verb and the noun in the same way (REE-serch or ri-SERCH) without causing any confusion.

You may also be interested in: 15 Best Online English Courses Free & Paid (2022)

In Conclusion

Those are the rules for the word research and researches. While researches is a correct word, it is seldom used as a plural noun.

“Research” is mostly used as an uncountable noun or verb.

If you are unsure whether to use research or researches , it is best to use “research” as the noun. This will avoid any confusion and misunderstanding.

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Stanford Medicine study flags unexpected cells in lung as suspected source of severe COVID

A previously overlooked type of immune cell allows SARS-CoV-2 to proliferate, Stanford Medicine scientists have found. The discovery has important implications for preventing severe COVID-19.

April 10, 2024 - By Bruce Goldman

In an uninfected interstitial macrophage, the nucleus (purple) and outer cell membrane (blue) are intact. In an infected interstitial macrophage, the nucleus is shattered, copious newly made viral components (red) clump together, and the cell broadcasts inflammatory and scar-tissue-inducing chemical signals (yellow). Emily Moskal

The lung-cell type that’s most susceptible to infection by SARS-CoV-2, the virus that causes COVID-19, is not the one previously assumed to be most vulnerable. What’s more, the virus enters this susceptible cell via an unexpected route. The medical consequences may be significant.

Stanford Medicine investigators have implicated a type of immune cell known as an interstitial macrophage in the critical transition from a merely bothersome COVID-19 case to a potentially deadly one. Interstitial macrophages are situated deep in the lungs, ordinarily protecting that precious organby, among other things, engorging viruses, bacteria, fungi and dust particles that make their way down our airways. But it’s these very cells, the researchers have shown in a study published online April 10 in the  Journal of Experimental Medicine , that of all known types of cells composing lung tissue are most susceptible to infection by SARS-CoV-2.

SARS-CoV-2-infected interstitial macrophages, the scientists have learned, morph into virus producersand squirt out inflammatory and scar-tissue-inducing chemical signals, potentially paving the road to pneumonia and damaging the lungs to the point where the virus, along with those potent secreted substances, can break out of the lungs and wreak havoc throughout the body.

The surprising findings point to new approaches in preventing a SARS-CoV-2 infection from becoming a life-threatening disease. Indeed, they may explain why monoclonal antibodies meant to combat severe COVID didn’t work well, if at all — and when they did work, it was only when they were administered early in the course of infection, when the virus was infecting cells in the upper airways leading to the lungs but hadn’t yet ensconced itself in lung tissue.

The virus surprises

“We’ve overturned a number of false assumptions about how the virus actually replicates in the human lung,” said  Catherine Blish , MD, PhD, a professor of infectious diseases and of microbiology and immunology and the George E. and Lucy Becker Professor in Medicine and associate dean for basic and translational research.

Blish is the co-senior author of the study, along with  Mark Krasnow , MD, PhD, the Paul and Mildred Berg Professor of biochemistry and the Executive Director of the Vera Moulton Wall Center for pulmonary vascular disease.

“The critical step, we think, is when the virus infects interstitial macrophages, triggering a massive inflammatory reaction that can flood the lungs and spread infection and inflammation to other organs,” Krasnow said. Blocking that step, he said, could prove to be a major therapeutic advance. But there’s a plot twist: The virus has an unusual way of getting inside these cells — a route drug developers have not yet learned how to block effectively — necessitating a new focus on that alternative mechanism, he added.

Catherine Blish

In a  paper  published in  Nature  in early 2020, Krasnow and his colleagues including then-graduate student Kyle Travaglini, PhD — who is also one of the new study’s co-lead authors along with MD-PhD student  Timothy Wu  — described a technique they’d worked out for isolating fresh human lungs; dissociating the cells from one another; and characterizing them, one by one, on the basis of which genes within each cell were active and how much so. Using that technique, the Krasnow lab and collaborators were able to discern more than 50 distinct cell types, assembling an atlas of healthy lung cells.

“We’d just compiled this atlas when the COVID-19 pandemic hit,” Krasnow said. Soon afterward, he learned that Blish and  Arjun Rustagi , MD, PhD, instructor of infectious diseases and another lead co-author of the study, were building an ultra-safe facility where they could safely grow SARS-CoV-2 and infect cells with it.

A collaboration ensued. Krasnow and Blish and their associates obtained fresh healthy lung tissue excised from seven surgical patients and five deceased lung donors whose lungs were virus-free but for one reason or another not used in transplants. After infecting the lung tissue with SARS-CoV-2 and waiting one to three days for the infection to spread, they separated and typed the cells to generate an infected-lung-cell atlas, analogous to the one Krasnow’s team had created with healthy lung cells. They saw most of the cell types that Krasnow’s team had identified in healthy lung tissue.

Now the scientists could compare pristine versus SARS-CoV-2-infected lungs cells of the same cell type and see how they differed: They wanted to know which cells the virus infected, how easily SARS-CoV-2 replicated in infected cells, and which genes the infected cells cranked up or dialed down compared with their healthy counterparts’ activity levels. They were able to do this for each of the dozens of different cell types they’d identified in both healthy and infected lungs.

“It was a straightforward experiment, and the questions we were asking were obvious,” Krasnow said. “It was the  answers  we weren’t prepared for.”

It’s been assumed that the cells in the lungs that are most vulnerable to SARS-CoV-2 infection are those known as alveolar type 2 cells. That’s because the surfaces of these cells, along with those of numerous other cell types in the heart, gut and other organs, sport many copies of a molecule known as ACE2. SARS-CoV-2 has been shown to be able to grab onto ACE2 and manipulate it in a way that allows the virus to maneuver its way into cells.

Alveolar type 2 cells are somewhat vulnerable to SARS-CoV-2, the scientists found. But the cell types that were by far the most frequently infected turned out to be two varieties of a cell type called a macrophage.

Virus factories

The word “macrophage” comes from two Greek terms meaning, roughly, “big eater.” This name is not unearned. The air we inhale carries not only oxygen but, unfortunately, tiny airborne dirt particles, fungal spores, bacteria and viruses. A macrophage earns its keep by, among other things, gobbling up these foreign bodies.

Mark Krasnow

The airways leading to our lungs culminate in myriad alveoli, minuscule one-cell-thick air sacs, whichare abutted by abundant capillaries. This interface, called the interstitium, is where oxygen in the air we breathe enters the bloodstream and is then distributed to the rest of the body by the circulatory system.

The two kinds of SARS-CoV-2-susceptible lung-associated macrophages are positioned in two different places. So-called alveolar macrophages hang out in the air spaces within the alveoli. Once infected, these cells smolder, producing and dribbling out some viral progeny at a casual pace but more or less keeping a stiff upper lip and maintaining their normal function. This behavior may allow them to feed SARS-CoV-2’s progression by incubating and generating a steady supply of new viral particles that escape by stealth and penetrate the layer of cells enclosing the alveoli.

Interstitial macrophages, the other cell type revealed to be easily and profoundly infected by SARS-CoV-2, patrol the far side of the alveoli, where the rubber of oxygen meets the road of red blood cells. If an invading viral particle or other microbe manages to evade alveolar macrophages’ vigilance, infect and punch through the layer of cells enclosing the alveoli, jeopardizing not only the lungs but the rest of the body, interstitial macrophages are ready to jump in and protect the neighborhood.

At least, usually. But when an interstitial macrophage meets SARS-CoV-2, it’s a different story. Rather than get eaten by the omnivorous immune cell, the virus infects it.

And an infected interstitial macrophage doesn’t just smolder; it catches on fire. All hell breaks loose as the virus literally seizes the controls and takes over, hijacking a cell’s protein- and nucleic-acid-making machinery. In the course of producing massive numbers of copies of itself, SARS-CoV-2 destroys the boundaries separating the cell nucleus from the rest of the cell like a spatula shattering and scattering the yolk of a raw egg. The viral progeny exit the spent macrophage and move on to infect other cells.

But that’s not all. In contrast to alveolar macrophages, infected interstitial macrophages pump out substances that signal other immune cells elsewhere in the body to head for the lungs. In a patient, Krasnow suggested, this would trigger an inflammatory influx of such cells. As the lungs fill with cells and fluid that comes with them, oxygen exchange becomes impossible. The barrier maintaining alveolar integrity grows progressively damaged. Leakage of infected fluids from damaged alveoli propels viral progeny into the bloodstream, blasting the infection and inflammation to distant organs.

Yet other substances released by SARS-CoV-2-infected interstitial macrophages stimulate the production of fibrous material in connective tissue, resulting in scarring of the lungs. In a living patient, the replacement of oxygen-permeable cells with scar tissue would further render the lungs incapable of executing oxygen exchange.

“We can’t say that a lung cell sitting in a dish is going to get COVID,” Blish said. “But we suspect this may be the point where, in an actual patient, the infection transitions from manageable to severe.”

Another point of entry

Compounding this unexpected finding is the discovery that SARS-CoV-2 uses a different route to infect interstitial macrophages than the one it uses to infect the other types.

Unlike alveolar type 2 cells and alveolar macrophages, to which the virus gains access by clinging to ACE2 on their surfaces, SARS-CoV-2 breaks into interstitial macrophages using a different receptor these cells display. In the study, blocking SARS-CoV-2’s binding to ACE2 protected the former cells but failed to dent the latter cells’ susceptibility to SARS-CoV-2 infection.

“SARS-CoV-2 was not using ACE2 to get into interstitial macrophages,” Krasnow said. “It enters via another receptor called CD209.”

That would seem to explain why monoclonal antibodies developed specifically to block SARS-CoV-2/ACE2 interaction failed to mitigate or prevent severe COVID-19 cases.

It’s time to find a whole new set of drugs that can impede SARS-CoV-2/CD209 binding. Now, Krasnow said.

The study was funded by the National Institutes of Health (grants K08AI163369, T32AI007502 and T32DK007217), the Bill & Melinda Gates Foundation, Chan Zuckerberg Biohub, the Burroughs Wellcome Fund, Stanford Chem-H, the Stanford Innovative Medicine Accelerator, and the Howard Hughes Medical Institute.

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu .

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Prestigious cancer research institute has retracted 7 studies amid controversy over errors

Seven studies from researchers at the prestigious Dana-Farber Cancer Institute have been retracted over the last two months after a scientist blogger alleged that images used in them had been manipulated or duplicated.

The retractions are the latest development in a monthslong controversy around research at the Boston-based institute, which is a teaching affiliate of Harvard Medical School. 

The issue came to light after Sholto David, a microbiologist and volunteer science sleuth based in Wales, published a scathing post on his blog in January, alleging errors and manipulations of images across dozens of papers produced primarily by Dana-Farber researchers . The institute acknowledged errors and subsequently announced that it had requested six studies to be retracted and asked for corrections in 31 more papers. Dana-Farber also said, however, that a review process for errors had been underway before David’s post. 

Now, at least one more study has been retracted than Dana-Farber initially indicated, and David said he has discovered an additional 30 studies from authors affiliated with the institute that he believes contain errors or image manipulations and therefore deserve scrutiny.

The episode has imperiled the reputation of a major cancer research institute and raised questions about one high-profile researcher there, Kenneth Anderson, who is a senior author on six of the seven retracted studies. 

Anderson is a professor of medicine at Harvard Medical School and the director of the Jerome Lipper Multiple Myeloma Center at Dana-Farber. He did not respond to multiple emails or voicemails requesting comment. 

The retractions and new allegations add to a larger, ongoing debate in science about how to protect scientific integrity and reduce the incentives that could lead to misconduct or unintentional mistakes in research. 

The Dana-Farber Cancer Institute has moved relatively swiftly to seek retractions and corrections. 

“Dana-Farber is deeply committed to a culture of accountability and integrity, and as an academic research and clinical care organization we also prioritize transparency,” Dr. Barrett Rollins, the institute’s integrity research officer, said in a statement. “However, we are bound by federal regulations that apply to all academic medical centers funded by the National Institutes of Health among other federal agencies. Therefore, we cannot share details of internal review processes and will not comment on personnel issues.”

The retracted studies were originally published in two journals: One in the Journal of Immunology and six in Cancer Research. Six of the seven focused on multiple myeloma, a form of cancer that develops in plasma cells. Retraction notices indicate that Anderson agreed to the retractions of the papers he authored.

Elisabeth Bik, a microbiologist and longtime image sleuth, reviewed several of the papers’ retraction statements and scientific images for NBC News and said the errors were serious. 

“The ones I’m looking at all have duplicated elements in the photos, where the photo itself has been manipulated,” she said, adding that these elements were “signs of misconduct.” 

Dr.  John Chute, who directs the division of hematology and cellular therapy at Cedars-Sinai Medical Center and has contributed to studies about multiple myeloma, said the papers were produced by pioneers in the field, including Anderson. 

“These are people I admire and respect,” he said. “Those were all high-impact papers, meaning they’re highly read and highly cited. By definition, they have had a broad impact on the field.” 

Chute said he did not know the authors personally but had followed their work for a long time.

“Those investigators are some of the leading people in the field of myeloma research and they have paved the way in terms of understanding our biology of the disease,” he said. “The papers they publish lead to all kinds of additional work in that direction. People follow those leads and industry pays attention to that stuff and drug development follows.”

The retractions offer additional evidence for what some science sleuths have been saying for years: The more you look for errors or image manipulation, the more you might find, even at the top levels of science. 

Scientific images in papers are typically used to present evidence of an experiment’s results. Commonly, they show cells or mice; other types of images show key findings like western blots — a laboratory method that identifies proteins — or bands of separated DNA molecules in gels. 

Science sleuths sometimes examine these images for irregular patterns that could indicate errors, duplications or manipulations. Some artificial intelligence companies are training computers to spot these kinds of problems, as well. 

Duplicated images could be a sign of sloppy lab work or data practices. Manipulated images — in which a researcher has modified an image heavily with photo editing tools — could indicate that images have been exaggerated, enhanced or altered in an unethical way that could change how other scientists interpret a study’s findings or scientific meaning. 

Top scientists at big research institutions often run sprawling laboratories with lots of junior scientists. Critics of science research and publishing systems allege that a lack of opportunities for young scientists, limited oversight and pressure to publish splashy papers that can advance careers could incentivize misconduct. 

These critics, along with many science sleuths, allege that errors or sloppiness are too common , that research organizations and authors often ignore concerns when they’re identified, and that the path from complaint to correction is sluggish. 

“When you look at the amount of retractions and poor peer review in research today, the question is, what has happened to the quality standards we used to think existed in research?” said Nick Steneck, an emeritus professor at the University of Michigan and an expert on science integrity.

David told NBC News that he had shared some, but not all, of his concerns about additional image issues with Dana-Farber. He added that he had not identified any problems in four of the seven studies that have been retracted. 

“It’s good they’ve picked up stuff that wasn’t in the list,” he said. 

NBC News requested an updated tally of retractions and corrections, but Ellen Berlin, a spokeswoman for Dana-Farber, declined to provide a new list. She said that the numbers could shift and that the institute did not have control over the form, format or timing of corrections. 

“Any tally we give you today might be different tomorrow and will likely be different a week from now or a month from now,” Berlin said. “The point of sharing numbers with the public weeks ago was to make clear to the public that Dana-Farber had taken swift and decisive action with regard to the articles for which a Dana-Farber faculty member was primary author.” 

She added that Dana-Farber was encouraging journals to correct the scientific record as promptly as possible. 

Bik said it was unusual to see a highly regarded U.S. institution have multiple papers retracted. 

“I don’t think I’ve seen many of those,” she said. “In this case, there was a lot of public attention to it and it seems like they’re responding very quickly. It’s unusual, but how it should be.”

Evan Bush is a science reporter for NBC News. He can be reached at [email protected].

No sign of greenhouse gases increases slowing in 2023

• April 5, 2024

Levels of the three most important human-caused greenhouse gases – carbon dioxide (CO 2 ), methane and nitrous oxide – continued their steady climb during 2023, according to NOAA scientists. 

While the rise in the three heat-trapping gases recorded in the air samples collected by NOAA’s Global Monitoring Laboratory (GML) in 2023 was not quite as high as the record jumps observed in recent years, they were in line with the steep increases observed during the past decade. 

“NOAA’s long-term air sampling program is essential for tracking causes of climate change and for supporting the U.S. efforts to establish an integrated national greenhouse gas measuring, monitoring and information system,” said GML Director Vanda Grubišić. “As these numbers show, we still have a lot of work to do to make meaningful progress in reducing the amount of greenhouse gases accumulating in the atmosphere.” 

The global surface concentration of CO 2 , averaged across all 12 months of 2023, was 419.3 parts per million (ppm), an increase of 2.8 ppm during the year. This was the 12th consecutive year CO 2 increased by more than 2 ppm, extending the highest sustained rate of CO 2 increases during the 65-year monitoring record. Three consecutive years of CO 2  growth of 2 ppm or more had not been seen in NOAA’s monitoring records prior to 2014. Atmospheric CO 2 is now more than 50% higher than pre-industrial levels.

This graph shows the globally averaged monthly mean carbon dioxide abundance measured at the Global Monitoring Laboratory’s global network of air sampling sites since 1980. Data are still preliminary, pending recalibrations of reference gases and other quality control checks. Credit: NOAA GML

“The 2023 increase is the third-largest in the past decade, likely a result of an ongoing increase of fossil fuel CO 2 emissions, coupled with increased fire emissions possibly as a result of the transition from La Nina to El Nino,” said Xin Lan, a CIRES scientist who leads GML’s effort to synthesize data from the NOAA Global Greenhouse Gas Reference Network for tracking global greenhouse gas trends .

Atmospheric methane, less abundant than CO 2 but more potent at trapping heat in the atmosphere, rose to an average of 1922.6 parts per billion (ppb). The 2023 methane increase over 2022 was 10.9 ppb, lower than the record growth rates seen in 2020 (15.2 ppb), 2021(18 ppb)  and 2022 (13.2 ppb), but still the 5th highest since renewed methane growth started in 2007. Methane levels in the atmosphere are now more than 160% higher than their pre-industrial level.

This graph shows globally-averaged, monthly mean atmospheric methane abundance determined from marine surface sites for the full NOAA time-series starting in 1983. Values for the last year are preliminary, pending recalibrations of standard gases and other quality control steps. Credit: NOAA GM

In 2023, levels of nitrous oxide, the third-most significant human-caused greenhouse gas, climbed by 1 ppb to 336.7 ppb. The two years of highest growth since 2000 occurred in 2020 (1.3 ppb) and 2021 (1.3 ppb). Increases in atmospheric nitrous oxide during recent decades are mainly from use of nitrogen fertilizer and manure from the expansion and intensification of agriculture. Nitrous oxide concentrations are 25% higher than the pre-industrial level of 270 ppb.

Taking the pulse of the planet one sample at a time NOAA’s Global Monitoring Laboratory collected more than 15,000 air samples from monitoring stations around the world in 2023 and analyzed them in its state-of-the-art laboratory in Boulder,

Colorado. Each spring, NOAA scientists release preliminary calculations of the global average levels of these three primary long-lived greenhouse gases observed during the previous year to track their abundance, determine emissions and sinks, and understand carbon cycle feedbacks.

Measurements are obtained from air samples collected from sites in NOAA’s Global Greenhouse Gas Reference Network , which includes about 53 cooperative sampling sites around the world, 20 tall tower sites, and routine aircraft operation sites from North America. 

Carbon dioxide emissions remain the biggest problem 

By far the most important contributor to climate change is CO 2 , which is primarily emitted by burning of fossil fuels. Human-caused CO 2 pollution increased from 10.9 billion tons per year in the 1960s – which is when the measurements at the Mauna Loa Observatory in Hawaii began – to about 36.8 billion tons per year in 2023. This sets a new record, according to the Global Carbon Project , which uses NOAA’s Global Greenhouse Gas Reference Network measurements to define the net impact of global carbon emissions and sinks.

The amount of CO 2 in the atmosphere today is comparable to where it was around 4.3 million years ago during the mid- Pliocene epoch , when sea level was about 75 feet higher than today, the average temperature was 7 degrees Fahrenheit higher than in pre-industrial times, and large forests occupied areas of the Arctic that are now tundra. 

About half of the CO 2 emissions from fossil fuels to date have been absorbed at the Earth’s surface, divided roughly equally between oceans and land ecosystems, including grasslands and forests. The CO 2 absorbed by the world’s oceans contributes to ocean acidification, which is causing a fundamental change in the chemistry of the ocean, with impacts to marine life and the people who depend on them. The oceans have also absorbed an estimated 90% of the excess heat trapped in the atmosphere by greenhouse gases. 

Research continues to point to microbial sources for rising methane

NOAA’s measurements show that atmospheric methane increased rapidly during the 1980s, nearly stabilized in the late-1990s and early 2000s, then resumed a rapid rise in 2007. 

A 2022 study by NOAA and NASA scientists and additional NOAA research in 2023 suggests that more than 85% of the increase from 2006 to 2021 was due to increased microbial emissions generated by livestock, agriculture, human and agricultural waste, wetlands and other aquatic sources. The rest of the increase was attributed to increased fossil fuel emissions. 

“In addition to the record high methane growth in 2020-2022, we also observed sharp changes in the isotope composition of the methane that indicates an even more dominant role of microbial emission increase,” said Lan. The exact causes of the recent increase in methane are not yet fully known. 

NOAA scientists are investigating the possibility that climate change is causing wetlands to give off increasing methane emissions in a feedback loop. 

To learn more about the Global Monitoring Laboratory’s greenhouse gas monitoring, visit: https://gml.noaa.gov/ccgg/trends/.

Media Contact: Theo Stein, [email protected] , 303-819-7409

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Neolithic women in Europe were tied up and buried alive in ritual sacrifices, study suggests

The research found evidence of the "incaprettamento" method of murder at 14 Neolithic sites in Europe.

The murder of sacrificial victims by "incaprettamento" — tying their neck to their legs bent behind their back, so that they effectively strangled themselves — seems to have been a tradition across much of Neolithic Europe, with a new study identifying more than a dozen such murders over more than 2,000 years.

The study comes after a reassessment of an ancient tomb that was discovered more than 20 years ago at Saint-Paul-Trois-Châteaux near Avignon, in southern France. The tomb mimics a silo, or pit where grain was stored, and it held the remains of three women who were buried there about 5,500 years ago.

The new study, published Wednesday (April 10) in the journal Science Advances , reinterprets the positions of two of the skeletons and suggests the individuals were deliberately killed — first by tying them up in the manner called "incaprettamento" and then by burying them while they were still alive, perhaps for an agricultural ritual.

Study senior author Eric Crubézy , a biological anthropologist at Paul Sabatier University in Toulouse, France, told Live Science that there was a lot of agricultural symbolism to the tomb. He noted that a wooden structure built over it was aligned with the sun at the solstices and that several broken stones for grinding grain were found nearby. "You have the alignment, you have the silo, you have the broken stones — so it seems that it was a rite related to agriculture."

Related: Skull of Neolithic 'bog body' from Denmark was smashed by 8 heavy blows in violent murder

To investigate the idea of human sacrifice at Saint-Paul-Trois-Châteaux, Crubézy, who worked on the initial discovery of the tomb, and colleagues examined earlier archaeological studies of tomb sites throughout Europe. The team included forensic pathologist Bertrand Ludes , of Paris Cité University and the study's lead author.

They found evidence of 20 probable cases of sacrificial murders using incaprettamento at 14 Neolithic (New Stone Age) sites dating to between 5400 and 3500 B.C. They also found papers describing Mesolithic (Middle Stone Age) rock art in the Addaura Cave in Sicily, made between 14000 and 11000 B.C., that seems to depict two human figures bound in the incaprettamento manner.

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Crubézy said it appears incaprettamento originated as a sacrificial custom in the Mesolithic period, before agriculture, and later came to be used for human sacrifices associated with agriculture in the Neolithic period.

As a method of human sacrifice, incaprettamento seems to have been widespread across much of Neolithic Europe, with evidence of the practice at sites ranging from the Czech Republic to Spain. The earliest is a tomb near Brno-Bohunice in the Czech Republic that is dated to about 5400 B.C., and the latest is the tomb at Saint-Paul-Trois-Châteaux, suggesting that the practice persisted for more than 2,000 years, Crubézy said.

Gruesome murders

The bindings used to tie the two individuals at Saint-Paul-Trois-Châteaux have long since decayed, but a few features of their skeletons — such as the unusual positions of their legs — suggest how they died, Crubézy said.

The third woman in the tomb seems to have been older and likely died from natural causes, the researchers found. She was also interred normally for the time, on her side in the center of the tomb. This suggests that she had been ceremonially buried after her natural death and that the two younger women had been sacrificed to be buried with her, he said.

— 15 people were brutally murdered 5,000 years ago, but the bodies were buried with care

— 2 waves of mass murder struck prehistoric Denmark, genetic study reveals

— Why were dozens of people butchered 6,200 years ago and buried in a Neolithic death pit?

The two sacrificial victims seem to have been pinned down with heavy fragments of stones used for grinding grain, indicating that, despite their bindings, they were still alive when they were buried, he said.

Today, the gruesome incaprettamento murder method is associated with the Italian Mafia , who have sometimes used it as a form of warning or reprimand.

Crubézy said it wasn't known why incaprettamento was used for Stone Age human sacrifices, but it might have been because a person bound in this way could be seen as strangling themselves, rather than being killed by someone else.

Tom Metcalfe is a freelance journalist and regular Live Science contributor who is based in London in the United Kingdom. Tom writes mainly about science, space, archaeology, the Earth and the oceans. He has also written for the BBC, NBC News, National Geographic, Scientific American, Air & Space, and many others.

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Qualitative study.

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Last Update: September 18, 2022 .

• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervene or introduce treatments just like in quantitative research, qualitative research helps generate hypotheses as well as further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and application of qualitative research.

Qualitative research at its core, ask open-ended questions whose answers are not easily put into numbers such as ‘how’ and ‘why’. [2] Due to the open-ended nature of the research questions at hand, qualitative research design is often not linear in the same way quantitative design is. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be difficult to accurately capture quantitatively, whereas a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a certain time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify and it is important to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore ‘compete’ against each other and the philosophical paradigms associated with each, qualitative and quantitative work are not necessarily opposites nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites, and they are certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined that there is a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated together.

Examples of Qualitative Research Approaches

Ethnography

Ethnography as a research design has its origins in social and cultural anthropology, and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques with the aim of being able to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc. through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded Theory

Grounded Theory is the “generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior.” [5] As opposed to quantitative research which is deductive and tests or verifies an existing theory, grounded theory research is inductive and therefore lends itself to research that is aiming to study social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain for example how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is defined as the “study of the meaning of phenomena or the study of the particular”. [5] At first glance, it might seem that Grounded Theory and Phenomenology are quite similar, but upon careful examination, the differences can be seen. At its core, phenomenology looks to investigate experiences from the perspective of the individual. [2] Phenomenology is essentially looking into the ‘lived experiences’ of the participants and aims to examine how and why participants behaved a certain way, from their perspective . Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources whereas Phenomenology focuses on describing and explaining an event or phenomena from the perspective of those who have experienced it.

Narrative Research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called ‘thick’ or ‘rich’ description and is a strength of qualitative research. Narrative research is rife with the possibilities of ‘thick’ description as this approach weaves together a sequence of events, usually from just one or two individuals, in the hopes of creating a cohesive story, or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be “opportunities for innovation”. [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards that underpin different approaches to research. Essentially, research paradigms are the ‘worldview’ that inform research. [4] It is valuable for researchers, both qualitative and quantitative, to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontology and epistemologies . Ontology is defined as the "assumptions about the nature of reality” whereas epistemology is defined as the “assumptions about the nature of knowledge” that inform the work researchers do. [2] It is important to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a full understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, it is crucial that researchers understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist vs Postpositivist

To further understand qualitative research, we need to discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social as well as natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in its research which stems from positivist ontology that there is an objective reality that exists that is fully independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained but it could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world” and therefore postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are constructivist as well, meaning they think there is no objective external reality that exists but rather that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. “Constructivism contends that individuals’ views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality”. [6] Essentially, Constructivist thought focuses on how ‘reality’ is not a fixed certainty and experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike in positivist views, that there is not necessarily an ‘objective’ reality we all experience. This is the ‘relativist’ ontological view that reality and the world we live in are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have and can even change the role of the researcher themselves. [2] For example, is the researcher an ‘objective’ observer such as in positivist quantitative work? Or is the researcher an active participant in the research itself, as in postpositivist qualitative work? Understanding the philosophical base of the research undertaken allows researchers to fully understand the implications of their work and their role within the research, as well as reflect on their own positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors at play. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale in terms of being the most informative.
• Criterion sampling-selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling-selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one on one and is appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be a participant-observer to share the experiences of the subject or a non-participant or detached observer.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or in the environment of the participants, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed which may then be coded manually or with the use of Computer Assisted Qualitative Data Analysis Software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results also could be in the form of themes and theory or model development.

Dissemination

To standardize and facilitate the dissemination of qualitative research outcomes, the healthcare team can use two reporting standards. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a wider range of qualitative research. [13]

Examples of Application

Many times a research question will start with qualitative research. The qualitative research will help generate the research hypothesis which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data for a better understanding of what the numbers truly mean and their implications. The qualitative methods can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research researchers can explore subjects that are poorly studied with quantitative methods. These include opinions, individual's actions, and social science research.

A good qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure there are no omissions of part of the target population. A proper collection method should be selected which will help obtain the desired information without overly limiting the collected data because many times, the information sought is not well compartmentalized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of both why teens start to smoke as well as factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered “cool,” and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current non-smokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the results of the survey to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the major factor that keeps teens from starting to smoke, and peer pressure was the major factor that contributed to teens to start smoking. The researcher can go back to qualitative research methods to dive deeper into each of these for more information. The researcher wants to focus on how to keep teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and/or focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking first starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure of smoking. The researcher finds a local park where many local teenagers hang out and see that a shady, overgrown area of the park is where the smokers tend to hang out. The researcher notes the smoking teenagers buy their cigarettes from a local convenience store adjacent to the park where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region of the park, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to the smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk population their perceptions of the changes, what factors are still at play, as well as quantitative research that includes teen smoking rates in the community, the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or in combination with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation to not only help generate hypotheses which can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are.  Qualitative research provides researchers with a way to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many different ways, including the criteria for evaluating them. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. The correlating concepts in qualitative research are credibility, transferability, dependability, and confirmability. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept is on the left, and the qualitative concept is on the right:

• Internal validity--- Credibility
• External validity---Transferability
• Reliability---Dependability
• Objectivity---Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid so should qualitative researchers ensure that their work has credibility.  

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple methods of data collection to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable by also interviewing the magician, back-stage hand, and the person who "vanished." In qualitative research, triangulation can include using telephone surveys, in-person surveys, focus groups, and interviews as well as surveying an adequate cross-section of the target demographic.
• Peer examination: Results can be reviewed by a peer to ensure the data is consistent with the findings.

‘Thick’ or ‘rich’ description can be used to evaluate the transferability of qualitative research whereas using an indicator such as an audit trail might help with evaluating the dependability and confirmability.

• Thick or rich description is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was carried out. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data themselves, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original records of information should also be kept (e.g., surveys, notes, recordings).

One issue of concern that qualitative researchers should take into consideration is observation bias. Here are a few examples:

• Hawthorne effect: The Hawthorne effect is the change in participant behavior when they know they are being observed. If a researcher was wanting to identify factors that contribute to employee theft and tells the employees they are going to watch them to see what factors affect employee theft, one would suspect employee behavior would change when they know they are being watched.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens in an unconscious manner for the participant so it is important to eliminate or limit transmitting the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in artificial scenarios and/or with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative research by itself or combined with quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research does not exist as an island apart from quantitative research, but as an integral part of research methods to be used for the understanding of the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is important for all members of the health care team as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research.  Much of the qualitative research data acquisition is completed by numerous team members including social works, scientists, nurses, etc.  Within each area of the medical field, there is copious ongoing qualitative research including physician-patient interactions, nursing-patient interactions, patient-environment interactions, health care team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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Rising numbers of americans say jews and muslims face a lot of discrimination, most u.s. adults think speech related to israeli and palestinian statehood should be allowed, but not calls for violence.

Pew Research Center conducted this survey to explore the U.S. public’s views on discrimination and free speech in the context of the Israel-Hamas war. We surveyed a total of 12,693 U.S. adults from Feb. 13 to 25, 2024. Most of the respondents (10,642) are members of Pew Research Center’s American Trends Panel, an online survey panel recruited through national random sampling of residential addresses, which gives nearly all U.S. adults a chance of selection.

The remaining 2,051 respondents are members of three other survey panels – Ipsos’ KnowledgePanel, SSRS’s Opinion Panel, and NORC at the University of Chicago’s AmeriSpeak Panel – who were interviewed because they identify as Jewish or Muslim.

We “oversampled” (i.e., interviewed a disproportionately large number of) Jews and Muslims to provide more reliable estimates of their views on the topics covered in this survey. But these groups are not overrepresented in the national estimates reported here, because we adjusted for the oversampling in the weighting of the data. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education, religious affiliation and other categories. In total, 1,941 Jewish and 414 Muslim respondents participated in this survey.

While the sample design was identical for Jews and Muslims, the resulting sample sizes are different. There are two main reasons for this. The Jewish population in the United States is roughly double the size of the Muslim population . Consequently, national survey panels have roughly twice as many or more Jewish panelists as Muslim ones. In addition, decades of research on survey nonresponse has shown that some groups in the U.S. are more likely to participate in surveys than others. Generally speaking, Jewish adults are more likely to participate in surveys than Muslim adults.

The survey also included questions about where people were born and whether people identify as Arab or of Arab origin. Because of insufficient sample size, we are unable to analyze Arab Americans or Americans of Israeli or Palestinian descent separately.

In this survey, Jews and Muslims are defined as U.S. adults who answer a question about their current religion by saying they are Jewish or Muslim, respectively. Unlike our 2020 report on Jews in America , this report does not separately analyze the views of “Jews of no religion” (i.e., people who identify as Jewish culturally, ethnically or by family background but not by religion).

For more information on how we conducted this survey, refer to the ATP’s Methodology and the Methodology for this report . Read the questions used in this report , along with responses.

The share of U.S. adults who say there is a lot of discrimination against Jews in our society has doubled in the last three years, according to a new Pew Research Center survey, jumping from 20% in 2021 to 40% today. A somewhat larger share – 44% – say Muslims face a lot of discrimination, up 5 percentage points since 2021.

Many Americans particularly sense that discrimination against Muslims and Jews has risen since the start of the Israel-Hamas war. The vast majority of U.S. Muslims and Jews themselves agree: Seven-in-ten Muslims and nine-in-ten Jews surveyed say they have felt an increase in discrimination against their respective groups since the war began in October.

The survey, conducted Feb. 13-25 among a nationally representative sample of 12,693 U.S. adults that includes an oversample of American Jews and Muslims, also probed the public’s views on the limits of free speech related to the war.

It finds that Americans are broadly comfortable with speech both for and against Israeli and Palestinian statehood. But most U.S. adults are not OK with calls for violence against Jews or Muslims.

Pew Research Center surveys conducted on our American Trends Panel (ATP) always include Jews and Muslims. But these surveys do not always have enough Jewish or Muslim respondents to report their answers separately. This is because they make up relatively small shares of the U.S. adult population: Roughly 2% of Americans say their religion is Judaism , and 1% say their religion is Islam .

To provide more reliable estimates of Jewish and Muslim views on the topics covered in this survey, we included Jewish and Muslim respondents from three other national panels run by large research organizations (Ipsos, NORC and SSRS). All these panels are probability based, meaning they use random sampling methods to recruit respondents. They are not “opt-in” polls . In total, 1,941 Jewish and 414 Muslim respondents participated in this survey.

In this report, Jews and Muslims are defined as U.S. adults who answer a question about their current religion by saying they are Jewish or Muslim, respectively. Unlike our 2020 report on Jews in America , this report does not analyze the views of “Jews of no religion” (i.e., people who identify as Jewish culturally, ethnically or by family background but not by religion).

While the sample design was identical for Jews and Muslims, the resulting sample sizes are different. There are two main reasons for this. The Jewish population in the U.S. is roughly double the size of the Muslim population . Consequently, national survey panels have roughly twice as many or more Jewish panelists as Muslim ones. In addition, decades of research on survey nonresponse has shown that some groups in the U.S. are more likely to participate in surveys than others. Generally speaking, Jewish adults are more likely to participate in surveys than Muslim adults.

• 70% say expressing support for “Israel’s right to exist as a Jewish state” should be allowed.
• 58% say expressing opposition to Israel’s right to exist should be allowed.
• 66% say speech supporting “Palestinians having their own state” should be allowed.
• 61% say speech opposing a Palestinian state should be allowed.
• One-in-ten say calls for violence against either Jews or Muslims should be allowed.

On the questions about speech related to statehood, substantial shares of respondents are not sure. For example, 23% say they aren’t sure whether speech opposing Israel’s right to exist as a Jewish state should be allowed. And 25% say they aren’t sure whether speech opposing Palestinian statehood should be allowed.

When it comes to speech advocating violence, however, there is less uncertainty. Roughly three-quarters of Americans say that calls for violence against either Muslims or Jews should not be allowed.

The survey comes amid a flurry of news reports about antisemitic and anti-Muslim incidents in the United States, especially on college campuses , where fierce debates have erupted over the limits of free speech . For many Jewish and Muslim Americans, these debates are not just ideological, but personal:

• 74% of U.S. Jews and 60% of U.S. Muslims surveyed say they have felt offended by something they saw on the news or social media about the Israel-Hamas war.
• 27% of Muslims and 26% of Jews in the survey say they have stopped talking to someone in person – or unfollowed or blocked someone online – because of something that person said about the war.

A previous Pew Research Center report, based on the same survey, examined the U.S. public’s views on the war, including questions about:

• The acceptability of Hamas’ Oct. 7 attack and Israel’s military response
• Americans’ attention to the war
• Americans’ knowledge about the war
• The emotions the conflict has unleashed

In this report, we focus on perceived levels of discrimination against Jews, Muslims and Arab people in the U.S. For context, we analyze perceptions of discrimination against other religious, racial and ethnic groups, including evangelical Christians and Asian, Black, Hispanic and White Americans ( Chapter 1 ).

We also delve into public attitudes toward speech related to the war, including how these views vary by age, education, political partisanship and other demographic factors ( Chapter 2 ).

How much discrimination do U.S. Jews and Muslims see against their own group?

The vast majority of U.S. Muslims surveyed (85%) say there is at least some discrimination against Muslims in our society today, including 67% who say there is a lot . Overall, Muslim respondents are more likely to feel there is at least some discrimination against their own religious group than to say the same about Jews (50%).

An overwhelming majority of U.S. Jews (94%) say there is at least some discrimination against Jews in our society, including 72% who say there is a lot . And more say there is a lot of discrimination against Jews than say the same about Muslims (57%).

For Jews, this represents a shift: In our 2020 and 2013 surveys of American Jews, they were more likely to say that Muslims (as well as Black people) face a lot of discrimination than to say this about themselves. 1

The change in Jewish Americans’ perceptions appears to be tied, at least in part, to the conflict in the Middle East: 89% of Jewish respondents say they have perceived a rise in discrimination against Jews since the start of the Israel-Hamas war.

They are not alone in feeling the effects of the conflict. Seven-in-ten Muslim respondents say discrimination against Muslims has risen since the start of the war. (Jewish and Muslim Americans are also paying greater attention to news about the Israel-Hamas war than most other Americans.)

In addition, most Muslims and nearly half of Jews say discrimination has increased against Arabs since the war began.

Unlike most U.S. polls, this survey has enough Jewish and Muslim respondents to allow their opinions to be broken out separately . Although Arab Americans also are included in the survey, there are not enough of them to reliably represent the views of Arab Americans as a whole. All three groups are very small in proportion to the overall U.S. population, which makes it hard to get a representative estimate through random sampling alone.

Free speech and the Israel-Hamas war

The survey included several questions to gauge tolerance for public speech about Israeli and Palestinian statehood, asking whether people in the U.S. should be able to express these sentiments – even if they might offend some people. Outright opposition to these expressions of opinion are relatively rare; instead, sizable shares say they are unsure. In contrast, most Americans say public speech calling for violence against Jews or Muslims should not be allowed.

Like the public overall, a large majority of U.S. Jews are in favor of allowing people to express support for Israel’s right to exist as a Jewish state (92%). Majorities of Jews also say speech either supporting (77%) or opposing (74%) Palestinians having their own state should be allowed. But Jews are less likely to say this about speech opposing Israel’s right to exist as a Jewish state: 55% say this kind of speech should be allowed, while 34% say it should not be allowed.

Similarly, a solid majority of U.S. Muslims say that speech supporting a Palestinian state should be allowed (70%). About half of Muslims say people should be allowed to express support for (47%) or opposition to (50%) Israel’s existence as a Jewish state. And 43% of Muslims say that speech opposing a Palestinian state should be allowed; 27% say this kind of speech should not be allowed, and 28% are unsure.

Like many public attitudes toward the Israel-Hamas war, opinions on these issues vary depending on people’s age, political party and education:

• Compared with other age groups, Americans 65 and older are more likely to say there is a lot of discrimination against Jews in our society today. Older Americans are far more likely to report an increase in discrimination against Jews than against Muslims or Arabs.
• By contrast, Americans ages 18 to 29 are more likely to say that Black, Muslim, Arab and Hispanic people experience a lot of discrimination than to say the same about Jews. Adults under 30 are equally likely to perceive an increase in discrimination against Muslims, Arabs and Jews since the start of the Israel-Hamas war (47% each).
• People ages 65 and older are the most likely to say they have felt personally offended by something they saw on the news or social media about the war (41%).
• Adults under 30 are the most likely to say they stopped talking to someone, or unfollowed or blocked someone online, because of something that person said about the Israel-Hamas war (16%).

Partisanship

• Democrats and Democratic-leaning independents are generally more likely than Republicans and Republican leaners to say there is a lot of discrimination against the groups asked about in the survey; Democrats are most likely to say there is a lot of discrimination against Black people (62%), Muslims (61%), Arab people (55%) and Jews (41%).
• Republicans are most likely to say there is a lot of discrimination against Jews (40%), followed by Muslims (27%), evangelical Christians (24%) and White people (24%).
• Democrats are about twice as likely as Republicans to say that, since the start of the Israel-Hamas war, discrimination has increased against Muslims (52% vs. 26%) and Arabs (49% vs. 23%).
• Republicans (61%) and Democrats (57%) largely agree that discrimination against Jews has increased since the outbreak of the war.
• Republicans and Democrats are also broadly in sync on the survey’s questions about speech. They largely are in favor of allowing expressions for or against statehood, but do not think calls for violence should be allowed.
• Americans with at least a college degree are more likely than those with less education to say discrimination against Jews, Muslims and Arabs has increased since the start of the Israel-Hamas war.
• People with at least a college degree are far more likely than those with less education to say that speech supporting and opposing Israeli or Palestinian statehood should be allowed. Those with lower levels of education are much more likely to say they are unsure.
• The 2013 survey of Jewish Americans included a similar question about discrimination, but the response options were different. The 2020 survey response options were “A lot,” “Some,” “Not much” and “None at all,” while in the 2013 survey the response options were “Yes, there is a lot of discrimination” and “No, not a lot of discrimination.” Despite this change, both of these previous surveys found that more Jews perceived a lot of discrimination against some other minority groups than against Jews. ↩

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• Research Objectives | Definition & Examples

Research Objectives | Definition & Examples

Published on July 12, 2022 by Eoghan Ryan . Revised on November 20, 2023.

Research objectives describe what your research is trying to achieve and explain why you are pursuing it. They summarize the approach and purpose of your project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement . They should:

• Establish the scope and depth of your project
• Contribute to your research design
• Indicate how your project will contribute to existing knowledge

Table of contents

What is a research objective, why are research objectives important, how to write research aims and objectives, smart research objectives, other interesting articles, frequently asked questions about research objectives.

Research objectives describe what your research project intends to accomplish. They should guide every step of the research process , including how you collect data , build your argument , and develop your conclusions .

Your research objectives may evolve slightly as your research progresses, but they should always line up with the research carried out and the actual content of your paper.

Research aims

A distinction is often made between research objectives and research aims.

A research aim typically refers to a broad statement indicating the general purpose of your research project. It should appear at the end of your problem statement, before your research objectives.

Your research objectives are more specific than your research aim and indicate the particular focus and approach of your project. Though you will only have one research aim, you will likely have several research objectives.

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Research objectives are important because they:

• Establish the scope and depth of your project: This helps you avoid unnecessary research. It also means that your research methods and conclusions can easily be evaluated .
• Contribute to your research design: When you know what your objectives are, you have a clearer idea of what methods are most appropriate for your research.
• Indicate how your project will contribute to extant research: They allow you to display your knowledge of up-to-date research, employ or build on current research methods, and attempt to contribute to recent debates.

Once you’ve established a research problem you want to address, you need to decide how you will address it. This is where your research aim and objectives come in.

Step 1: Decide on a general aim

Your research aim should reflect your research problem and should be relatively broad.

Step 2: Decide on specific objectives

Break down your aim into a limited number of steps that will help you resolve your research problem. What specific aspects of the problem do you want to examine or understand?

Step 3: Formulate your aims and objectives

Once you’ve established your research aim and objectives, you need to explain them clearly and concisely to the reader.

You’ll lay out your aims and objectives at the end of your problem statement, which appears in your introduction. Frame them as clear declarative statements, and use appropriate verbs to accurately characterize the work that you will carry out.

The acronym “SMART” is commonly used in relation to research objectives. It states that your objectives should be:

• Specific: Make sure your objectives aren’t overly vague. Your research needs to be clearly defined in order to get useful results.
• Measurable: Know how you’ll measure whether your objectives have been achieved.
• Achievable: Your objectives may be challenging, but they should be feasible. Make sure that relevant groundwork has been done on your topic or that relevant primary or secondary sources exist. Also ensure that you have access to relevant research facilities (labs, library resources , research databases , etc.).
• Relevant: Make sure that they directly address the research problem you want to work on and that they contribute to the current state of research in your field.
• Time-based: Set clear deadlines for objectives to ensure that the project stays on track.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

Your research objectives indicate how you’ll try to address your research problem and should be specific:

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

• Budget constraints or any specifics of grant funding
• Your proposed timeline and duration
• Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
• Any inclusion and exclusion criteria
• Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

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Ryan, E. (2023, November 20). Research Objectives | Definition & Examples. Scribbr. Retrieved April 11, 2024, from https://www.scribbr.com/research-process/research-objectives/

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