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Research Findings – Types Examples and Writing Guide

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Research Findings

Definition:

Research findings refer to the results obtained from a study or investigation conducted through a systematic and scientific approach. These findings are the outcomes of the data analysis, interpretation, and evaluation carried out during the research process.

Types of Research Findings

There are two main types of research findings:

Qualitative Findings

Qualitative research is an exploratory research method used to understand the complexities of human behavior and experiences. Qualitative findings are non-numerical and descriptive data that describe the meaning and interpretation of the data collected. Examples of qualitative findings include quotes from participants, themes that emerge from the data, and descriptions of experiences and phenomena.

Quantitative Findings

Quantitative research is a research method that uses numerical data and statistical analysis to measure and quantify a phenomenon or behavior. Quantitative findings include numerical data such as mean, median, and mode, as well as statistical analyses such as t-tests, ANOVA, and regression analysis. These findings are often presented in tables, graphs, or charts.

Both qualitative and quantitative findings are important in research and can provide different insights into a research question or problem. Combining both types of findings can provide a more comprehensive understanding of a phenomenon and improve the validity and reliability of research results.

Parts of Research Findings

Research findings typically consist of several parts, including:

• Introduction: This section provides an overview of the research topic and the purpose of the study.
• Literature Review: This section summarizes previous research studies and findings that are relevant to the current study.
• Methodology : This section describes the research design, methods, and procedures used in the study, including details on the sample, data collection, and data analysis.
• Results : This section presents the findings of the study, including statistical analyses and data visualizations.
• Discussion : This section interprets the results and explains what they mean in relation to the research question(s) and hypotheses. It may also compare and contrast the current findings with previous research studies and explore any implications or limitations of the study.
• Conclusion : This section provides a summary of the key findings and the main conclusions of the study.
• Recommendations: This section suggests areas for further research and potential applications or implications of the study’s findings.

How to Write Research Findings

Writing research findings requires careful planning and attention to detail. Here are some general steps to follow when writing research findings:

• Organize your findings: Before you begin writing, it’s essential to organize your findings logically. Consider creating an outline or a flowchart that outlines the main points you want to make and how they relate to one another.
• Use clear and concise language : When presenting your findings, be sure to use clear and concise language that is easy to understand. Avoid using jargon or technical terms unless they are necessary to convey your meaning.
• Use visual aids : Visual aids such as tables, charts, and graphs can be helpful in presenting your findings. Be sure to label and title your visual aids clearly, and make sure they are easy to read.
• Use headings and subheadings: Using headings and subheadings can help organize your findings and make them easier to read. Make sure your headings and subheadings are clear and descriptive.
• Interpret your findings : When presenting your findings, it’s important to provide some interpretation of what the results mean. This can include discussing how your findings relate to the existing literature, identifying any limitations of your study, and suggesting areas for future research.
• Be precise and accurate : When presenting your findings, be sure to use precise and accurate language. Avoid making generalizations or overstatements and be careful not to misrepresent your data.
• Edit and revise: Once you have written your research findings, be sure to edit and revise them carefully. Check for grammar and spelling errors, make sure your formatting is consistent, and ensure that your writing is clear and concise.

Research Findings Example

Following is a Research Findings Example sample for students:

Title: The Effects of Exercise on Mental Health

Sample : 500 participants, both men and women, between the ages of 18-45.

Methodology : Participants were divided into two groups. The first group engaged in 30 minutes of moderate intensity exercise five times a week for eight weeks. The second group did not exercise during the study period. Participants in both groups completed a questionnaire that assessed their mental health before and after the study period.

Findings : The group that engaged in regular exercise reported a significant improvement in mental health compared to the control group. Specifically, they reported lower levels of anxiety and depression, improved mood, and increased self-esteem.

Conclusion : Regular exercise can have a positive impact on mental health and may be an effective intervention for individuals experiencing symptoms of anxiety or depression.

Applications of Research Findings

Research findings can be applied in various fields to improve processes, products, services, and outcomes. Here are some examples:

• Healthcare : Research findings in medicine and healthcare can be applied to improve patient outcomes, reduce morbidity and mortality rates, and develop new treatments for various diseases.
• Education : Research findings in education can be used to develop effective teaching methods, improve learning outcomes, and design new educational programs.
• Technology : Research findings in technology can be applied to develop new products, improve existing products, and enhance user experiences.
• Business : Research findings in business can be applied to develop new strategies, improve operations, and increase profitability.
• Public Policy: Research findings can be used to inform public policy decisions on issues such as environmental protection, social welfare, and economic development.
• Social Sciences: Research findings in social sciences can be used to improve understanding of human behavior and social phenomena, inform public policy decisions, and develop interventions to address social issues.
• Agriculture: Research findings in agriculture can be applied to improve crop yields, develop new farming techniques, and enhance food security.
• Sports : Research findings in sports can be applied to improve athlete performance, reduce injuries, and develop new training programs.

When to use Research Findings

Research findings can be used in a variety of situations, depending on the context and the purpose. Here are some examples of when research findings may be useful:

• Decision-making : Research findings can be used to inform decisions in various fields, such as business, education, healthcare, and public policy. For example, a business may use market research findings to make decisions about new product development or marketing strategies.
• Problem-solving : Research findings can be used to solve problems or challenges in various fields, such as healthcare, engineering, and social sciences. For example, medical researchers may use findings from clinical trials to develop new treatments for diseases.
• Policy development : Research findings can be used to inform the development of policies in various fields, such as environmental protection, social welfare, and economic development. For example, policymakers may use research findings to develop policies aimed at reducing greenhouse gas emissions.
• Program evaluation: Research findings can be used to evaluate the effectiveness of programs or interventions in various fields, such as education, healthcare, and social services. For example, educational researchers may use findings from evaluations of educational programs to improve teaching and learning outcomes.
• Innovation: Research findings can be used to inspire or guide innovation in various fields, such as technology and engineering. For example, engineers may use research findings on materials science to develop new and innovative products.

Purpose of Research Findings

The purpose of research findings is to contribute to the knowledge and understanding of a particular topic or issue. Research findings are the result of a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques.

The main purposes of research findings are:

• To generate new knowledge : Research findings contribute to the body of knowledge on a particular topic, by adding new information, insights, and understanding to the existing knowledge base.
• To test hypotheses or theories : Research findings can be used to test hypotheses or theories that have been proposed in a particular field or discipline. This helps to determine the validity and reliability of the hypotheses or theories, and to refine or develop new ones.
• To inform practice: Research findings can be used to inform practice in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners to make informed decisions and improve outcomes.
• To identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research.
• To contribute to policy development: Research findings can be used to inform policy development in various fields, such as environmental protection, social welfare, and economic development. By providing evidence-based recommendations, research findings can help policymakers to develop effective policies that address societal challenges.

Characteristics of Research Findings

Research findings have several key characteristics that distinguish them from other types of information or knowledge. Here are some of the main characteristics of research findings:

• Objective : Research findings are based on a systematic and rigorous investigation of a research question or hypothesis, using appropriate research methods and techniques. As such, they are generally considered to be more objective and reliable than other types of information.
• Empirical : Research findings are based on empirical evidence, which means that they are derived from observations or measurements of the real world. This gives them a high degree of credibility and validity.
• Generalizable : Research findings are often intended to be generalizable to a larger population or context beyond the specific study. This means that the findings can be applied to other situations or populations with similar characteristics.
• Transparent : Research findings are typically reported in a transparent manner, with a clear description of the research methods and data analysis techniques used. This allows others to assess the credibility and reliability of the findings.
• Peer-reviewed: Research findings are often subject to a rigorous peer-review process, in which experts in the field review the research methods, data analysis, and conclusions of the study. This helps to ensure the validity and reliability of the findings.
• Reproducible : Research findings are often designed to be reproducible, meaning that other researchers can replicate the study using the same methods and obtain similar results. This helps to ensure the validity and reliability of the findings.

Advantages of Research Findings

Research findings have many advantages, which make them valuable sources of knowledge and information. Here are some of the main advantages of research findings:

• Evidence-based: Research findings are based on empirical evidence, which means that they are grounded in data and observations from the real world. This makes them a reliable and credible source of information.
• Inform decision-making: Research findings can be used to inform decision-making in various fields, such as healthcare, education, and business. By identifying best practices and evidence-based interventions, research findings can help practitioners and policymakers to make informed decisions and improve outcomes.
• Identify gaps in knowledge: Research findings can help to identify gaps in knowledge and understanding of a particular topic, which can then be addressed by further research. This contributes to the ongoing development of knowledge in various fields.
• Improve outcomes : Research findings can be used to develop and implement evidence-based practices and interventions, which have been shown to improve outcomes in various fields, such as healthcare, education, and social services.
• Foster innovation: Research findings can inspire or guide innovation in various fields, such as technology and engineering. By providing new information and understanding of a particular topic, research findings can stimulate new ideas and approaches to problem-solving.
• Enhance credibility: Research findings are generally considered to be more credible and reliable than other types of information, as they are based on rigorous research methods and are subject to peer-review processes.

Limitations of Research Findings

While research findings have many advantages, they also have some limitations. Here are some of the main limitations of research findings:

• Limited scope: Research findings are typically based on a particular study or set of studies, which may have a limited scope or focus. This means that they may not be applicable to other contexts or populations.
• Potential for bias : Research findings can be influenced by various sources of bias, such as researcher bias, selection bias, or measurement bias. This can affect the validity and reliability of the findings.
• Ethical considerations: Research findings can raise ethical considerations, particularly in studies involving human subjects. Researchers must ensure that their studies are conducted in an ethical and responsible manner, with appropriate measures to protect the welfare and privacy of participants.
• Time and resource constraints : Research studies can be time-consuming and require significant resources, which can limit the number and scope of studies that are conducted. This can lead to gaps in knowledge or a lack of research on certain topics.
• Complexity: Some research findings can be complex and difficult to interpret, particularly in fields such as science or medicine. This can make it challenging for practitioners and policymakers to apply the findings to their work.
• Lack of generalizability : While research findings are intended to be generalizable to larger populations or contexts, there may be factors that limit their generalizability. For example, cultural or environmental factors may influence how a particular intervention or treatment works in different populations or contexts.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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• USC Libraries
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Organizing Your Social Sciences Research Paper

• 9. The Conclusion
• Purpose of Guide
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The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points derived from the findings of your study and, if applicable, where you recommend new areas for future research. For most college-level research papers, two or three well-developed paragraphs is sufficient for a conclusion, although in some cases, more paragraphs may be required in describing the key findings and their significance.

Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University.

Importance of a Good Conclusion

A well-written conclusion provides you with important opportunities to demonstrate to the reader your understanding of the research problem. These include:

• Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key findings in your analysis that advance new understanding about the research problem, that are unusual or unexpected, or that have important implications applied to practice.
• Summarizing your thoughts and conveying the larger significance of your study . The conclusion is an opportunity to succinctly re-emphasize  your answer to the "So What?" question by placing the study within the context of how your research advances past research about the topic.
• Identifying how a gap in the literature has been addressed . The conclusion can be where you describe how a previously identified gap in the literature [first identified in your literature review section] has been addressed by your research and why this contribution is significant.
• Demonstrating the importance of your ideas . Don't be shy. The conclusion offers an opportunity to elaborate on the impact and significance of your findings. This is particularly important if your study approached examining the research problem from an unusual or innovative perspective.
• Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing or contextualizing the research problem based on the results of your study.

Bunton, David. “The Structure of PhD Conclusion Chapters.” Journal of English for Academic Purposes 4 (July 2005): 207–224; Conclusions. The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Conclusions. The Writing Lab and The OWL. Purdue University; Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Structure and Writing Style

I.  General Rules

The general function of your paper's conclusion is to restate the main argument . It reminds the reader of the strengths of your main argument(s) and reiterates the most important evidence supporting those argument(s). Do this by clearly summarizing the context, background, and necessity of pursuing the research problem you investigated in relation to an issue, controversy, or a gap found in the literature. However, make sure that your conclusion is not simply a repetitive summary of the findings. This reduces the impact of the argument(s) you have developed in your paper.

When writing the conclusion to your paper, follow these general rules:

• Present your conclusions in clear, concise language. Re-state the purpose of your study, then describe how your findings differ or support those of other studies and why [i.e., what were the unique, new, or crucial contributions your study made to the overall research about your topic?].
• Do not simply reiterate your findings or the discussion of your results. Provide a synthesis of arguments presented in the paper to show how these converge to address the research problem and the overall objectives of your study.
• Indicate opportunities for future research if you haven't already done so in the discussion section of your paper. Highlighting the need for further research provides the reader with evidence that you have an in-depth awareness of the research problem but that further investigations should take place beyond the scope of your investigation.

Consider the following points to help ensure your conclusion is presented well:

• If the argument or purpose of your paper is complex, you may need to summarize the argument for your reader.
• If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data [this is opposite of the introduction, which begins with general discussion of the context and ends with a detailed description of the research problem]. 

The conclusion also provides a place for you to persuasively and succinctly restate the research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented. However, the nature of being introspective about the research you have conducted will depend on the topic and whether your professor wants you to express your observations in this way. If asked to think introspectively about the topics, do not delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply, not to guess at possible outcomes or make up scenarios not supported by the evidence.

II.  Developing a Compelling Conclusion

Although an effective conclusion needs to be clear and succinct, it does not need to be written passively or lack a compelling narrative. Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following:

• If your essay deals with a critical, contemporary problem, warn readers of the possible consequences of not attending to the problem proactively.
• Recommend a specific course or courses of action that, if adopted, could address a specific problem in practice or in the development of new knowledge leading to positive change.
• Cite a relevant quotation or expert opinion already noted in your paper in order to lend authority and support to the conclusion(s) you have reached [a good source would be from your literature review].
• Explain the consequences of your research in a way that elicits action or demonstrates urgency in seeking change.
• Restate a key statistic, fact, or visual image to emphasize the most important finding of your paper.
• If your discipline encourages personal reflection, illustrate your concluding point by drawing from your own life experiences.
• Return to an anecdote, an example, or a quotation that you presented in your introduction, but add further insight derived from the findings of your study; use your interpretation of results from your study to recast it in new or important ways.
• Provide a "take-home" message in the form of a succinct, declarative statement that you want the reader to remember about your study.

III. Problems to Avoid

Failure to be concise Your conclusion section should be concise and to the point. Conclusions that are too lengthy often have unnecessary information in them. The conclusion is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, and other forms of analysis that you make. Strategies for writing concisely can be found here .

Failure to comment on larger, more significant issues In the introduction, your task was to move from the general [the field of study] to the specific [the research problem]. However, in the conclusion, your task is to move from a specific discussion [your research problem] back to a general discussion framed around the implications and significance of your findings [i.e., how your research contributes new understanding or fills an important gap in the literature]. In short, the conclusion is where you should place your research within a larger context [visualize your paper as an hourglass--start with a broad introduction and review of the literature, move to the specific analysis and discussion, conclude with a broad summary of the study's implications and significance].

Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. These are problems, deficiencies, or challenges encountered during your study. They should be summarized as a way of qualifying your overall conclusions. If you encountered negative or unintended results [i.e., findings that are validated outside the research context in which they were generated], you must report them in the results section and discuss their implications in the discussion section of your paper. In the conclusion, use negative results as an opportunity to explain their possible significance and/or how they may form the basis for future research.

Failure to provide a clear summary of what was learned In order to be able to discuss how your research fits within your field of study [and possibly the world at large], you need to summarize briefly and succinctly how it contributes to new knowledge or a new understanding about the research problem. This element of your conclusion may be only a few sentences long.

Failure to match the objectives of your research Often research objectives in the social and behavioral sciences change while the research is being carried out. This is not a problem unless you forget to go back and refine the original objectives in your introduction. As these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].

Resist the urge to apologize If you've immersed yourself in studying the research problem, you presumably should know a good deal about it [perhaps even more than your professor!]. Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts! Don't undermine your authority as a researcher by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches that...." The overall tone of your conclusion should convey confidence to the reader about the study's validity and realiability.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University; Freedman, Leora  and Jerry Plotnick. Introductions and Conclusions. The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count. The Writer’s Handbook. Writing Center. University of Wisconsin Madison; Miquel, Fuster-Marquez and Carmen Gregori-Signes. “Chapter Six: ‘Last but Not Least:’ Writing the Conclusion of Your Paper.” In Writing an Applied Linguistics Thesis or Dissertation: A Guide to Presenting Empirical Research . John Bitchener, editor. (Basingstoke,UK: Palgrave Macmillan, 2010), pp. 93-105; Tips for Writing a Good Conclusion. Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Writing Conclusions. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization. Institute for Writing Rhetoric. Dartmouth College.

Writing Tip

Don't Belabor the Obvious!

Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining that they are reaching the end of your paper. You'll irritate your readers if you belabor the obvious.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Another Writing Tip

New Insight, Not New Information!

Don't surprise the reader with new information in your conclusion that was never referenced anywhere else in the paper. This why the conclusion rarely has citations to sources. If you have new information to present, add it to the discussion or other appropriate section of the paper. Note that, although no new information is introduced, the conclusion, along with the discussion section, is where you offer your most "original" contributions in the paper; the conclusion is where you describe the value of your research, demonstrate that you understand the material that you’ve presented, and position your findings within the larger context of scholarship on the topic, including describing how your research contributes new insights to that scholarship.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Conclusions. The Writing Center. University of North Carolina.

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How to Synthesize Written Information from Multiple Sources

Shona McCombes

Content Manager

B.A., English Literature, University of Glasgow

Shona McCombes is the content manager at Scribbr, Netherlands.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

When you write a literature review or essay, you have to go beyond just summarizing the articles you’ve read – you need to synthesize the literature to show how it all fits together (and how your own research fits in).

Synthesizing simply means combining. Instead of summarizing the main points of each source in turn, you put together the ideas and findings of multiple sources in order to make an overall point.

At the most basic level, this involves looking for similarities and differences between your sources. Your synthesis should show the reader where the sources overlap and where they diverge.

Unsynthesized Example

Franz (2008) studied undergraduate online students. He looked at 17 females and 18 males and found that none of them liked APA. According to Franz, the evidence suggested that all students are reluctant to learn citations style. Perez (2010) also studies undergraduate students. She looked at 42 females and 50 males and found that males were significantly more inclined to use citation software ( p < .05). Findings suggest that females might graduate sooner. Goldstein (2012) looked at British undergraduates. Among a sample of 50, all females, all confident in their abilities to cite and were eager to write their dissertations.

Synthesized Example

Studies of undergraduate students reveal conflicting conclusions regarding relationships between advanced scholarly study and citation efficacy. Although Franz (2008) found that no participants enjoyed learning citation style, Goldstein (2012) determined in a larger study that all participants watched felt comfortable citing sources, suggesting that variables among participant and control group populations must be examined more closely. Although Perez (2010) expanded on Franz’s original study with a larger, more diverse sample…

Step 1: Organize your sources

After collecting the relevant literature, you’ve got a lot of information to work through, and no clear idea of how it all fits together.

Before you can start writing, you need to organize your notes in a way that allows you to see the relationships between sources.

One way to begin synthesizing the literature is to put your notes into a table. Depending on your topic and the type of literature you’re dealing with, there are a couple of different ways you can organize this.

Summary table

A summary table collates the key points of each source under consistent headings. This is a good approach if your sources tend to have a similar structure – for instance, if they’re all empirical papers.

Each row in the table lists one source, and each column identifies a specific part of the source. You can decide which headings to include based on what’s most relevant to the literature you’re dealing with.

For example, you might include columns for things like aims, methods, variables, population, sample size, and conclusion.

For each study, you briefly summarize each of these aspects. You can also include columns for your own evaluation and analysis.

The summary table gives you a quick overview of the key points of each source. This allows you to group sources by relevant similarities, as well as noticing important differences or contradictions in their findings.

Synthesis matrix

A synthesis matrix is useful when your sources are more varied in their purpose and structure – for example, when you’re dealing with books and essays making various different arguments about a topic.

Each column in the table lists one source. Each row is labeled with a specific concept, topic or theme that recurs across all or most of the sources.

Then, for each source, you summarize the main points or arguments related to the theme.

The purposes of the table is to identify the common points that connect the sources, as well as identifying points where they diverge or disagree.

Step 2: Outline your structure

Now you should have a clear overview of the main connections and differences between the sources you’ve read. Next, you need to decide how you’ll group them together and the order in which you’ll discuss them.

For shorter papers, your outline can just identify the focus of each paragraph; for longer papers, you might want to divide it into sections with headings.

There are a few different approaches you can take to help you structure your synthesis.

If your sources cover a broad time period, and you found patterns in how researchers approached the topic over time, you can organize your discussion chronologically .

That doesn’t mean you just summarize each paper in chronological order; instead, you should group articles into time periods and identify what they have in common, as well as signalling important turning points or developments in the literature.

If the literature covers various different topics, you can organize it thematically .

That means that each paragraph or section focuses on a specific theme and explains how that theme is approached in the literature.

Source Used with Permission: The Chicago School

If you’re drawing on literature from various different fields or they use a wide variety of research methods, you can organize your sources methodologically .

That means grouping together studies based on the type of research they did and discussing the findings that emerged from each method.

If your topic involves a debate between different schools of thought, you can organize it theoretically .

That means comparing the different theories that have been developed and grouping together papers based on the position or perspective they take on the topic, as well as evaluating which arguments are most convincing.

Step 3: Write paragraphs with topic sentences

What sets a synthesis apart from a summary is that it combines various sources. The easiest way to think about this is that each paragraph should discuss a few different sources, and you should be able to condense the overall point of the paragraph into one sentence.

This is called a topic sentence , and it usually appears at the start of the paragraph. The topic sentence signals what the whole paragraph is about; every sentence in the paragraph should be clearly related to it.

A topic sentence can be a simple summary of the paragraph’s content:

“Early research on [x] focused heavily on [y].”

For an effective synthesis, you can use topic sentences to link back to the previous paragraph, highlighting a point of debate or critique:

“Several scholars have pointed out the flaws in this approach.” “While recent research has attempted to address the problem, many of these studies have methodological flaws that limit their validity.”

By using topic sentences, you can ensure that your paragraphs are coherent and clearly show the connections between the articles you are discussing.

As you write your paragraphs, avoid quoting directly from sources: use your own words to explain the commonalities and differences that you found in the literature.

Don’t try to cover every single point from every single source – the key to synthesizing is to extract the most important and relevant information and combine it to give your reader an overall picture of the state of knowledge on your topic.

Step 4: Revise, edit and proofread

Like any other piece of academic writing, synthesizing literature doesn’t happen all in one go – it involves redrafting, revising, editing and proofreading your work.

Checklist for Synthesis

•   Do I introduce the paragraph with a clear, focused topic sentence?
•   Do I discuss more than one source in the paragraph?
•   Do I mention only the most relevant findings, rather than describing every part of the studies?
•   Do I discuss the similarities or differences between the sources, rather than summarizing each source in turn?
•   Do I put the findings or arguments of the sources in my own words?
•   Is the paragraph organized around a single idea?
•   Is the paragraph directly relevant to my research question or topic?
•   Is there a logical transition from this paragraph to the next one?

Further Information

How to Synthesise: a Step-by-Step Approach

Help…I”ve Been Asked to Synthesize!

Learn how to Synthesise (combine information from sources)

How to write a Psychology Essay

• UConn Library
• Literature Review: The What, Why and How-to Guide
• Strategies to Find Sources

Literature Review: The What, Why and How-to Guide — Strategies to Find Sources

• Getting Started
• Introduction
• How to Pick a Topic
• Evaluating Sources & Lit. Reviews
• Tips for Writing Literature Reviews
• Writing Literature Review: Useful Sites
• Citation Resources
• Other Academic Writings

The Research Process

Planning : Before searching for articles or books, brainstorm to develop keywords that better describe your research question.

Searching : While searching, take note of what other keywords are used to describe your topic, and use them to conduct additional searches

     ♠ Most articles include a keyword section

     ♠ Key concepts may change names throughout time so make sure to check for variations

Organizing : Start organizing your results by categories/key concepts or any organizing principle that make sense for you . This will help you later when you are ready to analyze your findings

Analyzing : While reading, start making notes of key concepts and commonalities and disagreement among the research articles you find.

♠ Create a spreadsheet  to record what articles you are finding useful and why.

♠ Create fields to write summaries of articles or quotes for future citing and paraphrasing .

Writing : Synthesize your findings. Use your own voice to explain to your readers what you learned about the literature on your topic. What are its weaknesses and strengths? What is missing or ignored?

Repeat : At any given time of the process, you can go back to a previous step as necessary.

Advanced Searching

All databases have Help pages that explain the best way to search their product. When doing literature reviews, you will want to take advantage of these features since they can facilitate not only finding the articles that you really need but also controlling the number of results and how relevant they are for your search. The most common features available in the advanced search option of databases and library online catalogs are:

• Boolean Searching (AND, OR, NOT): Allows you to connect search terms in a way that can either limit or expand your search results 
• Proximity Searching (N/# or W/#): Allows you to search for two or more words that occur within a specified number of words (or fewer) of each other in the database
• Limiters/Filters : These are options that let you control what type of document you want to search: article type, date, language, publication, etc.
• Question mark (?) or a pound sign (#) for wildcard: Used for retrieving alternate spellings of a word: colo?r will retrieve both the American spelling "color" as well as the British spelling "colour." 
• Asterisk (*) for truncation: Used for retrieving multiple forms of a word: comput* retrieves computer, computers, computing, etc.

Want to keep track of updates to your searches? Create an account in the database to receive an alert when a new article is published that meets your search parameters!

• EBSCOhost Advanced Search Tutorial Tips for searching a platform that hosts many library databases
• Library's General Search Tips Check the Search tips to better used our library catalog and articles search system
• ProQuest Database Search Tips Tips for searching another platform that hosts library databases

There is no magic number regarding how many sources you are going to need for your literature review; it all depends on the topic and what type of the literature review you are doing:

► Are you working on an emerging topic? You are not likely to find many sources, which is good because you are trying to prove that this is a topic that needs more research. But, it is not enough to say that you found few or no articles on your topic in your field. You need to look broadly to other disciplines (also known as triangulation ) to see if your research topic has been studied from other perspectives as a way to validate the uniqueness of your research question.

► Are you working on something that has been studied extensively? Then you are going to find many sources and you will want to limit how far back you want to look. Use limiters to eliminate research that may be dated and opt to search for resources published within the last 5-10 years.

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How To Write A Research Summary

It’s a common perception that writing a research summary is a quick and easy task. After all, how hard can jotting down 300 words be? But when you consider the weight those 300 words carry, writing a research summary as a part of your dissertation, essay or compelling draft for your paper instantly becomes daunting task.

A research summary requires you to synthesize a complex research paper into an informative, self-explanatory snapshot. It needs to portray what your article contains. Thus, writing it often comes at the end of the task list.

Regardless of when you’re planning to write, it is no less of a challenge, particularly if you’re doing it for the first time. This blog will take you through everything you need to know about research summary so that you have an easier time with it.

What is a Research Summary?

A research summary is the part of your research paper that describes its findings to the audience in a brief yet concise manner. A well-curated research summary represents you and your knowledge about the information written in the research paper.

While writing a quality research summary, you need to discover and identify the significant points in the research and condense it in a more straightforward form. A research summary is like a doorway that provides access to the structure of a research paper's sections.

Since the purpose of a summary is to give an overview of the topic, methodology, and conclusions employed in a paper, it requires an objective approach. No analysis or criticism.

Research summary or Abstract. What’s the Difference?

They’re both brief, concise, and give an overview of an aspect of the research paper. So, it’s easy to understand why many new researchers get the two confused. However, a research summary and abstract are two very different things with individual purpose. To start with, a research summary is written at the end while the abstract comes at the beginning of a research paper.

A research summary captures the essence of the paper at the end of your document. It focuses on your topic, methods, and findings. More like a TL;DR, if you will. An abstract, on the other hand, is a description of what your research paper is about. It tells your reader what your topic or hypothesis is, and sets a context around why you have embarked on your research.

Getting Started with a Research Summary

Before you start writing, you need to get insights into your research’s content, style, and organization. There are three fundamental areas of a research summary that you should focus on.

• While deciding the contents of your research summary, you must include a section on its importance as a whole, the techniques, and the tools that were used to formulate the conclusion. Additionally, there needs to be a short but thorough explanation of how the findings of the research paper have a significance.
• To keep the summary well-organized, try to cover the various sections of the research paper in separate paragraphs. Besides, how the idea of particular factual research came up first must be explained in a separate paragraph.
• As a general practice worldwide, research summaries are restricted to 300-400 words. However, if you have chosen a lengthy research paper, try not to exceed the word limit of 10% of the entire research paper.

How to Structure Your Research Summary

The research summary is nothing but a concise form of the entire research paper. Therefore, the structure of a summary stays the same as the paper. So, include all the section titles and write a little about them. The structural elements that a research summary must consist of are:

It represents the topic of the research. Try to phrase it so that it includes the key findings or conclusion of the task.

The abstract gives a context of the research paper. Unlike the abstract at the beginning of a paper, the abstract here, should be very short since you’ll be working with a limited word count.

Introduction

This is the most crucial section of a research summary as it helps readers get familiarized with the topic. You should include the definition of your topic, the current state of the investigation, and practical relevance in this part. Additionally, you should present the problem statement, investigative measures, and any hypothesis in this section.

Methodology

This section provides details about the methodology and the methods adopted to conduct the study. You should write a brief description of the surveys, sampling, type of experiments, statistical analysis, and the rationality behind choosing those particular methods.

Create a list of evidence obtained from the various experiments with a primary analysis, conclusions, and interpretations made upon that. In the paper research paper, you will find the results section as the most detailed and lengthy part. Therefore, you must pick up the key elements and wisely decide which elements are worth including and which are worth skipping.

This is where you present the interpretation of results in the context of their application. Discussion usually covers results, inferences, and theoretical models explaining the obtained values, key strengths, and limitations. All of these are vital elements that you must include in the summary.

Most research papers merge conclusion with discussions. However, depending upon the instructions, you may have to prepare this as a separate section in your research summary. Usually, conclusion revisits the hypothesis and provides the details about the validation or denial about the arguments made in the research paper, based upon how convincing the results were obtained.

The structure of a research summary closely resembles the anatomy of a scholarly article . Additionally, you should keep your research and references limited to authentic and  scholarly sources only.

Tips for Writing a Research Summary

The core concept behind undertaking a research summary is to present a simple and clear understanding of your research paper to the reader. The biggest hurdle while doing that is the number of words you have at your disposal. So, follow the steps below to write a research summary that sticks.

1. Read the parent paper thoroughly

You should go through the research paper thoroughly multiple times to ensure that you have a complete understanding of its contents. A 3-stage reading process helps.

a. Scan: In the first read, go through it to get an understanding of its basic concept and methodologies.

b. Read: For the second step, read the article attentively by going through each section, highlighting the key elements, and subsequently listing the topics that you will include in your research summary.

c. Skim: Flip through the article a few more times to study the interpretation of various experimental results, statistical analysis, and application in different contexts.

Sincerely go through different headings and subheadings as it will allow you to understand the underlying concept of each section. You can try reading the introduction and conclusion simultaneously to understand the motive of the task and how obtained results stay fit to the expected outcome.

2. Identify the key elements in different sections

While exploring different sections of an article, you can try finding answers to simple what, why, and how. Below are a few pointers to give you an idea:

• What is the research question and how is it addressed?
• Is there a hypothesis in the introductory part?
• What type of methods are being adopted?
• What is the sample size for data collection and how is it being analyzed?
• What are the most vital findings?
• Do the results support the hypothesis?

Discussion/Conclusion

• What is the final solution to the problem statement?
• What is the explanation for the obtained results?
• What is the drawn inference?
• What are the various limitations of the study?

3. Prepare the first draft

Now that you’ve listed the key points that the paper tries to demonstrate, you can start writing the summary following the standard structure of a research summary. Just make sure you’re not writing statements from the parent research paper verbatim.

Instead, try writing down each section in your own words. This will not only help in avoiding plagiarism but will also show your complete understanding of the subject. Alternatively, you can use a summarizing tool (AI-based summary generators) to shorten the content or summarize the content without disrupting the actual meaning of the article.

SciSpace Copilot is one such helpful feature! You can easily upload your research paper and ask Copilot to summarize it. You will get an AI-generated, condensed research summary. SciSpace Copilot also enables you to highlight text, clip math and tables, and ask any question relevant to the research paper; it will give you instant answers with deeper context of the article..

4. Include visuals

One of the best ways to summarize and consolidate a research paper is to provide visuals like graphs, charts, pie diagrams, etc.. Visuals make getting across the facts, the past trends, and the probabilistic figures around a concept much more engaging.

5. Double check for plagiarism

It can be very tempting to copy-paste a few statements or the entire paragraphs depending upon the clarity of those sections. But it’s best to stay away from the practice. Even paraphrasing should be done with utmost care and attention.

Also: QuillBot vs SciSpace: Choose the best AI-paraphrasing tool

6. Religiously follow the word count limit

You need to have strict control while writing different sections of a research summary. In many cases, it has been observed that the research summary and the parent research paper become the same length. If that happens, it can lead to discrediting of your efforts and research summary itself. Whatever the standard word limit has been imposed, you must observe that carefully.

7. Proofread your research summary multiple times

The process of writing the research summary can be exhausting and tiring. However, you shouldn’t allow this to become a reason to skip checking your academic writing several times for mistakes like misspellings, grammar, wordiness, and formatting issues. Proofread and edit until you think your research summary can stand out from the others, provided it is drafted perfectly on both technicality and comprehension parameters. You can also seek assistance from editing and proofreading services , and other free tools that help you keep these annoying grammatical errors at bay.

8. Watch while you write

Keep a keen observation of your writing style. You should use the words very precisely, and in any situation, it should not represent your personal opinions on the topic. You should write the entire research summary in utmost impersonal, precise, factually correct, and evidence-based writing.

9. Ask a friend/colleague to help

Once you are done with the final copy of your research summary, you must ask a friend or colleague to read it. You must test whether your friend or colleague could grasp everything without referring to the parent paper. This will help you in ensuring the clarity of the article.

Once you become familiar with the research paper summary concept and understand how to apply the tips discussed above in your current task, summarizing a research summary won’t be that challenging. While traversing the different stages of your academic career, you will face different scenarios where you may have to create several research summaries.

In such cases, you just need to look for answers to simple questions like “Why this study is necessary,” “what were the methods,” “who were the participants,” “what conclusions were drawn from the research,” and “how it is relevant to the wider world.” Once you find out the answers to these questions, you can easily create a good research summary following the standard structure and a precise writing style.

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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))

16k 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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• Published: 08 May 2024

Ligand cross-feeding resolves bacterial vitamin B 12 auxotrophies

• Gerrit Wienhausen   ORCID: orcid.org/0000-0002-3562-5997 1 , 2 ,
• Cristina Moraru   ORCID: orcid.org/0000-0002-5375-5437 1 , 3 ,
• Stefan Bruns   ORCID: orcid.org/0000-0002-4267-7832 1 ,
• Den Quoc Tran 1 ,
• Sabiha Sultana 1 ,
• Heinz Wilkes 1 ,
• Leon Dlugosch 1 ,
• Farooq Azam 2 &
• Meinhard Simon   ORCID: orcid.org/0000-0002-6151-6989 1 , 4  

Nature ( 2024 ) Cite this article

Metrics details

• Ecological networks
• Marine microbiology
• Metabolomics

Cobalamin (vitamin B 12 , herein referred to as B 12 ) is an essential cofactor for most marine prokaryotes and eukaryotes 1 , 2 . Synthesized by a limited number of prokaryotes, its scarcity affects microbial interactions and community dynamics 2 , 3 , 4 . Here we show that two bacterial B 12 auxotrophs can salvage different B 12 building blocks and cooperate to synthesize B 12 . A Colwellia sp. synthesizes and releases the activated lower ligand α-ribazole, which is used by another B 12 auxotroph, a Roseovarius sp., to produce the corrin ring and synthesize B 12 . Release of B 12 by Roseovarius sp. happens only in co-culture with Colwellia sp. and only coincidently with the induction of a prophage encoded in Roseovarius sp. Subsequent growth of Colwellia sp. in these conditions may be due to the provision of B 12 by lysed cells of Roseovarius sp. Further evidence is required to support a causative role for prophage induction in the release of B 12 . These complex microbial interactions of ligand cross-feeding and joint B 12 biosynthesis seem to be widespread in marine pelagic ecosystems. In the western and northern tropical Atlantic Ocean, bacteria predicted to be capable of salvaging cobinamide and synthesizing only the activated lower ligand outnumber B 12 producers. These findings add new players to our understanding of B 12 supply to auxotrophic microorganisms in the ocean and possibly in other ecosystems.

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Data availability

Complete genome sequences of Colwellia sp. M166 and Roseovarius sp. M141 were uploaded into the NCBI and annotated by JGI Gold. Genomes can be inquired by their IMG genome identifiers 2828890045 for Colwellia and 2828508468 for Roseovarius . Transcriptomic sequences generated in this study have been deposited into the ENA at EMBL-EBI with the accession number PRJEB43320 , using the data brokerage service of the GFBio in compliance with the Minimal Information about any (X) Sequence (MIxS) standard. The data from the sampling stations (ANT-XXVIII/4 and ANT-XXVIII/5) are available from PANGEA under the accession number PANGAEA.906247 , and respective sequence data can be retrieved from the ENA under the INSDC accession number PRJEB34453 . The SILVA and rfam database was used for transcriptome analysis. For bacterial gene annotation, the ProGenome database was used, and for phage gene and protein annotation, the NR database (from the NCBI), the Virus Orthologous Group database, the InterPro database and the HMM database were used.  Source data are provided with this paper.

Code availability

No specialized in-house code was used for this study. All software used for the data analyses in this study are publicly available and cited in the Methods . Custom scripts and the pipeline used have been deposited into GitHub ( https://github.com/LeonDlugosch/MetaSeq-Toolkit ).

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Acknowledgements

We are grateful to C. Alejandre-Colomo, R. Mosseló-Móra, R. Amann and V. Bischoff for providing the North Sea collection of bacterial isolates; B. Kuerzel and M. Wolterink for technical assistance in the HPLC analysis of amino acids and enumerating VLPs; the captains, their crews and the scientific groups of the cruises ANT XXVIII/4 and XXVIII/5 of RV Polarstern and RV Senckenberg for their support; S. Sañudo-Wilhelmy for stimulating discussions regarding B 12 analyses; and D. Kirchman for carefully revising a previous version of this publication This work was supported by Deutsche Forschungsgemeinschaft within the Transregional Collaborative Research Center Roseobacter (TRR51) and the Gordon and Betty Moore Foundation (to F.A.).

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Institute for Chemistry and Biology of the Marine Environment (ICBM), School of Mathematics and Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany

Gerrit Wienhausen, Cristina Moraru, Stefan Bruns, Den Quoc Tran, Sabiha Sultana, Heinz Wilkes, Leon Dlugosch & Meinhard Simon

Scripps Institution of Oceanography, Marine Biology Research Division, University of California San Diego, La Jolla, CA, USA

Gerrit Wienhausen & Farooq Azam

Environmental Metagenomics, Research Center One Health Ruhr of the University Alliance Ruhr, Faculty of Chemistry, University of Duisburg-Essen, Essen, Germany

Cristina Moraru

Helmholtz Institute for Functional Marine Biodiversity at the University of Oldenburg (HIFMB), Oldenburg, Germany

Meinhard Simon

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Contributions

G.W. designed the study, carried out the experiments, the genome analyses for B 12 biosynthetic pathways, the transcriptomic analyses and wrote the manuscript. C.M. and G.W. carried out the direct-geneFISH analyses for prophage induction and the prophage-related genomic analyses. D.Q.T. contributed to the CARD-FISH analyses. S.B. and H.W. analysed B 12 . S.S. assisted in the tripartite consortium experiment. L.D. carried out the transcriptome mapping and mapping of taxa with different B 12 genetic traits to the Atlantic Ocean microbiome. F.A. partially supervised the co-culture experiments. M.S. assisted in designing the study, partially supervised the experiments and data analyses and wrote the manuscript, together with G.W. All authors revised the manuscript to finalize it.

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Correspondence to Gerrit Wienhausen or Meinhard Simon .

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Extended data figures and tables

Extended data fig. 1 growth characteristics of colwellia and roseovarius when supplemented with and without b 12 and respective building blocks and methionine and chaetoceros muelleri in tri-culture with colwellia and roseovarius..

a , Maximum growth yield as means of triplicates ± SD as total cell numbers per ml assessed by flow cytometry of Roseovarius ; b , of Colwellia when supplemented with B 12 (at 1, 10 or 100 pM) or DMB / Cbi (at 1, 10 or 100 pM); Maximum growth yield as means of triplicates ± SD as determined by optical density of c , Roseovarius and d , Colwellia . Each isolate was supplemented with B 12 (100 pM), no addition (plain bar) and methionine (1 µM); e , Chlorophyll a fluorescence and total cell numbers enumerated by hemocytometer of axenic Chaetoceros muelleri over time when cultivated without any addition, f , supplemented with B 12 at 10 pM and g , 100 pM final concentration and h , when grown in tri-culture with Colwellia or Roseovarius . Experiments a - d were conducted in n = 3 and experiments e - h in n = 4 biological independent samples each in 1 independent experiment.

Source Data

Extended Data Fig. 2 Metabolic pathways related to cobalamin biosynthesis and transcript expression patterns of Colwellia and Roseovarius grown in co-culture.

Differential gene expression between the control, represented by the mono-cultures ( Roseovarius & Colwellia ) with B 12 added, and the co-culture, without B 12 addition, was quantified with the DESeq2 package as implemented in R v4.0.5 (R-Core-Team, 2022). In each treatment n = 3 biological independent samples were used. Coloring of genes refers to their LOG-2FC regulation, defined as downregulated (light red to red), upregulated (light green to dark green) and similarly regulated (orange). Genes that are significantly regulated (LOG2-FC larger than 2 and smaller than −2 with an BH adj. p -value < 0.05) are marked with an asterisk. When an illustration represents more than one gene (all genes > (-) 2 LOG-2FC and adj. p -value < 0.05), the asterisk is placed in brackets. Genes that were not identified in the genome (grey). Since the bluB gene in Roseovarius is missing a large section of the sequence, we have indicated this by outlining the gene in gray. Corresponding gene expression significances (adjusted p -value) and further details on genes are presented in Supplementary Data  2 . Our documented microbial interactions including the coincidence of prophage induction, host cell lysis and release of B 12 , whose causative relationships still need to be proven, are illustrated and explained by the dashed arrows and the explanations 1–6 in the legend.

Extended Data Fig. 3 Growth and substrate use of Colwellia and Roseovarius when supplemented with B 12 building blocks.

Presented are total bacterial cell numbers assessed by flow cytometry and glutamate (glutamic acid) concentrations of a - d , Colwellia and e - h , Roseovarius supplemented with a , e , B 12 , b , f , DMB and c , g , Cbi at 1 nM final concentrations each and d , h , without any supplementation and of as well as i , Colwellia + Roseovarius when cultivated in co-culture without any addition. Shown are means of triplicates ± SD. Each condition was carried out in n = 3 biological independent samples and growth characteristics were confirmed in independently conducted experiments.

Extended Data Fig. 4 Growth characteristics of Thalassiosira pseudonana and Colwellia and Roseovarius cultivated in consortium.

a , Growth of Colwellia and Roseovarius as monitored by flow cytometric cell counts and calculated by CARD-FISH analyses. Further, numbers of virus-like particles measured by flow cytometry are presented. b , cell numbers of T. pseudonana , assessed microscopically using a hemocytometer, and bacterial cells (black circle) assessed by flow cytometry. c , Total bacterial cell abundance and the ratio of virus-like particle counts to the number of Colwellia . d , Total bacterial cell abundance and the ratio of virus-like particle counts to the number of Roseovarius . e , Relative proportions of Colwellia and Roseovarius cells (% of total abundance) during the culturing time. f . Descriptive illustration of the growth progression of the participating partners of the consortium, T. pseudonana , Roseovarius and Colwellia as well as the phage induction over a period of ten weeks. g , Maximum relative fluorescence of T. pseudonana when cultured with Colwellia and Roseovarius , with addition of 100 pM B 12 , without any addition, in co-culture with Roseovarius and in co-culture with Colwellia . a - f , Means of triplicates g , and ± SD. Measured values of the respective triplicates can be viewed in the corresponding source data file. Each treatment was carried out in n = 3 biological independent samples and growth characteristics were confirmed in independently conducted tests.

Extended Data Fig. 5 Lower ligand building block concentration in the exudate of Colwellia at B 12 (20 pM) depleted growth conditions and in North Sea seawater samples.

a , means of triplicates + SD of growth of Colwellia supplemented with 1 nM B 12 , 20 pM B 12 and no addition, monitored by flow cytometric cell counts over time. Extracellular concentrations of α-ribazole and 5,6-dimethylbenzimidazole (DMB) were measured for the growth-limited culture when supplemented with 20 pM B 12 . b , concentrations of B 12 , cobinamide, DMB and α -ribazole in North Sea seawater samples as means of triplicates + SD. c , Map of the German Bight of the North Sea. Points mark the sampling stations of the analyzed seawater samples. Experiment a was conducted in n = 3 biological independent samples. Experiment b was conducted on n = 3 independent sampling locations and each sample was detected in n = 3 technical replicates. Experiments a - b were conducted in 1 independent experiment. The map was created using Ocean Data View.

Extended Data Fig. 6 Predicted cobamide biosynthesis phenotypes in genomes of marine bacteria and their relative abundance in the Atlantic Ocean.

a , Map showing 22 stations (black dots) from 62°S in the Southern Ocean sector to 47°N in the north Atlantic Ocean sampled at 20 m depth during cruises ANTXXVIII/4 and /5 with RV Polarstern. The percentage given along each pie chart represents the proportion of genome-sequenced prokaryotes of the entire prokaryotic community (identified by 16S rRNA gene). The pie chart of every station sampled presents relative proportions of prokaryotes encoding i) the complete B 12 biosynthesis pathway (B 12 producers; red), ii) corrin ring biosynthesiser (dark red), iii) cobinamide salvagers (lower ligand producers) (pink) iv) prokaryotes identified as B 12 non-producers (grey). Stations are overlayed on a map with annual mean concentrations of chlorophyll a at the surface ( https://oceandata.sci.gsfc.nasa.gov ). b - e , B 12 biosynthesis genes of 1,904 genomes of marine bacteria were analyzed and classified into cobamide biosynthesis phenotypes: as described above for a . Presented are relative abundance of b , all analyzed bacteria, c , phyla and classes, d , orders of Alphaproteobacteria and e , orders of Gammaproteobacteria.

Extended Data Fig. 7 Proportions of genes encoding reactions of B 12 biosynthesis in genomes of Rhodobacterales , Alteromonadales , Vibrionales and Betaproteobacteria.

Presence (as percentage) of individual B 12 biosynthesis genes in Rhodobacterales (220), Alteromonadales (96), Vibrionales (52) and Betaproteobacteria (126) genomes. Percent of gene abundance is given in color-coded 10% increments from red (0%) to dark green (100%). Genes depicted in grey were not identified in examined genomes.

Extended Data Fig. 8 (Pro)-phage targeting direct-geneFISH signal intensities.

Shown are the mean relative intensities of the (pro)-phage targeting direct-geneFISH signals of Roseovarius in triplicate co-culture samples withdrawn after 96 h and 120 h and the mono-culture Roseovarius samples withdrawn after 96 h as boxplots. Individual, small dots represent the (pro)-phage targeting direct-geneFISH signal intensities of the individually measured regions of interest (ROI; approximate one cell). At least 465 ROIs were defined and validated for each sample. The red dashed line defines the threshold for the definition of induced cells. The percentage below the samples indicates the proportion of induced cells in the total cells analyzed. In each treatment n = 3 biological independent samples were run. The lower and upper hinges of the box correspond to the first and third quartiles (the 25th and 75th percentiles). The central line in the box is the median. The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles). The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. Data beyond the end of the whiskers are called “outlying” points and are plotted individually. Prophage induction events, indicated by a significant increase of the phage signal intensity in regions of interest (ROI), were observed in 2 independent experiments.

Extended Data Fig. 9 Enumeration of bacterial cells and virus-like particles of Colwellia and Roseovarius grown in co- and mono-culture.

a , Bacterial cell numbers (white triangle) and ratio of virus-like particles to bacterial cell number (black circle) of Colwellia and Roseovarius growing in co-culture, c , Roseovarius and e , Colwellia in mono-culture with B 12 supplementation. b , Bacterial cell numbers (white triangle) and virus-like particles (black circle) of Colwellia and Roseovarius growing in co-culture, d , Roseovarius and f , Colwellia in mono-culture with B 12 supplementation. Shown are means of triplicates + SD. Each treatment was carried out in n = 3 biological independent samples and growth characteristics were confirmed in independently conducted tests.

Supplementary information

Supplementary figures.

Supplementary Figs. 1–5.

Reporting Summary

Peer review file, supplementary table 1.

Growth rate, growth yield and required molecules per cell of Colwellia and Roseovarius growing in mono-culture when supplemented with B 12 or respective B 12 building blocks.

Supplementary Table 2

Intracellular vitamin B 12 recovery (Hydroxycobalamin, Cyanocobalamin, Adenosylcobalamin, Methylcobalamin) by LC–MS of Colwellia and Roseovarius growing in mono-culture when supplemented with B 12 or respective B 12 building blocks.

Supplementary Table 3

Growth rate and growth yield of C. muelleri growing in mono-culture when supplemented with B 12 or in consortium with Colwellia and Roseovarius .

Supplementary Table 4

Composition of synASW medium and synASW medium trace elements solution, used for combined diatom–bacteria cultivation of C .  muellieri or T.   pseudonana with Roseovarius and Colwellia .

Supplementary Table 5

Settings used for selected reaction monitoring.

Supplementary Data 1

Identification of B 12 biosynthesis genes, B 12 -dependent reactions, B 12 -indipendent reactions, B 12 transporter genes and B 12 salvage genes in the genomes of Roseovarius and Colwellia .

Supplementary Data 2

Transcriptional gene regulation of both bacterial isolates in co-culture compared with gene regulation when supplemented with the addition of B 12 (1 nM) cultivated in mono-culture. Genes transcribed at a log 2 (FC) below –2 and above 2 are outlined in separate sheets, highlighting respective cellular functions.

Supplementary Data 3

Classification of B 12 pathway synthesizing groups of publicly available aquatic bacterial genomes.

Supplementary Data 4

Gene annotation of the prophage Roseophage ICBM167.

Supplementary Data 5

Polynucleotide probe mixture for the detection of Roseophage ICBM167 by targeted direct-geneFISH.

Source data

Source data fig. 1, source data fig. 3, source data fig. 4, source data extended data fig. 1, source data extended data fig. 3, source data extended data fig. 4, source data extended data fig. 5, source data extended data fig. 8, source data extended data fig. 9, rights and permissions.

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Wienhausen, G., Moraru, C., Bruns, S. et al. Ligand cross-feeding resolves bacterial vitamin B 12 auxotrophies. Nature (2024). https://doi.org/10.1038/s41586-024-07396-y

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COVID-19 Vaccination Public Education Campaign Saved Thousands of Lives, Billions of Dollars

Study found vaccine campaign saved $90 for every $1 spent 

The U.S. Department of Health and Human Services’ (HHS) COVID-19 Vaccination Public Education Campaign, We Can Do This, resulted in an estimated$731.9 billion in societal benefits due to averted illness and related costs, resulting in a nearly $90 return in societal benefits for every $1 spent, according to research published today in the American Journal of Preventive Medicine .

“At the height of the pandemic, we launched one of the largest public health education campaigns in U.S. history to encourage and educate Americans on the steps they could take to get and stay healthy. We now have research to confirm the COVID-19 Public Education Campaign, We Can Do This, was an indispensable part of efforts to vaccinate people and protect them from COVID-19, saving thousands of lives and billions of dollars in the process,” said HHS Secretary Xavier Becerra. “HHS is responsible for protecting the health and well-being of all Americans. As stewards of the public’s money, we wanted to deliver impact for the American people in the most efficient and effective ways. This confirms we did exactly that. We will no doubt use what we learned in this campaign to further improve our public health efforts in the future.”

The study showed the Campaign encouraged 22.3 million people to complete their primary COVID-19 vaccination series between April 2021 and March 2022, preventing nearly 2.6 million SARS-CoV-2 infections, the virus that causes COVID-19, including nearly 244,000 hospitalizations, during the time period that the highly contagious Delta and Omicron virus variants were spreading.

Preventing these outcomes resulted in societal benefits to the U.S. of $740.2 billion, accounting for such factors as medical expenses, wages, and other costs that people and institutions would have incurred in the absence of the Campaign. In comparison, the Campaign cost $377 million, with an additional $7.9 billion spent to vaccinate 22.3 million people in that time period.

According to the study, from April 2021 to March 2022, the net benefit of the Campaign—how much money these efforts saved minus how much they cost—came to $731.9 billion, translating to a return on investment of $89.54 for every $1 spent.

In April 2021, HHS launched the We Can Do This Public Education Campaign to increase COVID-19 vaccine confidence and uptake in the U.S. The Campaign, one of the largest public health education efforts in U.S. history, promoted COVID-19 vaccine uptake using integrated, multichannel, research-based strategies. It aimed to reach 90% of adults in the United States at least once per quarter, with even more intense outreach to high-risk communities. The Campaign featured more than 7,000 ads in 14 languages, with many culturally tailored and geographically targeted to specific minority, racial, and ethnic audiences. A multimedia approach bolstered widespread engagement with trusted messengers, partner organizations, and influencers who delivered persuasive, accurate, and culturally relevant information to vaccine-hesitant populations.

The benefit-cost study of We Can Do This is the only research study to date that looked at the contributions of a media campaign to encourage people to get COVID-19 vaccines during the pandemic emergency period. The newly published study is unique in that it demonstrates that the nationwide media Campaign was an indispensable component of the nation’s efforts to vaccinate people and protect them from COVID-19. It also adds to the body of evidence that shows the Campaign’s impact on behavior change.

“This research confirms the benefits of public health campaigns as part of a multi-layered response to a public health crisis and to the effort to provide accurate information to the American public,” said May Malik, Senior Advisor for Public Education Campaigns at HHS.

To evaluate the benefits and costs of the national Campaign, researchers used real-world data from multiple sources, such as data on COVID-19 outcomes, uptake of COVID-19 vaccines, and vaccine effectiveness, from the U.S. Centers for Disease Control and Prevention (CDC), along with survey data collected to measure the Campaign’s effects on vaccination behaviors over time.

The findings can help inform the Federal response to future public health threats. As part of a multipronged approach to addressing public health crises, this study demonstrates the return on investment possible from public education campaigns given their effectiveness in building vaccine confidence and supporting healthy behavior change.

The study, Benefit-Cost Analysis of the HHS COVID-19 Campaign: April 2021–March 2022 , was conducted by researchers from HHS Office of the Assistant Secretary for Public Affairs and Fors Marsh in Arlington, Virginia.

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Serotonergic neuron findings suggest possible treatment for depression-related infertility

by Nagoya University

Scientists from Nagoya University in Japan have clarified the relationship between energy levels and fertility in animals and humans. They identified signaling from serotonergic neurons as important for maintaining reproductive function by sensing glucose availability and subsequently enhancing the release of the reproductive hormone gonadotropin. Their findings also provide an explanation and possible treatment for the decreased fertility observed in people with depression.

The results were published in Scientific Reports .

People who lack sufficient nutrition encounter problems with their reproductive health. For example, ballet dancers can experience menstrual disruptions and women who fast can struggle to conceive. According to a new study led by Designated Associate Professor Sho Nakamura and Professors Hiroko Tsukamura and Satoshi Ohkura, one of the main factors that affect a person's reproductive health is glucose availability.

Nakamura, Tsukamura, and their colleagues from the Graduate School of Bioagricultural Sciences at Nagoya University discovered that elevated glucose availability in rat brain stimulates serotonergic neurons. This causes the release of serotonin in the brain. Serotonin is an important neurotransmitter that affects the body and mind. It influences functions such as mood and behavior, and physiological processes such as bone health and metabolism.

When the researchers administered serotonin to goat brains, it triggered the activation of the kisspeptin neurons, which are the primary stimulator for the release of key reproductive hormones, such as gonadotropin-releasing hormone and gonadotropins.

"We used rats and goats as models because rats are a useful human model, whereas goats serve as a livestock model," said Professor Ohkura.

Their findings indicate that serotonergic neurons can release serotonin when they sense high levels of glucose. By interacting with serotonin receptors in the kisspeptin neurons, they can improve reproductive functions.

The use of inhibitors for serotonergic signaling also allowed the researchers to establish that the opposite was true. This important finding sheds light on why mammals with a poor diet face problems associated with fertility.

Depression can often be attributed to malfunctioning serotonergic neurons in the brain, which are often targeted for treatment. The dysfunction of serotonergic neurons often observed in individuals with depression suggests that low serotonergic activity might be a part of its cause.

Nakamura's research lays the groundwork for treating depression-induced infertility in humans and reproductive disorders in livestock, which implies a possible underlying connection and a potential treatment.

"Since selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed to treat depression in patients, studies indicate that these drugs may also have potential benefits for addressing depression-related infertility and treating animals," said Professor Tsukamura, the Principal Investigator of the research group and corresponding author of the paper.

She proposes that SSRIs could potentially be used in the future for human and animal reproduction, or in combination with diet treatments for people with depression .

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Numbers, Facts and Trends Shaping Your World

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• Americans Remain Critical of China

Many see China as increasingly influential and consider limiting its power a top priority

Table of contents.

• Unfavorable views of China prevail
• China’s role in the world
• China’s territorial disputes
• Americans lack confidence in Xi Jinping
• Americans increasingly see China as an enemy
• Limiting China’s power and influence
• China’s economic influence on the U.S.
• Acknowledgments
• The American Trends Panel survey methodology

Pew Research Center conducted this study to understand Americans’ opinions of China, its role in the world and its impact on the U.S. economy. For this analysis, we surveyed 3,600 U.S. adults from April 1 to April 7, 2024. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this analysis, along with responses, and its methodology .

For the fifth year in a row, about eight-in-ten Americans report an unfavorable view of China, according to a new Pew Research Center survey. Today, 81% of U.S. adults see the country unfavorably, including 43% who hold a very unfavorable opinion. Chinese President Xi Jinping receives similarly negative ratings.

Still, many Americans agree that China’s influence in the world has been getting stronger in recent years (71%). This sense is accompanied by concern about how China interacts with other nations: 61% of Americans are at least somewhat concerned about China’s territorial disputes with neighboring countries. (For more U.S. views of China’s role in the world, go to Chapter 1 .)

When it comes to China’s relationship with the United States, few see China as a partner (6%) and most Americans instead label it a competitor (50%) or an enemy (42%) of the U.S. They are likewise critical of China’s impact on the U.S. economy, describing its influence as large and negative. Roughly half of Americans think limiting China’s power and influence should be a top U.S. foreign policy priority, and another 42% think this should be given some priority. (For more assessments of China’s relationship with the U.S., go to Chapter 2 .)

According to the Center survey, which was conducted April 1-7, 2024, among 3,600 U.S. adults, Republicans are more wary of China than Democrats are.

Republicans and Republican-leaning independents are about twice as likely as Democrats and Democratic leaners to hold a very unfavorable view of China and to consider China an enemy of the U.S. They are also more likely to say that China has recently become more influential.

Republicans also have wider ideological differences within their party, and conservative Republicans stand out on many measures :

• Conservative Republicans are 25 percentage points more likely than moderate and liberal Republicans to express a very unfavorable view of China (68% vs. 43%). There is no difference between liberal Democrats and moderate and conservative Democrats on this question.
• Conservative Republicans are also 31 points more likely than moderate and liberal Republicans to see China as an enemy of the U.S. No ideological difference is present among Democrats.
• While 83% of conservative Republicans say China’s influence in the world has been getting stronger in recent years, 68% of moderate and liberal Republicans say the same. The latter is similar to the shares of moderate and conservative Democrats (67%) and liberal Democrats (69%) who hold this view.

Older Americans are generally more critical of China. A 61% majority of adults ages 65 and older have a very unfavorable view of China, compared with 27% of adults under 30. Adults ages 65 and older are also more than twice as likely as those ages 18 to 29 to see China as an enemy of the U.S. For their part, younger adults are more likely than older ones to label China as a competitor and as a partner.

Older Americans also perceive more growth in China’s international influence. Roughly three-quarters of adults ages 65 and older say China’s influence has been getting stronger in recent years, while about two-thirds of adults under 30 say the same.

Americans with a sour view of the U.S. economy have more critical opinions of China. Those who say the current U.S. economic situation is bad are more likely to hold an unfavorable opinion of China and to say China has a great deal or fair amount of negative influence on the U.S. economy. They are also more likely to see China as an enemy when compared with those who see the economy positively.

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Empirical Tests of the Green Paradox for Climate Legislation

The Green Paradox posits that fossil fuel markets respond to changing expectations about climate legislation, which limits future consumption, by shifting consumption to the present through lower present-day prices. We demonstrate that oil futures responded negatively to daily changes in the prediction market's expectations that the Waxman-Markey bill — the US climate bill discussed in 2009-2010 — would pass. This effect is consistent across various maturities as the proposed legislation would reset the entire price and consumption path, unlike temporary supply or demand shocks that phase out over time. The bill’s passage would have increased current global oil consumption by 2-4%. Furthermore, a strengthening of climate policy, as measured by monthly variations in media salience regarding climate policy over the last four decades, and two court rulings signaling limited future fossil fuel use, were associated with negative abnormal oil future returns. Taken together, our findings confirm that restricting future fossil fuel use will accelerate current-day consumption.

We would like to thank Kyle Meng and Derek Lemoine for sharing the prediction market data and for helpful feedback, as well as participants of the Virtual Seminar on Climate Economics by the Federal Reserve Bank of San Francisco and the Harvard Seminar in Environmental Economics and Policy. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

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