research meaning with sentence

How to Use research in a Sentence

• The study is an important piece of research .
• He did a lot of research before buying his car.
• Recent research shows that the disease is caused in part by bad nutrition.
• She conducts research into the causes of Alzheimer's disease.
• The reporter made hundreds of telephone calls while researching the story.
• Before going out to eat, she researched area restaurants.
• He spent the summer researching his dissertation.

Some of these examples are programmatically compiled from various online sources to illustrate current usage of the word 'research.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

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Definition of research – Learner’s Dictionary

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• There is the potential for some really interesting research.
• She has done research into how children acquire language .
• The appeal raised over £2 million for AIDS research.
• This report echoes some of the earlier research I've read .
• The government has committed thousands of pounds to the research.

(Definition of research from the Cambridge Learner's Dictionary © Cambridge University Press)

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Definition of research noun from the Oxford Advanced Learner's Dictionary

• scientific/medical/academic research
• They are raising money for cancer research.
• to do/conduct/undertake research
• I've done some research to find out the cheapest way of travelling there.
• research into something He has carried out extensive research into renewable energy sources.
• research on something/somebody Recent research on deaf children has produced some interesting findings about their speech.
• Research on animals has led to some important medical advances.
• according to research According to recent research, more people are going to the movies than ever before.
• Their latest research project will be funded by the government.
• Are you hoping to get a research grant ?
• a research fellow/assistant/scientist
• a research institute/centre/laboratory
• The research findings were published in the Journal of Environmental Quality.
• formulate/​advance a theory/​hypothesis
• build/​construct/​create/​develop a simple/​theoretical/​mathematical model
• develop/​establish/​provide/​use a theoretical/​conceptual framework
• advance/​argue/​develop the thesis that…
• explore an idea/​a concept/​a hypothesis
• make a prediction/​an inference
• base a prediction/​your calculations on something
• investigate/​evaluate/​accept/​challenge/​reject a theory/​hypothesis/​model
• design an experiment/​a questionnaire/​a study/​a test
• do research/​an experiment/​an analysis
• make observations/​measurements/​calculations
• carry out/​conduct/​perform an experiment/​a test/​a longitudinal study/​observations/​clinical trials
• run an experiment/​a simulation/​clinical trials
• repeat an experiment/​a test/​an analysis
• replicate a study/​the results/​the findings
• observe/​study/​examine/​investigate/​assess a pattern/​a process/​a behaviour
• fund/​support the research/​project/​study
• seek/​provide/​get/​secure funding for research
• collect/​gather/​extract data/​information
• yield data/​evidence/​similar findings/​the same results
• analyse/​examine the data/​soil samples/​a specimen
• consider/​compare/​interpret the results/​findings
• fit the data/​model
• confirm/​support/​verify a prediction/​a hypothesis/​the results/​the findings
• prove a conjecture/​hypothesis/​theorem
• draw/​make/​reach the same conclusions
• read/​review the records/​literature
• describe/​report an experiment/​a study
• present/​publish/​summarize the results/​findings
• present/​publish/​read/​review/​cite a paper in a scientific journal
• a debate about the ethics of embryonic stem cell research
• For his PhD he conducted field research in Indonesia.
• Further research is needed.
• Future research will hopefully give us a better understanding of how garlic works in the human body.
• Dr Babcock has conducted extensive research in the area of agricultural production.
• the funding of basic research in biology, chemistry and genetics
• Activists called for a ban on animal research.
• Work is under way to carry out more research on the gene.
• She returned to Jamaica to pursue her research on the African diaspora.
• Bad punctuation can slow down people's reading speeds, according to new research carried out at Bradford University.
• He focused his research on the economics of the interwar era.
• Most research in the field has concentrated on the effects on children.
• One paper based on research conducted at Oxford suggested that the drug may cause brain damage.
• Research demonstrates that women are more likely than men to provide social support to others.
• She's doing research on Czech music between the wars.
• The research does not support these conclusions.
• They are carrying out research into the natural flow patterns of water.
• They lack the resources to do their own research.
• What has their research shown?
• Funding for medical research has been cut quite dramatically.
• a startling piece of historical research
• pioneering research into skin disease
• They were the first to undertake pioneering research into the human genome.
• There is a significant amount of research into the effects of stress on junior doctors.
• He's done a lot of research into the background of this story.
• research which identifies the causes of depression
• spending on military research and development
• the research done in the 1950s that linked smoking with cancer
• The children are taking part in a research project to investigate technology-enabled learning.
• The Lancet published a research paper by the scientist at the centre of the controversy.
• Who is directing the group's research effort?
• She is chief of the clinical research program at McLean Hospital.
• James is a 24-year-old research student from Iowa.
• You will need to describe your research methods.
• Before a job interview, do your research and find out as much as you can about the company.
• Most academic research is carried out in universities.
• This is a piece of research that should be taken very seriously.
• This is an important area of research.
• There's a large body of research linking hypertension directly to impaired brain function.
• In the course of my researches, I came across some of my grandfather's old letters.
• demonstrate something
• find something
• identify something
• programme/​program
• research in
• research into
• research on
• an area of research
• focus your research on something
• somebody’s own research

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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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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

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

17k Accesses

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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A Peek Inside the Brains of ‘Super-Agers’

New research explores why some octogenarians have exceptional memories.

By Dana G. Smith

When it comes to aging, we tend to assume that cognition gets worse as we get older. Our thoughts may slow down or become confused, or we may start to forget things, like the name of our high school English teacher or what we meant to buy at the grocery store.

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These findings are backed up by Dr. Rogalski’s research , initially conducted when she was at Northwestern University, which showed that super-agers’ brains looked more like 50- or 60-year-olds’ brains than their 80-year-old peers. When followed over several years, the super-agers’ brains atrophied at a slower rate than average.

No precise numbers exist on how many super-agers there are among us, but Dr. Rogalski said they’re “relatively rare,” noting that “far less than 10 percent” of the people she sees end up meeting the criteria.

But when you meet a super-ager, you know it, Dr. Strange said. “They are really quite energetic people, you can see. Motivated, on the ball, elderly individuals.”

Experts don’t know how someone becomes a super-ager, though there were a few differences in health and lifestyle behaviors between the two groups in the Spanish study. Most notably, the super-agers had slightly better physical health, both in terms of blood pressure and glucose metabolism, and they performed better on a test of mobility . The super-agers didn’t report doing more exercise at their current age than the typical older adults, but they were more active in middle age. They also reported better mental health .

But overall, Dr. Strange said, there were a lot of similarities between the super-agers and the regular agers. “There are a lot of things that are not particularly striking about them,” he said. And, he added, “we see some surprising omissions, things that you would expect to be associated with super-agers that weren’t really there.” For example, there were no differences between the groups in terms of their diets, the amount of sleep they got, their professional backgrounds or their alcohol and tobacco use.

The behaviors of some of the Chicago super-agers were similarly a surprise. Some exercised regularly, but some never had; some stuck to a Mediterranean diet, others subsisted off TV dinners; and a few of them still smoked cigarettes. However, one consistency among the group was that they tended to have strong social relationships , Dr. Rogalski said.

“In an ideal world, you’d find out that, like, all the super-agers, you know, ate six tomatoes every day and that was the key,” said Tessa Harrison, an assistant project scientist at the University of California, Berkeley, who collaborated with Dr. Rogalski on the first Chicago super-ager study.

Instead, Dr. Harrison continued, super-agers probably have “some sort of lucky predisposition or some resistance mechanism in the brain that’s on the molecular level that we don’t understand yet,” possibly related to their genes.

While there isn’t a recipe for becoming a super-ager, scientists do know that, in general , eating healthily, staying physically active, getting enough sleep and maintaining social connections are important for healthy brain aging.

Dana G. Smith is a Times reporter covering personal health, particularly aging and brain health. More about Dana G. Smith

A Guide to Aging Well

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Our research shows a strong link between unemployment and domestic violence: what does this mean for income support?

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Increasing income support could help keep women and children safe according to new work demonstrating strong links between financial insecurity and domestic violence.

Our mapping of local government areas in Melbourne and Sydney reinforces the relationship between unemployment and the greater risk of violence.

At a time when the nation is speaking out against the killing of women by men – with at least 27 deaths recorded since the start of this year – the federal government is under increasing pressure to help those at greatest risk.

How money might help

Financial dependence can trap people in abusive relationships. The dependency creates barriers to leaving , as victim-survivors may not have the money necessary for alternative housing, legal help and basic living expenses.

Higher income support for women can change the dynamics within relationships by enhancing their financial decision-making and bargaining power within the household.

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While higher income generally corresponds with lower domestic violence, overseas evidence suggests higher unemployment benefits may lengthen unemployment spells. In such situations, joblessness could lead to violence due to increased exposure between perpetrators and victim-survivors at home.

Economic downturns and personal financial crises can also cause uncertainty and household stress, which may escalate into abuse .

These economic patterns are clear in Australia. Areas with low-income and high-unemployment tend to have the highest levels of domestic violence.

Problem areas

The graphics below illustrate this by mapping unemployment and violence rates across local government areas in greater Sydney and greater Melbourne. The patterns are striking. High rates, marked in darker red, often occur in similar locations.

In Melbourne, the areas with the highest levels of both unemployment and domestic violence are greater Dandenong, Frankston, Casey, Cardinia, Maribyrnong, Brimbank, Melton and Hume. They are marked in red.

In Sydney, the highest rates are in Campbelltown, Liverpool, Canterbury-Bankstown, Fairfield, Penrith, Cumberland, Blacktown and Hawkesbury.

The economic disparities in domestic violence have also increased in recent years. In 2001, rates of violence in the most disadvantaged parts of New South Wales were about 5.6 times higher in the most advantaged suburbs. In 2023, these differences were almost 6.5 times higher.

Long lasting impact

Domestic violence disproportionately impacts women and children and can create significant long lasting social, health, psychological and financial damage.

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National data from 2016 which looked at costs including medical care, lost productivity, legal fees, and extended social services, puts the total annual costs at about $22 billion .

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Helping to solve the problem

Providing adequate financial support to vulnerable people during times of economic uncertainty is critical to reduce domestic violence and its harmful effects.

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Analysis of the almost doubling of payments during 2020 supports this conclusion.

Improving economic safety nets could help prevent environments that breed violence. Investing in safety is an essential step towards combating Australia’s domestic violence crisis.

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What is climate change mitigation and why is it urgent?

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• Climate change mitigation involves actions to reduce or prevent greenhouse gas emissions from human activities.
• Mitigation efforts include transitioning to renewable energy sources, enhancing energy efficiency, adopting regenerative agricultural practices and protecting and restoring forests and critical ecosystems.
• Effective mitigation requires a whole-of-society approach and structural transformations to reduce emissions and limit global warming to 1.5°C above pre-industrial levels.
• International cooperation, for example through the Paris Agreement, is crucial in guiding and achieving global and national mitigation goals.
• Mitigation efforts face challenges such as the world's deep-rooted dependency on fossil fuels, the increased demand for new mineral resources and the difficulties in revamping our food systems.
• These challenges also offer opportunities to improve resilience and contribute to sustainable development.

What is climate change mitigation?

Climate change mitigation refers to any action taken by governments, businesses or people to reduce or prevent greenhouse gases, or to enhance carbon sinks that remove them from the atmosphere. These gases trap heat from the sun in our planet’s atmosphere, keeping it warm. 

Since the industrial era began, human activities have led to the release of dangerous levels of greenhouse gases, causing global warming and climate change. However, despite unequivocal research about the impact of our activities on the planet’s climate and growing awareness of the severe danger climate change poses to our societies, greenhouse gas emissions keep rising. If we can slow down the rise in greenhouse gases, we can slow down the pace of climate change and avoid its worst consequences.

Reducing greenhouse gases can be achieved by:

• Shifting away from fossil fuels : Fossil fuels are the biggest source of greenhouse gases, so transitioning to modern renewable energy sources like solar, wind and geothermal power, and advancing sustainable modes of transportation, is crucial.
• Improving energy efficiency : Using less energy overall – in buildings, industries, public and private spaces, energy generation and transmission, and transportation – helps reduce emissions. This can be achieved by using thermal comfort standards, better insulation and energy efficient appliances, and by improving building design, energy transmission systems and vehicles.
• Changing agricultural practices : Certain farming methods release high amounts of methane and nitrous oxide, which are potent greenhouse gases. Regenerative agricultural practices – including enhancing soil health, reducing livestock-related emissions, direct seeding techniques and using cover crops – support mitigation, improve resilience and decrease the cost burden on farmers.
• The sustainable management and conservation of forests : Forests act as carbon sinks , absorbing carbon dioxide and reducing the overall concentration of greenhouse gases in the atmosphere. Measures to reduce deforestation and forest degradation are key for climate mitigation and generate multiple additional benefits such as biodiversity conservation and improved water cycles.
• Restoring and conserving critical ecosystems : In addition to forests, ecosystems such as wetlands, peatlands, and grasslands, as well as coastal biomes such as mangrove forests, also contribute significantly to carbon sequestration, while supporting biodiversity and enhancing climate resilience.
• Creating a supportive environment : Investments, policies and regulations that encourage emission reductions, such as incentives, carbon pricing and limits on emissions from key sectors are crucial to driving climate change mitigation.

Photo: Stephane Bellerose/UNDP Mauritius

Photo: La Incre and Lizeth Jurado/PROAmazonia

What is the 1.5°C goal and why do we need to stick to it?

In 2015, 196 Parties to the UN Climate Convention in Paris adopted the Paris Agreement , a landmark international treaty, aimed at curbing global warming and addressing the effects of climate change. Its core ambition is to cap the rise in global average temperatures to well below 2°C above levels observed prior to the industrial era, while pursuing efforts to limit the increase to 1.5°C.

The 1.5°C goal is extremely important, especially for vulnerable communities already experiencing severe climate change impacts. Limiting warming below 1.5°C will translate into less extreme weather events and sea level rise, less stress on food production and water access, less biodiversity and ecosystem loss, and a lower chance of irreversible climate consequences.

To limit global warming to the critical threshold of 1.5°C, it is imperative for the world to undertake significant mitigation action. This requires a reduction in greenhouse gas emissions by 45 percent before 2030 and achieving net-zero emissions by mid-century.

What are the policy instruments that countries can use to drive mitigation?

Everyone has a role to play in climate change mitigation, from individuals adopting sustainable habits and advocating for change to governments implementing regulations, providing incentives and facilitating investments. The private sector, particularly those businesses and companies responsible for causing high emissions, should take a leading role in innovating, funding and driving climate change mitigation solutions. 

International collaboration and technology transfer is also crucial given the global nature and size of the challenge. As the main platform for international cooperation on climate action, the Paris Agreement has set forth a series of responsibilities and policy tools for its signatories. One of the primary instruments for achieving the goals of the treaty is Nationally Determined Contributions (NDCs) . These are the national climate pledges that each Party is required to develop and update every five years. NDCs articulate how each country will contribute to reducing greenhouse gas emissions and enhance climate resilience.   While NDCs include short- to medium-term targets, long-term low emission development strategies (LT-LEDS) are policy tools under the Paris Agreement through which countries must show how they plan to achieve carbon neutrality by mid-century. These strategies define a long-term vision that gives coherence and direction to shorter-term national climate targets.

Photo: Mucyo Serge/UNDP Rwanda

Photo: William Seal/UNDP Sudan

At the same time, the call for climate change mitigation has evolved into a call for reparative action, where high-income countries are urged to rectify past and ongoing contributions to the climate crisis. This approach reflects the UN Framework Convention on Climate Change (UNFCCC) which advocates for climate justice, recognizing the unequal historical responsibility for the climate crisis, emphasizing that wealthier countries, having profited from high-emission activities, bear a greater obligation to lead in mitigating these impacts. This includes not only reducing their own emissions, but also supporting vulnerable countries in their transition to low-emission development pathways.

Another critical aspect is ensuring a just transition for workers and communities that depend on the fossil fuel industry and its many connected industries. This process must prioritize social equity and create alternative employment opportunities as part of the shift towards renewable energy and more sustainable practices.

For emerging economies, innovation and advancements in technology have now demonstrated that robust economic growth can be achieved with clean, sustainable energy sources. By integrating renewable energy technologies such as solar, wind and geothermal power into their growth strategies, these economies can reduce their emissions, enhance energy security and create new economic opportunities and jobs. This shift not only contributes to global mitigation efforts but also sets a precedent for sustainable development.

What are some of the challenges slowing down climate change mitigation efforts?

Mitigating climate change is fraught with complexities, including the global economy's deep-rooted dependency on fossil fuels and the accompanying challenge of eliminating fossil fuel subsidies. This reliance – and the vested interests that have a stake in maintaining it – presents a significant barrier to transitioning to sustainable energy sources.

The shift towards decarbonization and renewable energy is driving increased demand for critical minerals such as copper, lithium, nickel, cobalt, and rare earth metals. Since new mining projects can take up to 15 years to yield output, mineral supply chains could become a bottleneck for decarbonization efforts. In addition, these minerals are predominantly found in a few, mostly low-income countries, which could heighten supply chain vulnerabilities and geopolitical tensions.

Furthermore, due to the significant demand for these minerals and the urgency of the energy transition, the scaled-up investment in the sector has the potential to exacerbate environmental degradation, economic and governance risks, and social inequalities, affecting the rights of Indigenous Peoples, local communities, and workers. Addressing these concerns necessitates implementing social and environmental safeguards, embracing circular economy principles, and establishing and enforcing responsible policies and regulations .

Agriculture is currently the largest driver of deforestation worldwide. A transformation in our food systems to reverse the impact that agriculture has on forests and biodiversity is undoubtedly a complex challenge. But it is also an important opportunity. The latest IPCC report highlights that adaptation and mitigation options related to land, water and food offer the greatest potential in responding to the climate crisis. Shifting to regenerative agricultural practices will not only ensure a healthy, fair and stable food supply for the world’s population, but also help to significantly reduce greenhouse gas emissions.  

Photo: UNDP India

Photo: Nino Zedginidze/UNDP Georgia

What are some examples of climate change mitigation?

In Mauritius , UNDP, with funding from the Green Climate Fund, has supported the government to install battery energy storage capacity that has enabled 50 MW of intermittent renewable energy to be connected to the grid, helping to avoid 81,000 tonnes of carbon dioxide annually. 

In Indonesia , UNDP has been working with the government for over a decade to support sustainable palm oil production. In 2019, the country adopted a National Action Plan on Sustainable Palm Oil, which was collaboratively developed by government, industry and civil society representatives. The plan increased the adoption of practices to minimize the adverse social and environmental effects of palm oil production and to protect forests. Since 2015, 37 million tonnes of direct greenhouse gas emissions have been avoided and 824,000 hectares of land with high conservation value have been protected.

In Moldova and Paraguay , UNDP has helped set up Green City Labs that are helping build more sustainable cities. This is achieved by implementing urban land use and mobility planning, prioritizing energy efficiency in residential buildings, introducing low-carbon public transport, implementing resource-efficient waste management, and switching to renewable energy sources. 

UNDP has supported the governments of Brazil, Costa Rica, Ecuador and Indonesia to implement results-based payments through the REDD+ (Reducing emissions from deforestation and forest degradation in developing countries) framework. These include payments for environmental services and community forest management programmes that channel international climate finance resources to local actors on the ground, specifically forest communities and Indigenous Peoples. 

UNDP is also supporting small island developing states like the Comoros to invest in renewable energy and sustainable infrastructure. Through the Africa Minigrids Program , solar minigrids will be installed in two priority communities, Grand Comore and Moheli, providing energy access through distributed renewable energy solutions to those hardest to reach.

And in South Africa , a UNDP initative to boost energy efficiency awareness among the general population and improve labelling standards has taken over commercial shopping malls.

What is UNDP’s role in supporting climate change mitigation?

UNDP aims to assist countries with their climate change mitigation efforts, guiding them towards sustainable, low-carbon and climate-resilient development. This support is in line with achieving the Sustainable Development Goals (SDGs), particularly those related to affordable and clean energy (SDG7), sustainable cities and communities (SDG11), and climate action (SDG13). Specifically, UNDP’s offer of support includes developing and improving legislation and policy, standards and regulations, capacity building, knowledge dissemination, and financial mobilization for countries to pilot and scale-up mitigation solutions such as renewable energy projects, energy efficiency initiatives and sustainable land-use practices. 

With financial support from the Global Environment Facility and the Green Climate Fund, UNDP has an active portfolio of 94 climate change mitigation projects in 69 countries. These initiatives are not only aimed at reducing greenhouse gas emissions, but also at contributing to sustainable and resilient development pathways.

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What Reclassifying Marijuana Could Mean For Research And Drug Policy

In this photo illustration, packaging for a marijuana cigarette sits on top of dried cannabis flowers in San Anselmo, California. Justin Sullivan/Getty Images hide caption

In this photo illustration, packaging for a marijuana cigarette sits on top of dried cannabis flowers in San Anselmo, California.

For the last 50 years, the government has classified Marijuana as a schedule one drug.

Last Tuesday, Attorney General Merrick Garland did initiate the process to reclassify marijuana as a schedule three drug. Those substances are considered by the Drug Enforcement Agency to have moderate to low potential for physical and psychological dependence.

This recommendation does not make marijuana legal at the federal level. But for the first time, the government is acknowledging marijuana's potential medical benefits.

What does this move mean for marijuana research, and drug policy more broadly?

Find more of our programs online . Listen to 1A sponsor-free by signing up for 1A+ at plus.npr.org/the1a .

Did Miss USA Noelia Voigt's resignation statement contain a hidden message?

Noelia V oigt 's decision to relinquish her Miss USA crown has sparked a flurry of online speculation after fans noticed a strange detail about her statement.

Voigt, who was awarded Miss USA in September 2023, announced in a statement Monday on Instagram that she has decided to resign from the title, writing, "In life, I strongly value the importance of making decisions that feel best for you and your mental health."

But in the comments of her post and elsewhere on social media, users noticed that taking the first letter in each sentence of her statement reveals the phrase "I AM SILENCED" — though this discounts the last three sentences, the first letters of which spell "HIP." It was not immediately clear whether the message was intentional.

"First letter of each sentence. 'I AM SILENCED' we hear you Noelia!" read one comment on Instagram.

In a viral TikTok , user AnnaNoel suggested Voigt was "trying to tell us something important" with the "secret code," speculating, "(I) absolutely do not think this is a coincidence. ... Her putting this in there was so someone would find out and someone would be able to listen closely."

Need a break? Play the USA TODAY Daily Crossword Puzzle.

USA TODAY has reached out to Voigt and the Miss USA Organization for comment.

Miss USA Noelia Voigt makes 'tough decision' to step down. Read her full statement.

The organization previously said in a statement to USA TODAY, "We respect and support former Miss USA Noelia Voigt’s decision to step down from her duties. The well-being of our titleholders is a top priority, and we understand her need to prioritize herself at this time."

The statement added, "The organization is currently reviewing plans for the transition of responsibilities to a successor and an announcement regarding the crowning of the new Miss USA will be coming soon."

Miss Teen USA resigns days after Miss USA Noelia Voigt steps down

Prior to Voigt's announcement, Miss USA social media director Claudia Michelle shared on Instagram Friday that she has resigned from her role. In a statement posted to social media, she wrote, "I have had the privilege of getting to work with Noelia closely and have unfortunately seen a decline in her mental health since we (first) met. I feel like her ability to share her story and her platform have been diminished."

"I feel the way current management speaks about their titleholders is unprofessional and inappropriate," she went on to write. "I disavow workplace toxicity and bullying of any kind."

In an Instagram story, Michelle shared Voigt's statement and highlighted the "I AM SILENCED" letters.

In response to Michelle's post, the Miss USA Organization said in a statement to USA TODAY, "We are troubled to hear the false accusations made by a former Miss USA employee. Miss USA is committed to fostering a safe, inclusive, and supportive environment, and we take these allegations seriously. Indeed, we have and will continue to prioritize the well-being of all individuals involved with Miss USA."

In the caption of her original Instagram post, Voigt acknowledged that her resignation "may come as a large shock to many," but added, "Never compromise your physical and mental well-being."

Contributing: Erin Jensen , USA TODAY

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Steve bannon’s contempt of congress conviction upheld by appeals court, inside trump’s hush money trial with the electionline podcast; jfk, rfk jr & the state of mean + fighting iran’s death sentence against rapper toomaj salehi.

By Dominic Patten , Ted Johnson

Editors note:  Running until the final general election results come in, the  Deadline ElectionLine podcast  spotlights the 2024 campaign and the blurred lines between politics and entertainment in modern America. Hosted by Deadline’s political editor Ted Johnson and executive editor Dominic Patten, the podcast features commentary and interviews with top lawmakers and entertainment figures. At the same time, you can follow all the news in the Biden & Trump rematch and more on the  ElectionLine  hub on Deadline.

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In an America watching one historic norm after another collapse in Donald Trump ’s ongoing hush money trial, and the greater debasing of political dialogue, Welch’s blistering words are perhaps needed more than ever – as you can hear on the Deadline ElectionLine podcast above.

“It was interesting to hear Judge Merchan say to the prosecution team ‘I understand that your client is a little difficult to control,’” says Sean Piccoli of some of the fallout from Stormy Daniels ’ testimony this week at the Trump trial. “However much prep work they did up front, as you say, she’s going to play by her own rules, and her brain just seemed to be on fire when she spoke.”

With a unique perspective on one of the biggest stories around right now, Piccoli joins us on the podcast this week straight from the Manhattan criminal courts where he has been covering the former president’s trial for Deadline since its April 15 start. With not even still photographs now allowed in the court room, Piccili has an up close seat at American history in the making.

Also, Lord of the Rings: The Rings of Power ‘s Nazanin Boniadi  talks to us about the global fight she and other are waging against Iran’s pledg e to execute rapper Toomaj Salehi and imprison other artists who have protested against the Islamic Republic’s regime.

Then there is Congressman Mike Collins.

Just hours after it was revealed this week that Robert Kennedy Jr. suffered over a decade ago from a parasite eating a portion of his brain, the Georgia Republican decided a good way to get some attention would be to not only mock the independent presidential candidate’s health issues, but also the public assassination of his uncle President John F. Kennedy in Dallas in 1963.

Regardless of what you may think of JFK, RFK Jr, or any member of the Kennedy family, just because Collins believes in that P.T. Barnum adage that there is “no such thing as bad publicity,” doesn’t change the fact that his remarks are vile.

You either die a Kennedy with a hole in the brain or live long enough to become a Kennedy with a hole in the brain. — Rep. Mike Collins (@RepMikeCollins) May 8, 2024

As anyone who has ever attended a performance of Hamilton can tell you, men and women in public life in America have literally and figuratively been taking potshots at each other even before the Declaration of Independence was written. That’s nothing new from 1776 up to the bitter divisions of the Civil War. But, without trying to project era egotism, it sure feels like from Trump to Majorie Taylor Greene to the Jan. 6 assault on the Capitol and to Mike Collins that there is a coarsening of our culture.

Collins’ posting is a sure sign of that coarsening.

Yet, while the cruel comments spurred some outrage, by day’s end it was largely forgotten. Add to that, as we discuss on the podcast Friday, the fact that no major member of the GOP called Collins out for his rancor, and you have the sad state today of discourse in this country.

Still, with shame no longer a force in public life, Collins’ tweet is indicative of a new state of mean, where crassness is mistaken for toughness, and where any pushback is met with complaint that free speech is under attack, and the suggestion of apology is viewed as a signal of weakness. The goal is attention — the more outrage the better and no depth is too low.

Almost a generation ago, incumbent Republican senator George Allen referred to a Democratic operative in the crowd as “macaca,” a reference to his race. Allen apologized but lost his race for reelection.

Contrast that to now, such comments are all but overlooked. While not the only cause of such a debasement of the body politic, the rise of Trump has exacerbated and to a large degree, normalized the problem. For example, Trump repeatedly referred to his former transportation secretary Elaine Chow as “coco Chow.” While the comments got some pushback, it didn’t cost the once and present Republican nominee the important support of Chow’s husband, current Senate Minority leader Mitch McConnell. 

Collins’ attack on the Kennedys is another indication of where discourse has gone in this country — or, as Joseph N. Welch said 70 years ago: “Have you no sense of decency, sir?”

Stick with ElectionLine all the way to Election Day: Subscribe to the Deadline ElectionLine podcast on Spotify, Apple Music, iHeart, and all podcast platforms

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