a research about

* Research Basics *

Introduction

So What Do We Mean By “Formal Research?”

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Types of Research
Secondary Research | Literature Review
Developing Your Topic
Using and Evaluating Sources
Ethics & Responsible Conduct of Research
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Research is formalized curiosity. It is poking and prying with a purpose. - Zora Neale Hurston

A good working definition of research might be:

Research is the deliberate, purposeful, and systematic gathering of data, information, facts, and/or opinions for the advancement of personal, societal, or overall human knowledge.

Based on this definition, we all do research all the time. Most of this research is casual research. Asking friends what they think of different restaurants, looking up reviews of various products online, learning more about celebrities; these are all research.

Formal research includes the type of research most people think of when they hear the term “research”: scientists in white coats working in a fully equipped laboratory. But formal research is a much broader category that just this. Most people will never do laboratory research after graduating from college, but almost everybody will have to do some sort of formal research at some point in their careers.

Casual research is inward facing: it’s done to satisfy our own curiosity or meet our own needs, whether that’s choosing a reliable car or figuring out what to watch on TV. Formal research is outward facing. While it may satisfy our own curiosity, it’s primarily intended to be shared in order to achieve some purpose. That purpose could be anything: finding a cure for cancer, securing funding for a new business, improving some process at your workplace, proving the latest theory in quantum physics, or even just getting a good grade in your Humanities 200 class.

What sets formal research apart from casual research is the documentation of where you gathered your information from. This is done in the form of “citations” and “bibliographies.” Citing sources is covered in the section "Citing Your Sources."

Formal research also follows certain common patterns depending on what the research is trying to show or prove. These are covered in the section “Types of Research.”

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Last Updated: Jul 24, 2024 4:33 PM
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Home Market Research

What is Research: Definition, Methods, Types & Examples

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

Content Index

What is Research?

What are the characteristics of research.

Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

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

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

Research is conducted with a purpose to:

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

What is the purpose of research?

There are three main purposes:

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

LEARN ABOUT: Descriptive Analysis

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

LEARN ABOUT: Best Data Collection Tools

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

Here is a comparative analysis chart for a better understanding:


Approach used	Unstructured	Structured	Highly structured
Conducted through	Asking questions	Asking questions	By using hypotheses.
Time	Early stages of decision making	Later stages of decision making	Later stages of decision making

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

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

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

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

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

Types of qualitative methods include:

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

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

Types of quantitative methods include:

Survey research
Descriptive research
Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

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

It is essential to ensure that your data is:

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

Gather insights

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

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

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113 Great Research Paper Topics

General Education

One of the hardest parts of writing a research paper can be just finding a good topic to write about. Fortunately we've done the hard work for you and have compiled a list of 113 interesting research paper topics. They've been organized into ten categories and cover a wide range of subjects so you can easily find the best topic for you.

In addition to the list of good research topics, we've included advice on what makes a good research paper topic and how you can use your topic to start writing a great paper.

What Makes a Good Research Paper Topic?

Not all research paper topics are created equal, and you want to make sure you choose a great topic before you start writing. Below are the three most important factors to consider to make sure you choose the best research paper topics.

#1: It's Something You're Interested In

A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject. Even if a certain research paper topic is getting a lot of buzz right now or other people seem interested in writing about it, don't feel tempted to make it your topic unless you genuinely have some sort of interest in it as well.

#2: There's Enough Information to Write a Paper

Even if you come up with the absolute best research paper topic and you're so excited to write about it, you won't be able to produce a good paper if there isn't enough research about the topic. This can happen for very specific or specialized topics, as well as topics that are too new to have enough research done on them at the moment. Easy research paper topics will always be topics with enough information to write a full-length paper.

Trying to write a research paper on a topic that doesn't have much research on it is incredibly hard, so before you decide on a topic, do a bit of preliminary searching and make sure you'll have all the information you need to write your paper.

#3: It Fits Your Teacher's Guidelines

Don't get so carried away looking at lists of research paper topics that you forget any requirements or restrictions your teacher may have put on research topic ideas. If you're writing a research paper on a health-related topic, deciding to write about the impact of rap on the music scene probably won't be allowed, but there may be some sort of leeway. For example, if you're really interested in current events but your teacher wants you to write a research paper on a history topic, you may be able to choose a topic that fits both categories, like exploring the relationship between the US and North Korea. No matter what, always get your research paper topic approved by your teacher first before you begin writing.

113 Good Research Paper Topics

Below are 113 good research topics to help you get you started on your paper. We've organized them into ten categories to make it easier to find the type of research paper topics you're looking for.

Arts/Culture

Discuss the main differences in art from the Italian Renaissance and the Northern Renaissance .
Analyze the impact a famous artist had on the world.
How is sexism portrayed in different types of media (music, film, video games, etc.)? Has the amount/type of sexism changed over the years?
How has the music of slaves brought over from Africa shaped modern American music?
How has rap music evolved in the past decade?
How has the portrayal of minorities in the media changed?

Current Events

What have been the impacts of China's one child policy?
How have the goals of feminists changed over the decades?
How has the Trump presidency changed international relations?
Analyze the history of the relationship between the United States and North Korea.
What factors contributed to the current decline in the rate of unemployment?
What have been the impacts of states which have increased their minimum wage?
How do US immigration laws compare to immigration laws of other countries?
How have the US's immigration laws changed in the past few years/decades?
How has the Black Lives Matter movement affected discussions and view about racism in the US?
What impact has the Affordable Care Act had on healthcare in the US?
What factors contributed to the UK deciding to leave the EU (Brexit)?
What factors contributed to China becoming an economic power?
Discuss the history of Bitcoin or other cryptocurrencies (some of which tokenize the S&P 500 Index on the blockchain) .
Do students in schools that eliminate grades do better in college and their careers?
Do students from wealthier backgrounds score higher on standardized tests?
Do students who receive free meals at school get higher grades compared to when they weren't receiving a free meal?
Do students who attend charter schools score higher on standardized tests than students in public schools?
Do students learn better in same-sex classrooms?
How does giving each student access to an iPad or laptop affect their studies?
What are the benefits and drawbacks of the Montessori Method ?
Do children who attend preschool do better in school later on?
What was the impact of the No Child Left Behind act?
How does the US education system compare to education systems in other countries?
What impact does mandatory physical education classes have on students' health?
Which methods are most effective at reducing bullying in schools?
Do homeschoolers who attend college do as well as students who attended traditional schools?
Does offering tenure increase or decrease quality of teaching?
How does college debt affect future life choices of students?
Should graduate students be able to form unions?

What are different ways to lower gun-related deaths in the US?
How and why have divorce rates changed over time?
Is affirmative action still necessary in education and/or the workplace?
Should physician-assisted suicide be legal?
How has stem cell research impacted the medical field?
How can human trafficking be reduced in the United States/world?
Should people be able to donate organs in exchange for money?
Which types of juvenile punishment have proven most effective at preventing future crimes?
Has the increase in US airport security made passengers safer?
Analyze the immigration policies of certain countries and how they are similar and different from one another.
Several states have legalized recreational marijuana. What positive and negative impacts have they experienced as a result?
Do tariffs increase the number of domestic jobs?
Which prison reforms have proven most effective?
Should governments be able to censor certain information on the internet?
Which methods/programs have been most effective at reducing teen pregnancy?
What are the benefits and drawbacks of the Keto diet?
How effective are different exercise regimes for losing weight and maintaining weight loss?
How do the healthcare plans of various countries differ from each other?
What are the most effective ways to treat depression ?
What are the pros and cons of genetically modified foods?
Which methods are most effective for improving memory?
What can be done to lower healthcare costs in the US?
What factors contributed to the current opioid crisis?
Analyze the history and impact of the HIV/AIDS epidemic .
Are low-carbohydrate or low-fat diets more effective for weight loss?
How much exercise should the average adult be getting each week?
Which methods are most effective to get parents to vaccinate their children?
What are the pros and cons of clean needle programs?
How does stress affect the body?
Discuss the history of the conflict between Israel and the Palestinians.
What were the causes and effects of the Salem Witch Trials?
Who was responsible for the Iran-Contra situation?
How has New Orleans and the government's response to natural disasters changed since Hurricane Katrina?
What events led to the fall of the Roman Empire?
What were the impacts of British rule in India ?
Was the atomic bombing of Hiroshima and Nagasaki necessary?
What were the successes and failures of the women's suffrage movement in the United States?
What were the causes of the Civil War?
How did Abraham Lincoln's assassination impact the country and reconstruction after the Civil War?
Which factors contributed to the colonies winning the American Revolution?
What caused Hitler's rise to power?
Discuss how a specific invention impacted history.
What led to Cleopatra's fall as ruler of Egypt?
How has Japan changed and evolved over the centuries?
What were the causes of the Rwandan genocide ?

Why did Martin Luther decide to split with the Catholic Church?
Analyze the history and impact of a well-known cult (Jonestown, Manson family, etc.)
How did the sexual abuse scandal impact how people view the Catholic Church?
How has the Catholic church's power changed over the past decades/centuries?
What are the causes behind the rise in atheism/ agnosticism in the United States?
What were the influences in Siddhartha's life resulted in him becoming the Buddha?
How has media portrayal of Islam/Muslims changed since September 11th?

Science/Environment

How has the earth's climate changed in the past few decades?
How has the use and elimination of DDT affected bird populations in the US?
Analyze how the number and severity of natural disasters have increased in the past few decades.
Analyze deforestation rates in a certain area or globally over a period of time.
How have past oil spills changed regulations and cleanup methods?
How has the Flint water crisis changed water regulation safety?
What are the pros and cons of fracking?
What impact has the Paris Climate Agreement had so far?
What have NASA's biggest successes and failures been?
How can we improve access to clean water around the world?
Does ecotourism actually have a positive impact on the environment?
Should the US rely on nuclear energy more?
What can be done to save amphibian species currently at risk of extinction?
What impact has climate change had on coral reefs?
How are black holes created?
Are teens who spend more time on social media more likely to suffer anxiety and/or depression?
How will the loss of net neutrality affect internet users?
Analyze the history and progress of self-driving vehicles.
How has the use of drones changed surveillance and warfare methods?
Has social media made people more or less connected?
What progress has currently been made with artificial intelligence ?
Do smartphones increase or decrease workplace productivity?
What are the most effective ways to use technology in the classroom?
How is Google search affecting our intelligence?
When is the best age for a child to begin owning a smartphone?
Has frequent texting reduced teen literacy rates?

How to Write a Great Research Paper

Even great research paper topics won't give you a great research paper if you don't hone your topic before and during the writing process. Follow these three tips to turn good research paper topics into great papers.

#1: Figure Out Your Thesis Early

Before you start writing a single word of your paper, you first need to know what your thesis will be. Your thesis is a statement that explains what you intend to prove/show in your paper. Every sentence in your research paper will relate back to your thesis, so you don't want to start writing without it!

As some examples, if you're writing a research paper on if students learn better in same-sex classrooms, your thesis might be "Research has shown that elementary-age students in same-sex classrooms score higher on standardized tests and report feeling more comfortable in the classroom."

If you're writing a paper on the causes of the Civil War, your thesis might be "While the dispute between the North and South over slavery is the most well-known cause of the Civil War, other key causes include differences in the economies of the North and South, states' rights, and territorial expansion."

#2: Back Every Statement Up With Research

Remember, this is a research paper you're writing, so you'll need to use lots of research to make your points. Every statement you give must be backed up with research, properly cited the way your teacher requested. You're allowed to include opinions of your own, but they must also be supported by the research you give.

#3: Do Your Research Before You Begin Writing

You don't want to start writing your research paper and then learn that there isn't enough research to back up the points you're making, or, even worse, that the research contradicts the points you're trying to make!

Get most of your research on your good research topics done before you begin writing. Then use the research you've collected to create a rough outline of what your paper will cover and the key points you're going to make. This will help keep your paper clear and organized, and it'll ensure you have enough research to produce a strong paper.

What's Next?

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These recommendations are based solely on our knowledge and experience. If you purchase an item through one of our links, PrepScholar may receive a commission.

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Home » Research Paper – Structure, Examples and Writing Guide

Research Paper – Structure, Examples and Writing Guide

Table of Contents

Research Paper

Definition:

Research Paper is a written document that presents the author’s original research, analysis, and interpretation of a specific topic or issue.

It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new knowledge or insights to a particular field of study, and to demonstrate the author’s understanding of the existing literature and theories related to the topic.

Structure of Research Paper

The structure of a research paper typically follows a standard format, consisting of several sections that convey specific information about the research study. The following is a detailed explanation of the structure of a research paper:

The title page contains the title of the paper, the name(s) of the author(s), and the affiliation(s) of the author(s). It also includes the date of submission and possibly, the name of the journal or conference where the paper is to be published.

The abstract is a brief summary of the research paper, typically ranging from 100 to 250 words. It should include the research question, the methods used, the key findings, and the implications of the results. The abstract should be written in a concise and clear manner to allow readers to quickly grasp the essence of the research.

Introduction

The introduction section of a research paper provides background information about the research problem, the research question, and the research objectives. It also outlines the significance of the research, the research gap that it aims to fill, and the approach taken to address the research question. Finally, the introduction section ends with a clear statement of the research hypothesis or research question.

Literature Review

The literature review section of a research paper provides an overview of the existing literature on the topic of study. It includes a critical analysis and synthesis of the literature, highlighting the key concepts, themes, and debates. The literature review should also demonstrate the research gap and how the current study seeks to address it.

The methods section of a research paper describes the research design, the sample selection, the data collection and analysis procedures, and the statistical methods used to analyze the data. This section should provide sufficient detail for other researchers to replicate the study.

The results section presents the findings of the research, using tables, graphs, and figures to illustrate the data. The findings should be presented in a clear and concise manner, with reference to the research question and hypothesis.

The discussion section of a research paper interprets the findings and discusses their implications for the research question, the literature review, and the field of study. It should also address the limitations of the study and suggest future research directions.

The conclusion section summarizes the main findings of the study, restates the research question and hypothesis, and provides a final reflection on the significance of the research.

The references section provides a list of all the sources cited in the paper, following a specific citation style such as APA, MLA or Chicago.

How to Write Research Paper

You can write Research Paper by the following guide:

Choose a Topic: The first step is to select a topic that interests you and is relevant to your field of study. Brainstorm ideas and narrow down to a research question that is specific and researchable.
Conduct a Literature Review: The literature review helps you identify the gap in the existing research and provides a basis for your research question. It also helps you to develop a theoretical framework and research hypothesis.
Develop a Thesis Statement : The thesis statement is the main argument of your research paper. It should be clear, concise and specific to your research question.
Plan your Research: Develop a research plan that outlines the methods, data sources, and data analysis procedures. This will help you to collect and analyze data effectively.
Collect and Analyze Data: Collect data using various methods such as surveys, interviews, observations, or experiments. Analyze data using statistical tools or other qualitative methods.
Organize your Paper : Organize your paper into sections such as Introduction, Literature Review, Methods, Results, Discussion, and Conclusion. Ensure that each section is coherent and follows a logical flow.
Write your Paper : Start by writing the introduction, followed by the literature review, methods, results, discussion, and conclusion. Ensure that your writing is clear, concise, and follows the required formatting and citation styles.
Edit and Proofread your Paper: Review your paper for grammar and spelling errors, and ensure that it is well-structured and easy to read. Ask someone else to review your paper to get feedback and suggestions for improvement.
Cite your Sources: Ensure that you properly cite all sources used in your research paper. This is essential for giving credit to the original authors and avoiding plagiarism.

Research Paper Example

Note : The below example research paper is for illustrative purposes only and is not an actual research paper. Actual research papers may have different structures, contents, and formats depending on the field of study, research question, data collection and analysis methods, and other factors. Students should always consult with their professors or supervisors for specific guidelines and expectations for their research papers.

Research Paper Example sample for Students:

Title: The Impact of Social Media on Mental Health among Young Adults

Abstract: This study aims to investigate the impact of social media use on the mental health of young adults. A literature review was conducted to examine the existing research on the topic. A survey was then administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO (Fear of Missing Out) are significant predictors of mental health problems among young adults.

Introduction: Social media has become an integral part of modern life, particularly among young adults. While social media has many benefits, including increased communication and social connectivity, it has also been associated with negative outcomes, such as addiction, cyberbullying, and mental health problems. This study aims to investigate the impact of social media use on the mental health of young adults.

Literature Review: The literature review highlights the existing research on the impact of social media use on mental health. The review shows that social media use is associated with depression, anxiety, stress, and other mental health problems. The review also identifies the factors that contribute to the negative impact of social media, including social comparison, cyberbullying, and FOMO.

Methods : A survey was administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The survey included questions on social media use, mental health status (measured using the DASS-21), and perceived impact of social media on their mental health. Data were analyzed using descriptive statistics and regression analysis.

Results : The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO are significant predictors of mental health problems among young adults.

Discussion : The study’s findings suggest that social media use has a negative impact on the mental health of young adults. The study highlights the need for interventions that address the factors contributing to the negative impact of social media, such as social comparison, cyberbullying, and FOMO.

Conclusion : In conclusion, social media use has a significant impact on the mental health of young adults. The study’s findings underscore the need for interventions that promote healthy social media use and address the negative outcomes associated with social media use. Future research can explore the effectiveness of interventions aimed at reducing the negative impact of social media on mental health. Additionally, longitudinal studies can investigate the long-term effects of social media use on mental health.

Limitations : The study has some limitations, including the use of self-report measures and a cross-sectional design. The use of self-report measures may result in biased responses, and a cross-sectional design limits the ability to establish causality.

Implications: The study’s findings have implications for mental health professionals, educators, and policymakers. Mental health professionals can use the findings to develop interventions that address the negative impact of social media use on mental health. Educators can incorporate social media literacy into their curriculum to promote healthy social media use among young adults. Policymakers can use the findings to develop policies that protect young adults from the negative outcomes associated with social media use.

References :

Twenge, J. M., & Campbell, W. K. (2019). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 15, 100918.
Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., … & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among US young adults. Computers in Human Behavior, 69, 1-9.
Van der Meer, T. G., & Verhoeven, J. W. (2017). Social media and its impact on academic performance of students. Journal of Information Technology Education: Research, 16, 383-398.

Appendix : The survey used in this study is provided below.

Social Media and Mental Health Survey

How often do you use social media per day?
Less than 30 minutes
30 minutes to 1 hour
1 to 2 hours
2 to 4 hours
More than 4 hours
Which social media platforms do you use?
Others (Please specify)
How often do you experience the following on social media?
Social comparison (comparing yourself to others)
Cyberbullying
Fear of Missing Out (FOMO)
Have you ever experienced any of the following mental health problems in the past month?
Do you think social media use has a positive or negative impact on your mental health?
Very positive
Somewhat positive
Somewhat negative
Very negative
In your opinion, which factors contribute to the negative impact of social media on mental health?
Social comparison
In your opinion, what interventions could be effective in reducing the negative impact of social media on mental health?
Education on healthy social media use
Counseling for mental health problems caused by social media
Social media detox programs
Regulation of social media use

Thank you for your participation!

Applications of Research Paper

Research papers have several applications in various fields, including:

Advancing knowledge: Research papers contribute to the advancement of knowledge by generating new insights, theories, and findings that can inform future research and practice. They help to answer important questions, clarify existing knowledge, and identify areas that require further investigation.
Informing policy: Research papers can inform policy decisions by providing evidence-based recommendations for policymakers. They can help to identify gaps in current policies, evaluate the effectiveness of interventions, and inform the development of new policies and regulations.
Improving practice: Research papers can improve practice by providing evidence-based guidance for professionals in various fields, including medicine, education, business, and psychology. They can inform the development of best practices, guidelines, and standards of care that can improve outcomes for individuals and organizations.
Educating students : Research papers are often used as teaching tools in universities and colleges to educate students about research methods, data analysis, and academic writing. They help students to develop critical thinking skills, research skills, and communication skills that are essential for success in many careers.
Fostering collaboration: Research papers can foster collaboration among researchers, practitioners, and policymakers by providing a platform for sharing knowledge and ideas. They can facilitate interdisciplinary collaborations and partnerships that can lead to innovative solutions to complex problems.

When to Write Research Paper

Research papers are typically written when a person has completed a research project or when they have conducted a study and have obtained data or findings that they want to share with the academic or professional community. Research papers are usually written in academic settings, such as universities, but they can also be written in professional settings, such as research organizations, government agencies, or private companies.

Here are some common situations where a person might need to write a research paper:

For academic purposes: Students in universities and colleges are often required to write research papers as part of their coursework, particularly in the social sciences, natural sciences, and humanities. Writing research papers helps students to develop research skills, critical thinking skills, and academic writing skills.
For publication: Researchers often write research papers to publish their findings in academic journals or to present their work at academic conferences. Publishing research papers is an important way to disseminate research findings to the academic community and to establish oneself as an expert in a particular field.
To inform policy or practice : Researchers may write research papers to inform policy decisions or to improve practice in various fields. Research findings can be used to inform the development of policies, guidelines, and best practices that can improve outcomes for individuals and organizations.
To share new insights or ideas: Researchers may write research papers to share new insights or ideas with the academic or professional community. They may present new theories, propose new research methods, or challenge existing paradigms in their field.

Purpose of Research Paper

The purpose of a research paper is to present the results of a study or investigation in a clear, concise, and structured manner. Research papers are written to communicate new knowledge, ideas, or findings to a specific audience, such as researchers, scholars, practitioners, or policymakers. The primary purposes of a research paper are:

To contribute to the body of knowledge : Research papers aim to add new knowledge or insights to a particular field or discipline. They do this by reporting the results of empirical studies, reviewing and synthesizing existing literature, proposing new theories, or providing new perspectives on a topic.
To inform or persuade: Research papers are written to inform or persuade the reader about a particular issue, topic, or phenomenon. They present evidence and arguments to support their claims and seek to persuade the reader of the validity of their findings or recommendations.
To advance the field: Research papers seek to advance the field or discipline by identifying gaps in knowledge, proposing new research questions or approaches, or challenging existing assumptions or paradigms. They aim to contribute to ongoing debates and discussions within a field and to stimulate further research and inquiry.
To demonstrate research skills: Research papers demonstrate the author’s research skills, including their ability to design and conduct a study, collect and analyze data, and interpret and communicate findings. They also demonstrate the author’s ability to critically evaluate existing literature, synthesize information from multiple sources, and write in a clear and structured manner.

Characteristics of Research Paper

Research papers have several characteristics that distinguish them from other forms of academic or professional writing. Here are some common characteristics of research papers:

Evidence-based: Research papers are based on empirical evidence, which is collected through rigorous research methods such as experiments, surveys, observations, or interviews. They rely on objective data and facts to support their claims and conclusions.
Structured and organized: Research papers have a clear and logical structure, with sections such as introduction, literature review, methods, results, discussion, and conclusion. They are organized in a way that helps the reader to follow the argument and understand the findings.
Formal and objective: Research papers are written in a formal and objective tone, with an emphasis on clarity, precision, and accuracy. They avoid subjective language or personal opinions and instead rely on objective data and analysis to support their arguments.
Citations and references: Research papers include citations and references to acknowledge the sources of information and ideas used in the paper. They use a specific citation style, such as APA, MLA, or Chicago, to ensure consistency and accuracy.
Peer-reviewed: Research papers are often peer-reviewed, which means they are evaluated by other experts in the field before they are published. Peer-review ensures that the research is of high quality, meets ethical standards, and contributes to the advancement of knowledge in the field.
Objective and unbiased: Research papers strive to be objective and unbiased in their presentation of the findings. They avoid personal biases or preconceptions and instead rely on the data and analysis to draw conclusions.

Advantages of Research Paper

Research papers have many advantages, both for the individual researcher and for the broader academic and professional community. Here are some advantages of research papers:

Contribution to knowledge: Research papers contribute to the body of knowledge in a particular field or discipline. They add new information, insights, and perspectives to existing literature and help advance the understanding of a particular phenomenon or issue.
Opportunity for intellectual growth: Research papers provide an opportunity for intellectual growth for the researcher. They require critical thinking, problem-solving, and creativity, which can help develop the researcher’s skills and knowledge.
Career advancement: Research papers can help advance the researcher’s career by demonstrating their expertise and contributions to the field. They can also lead to new research opportunities, collaborations, and funding.
Academic recognition: Research papers can lead to academic recognition in the form of awards, grants, or invitations to speak at conferences or events. They can also contribute to the researcher’s reputation and standing in the field.
Impact on policy and practice: Research papers can have a significant impact on policy and practice. They can inform policy decisions, guide practice, and lead to changes in laws, regulations, or procedures.
Advancement of society: Research papers can contribute to the advancement of society by addressing important issues, identifying solutions to problems, and promoting social justice and equality.

Limitations of Research Paper

Research papers also have some limitations that should be considered when interpreting their findings or implications. Here are some common limitations of research papers:

Limited generalizability: Research findings may not be generalizable to other populations, settings, or contexts. Studies often use specific samples or conditions that may not reflect the broader population or real-world situations.
Potential for bias : Research papers may be biased due to factors such as sample selection, measurement errors, or researcher biases. It is important to evaluate the quality of the research design and methods used to ensure that the findings are valid and reliable.
Ethical concerns: Research papers may raise ethical concerns, such as the use of vulnerable populations or invasive procedures. Researchers must adhere to ethical guidelines and obtain informed consent from participants to ensure that the research is conducted in a responsible and respectful manner.
Limitations of methodology: Research papers may be limited by the methodology used to collect and analyze data. For example, certain research methods may not capture the complexity or nuance of a particular phenomenon, or may not be appropriate for certain research questions.
Publication bias: Research papers may be subject to publication bias, where positive or significant findings are more likely to be published than negative or non-significant findings. This can skew the overall findings of a particular area of research.
Time and resource constraints: Research papers may be limited by time and resource constraints, which can affect the quality and scope of the research. Researchers may not have access to certain data or resources, or may be unable to conduct long-term studies due to practical limitations.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to Do Research: A Step-By-Step Guide: Get Started

Get Started
1a. Select a Topic
1b. Develop Research Questions
1c. Identify Keywords
1d. Find Background Information
1e. Refine a Topic
2a. Search Strategies
2d. Articles
2e. Videos & Images
2f. Databases
2g. Websites
2h. Grey Literature
2i. Open Access Materials
3a. Evaluate Sources
3b. Primary vs. Secondary
3c. Types of Periodicals
4a. Take Notes
4b. Outline the Paper
4c. Incorporate Source Material
5a. Avoid Plagiarism
5b. Zotero & MyBib
5c. MLA Formatting
5d. MLA Citation Examples
5e. APA Formatting
5f. APA Citation Examples
5g. Annotated Bibliographies

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Research Process Overview

Step 1. Develop a topic Select a Topic | Develop Research Questions | Identify Keywords | Find Background Information | Refine a Topic

Step 3. Evaluate and analyze information Evaluate Sources | Primary vs Secondary | Types of Periodicals

Step 4. Write, organize, and communicate information Take Notes | Outline the Paper | Incorporate Source Material

For research help, use one of the following options:

Ask the GTL

Next: Step 1: Develop a Topic >>
Last Updated: Aug 13, 2024 3:10 PM
URL: https://libguides.elmira.edu/research

What is Research?: The Truth about Research

The Truth about Research
Research Steps
Evaluating Sources
Parts of a Research Article

Research isn't what you think it is. It's not just dusty books written by men long since gone from this world. No...research is something we all do almost every day of our lives. You do it when you ask your friend if the movie they saw was any good. You do it when you go on Yelp to find a place to eat. You even do it when you read the comments section of an article on your favorite site. The key is knowing how to do it well. Doing it well doesn't mean putting the same amount of research into every problem--it means knowing the level of research needed, as well as how to reach that level.

Different Topics (and Different Needs) Require Different Expertise

For example, Wikipedia is fine if I want to know what happened on my favorite tv show last season, but I can't cite Wikipedia on my term paper. I also wouldn't go to a lawyer to see if I need to have my appendix taken out. So when doing research, it is always important to take the author's experience and credentials into consideration. Just because I trust Rachael Ray to provide good recipes for game day doesn't mean I should take financial advice from her. So always consider the source.

All Information is Created for a Reason

The person creating the information you're reading, hearing, watching, etc., is doing it for a reason. Maybe it's to inform or educate you; maybe it's to entertain or persuade you; maybe it's to get back at his roommate for not washing the dishes. The point is that every piece of information you read was created with a specific purpose.

Knowledge is Power

All information has value. The amount of that value depends on the person who created that information and on the person who is receiving it. For instance, if your 8 year old nephew tells you that a meteorite is about to hit New Orleans, you are not going to value that information the same way you would if Neil deGrasse Tyson said it. Likewise, you probably wouldn't value details of the latest kids movie as much as your nephew would.

Research is Answering a Question

Any time you do research, you are simply trying to answer a question. In the process of answering that question, you may find that even more questions pop up. For instance, you may wonder why the sky is blue. You learn that it has to do with the way light refracts. You may wonder why light refracts, which would lead you to discover that light acts like a wave and a particle. And it goes on and on.

Articles and Books are Just Really Public Conversations

Most scholarly articles and books started as questions that the author had about a topic. From there, the author either agreed or disagreed with what he/she read. Tons of research later, the author publishes their opinion. Think of it as a really public, really slow, really long conversation between scholars on a topic.

Searching for Information is an Exploration You Should Plan for

It's easy to get lost in the din of information. Have a plan. It's okay to venture from the plan from time to time. But having a plan makes it easier to find your way back to what you're trying to find out. As you go along, you may decide that you'd prefer to go a slightly (or totally) different direction with your research. That's fine. That's normal. Just don't go off in a direction because you got distracted. Think Wikipedia--you start out looking up the plot of Game of Thrones and end up reading about cheetahs in the Serengeti.

Next: Research Steps >>
Last Updated: Jul 20, 2017 9:23 PM
URL: https://libguides.uno.edu/whatisresearch

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Explaining How Research Works

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Expaling How Research Works Infographic en español

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to [email protected].

Below are some additional resources:

Discoveries in Basic Science: A Perfectly Imperfect Process
When Clinical Research Is in the News
What is Basic Science and Why is it Important?
What is a Research Organism?
What Are Clinical Trials and Studies?
Basic Research – Digital Media Kit
Decoding Science: How Does Science Know What It Knows? (NAS)
Can Science Help People Make Decisions ? (NAS)

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What is Research? – Purpose of Research

By DiscoverPhDs
September 10, 2020

The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. A research purpose is met through forming hypotheses, collecting data, analysing results, forming conclusions, implementing findings into real-life applications and forming new research questions.

What is Research

Simply put, research is the process of discovering new knowledge. This knowledge can be either the development of new concepts or the advancement of existing knowledge and theories, leading to a new understanding that was not previously known.

As a more formal definition of research, the following has been extracted from the Code of Federal Regulations :

While research can be carried out by anyone and in any field, most research is usually done to broaden knowledge in the physical, biological, and social worlds. This can range from learning why certain materials behave the way they do, to asking why certain people are more resilient than others when faced with the same challenges.

The use of ‘systematic investigation’ in the formal definition represents how research is normally conducted – a hypothesis is formed, appropriate research methods are designed, data is collected and analysed, and research results are summarised into one or more ‘research conclusions’. These research conclusions are then shared with the rest of the scientific community to add to the existing knowledge and serve as evidence to form additional questions that can be investigated. It is this cyclical process that enables scientific research to make continuous progress over the years; the true purpose of research.

What is the Purpose of Research

From weather forecasts to the discovery of antibiotics, researchers are constantly trying to find new ways to understand the world and how things work – with the ultimate goal of improving our lives.

The purpose of research is therefore to find out what is known, what is not and what we can develop further. In this way, scientists can develop new theories, ideas and products that shape our society and our everyday lives.

Although research can take many forms, there are three main purposes of research:

Exploratory: Exploratory research is the first research to be conducted around a problem that has not yet been clearly defined. Exploration research therefore aims to gain a better understanding of the exact nature of the problem and not to provide a conclusive answer to the problem itself. This enables us to conduct more in-depth research later on.
Descriptive: Descriptive research expands knowledge of a research problem or phenomenon by describing it according to its characteristics and population. Descriptive research focuses on the ‘how’ and ‘what’, but not on the ‘why’.
Explanatory: Explanatory research, also referred to as casual research, is conducted to determine how variables interact, i.e. to identify cause-and-effect relationships. Explanatory research deals with the ‘why’ of research questions and is therefore often based on experiments.

Characteristics of Research

There are 8 core characteristics that all research projects should have. These are:

Empirical – based on proven scientific methods derived from real-life observations and experiments.
Logical – follows sequential procedures based on valid principles.
Cyclic – research begins with a question and ends with a question, i.e. research should lead to a new line of questioning.
Controlled – vigorous measures put into place to keep all variables constant, except those under investigation.
Hypothesis-based – the research design generates data that sufficiently meets the research objectives and can prove or disprove the hypothesis. It makes the research study repeatable and gives credibility to the results.
Analytical – data is generated, recorded and analysed using proven techniques to ensure high accuracy and repeatability while minimising potential errors and anomalies.
Objective – sound judgement is used by the researcher to ensure that the research findings are valid.
Statistical treatment – statistical treatment is used to transform the available data into something more meaningful from which knowledge can be gained.

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Types of Research

Research can be divided into two main types: basic research (also known as pure research) and applied research.

Basic Research

Basic research, also known as pure research, is an original investigation into the reasons behind a process, phenomenon or particular event. It focuses on generating knowledge around existing basic principles.

Basic research is generally considered ‘non-commercial research’ because it does not focus on solving practical problems, and has no immediate benefit or ways it can be applied.

While basic research may not have direct applications, it usually provides new insights that can later be used in applied research.

Applied Research

Applied research investigates well-known theories and principles in order to enhance knowledge around a practical aim. Because of this, applied research focuses on solving real-life problems by deriving knowledge which has an immediate application.

Methods of Research

Research methods for data collection fall into one of two categories: inductive methods or deductive methods.

Inductive research methods focus on the analysis of an observation and are usually associated with qualitative research. Deductive research methods focus on the verification of an observation and are typically associated with quantitative research.

Qualitative Research

Qualitative research is a method that enables non-numerical data collection through open-ended methods such as interviews, case studies and focus groups .

It enables researchers to collect data on personal experiences, feelings or behaviours, as well as the reasons behind them. Because of this, qualitative research is often used in fields such as social science, psychology and philosophy and other areas where it is useful to know the connection between what has occurred and why it has occurred.

Quantitative Research

Quantitative research is a method that collects and analyses numerical data through statistical analysis.

It allows us to quantify variables, uncover relationships, and make generalisations across a larger population. As a result, quantitative research is often used in the natural and physical sciences such as engineering, biology, chemistry, physics, computer science, finance, and medical research, etc.

What does Research Involve?

Research often follows a systematic approach known as a Scientific Method, which is carried out using an hourglass model.

A research project first starts with a problem statement, or rather, the research purpose for engaging in the study. This can take the form of the ‘ scope of the study ’ or ‘ aims and objectives ’ of your research topic.

Subsequently, a literature review is carried out and a hypothesis is formed. The researcher then creates a research methodology and collects the data.

The data is then analysed using various statistical methods and the null hypothesis is either accepted or rejected.

In both cases, the study and its conclusion are officially written up as a report or research paper, and the researcher may also recommend lines of further questioning. The report or research paper is then shared with the wider research community, and the cycle begins all over again.

Although these steps outline the overall research process, keep in mind that research projects are highly dynamic and are therefore considered an iterative process with continued refinements and not a series of fixed stages.

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What is Research? Definition, Types, Methods, and Examples

Academic research is a methodical way of exploring new ideas or understanding things we already know. It involves gathering and studying information to answer questions or test ideas and requires careful thinking and persistence to reach meaningful conclusions. Let’s try to understand what research is.

Table of Contents

Why is research important?

Whether it’s doing experiments, analyzing data, or studying old documents, research helps us learn more about the world. Without it, we rely on guesswork and hearsay, often leading to mistakes and misconceptions. By using systematic methods, research helps us see things clearly, free from biases. (1)

What is the purpose of research?

In the real world, academic research is also a key driver of innovation. It brings many benefits, such as creating valuable opportunities and fostering partnerships between academia and industry. By turning research into products and services, science makes meaningful improvements to people’s lives and boosts the economy. (2)(3)

What are the characteristics of research?

The research process collects accurate information systematically. Logic is used to analyze the collected data and find insights. Checking the collected data thoroughly ensures accuracy. Research also leads to new questions using existing data.

Accuracy is key in research, which requires precise data collection and analysis. In scientific research, laboratories ensure accuracy by carefully calibrating instruments and controlling experiments. Every step is checked to maintain integrity, from instruments to final results. Accuracy gives reliable insights, which in turn help advance knowledge.

Types of research

The different forms of research serve distinct purposes in expanding knowledge and understanding:

Exploratory research ventures into uncharted territories, exploring new questions or problem areas without aiming for conclusive answers. For instance, a study may delve into unexplored market segments to better understand consumer behaviour patterns.
Descriptive research delves into current issues by collecting and analyzing data to describe the behaviour of a sample population. For instance, a survey may investigate millennials’ spending habits to gain insights into their purchasing behaviours.
Explanatory research, also known as causal research, seeks to understand the impact of specific changes in existing procedures. An example might be a study examining how changes in drug dosage over some time improve patients’ health.
Correlational research examines connections between two sets of data to uncover meaningful relationships. For instance, a study may analyze the relationship between advertising spending and sales revenue.
Theoretical research deepens existing knowledge without attempting to solve specific problems. For example, a study may explore theoretical frameworks to understand the underlying principles of human behaviour.
Applied research focuses on real-world issues and aims to provide practical solutions. An example could be a study investigating the effectiveness of a new teaching method in improving student performance in schools. (4)

Types of research methods

Qualitative Method: Qualitative research gathers non-numerical data through interactions with participants. Methods include one-to-one interviews, focus groups, ethnographic studies, text analysis, and case studies. For example, a researcher interviews cancer patients to understand how different treatments impact their lives emotionally.
Quantitative Method: Quantitative methods deal with numbers and measurable data to understand relationships between variables. They use systematic methods to investigate events and aim to explain or predict outcomes. For example, Researchers study how exercise affects heart health by measuring variables like heart rate and blood pressure in a large group before and after an exercise program. (5)

Basic steps involved in the research process

Here are the basic steps to help you understand the research process:

Choose your topic: Decide the specific subject or area that you want to study and investigate. This decision is the foundation of your research journey.
Find information: Look for information related to your research topic. You can search in journals, books, online, or ask experts for help.
Assess your sources: Make sure the information you find is reliable and trustworthy. Check the author’s credentials and the publication date.
Take notes: Write down important information from your sources that you can use in your research.
Write your paper: Use your notes to write your research paper. Broadly, start with an introduction, then write the body of your paper, and finish with a conclusion.
Cite your sources: Give credit to the sources you used by including citations in your paper.
Proofread: Check your paper thoroughly for any errors in spelling, grammar, or punctuation before you submit it. (6)

How to ensure research accuracy?

Ensuring accuracy in research is a mix of several essential steps:

Clarify goals: Start by defining clear objectives for your research. Identify your research question, hypothesis, and variables of interest. This clarity will help guide your data collection and analysis methods, ensuring that your research stays focused and purposeful.
Use reliable data: Select trustworthy sources for your information, whether they are primary data collected by you or secondary data obtained from other sources. For example, if you’re studying climate change, use data from reputable scientific organizations with transparent methodologies.
Validate data: Validate your data to ensure it meets the standards of your research project. Check for errors, outliers, and inconsistencies at different stages, such as during data collection, entry, cleaning, or analysis.
Document processes: Documenting your data collection and analysis processes is essential for transparency and reproducibility. Record details such as data collection methods, cleaning procedures, and analysis techniques used. This documentation not only helps you keep track of your research but also enables others to understand and replicate your work.
Review results: Finally, review and verify your research findings to confirm their accuracy and reliability. Double-check your analyses, cross-reference your data, and seek feedback from peers or supervisors. (7)

Research is crucial for better understanding our world and for social and economic growth. By following ethical guidelines and ensuring accuracy, researchers play a critical role in driving this progress, whether through exploring new topics or deepening existing knowledge.

References:

Why is Research Important – Introductory Psychology – Washington State University
The Role Of Scientific Research In Driving Business Innovation – Forbes
Innovation – Royal Society
Types of Research – Definition & Methods – Bachelor Print
What Is Qualitative vs. Quantitative Study? – National University
Basic Steps in the Research Process – North Hennepin Community College
Best Practices for Ensuring Data Accuracy in Research – LinkedIn

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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))

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Abstractspiepr Abs1

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

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.

An image of the book's description with the words like research, science, and inquiry and what the word research meant in the scientific world.

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.

An image represents the observation required in the scientific inquiry including planning and explaining.

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.

An image represents the data explanation as it is not limited and takes numerous non-quantitative forms including an interview, journal entries, etc.

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. ).

An image represents the scientific inquiry definition given by the editors of Britannica and also defines the hypothesis on the basis of the experiments.

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.

An image represents the rationale and the prediction for the scientific inquiry and different types of information provided by the terms.

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.

An image represents the cycle of events that take place before making predictions, developing the rationale, and studying the prediction and rationale multiple times.

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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Education and Communications

How to Do Research

Last Updated: March 13, 2023 References

This article was co-authored by Matthew Snipp, PhD and by wikiHow staff writer, Jennifer Mueller, JD . C. Matthew Snipp is the Burnet C. and Mildred Finley Wohlford Professor of Humanities and Sciences in the Department of Sociology at Stanford University. He is also the Director for the Institute for Research in the Social Science’s Secure Data Center. He has been a Research Fellow at the U.S. Bureau of the Census and a Fellow at the Center for Advanced Study in the Behavioral Sciences. He has published 3 books and over 70 articles and book chapters on demography, economic development, poverty and unemployment. He is also currently serving on the National Institute of Child Health and Development’s Population Science Subcommittee. He holds a Ph.D. in Sociology from the University of Wisconsin—Madison. This article has been viewed 229,895 times.

The idea of doing research may seem daunting, but as long as you keep yourself organized and focus on the question you want to answer, you'll be fine. If you're curious and interested in the topic, you might even find it fun! We here at wikiHow have gathered answers to all your most common questions about how to do research, from finding a good topic to identifying the best sources and writing your final paper.

How do I find a topic to research?

Preliminary research in your field of study helps you find a topic.

For example, if you're researching in the political science field, you might be interested in determining what leads people to believe that the 2020 US presidential election was illegitimate.

How do I get started on my research?

Look for overview articles to gain a better understanding of your topic.

For example, if you're researching the 2020 election, you might find that "absentee ballots" and "voting by mail" come up frequently. Those are issues you could look into further to figure out how they impacted the final election results.
You don't necessarily have to use the overview articles you look at as resources in your actual paper. Even Wikipedia articles can be a good way to learn more about a topic and you can check the references for more reputable sources that might work for your paper.

What's the best way to keep track of my sources?

Use index cards to take notes and record citation information for each source.

Research papers typically discuss 2 or 3 separate things that work together to answer the research question. You might also want to make a note on the front of which thing that source relates to. That'll make it easier for you to organize your sources later.
For example, if you're researching the 2020 election, you might have a section of your paper discussing voting by mail. For the sources that directly address that issue, write "voting by mail" in the corner.

What kind of notes should I be taking as I research?

Try to put ideas in your own words rather than copying from the source.

If you find something that you think would make a good quote, copy it out exactly with quote marks around it, then add the page number where it appears so you can correctly cite it in your paper without having to go back and hunt for it again.

How do I evaluate the quality of a source?

Check into the background of the author and the publication.

Does the article discuss or reference another article? (If so, use that article instead.)
What expertise or authority does the author have?
When was the material written? (Is it the most up-to-date reference you could use?)
Why was the article published? (Is it trying to sell you something or persuade you to adopt a certain viewpoint?)
Are the research methods used consistent and reliable? (Appropriate research methods depend on what was studied.)

What if I'm having a hard time finding good sources?

If there aren't enough sources, broaden your topic.

For example, if you're writing about the 2020 election, you might find tons of stories online, but very little that is reputable enough for you to use in your paper. Because the election happened so recently, it might be too soon for there to be a lot of solid academic research on it. Instead, you might focus on the 2016 election.
You can also ask for help. Your instructor might be able to point you toward good sources. Research librarians are also happy to help you.

How do I organize my research for my paper?

Start making a rough outline of your paper while you're researching.

For example, if you're researching the effect of the COVID-19 pandemic on the 2020 election, you might have sections on social distancing and cleaning at in-person voting locations, the accessibility of mail-in ballots, and early voting.

What's the best way to start writing my paper?

Start writing the middle, or body, of your paper.

Include an in-text citation for everything that needs one, even in your initial rough draft. That'll help you make sure that you don't inadvertently misattribute or fail to cite something as you work your way through substantive drafts.
Write your introduction and conclusion only after you're satisfied that the body of your paper is essentially what you want to turn in. Then, you can polish everything up for the final draft.

How can I make sure I'm not plagiarizing?

Include a citation for every idea that isn't your original thought.

If you have any doubt over whether you should cite something, go ahead and do it. You're better off to err on the side of over-citing than to look like you're taking credit for an idea that isn't yours.
↑ https://www.nhcc.edu/student-resources/library/doinglibraryresearch/basic-steps-in-the-research-process
↑ Matthew Snipp, PhD. Sociology Professor, Stanford University. Expert Interview. 26 March 2020.
↑ https://library.taylor.edu/eng-212/research-paper
↑ http://www.butte.edu/departments/cas/tipsheets/research/research_paper.html
↑ https://www.potsdam.edu/sites/default/files/documents/support/tutoring/cwc/6-Simple-Steps-for-Writing-a-Research-Paper.pdf
↑ https://www.umgc.edu/current-students/learning-resources/writing-center/online-guide-to-writing/tutorial/chapter4/ch4-05.html

Expert Q&A

About This Article

If you need to do research on a particular topic, start by searching the internet for any information you can find on the subject. In particular, look for sites that are sourced by universities, scientists, academic journals, and government agencies. Next, visit your local library and use the electric card catalog to research which books, magazines, and journals will have information on your topic. Take notes as you read, and write down all of the information you’ll need to cite your sources in your final project. To learn how interviewing a first-hand source can help you during your research, read on! Did this summary help you? Yes No

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The Research Whisperer

Just like the thesis whisperer – but with more money, what is research.

We all know what research is – it’s the thing we do when we want to find something out. It is what we are trained to do in a PhD program. It’s what comes before development.

The wonderful people at Wordnet define research as

Noun: systematic investigation to establish facts; a search for knowledge. Verb: attempt to find out in a systematically and scientific manner; inquire into.

An etymologist might tell us that it comes from the Old French word cerchier , to search , with re- expressing intensive force. I guess it is saying that before 1400 in France, research meant to search really hard.

If I was talking to a staff member at my university, though, I would say that searching hard was scholarship . The difference? Research has to have an element of discovering something new, of creating knowledge. While a literature search is one important part of a research project, it isn’t research in and of itself. It is scholarship.

Don’t take my word for it. In Australian universities, we define research this way:

Research is defined as the creation of new knowledge and/or the use of existing knowledge in a new and creative way so as to generate new concepts, methodologies and understandings. This could include synthesis and analysis of previous research to the extent that it leads to new and creative outcomes. This definition of research is consistent with a broad notion of research and experimental development (R&D) as comprising of creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of humanity, culture and society, and the use of this stock of knowledge to devise new applications This definition of research encompasses pure and strategic basic research, applied research and experimental development. Applied research is original investigation undertaken to acquire new knowledge but directed towards a specific, practical aim or objective (including a client-driven purpose).

Drawn from the 2012 Higher Education Research Data Collection (HERDC) specifications for the collection of 2011 data .

What research sounds like

Sometimes, however, you don’t want to talk about ‘Research ‘ . If you are applying to a philanthropic foundation, for example, they may not be interested in your new knowledge so much as the impact that your work will have, your capacity to help them to solve a problem. Industry partners may also be wary of the ‘R’ word. “Don’t bank your business on someone’s PhD”, they will say (and I would wholeheartedly agree).

This creates something of a quandary, as the government gives us money based on how much research income we bring in. They audit our claims, so everything we say is research has to actually be research. So, it helps to flag it as research, even if you don’t say it explicitly.

Instead, you might talk about innovation , or about experimentation . You could describe the element of risk associated with discovery . Investigation might lead to analysis . There might be tests that you will undertake to prove your hypothesis . You could just say that this work is original and has never been done before. You could talk about what new knowledge your work will lead to.

You might describe a new method or a new data source that will lead to a breakthrough or an incremental improvement over current practice. You could make it clear that it is the precursor to development , in the sense of ‘research and development’.

It really helps if you are doing something new .

What research looks like

Sometimes, it isn’t what you say, but what you do. If your work will lead to a patent, book or book chapter, refereed journal article or conference publication, or an artwork or exhibition (in the case of creative outputs), then it almost always fulfills the definition no matter what you call it.

What research isn’t

Sometimes, you can see a thing more clearly by describing what it isn’t.

Research isn’t teaching. Don’t get me wrong – you can research teaching, just like you can research anything else. However, teaching itself is generally regarded as the synthesis and transfer of existing knowledge. Generally, the knowledge has to exist before you can teach it. Most of the time, you aren’t creating new knowledge as you teach. Some lecturers may find that their students create strange new ‘knowledge’ in their assignments, but making stuff up doesn’t count as research either.

Research isn’t scholarship. As I said at the start, a literature search is an important aspect of the research process but it isn’t research in and of itself. Scholarship (the process of being a scholar) generally describes surveying existing knowledge. You might be looking for new results that you hadn’t read before, or you might be synthesizing the information for your teaching practice. Either way, you aren’t creating new knowledge, you are reviewing what already exists.

Research isn’t encyclopaedic. Encyclopedias, by and large, seek to present a synthesis of existing knowledge. Collecting and publishing existing knowledge isn’t research, as it doesn’t create new knowledge.

Research isn’t just data-gathering. Data-gathering is a vital part of research, but it doesn’t lead to new knowledge without some analysis, some further work. Just collecting the data doesn’t count, unless you do something else with it.

Research isn’t just about methodology. Just because you are using mice, or interviewing people, or using a High Performance Liquid Chromatograph (HPLC) doesn’t mean you are doing research. You might be, if you are using a new data set or using the method in a new way or testing a new hypothesis. However, if you are using the same method, on the same data, exploring the same question, then you will almost certainly get the same results. And that is repetition, not research.

Research isn’t repetition, except in some special circumstances. If you are doing the same thing that someone else has already done, then generally that isn’t research unless you are specifically trying to prove or disprove their work. What’s the difference? Repeating an experiment from 1400 isn’t research. You know what the result will be before your start – it has already been verified many times before. Repeating an experiment reported last year probably is research because the original result can’t be relied upon until it is verified.

Is development research? Development (as in ‘research and development’) may or may not be classified as research, depending on the type of risk involved. Sometimes, the two are inextricably linked: the research leads to the development and the development refines the research. At other times, you are creating something new, but it is a new product or process, not new knowledge. It is based on new knowledge, rather than creating new knowledge. If the risk involved is a business risk, rather than intellectual risk, then the knowledge is already known.

Help me out here – what are your favourite words that signal research?

From ideas to studies: how to get ideas and sharpen them into research questions

Jan p vandenbroucke.

1 Leiden University Medical Center, Leiden, the Netherlands

2 Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark

3 Department of Medical Statistics and Centre for Global NCDs, London School of Hygiene and Tropical Medicine, London, UK

Neil Pearce

Where do new research questions come from? This is at best only partially taught in courses or textbooks about clinical or epidemiological research. Methods are taught under the assumption that a researcher already knows the research question and knows which methods will fit that question. Similarly, the real complexity of the thought processes that lead to a scientific undertaking is almost never described in published papers. In this paper, we first discuss how to get an idea that is worth researching. We describe sources of new ideas and how to foster a creative attitude by “cultivating your thoughts”. Only a few of these ideas will make it into a study. Next, we describe how to sharpen and focus a research question so that a study becomes feasible and a valid test of the underlying idea. To do this, the idea needs to be “pruned”. Pruning a research question means cutting away anything that is unnecessary, so that only the essence remains. This includes determining both the latent and the stated objectives, specific pruning questions, and the use of specific schemes to structure reasoning. After this, the following steps include preparation of a brief protocol, conduct of a pilot study, and writing a draft of the paper including draft tables. Then you are ready to carry out your research.

Introduction

How do you get an idea for a study? How do you turn your idea into a testable hypothesis, and turn this into an appropriate and feasible study design? This is usually at best only partially taught in epidemiology courses. Most courses and textbooks assume that you know your research question and the general methods that you will need to answer it. Somehow it is assumed that you can readily translate your idea into a specific framework, such as the PICO framework (Patient, Intervention, Control or Comparison, Outcome) 1 or the FINER framework (Feasible, Interesting, Novel, Ethical, and Relevant) 2 or that you can fit it into counterfactual reasoning. 3 However, before describing your project in one of these frameworks, you first need to have an idea for your study and think about it in general terms: why you might do a study and how you might do a study.

This paper considers the complex process of having ideas, keeping track of them, turning them into studies, trying them out in pilot studies, and writing a draft paper before you finally embark on your study.

The paper is intended for novice researchers in clinical or public health epidemiology. It is not intended to be a comprehensive literature review about creativity, nor a sociology or philosophical treatise about why scientists get particular ideas (and not other ideas). It is based on our personal experience of (a combined) 70+ epidemiologic research-years. We have worked on very different topics, mostly on opposite sides of the globe, yet found that our experiences are quite similar. The fact that these issues are rarely covered in epidemiology courses has provided motivation to reflect on our experience.

Getting new ideas

So how do you get an idea? How some juxtaposition of neural patterns in our brain suddenly creates a new idea is a process that we are far from understanding. According to Karl Popper, the origin of new ideas does not matter; the only thing of interest is to devise how to test them. 4 Over the past decades, the literature has been enriched with new ideas about “being creative” in science – as witnessed in the book Innovation Generation by Ness. 5

In the present paper, we will not cover the literature about creativity and discovery in depth, but we will discuss the issues that we consider relevant to epidemiologic research. We will first consider the more general principles.

The real complexity of the thought processes that lead to a scientific undertaking is almost never described in published papers. Immunologist Medawar claimed that in this respect almost all scientific papers may be a fraud – not in the sense that scientists deliberately produce misleading data, but in the sense that the real thought processes that lead to the data and conclusions are not mentioned. 6 Scientists tell us about their real thought processes in memoirs, inaugural, or valedictory lectures – which is why these are so much more interesting than “standard” papers or presentations.

What strikes our minds: regularities or anomalies?

All sciences study a particular “object of knowledge” (eg, “matter”, “life”). Ideas come from experience and previous knowledge or facts about this object of knowledge, although this knowledge is always filtered through the perspective of one or more theories. 7 Epidemiology studies the distribution and determinants of disease in human populations, 8 and epidemiological ideas arise from observing and thinking about populations. 9 These could be clinical populations (ie, clinical experience, sometimes involving just a few patients), exposure-based populations (eg, workers exposed to a particular chemical), or general populations (geographically defined or sociologically defined). Whatever the population we are interested in, ideas come from observing either regularities or anomalies.

The observation of regularities (“induction”) is a common origin of new ideas. 4 , 10 – 13 Philosopher David Hume described “Induction” as: regularly seeing two things happening in succession (like pushing a switch and a light going on) leads to suspicions of causality. As he pointed out, causality can never be proven by the mere observation of “constant conjunctions”, but observing regularities can start our train of thought. 12

An anomaly (or irregularity) strikes our mind, because it defies our expectations. The regularity that we expected was our “hypothesis” (even if it was not really explicitly formulated); the anomaly is a “refutation”. 4 , 13 It forces us to think about other explanations, and these lead to new hypotheses that we then try to test. Thus, scientists do not usually start from hypotheses that are nicely formulated “out of the blue”, but instead start from previous knowledge and experience; when they are challenged by anomalies, scientists seek new explanations. 14

An interesting way to discover anomalies is to enter a new field of research; since you have other background experience than the people already in the field, you see things that they take for granted but that strike you as odd – at the same time, you may also see new explanations for these anomalies. One of the pioneers of clinical epidemiology, Sackett, once wrote that scientists should “retire” from a field as soon as they become “experts”. 15 When you are too long in a field, you will no longer see the anomalies, and you may even obstruct newcomers with new explanations. Of course, there are differences between scientists: some roam across various fields and others stick to a problem area that they explore with increasing depth – then the increasing depth and the new techniques that one needs for advancing one’s thoughts will be like a “new field”.

Taxonomies of discovery

Few researchers have listed the different ways in which one can arrive at new ideas, that is, lists of ways of discovery. We will present two of them – which have very different origins but remarkable similarities. Several examples of studies corresponding to items on these two lists are given in Appendix Examples A1–A10 .

Sources for new ideas about health care evaluation were described by Crombie and Davies in the chapter “Developing the research question” of their book on Research in Health Care that reflects a UK public health experience. 16

“Review existing practice […] the current organisation and delivery of health care is not as good as it could be […]”
“Challenge accepted ideas […] much of health care is based on accepted practice rather than research evidence […]” ( Appendix Example A3 )
“Look for conflicting views […] which indicate either that there is not enough evidence, or that some practitioners are misinformed”
“Investigate geographical variation […] reflecting on the reasons [for geographical variation] can be a fruitful source of research questions […]” ( Appendix Example A6 )
“Identify Cinderella topics […] important areas of health care are often overlooked […]”
“Let loose the imagination […] look for wild or impossible ideas […] free the mind from the constraints of conventional wisdom […].”

A taxonomy for sources of clinical research questions about medical care and clinical problems was proposed by Hulley and Cummings, in the context of clinical research in the US: 2

“Build on experience;” your own experience, that of close colleagues with whom you can freely discuss your research ideas, and that of a good mentor, because young researchers might not yet have much experience, “An essential strategy for a young investigator is to apprentice himself to an experienced senior scientist who has the time and interest to work with him regularly.”
○ By harvesting “the medical literature and attending journal clubs, national and international meetings, seeking informal conversations with other scientists and colleagues”
○ “A sceptical attitude about prevailing beliefs can stimulate good research questions”
○ Be alert to “careful observation of patients, which has historically been one of the major sources of descriptive studies” ( Appendix Examples A1 and A2 )
○ Your experiences in teaching; having to explain something may make you aware of gaps in your knowledge; questions by patients and colleagues may similarly identify things that we do not fully understand or ignore
“Keep the imagination roaming […]” by a mixture of creativity and tenacity; “put an unresolved question clearly in view and turn on the mental switch that lets the mind run freely toward it”.

A special mention needs to be made about the last categories of both the lists: “Let loose the imagination” and “Keep the imagination roaming”. These are especially important to find innovative solutions. In many situations wherein you cannot do a perfect study and you run a grave danger of potential confounding or bias, it helps to “get deeply immersed”: to understand the problem biologically, clinically, socially, organizationally, and environmentally will help you to think about what is happening, why it is happening, and whether you can find situations in which the potential confounders or biases do not exist or exists in reverse. You should forget formal designs and think out of the box: you will find instances of studies that mutually reinforce each other and may even arrive at formulating new designs or analytic solutions (see Appendix Examples A7–A10 ).

Keeping track of your ideas

It is not only important to have good ideas but also important to develop them. Researchers who work in laboratories have the habit of keeping “lab logs”. They write down briefly the results of an experiment, note why they think it went wrong, and how they will perform the next experiment. This permits them to trace how they changed the experiments or even the content and the direction of their research. We should do the same in epidemiologic and clinical research, particularly in the stage of creating new ideas. Such notes about ideas can include not only hypotheses and views or results by others but also drawing directed acyclic graphs (DAGs) (see “Intermezzo: specific schemes to structure reasoning” section) to make the causal structures of ideas clear.

The greatest minds kept track of their thoughts. Charles Darwin’s notebooks document his ideas, his observations, his readings, and new theories and facts that struck him. 17 For example, Darwin noted a story that he heard from his father, a medical practitioner. His father recounted that he had been struck by one of his patients’ ways of expressing himself, because he had attended a parent of the patient who had had the same mannerisms – even though the parent had died when the patient was still an infant. Remarks like these still have relevance today when we think about the heredity and evolution of behavior.

The sociologist C Wright Mills carried the description of the process one step further in the appendix of his book on The Sociological Imagination . 18 He encourages young sociologists to set up a file of stacked cards to keep track of “[…] personal experience and professional activities, studies underway and studies planned […]” which “[…] encourages you to capture ‘fringe thoughts’: various ideas which may be by-products of everyday life, stretches of conversations […]”. These notes are continuously reshuffled, regrouped under new headings, and pondered. Mills denounced the habit of most (social) scientists who feel the need to write about their plans only when they are going to apply for a grant. He thought that scientists should continually work with their file of ideas and regularly take stock of how these have evolved.

Such strategies are still relevant today, even if our “logs” are kept in electronic form, particularly because grant writing has become more demanding, hectic, and time-consuming. From such files, new research projects are born: while your ideas gradually develop, you keep wondering what data you might need to prove a certain proposition, and how you might get those data in the easiest way possible. Often, ideas are reshuffled and regrouped under new headings. A new observation, a new piece of literature may make old ones fall into place, or there may suddenly be a new opportunity to work out an old idea.

A complementary advice recently came in a blog from a contemporary sociologist, Aldrich: his advice is to “Write as if you don’t have the data”, that is, to write “[…] the literature review and planning phase of a project, preferably before it has been locked into a specific research design”. 19

The role of emotions

Underlying the discovery process, there are often two emotions: “surprise” and “indignation”. Surprise is the intellectual emotion when we see something happening against expectation: a patient with an unusual exposure, unusual disease manifestation, sudden cure, or sudden ill-understood deterioration; a laboratory result that is an anomaly; and a sudden epidemic of disease in a population. Indignation is the moral emotion: a group of patients is not being treated well because we lack sufficient knowledge, or because we are blundering in organizing health care or in transmitting and applying public health knowledge. Some passion is useful to bring any undertaking to a good end, be it that the passion should be restrained and channeled into polite undertakings, like in a research protocol. While doing the research project, maintaining some of the original passion will help you to find ways to overcome the daily hassles of research, the misadventures, the difficulties of getting others to collaborate, and the difficulties of getting published ( Appendix Example A11 ).

Sharpening the research question: the pruning

Pruning a research question means cutting away anything that is unnecessary, so that only the essence remains.

The initial spark of an idea will usually lead to some rather general research question. Invariably, this is too ambitious, or so all-encompassing that it cannot be researched (at least not within the time frame of a single grant or PhD project). You have to refine your research question into something that is interesting, yet feasible. To do so, you have to know clearly where you are heading. The emphasis on a clear preconceived idea about what you want to attain by your research often comes as a surprise; some people object: “[…] isn’t research about discovery? How can you know in advance what you want to find?”

The social scientist Verschuren proposed the “wristwatch metaphor”. 20 A researcher is not like a beachcomber, who strolls along the beach to see whether anything valuable washed ashore. Rather, a researcher is like someone who has lost her wristwatch on the beach and returns to search for it. She knows what part of the beach to look, she can describe her wristwatch in detail, and once she has found it, she knows that this is the watch she was looking for. Some further background to these ideas can be found in Appendix B .

Charles Medawar wrote in his Advice to a Young Scientist (page 18) 21 that as much as politics is the ‘art of the possible’, research is the ‘art of the soluble’. A research question should be limited to a question that can be solved with the resources at hand. This does not mean that you should preferentially study “trivial” questions with easy solutions. It does mean that you should seek out your particular niche: something specific, something that was overlooked by others, or some new twist to a general question, so that you can make your own contribution.

The concept of “serendipity” is often invoked when thinking of “seeking novelty”: it means finding something that you were not looking for. For a full discussion of the more complex reality that shows how, in reality, “chance favors a prepared mind”, see Appendix C .

Proceed in the inverse order of the paper that you will write

From the aforementioned, we know that we need a precise aim and a soluble research question.

How can we achieve this? The best approach is to “begin at the end”, that is, the conclusion that you hope to support when you eventually publish your research findings, perhaps many years from now. 22 Most medical research papers have a fixed format: introduction, methods, results, discussion. Usually, the discussion has three parts: summary of the results, discussion of the strengths and limitations, and the importance and interpretation of the findings. There you start: you try to imagine what such last lines of the eventual paper might be – in particular what their intent, their message to the reader might be. Another useful strategy would be to imagine what might be written in the separate box “What this paper adds” that many journals nowadays ask to convey the message from the authors clearly and succinctly to the readers.

The “latent” versus the “stated” objective

The pioneer clinical epidemiologist Feinstein wrote that a good research consultant should be like a good clinician, who first wants to learn from the patient: “What is the chief complaint?”, that is, which is the problem that you want to study. Next, “What will you do with the answer?” 22 The latter question is not just about the potential conclusions of the research paper, but more importantly, their meaning. What is the intended effect (or impact) of the findings? He called this the “latent objective”: what do you want to achieve or change by your project; the “stated objective” is different, it is the type of result that the study will deliver. For example, the stated objective can be that you want to do a randomized trial to compare one intervention versus another and that you will look at recurrence of disease. The latent objective might be that you are concerned that one intervention may be harmful to patients, driven by special interests, and that if this is the case it should be abolished.

Rather analogously, the long-time editor of the Annals of Internal Medicine , Edward Huth, proposed in his book about medical publishing the “So-What” and the “Who-Cares” tests: “What may happen if the paper’s message is correct?”; may it change concepts and treatment or stimulate further exciting research? 23 In fact, many funders now require such an “impact statement” as part of the grant application process.

Experienced research consultants know that when trying to discover the latent objective, it is useful to brush aside the detailed protocol and to ask directly what the meaning of the research is. The meaning of the research is often not clearly stated in a formal study protocol that limits itself more or less to “stated aims”. 24 Like a patient who cannot articulate her/his complaints very well, would-be researchers lose themselves in trivial “side issues” or operational details of the protocol. Appendix Examples A2 and A11 explain the importance of elucidating the underlying frustration of the clinician-researcher to clearly guide a research effort.

After initial questions have set the scene and clarified the “latent objective” of a project, the next questions are more operational, translating the latent objective back into a “stated objective”. 22 The stated objective should be a feasible research project. According to Feinstein, one should ask: what maneuver is to be executed (what intervention, deliberate or not, and how is it administered), what groups are to be compared (and why those groups), and what is the outcome that we will study?

In these phases of discussion, one needs to immerse oneself into the problem: one has to understand it biologically and clinically, and how it is dealt with in the daily practice of health care in the setting in which you will do research. Getting deeply immersed in the problem is the only way of arriving at shrewd or new solutions for studies on vexing medical or public health problems ( Appendix Example A9 ). Mere discussion of technical or procedural aspects of a proposed design, data collection, or analysis will usually not lead to new insights.

Specific pruning questions, to ask yourself or others

In initial discussions, one goes back and forth between the general aim (the latent objective), the scientific questions that follow from it, and the possible research designs (with stated objectives). After feeling secure about the “latent” aim, proceed with more specific questions.

Try to describe exactly the knowledge gap that you want to fill (ie, the watch that you lost at the beach). Is it about etiology, about pathogenesis, about prognosis? What should change for the benefit of a particular group of patients? Try to be as specific as possible. Do your colleagues see these problems and their solutions as you do? – and if not, why don’t they?
Once you know the point you want to make, describe what table or figure you need to fill the gap in knowledge, that is, what would your results look like? This means drawing a simple table or graph. Are these the data you want? Will these tables convince your colleagues? What objections might they have? Keep in mind that if the research results go against ingrained beliefs, they will be scrutinized mercilessly, so the important aspects of your research should be able to withstand likely objections.
Thereafter, the questions become more practical: what study design is needed to produce this table, this figure? Can we do this? Do we have the resources or can we find them?

Be self-critical

You should always remain self-critical about the aspects that threaten the validity of your study ( Appendix Example A12 ). 25 If the practical problems are too large, or the research question too unfeasibly grandiose, it might be wise to settle for a less ambitious aim ( Appendix Example A13 ).

Paraphrasing Miettinen, 26 the first decision is whether you should do the study at all. There might be several reasons to decide not to pursue a study. One might be that arriving at a satisfactory design will be impossible, because of biases that you are unable to solve. It serves no purpose to add another study that suffers from the same unsolved problems as previous studies. For example, it does not serve any purpose to do yet another study that shows lower mortality in vegetarians, if you cannot solve the problems of confounding that vegetarians are persons who have different lifestyles in comparison with others. 27 (If, however, you have found a solution – pursue it at all means!) Nevertheless, thinking about the potential problems and ultimate aims of a seemingly impossible question can foster the development of a new study design or a new method of analysis, ( Appendix Examples A2, A9, and A10 ). In the same vein, deciding that you cannot do a study yourself might make you look for collaboration with persons who have the type of data that you do not, for example, in a different population where it is believed that confounding is not so severe or may even be in the opposite direction.

All studies have imperfections, but you need to be aware which ones you can tolerate. 28 In the early stages of an enquiry, an “imperfect” study might still be worthwhile to see whether “there might be something in it”. For example, time trends or ecological comparisons are often seen as poor study designs to assess causality by themselves, but they can be very valuable in helping to develop ideas, as well as providing a “reality check” about the potential credibility of some hypothesis. 29

Conversely, it is pointless to add yet another study, however perfect, showing what is already known very well – unless you have to do it for “political” purposes, say, for convincing decision makers in your own country.

Finally, it is not a good use of your time to chase something completely improbable or futile. For example, at the present state of the debate, it serves no purpose to add another study about the presence or absence of clinical benefits or harms of homeopathy: no one will change his or her mind about the issue. 30 , 31 An exception might be something that is highly improbable, but that if true might lead to completely revolutionary insights – such an idea might be worth pursuing, even if the initial reaction of outsiders might remain incredulousness. Still, you should pursue unlikely hypotheses knowingly, that is, with the right amount of self-criticism – in particular, to make yourself aware when you are in a blind alley.

To keep yourself on the “straight and narrow”, it helps to form a group of people who cover different aspects of the problem you want to study: clinical, biochemical and physiological, and methodological – to discuss the project as equals. Such discussions can not only be tremendous fun but also will invariably lead to more profound and diverse research questions and will help to find solutions for practical as well as theoretical problems. In the right circumstances of a “machtsfreie Dialog” 32 (a communication in which all are equal and that is only based on rational arguments and not on power – which all scientific debates should be), such a circle of colleagues and friends will help you to be self-critical.

Finally, when pursuing one’s research interests, one should be prepared to learn new skills from other fields or collaborate with others from these fields. If one stays only with the techniques and skills that one knows, it might not lead to the desired answers. 33

What if the data already exist? And you are employed to do a particular analysis with an existing protocol?

Even in the circumstance that the data already exist, it greatly helps to not jump into an analysis, but to think for yourself what you would ideally like to do – if there were no constraints. As Aldrich mentioned, 19 also in that circumstance researchers should still

[…] begin their literature review and conceptual modeling as if they had the luxury of a blank slate […]. Writing without data constraints will, I believe, free their imaginations to range widely over the realm of possibilities, before they are brought to earth by practical necessities.

Moreover, this will make clear what compromises one will make by accepting the available data and the existing analysis protocol. Otherwise, one starts an analysis without being sufficiently aware of the limitations of a particular analysis on particular data.

The difference between explanatory and pragmatic research

A useful distinction is between explanatory and pragmatic research: the former is research that aims at discovery and explanation, whereas the latter is intended to evaluate interventions or diagnostic procedures. The first type of research consists of chasing explanations by pursuing different and evolving hypotheses; the second type of research aims at making decisions about actions in future patients. 27 The two opposites differ strongly in their thinking about the types of studies to pursue (eg, observational vs randomized), about the role of prior specification of a research hypothesis, about the need for “sticking to a prespecified protocol”, and about subgroup analyses and multiplicity of analyses. Some of these will be explained in the following subheadings.

The difference between explanatory and pragmatic trials is sometimes thought to mirror the difference between doing randomized trials versus observational research. However, even for randomized trials, a difference exists between “ pragmatic” and “explanatory” trials (coined first by Schwartz and Lellouch). 34 Because it is not always easy to delineate what aspects of a randomized trial are “pragmatic” or “explanatory”, instruments have been crafted to help researchers and evaluators. 35 , 36 Conversely, not all observational studies are explanatory: some are needed for pragmatic decisions (think about adverse effects of drugs and also about diagnostic evaluations where studies should influence practice guidelines) – while other studies aim at explaining how nature works.

Which iterations should you allow yourself? Anticipating the next project

Thinking about a research problem is a strongly iterative process. 2 , 33 , 37 One starts with a broad aim and then tries out several possible ideas about studies that might lead to better understanding or to better solutions.

Likewise, project proposals characteristically go through many iterations. In the early phases of the research, it is commonplace that the study design or even the research question is changed. Specific suggestions about common research problems and their potential solutions were given by Hulley and Cummings, 2 which we reproduce in Appendix D .

The revision of the aims of a project may be profound, in particular in explanatory research (see “The difference between explanatory and pragmatic research” section), in contrast to pragmatic research (see “Shouldn’t you stick to a predefined protocol?” section). The chemist Whitesides wrote: “Often the objectives of a paper when it is finished are different from those used to justify starting the work. Much of good science is opportunistic and revisionist”. 38 Along a similar line, Medawar proposed that to do justice to the real thought processes of a research undertaking, the discussion section of a paper should come at the beginning, since the thought processes of a scientist start with an expectation about particular results. The expectation determines which findings are of interest and why they will be interpreted in a particular way. 6 He added that in real scientific life, scientists get new ideas (ie, new expectations) while doing their research, but “[…] many of them apparently are ashamed to admit, that hypotheses appear in their mind along uncharted byways of thought”. 6

“Seeing something in the data” can be an important part of scientific discovery. This is often decried as “data dredging”, which it is not: one sees something because of one’s background knowledge and thereby there always is some “prior” that exists – even if that was not specified beforehand in the study protocol. 27 , 39 The word “exploratory” is often misused when it is used to characterize a study. True “exploratory” data analysis would only exists if it is mindlessly done, such as a Genome Wide Association Study (GWAS) analysis – but even GWAS analyses have specific aims, which becomes clear when results are interpreted and some findings are designated as “important” and others not. As stated by Rothman:

Hypotheses are not generated by data; they are proposed by scientists. The process by which scientists use their imagination to create hypotheses has no formal methodology […]. Any study, whether considered exploratory or not, can serve to refute a hypothesis. 40

Appendix Examples A5 and A7 show how projects changed mid-course because of a new discovery in the data or in the background knowledge about a research topic.

Generally, it is a good habit to think through what the next project might be, once you will have the result of the project you are currently thinking about, so as to know what direction your research might take. 33

Shouldn’t you stick to a predefined protocol?

Different research aims, in particular along the “explanatory” versus “pragmatic” continuum, may lead to different attitudes on the amount of change that protocols may endure while doing research. 27 , 39 For randomized trials, and also for pragmatic observational research, the research question is usually fixed: does a new therapy lead to better outcomes for a particular group of patients in a particular setting? Because findings from randomized trials or pragmatic observational research may lead to millions of patients to adopt or avoid a particular therapy (which means that their well-being or even life depends on the research) researchers are generally not at liberty to change their hypotheses at the last moment – for example, by suddenly declaring an interest in a particular subgroup. They should stick to the predefined protocol. If a change is needed for practical reasons, it should be clearly stated in the resulting publications. This makes thinking about research questions and doing pilot studies beforehand all the more important (see “Pilot Study” section).

In contrast, much epidemiologic and clinical research tries to explain how nature works. This gives greater leeway: exploration of data can lead to new insights. Thus, “sticking to the protocol” is a good rule for randomized trials and pragmatic observational research, but may be counterproductive for explanatory research. 39 , 41 Nevertheless, it is good to keep track of the changes in your thoughts and in the protocol, even if only for yourself. In practice, many situations are intermediate; in particular when using large available data sets, it often happens that one envisages in a protocol what one would do with the data, only to discover upon opening the data files that the data fall short or are more complex than imagined; this is another reason for doing pilot studies, even with large available data sets (see “Pilot Study” section).

How much literature should you read?

If you are setting up a new research project in a new area, do not start by reading too much. You will quickly drown in the ideas of others. Rather, read a few general reviews that identify unanswered problems. Only return to the literature after you have defined your research question and provisionally your study design. Now, the literature suddenly becomes extremely interesting, since you know what types of papers you need. You also know what the potential objections and shortcomings are of the different design options, because you thought about them yourself. The number of relevant papers usually greatly shrinks, see Appendix Example A4 .

Shouldn’t you do a systematic review first?

It is argued that before embarking on a new piece of research, one should first do a systematic review and/or meta-analysis, because this may help to define the gaps in knowledge more precisely, and guide new research – or may show that the question has been solved. This argument is somewhat circular. A systematic review is a piece of research in itself, intended for publication, and requires much time and effort. Like any piece of research, it requires a clear research question. As such it does not “identify gaps”: a systematic review is about a research question which is already specified, but for which more information is needed. Thus, the main function of the advice to first do a systematic review is to know whether the research question that one has in mind has not yet been solved by others. Perusing the literature in depth is absolutely needed, for example, before embarking on a randomized trial or on a major observational study. However, this is not the same as doing a formal systematic review. In-depth scoping of the literature will suffice. If it is found that potentially valuable studies already exist on the research question that one has in mind, then the new study that one is thinking about may be discarded, and a systematic review should be done instead.

Intermezzo: specific schemes to structure reasoning

Specific schemes have been proposed to guide our reasoning between the stage of delineation of the “gap in knowledge” and the stage of proposing the research design.

The acronym FINER (feasible, interesting, novel, ethical, and relevant) was coined by Hulley and Cummings 2 and denotes the different aspects that one should consider to judge a budding research proposal. These words are a good checklist for an in-depth self-scrutiny of your research. The central aspects are the feasibility and whether the possible answers are exciting (and/or much needed).

The PICO format (Patient, Intervention, Control or Comparison, Outcome) is advocated by the evidence-based medicine and Cochrane movements and is very useful for clinical therapeutic research, particularly randomized controlled trials (RCTs). 1 , 42 Questions about therapeutic interventions are highly specific, for example, a particular chemotherapeutic scheme (the intervention) is proposed to study survival (the outcome) among young women with a particular form of stage III breast cancer (the patients). This framework is less useful, and becomes a bit pointless, for etiologic research about generalizable questions such as: “Does smoking cause lung cancer?” which applies to all humans and to different types of smoking. Of course, all research will be done in particular population, with particular smoking habits, but this does not necessarily define the research question. Some of the first investigations about smoking and lung cancer were done in male doctors aged ≥35 years in the UK 43 – this was a very convenient group to research, but being a male doctor in the UK is not part of the research question.

The PICO format is thus most applicable for pragmatic research. A much more detailed and elaborate scheme for pragmatic research was proposed by the US Patient-Centered Outcomes Research Institute (PCORI) which has published Methodology Standards, including “Standards for Formulating Research Questions”. While we would not agree with all six standards, junior investigators may find the structure useful as they think through their options – especially for pragmatic research questions. 44

Counterfactual reasoning 3 emphasizes those aspects of the “ideal randomized trial” that should be mimicked by an observational study. A key question is whether your study is addressing a hypothesis that could in theory be studied in a randomized trial. For example, if the research question is “does smoking cause lung cancer?”, then this is a question that could in theory (but not in practice) be addressed by randomizing study participants to be smokers or nonsmokers. In this situation, it may be useful to design your observational study with the intention of obtaining the same answer that would have been obtained if you had been able to do a randomized trial.

However, the aims of explanatory observational research are different from those of randomized trials. 27 Explanatory research about disease etiology may involve “states” like being female, being old, being obese, having hypertension, having a high serum cholesterol, carrying the BrCa1 gene, and so on, as causes of disease. None of these causes are interventions. In contrast, RCTs focus on what to do to change particular causes: which interventions are feasible and work? For example, being female might expose a person to job discrimination; the intervention might be to have women on the appointment committee or to use some kind of positive discrimination. Likewise, the gene for phenylketonuria leads to disease, but the intervention is to change the diet. For carriers of BRCa1 genes, different strategies can be evaluated in RCTs to evaluate their effectiveness in preventing premature death due to breast cancer: frequent screening, prophylactic mastectomy, hormone treatment, and so on – which may have different effects. For obesity or hypertension or hypercholesterolemia, different types of interventions are possible – with potentially different effects and different adverse effects.

The interventionist outlook, that is, trying to mimic an RCT, can be very useful, for some type of observational studies, for example, about the adverse effects of drugs. It helps to make certain that one can mimic an “intervention” (ie, patients starting to use particular drugs) that is specific and consistent in groups of patients that are comparable (more technically, exchangeable – meaning that the results of the investigation would not change if the persons exposed and nonexposed were swapped). These conditions can be met in a credible way, if there are competing drugs for a similar indication, so that there is an active drug comparator: the interventions (use of different drugs in different patients) will be well defined, and the patients on the different drugs will tend to be comparable. This works particularly well if you are focusing on adverse drug effects that were unknown or unpredictable at the time of prescription. 45 , 46 For example, you may obtain more valid findings in a study that compares the adverse effects of two different beta agonists for asthma care (ie, two different drugs within the same class), than to design a study which compares patients who are prescribed beta agonists with patients who are prescribed other asthma medication, or no medication at all – because the latter might be a highly different group of patients. 47

As mentioned, there are some important studies about causes of diseases where a randomized trial is not feasible, even in theory. In particular, there are various “states” which are major causes of disease (obesity, cholesterol, hypertension, diabetes, etc). These states strongly affect the risks of disease and death, but cannot be randomized. For example, it is difficult to conceive of randomizing study participants to be obese or not obese; however, we could randomize them for the reduction of obesity, for example, through exercise, but such a study would assess the effects of a particular intervention, not of obesity itself. Still, it remains important to estimate the overall effects of obesity, that is, to answer the question “would this group of people have had different health status, on the average, if they had not been obese”. In this situation, the concept of “interventions” is not relevant to designing your study (at least in the way that the term “intervention” is commonly used). What is more relevant is simply to focus on the counterfactual contrast which is being assessed (eg, a body mass index [BMI] of 35 versus a BMI of 25), without specifying how this contrast came about.

A technique that has gone hand in hand with counterfactual reasoning in epidemiology is drawing DAGs; several introductions to DAG theory can be found in epidemiologic textbooks. 3 , 48 DAGs can be useful in the brainstorming phase of a study, after the general research question has been defined. At this stage, a general structure for the study is envisaged and the complexity of the causal processes needs clarification. A DAG can be extremely useful for illustrating the context in which a causal question is being asked, the assumptions that will be involved in the analyses (eg, whether a particular risk factor is a confounder, a mediator, or a col-lider), and help us question the validity of our reasoning. 49 Using DAGs helps us also decide which variables we need to collect information on and how they should be measured and defined. Given that DAGs root in causal thinking, their construction is, of necessity, subjective.

Preparation: pilot study, protocol, and advance writing

Doing a pilot study and collecting ancillary information about feasibility.

May I now start? is a question heard after lengthy deliberations about the research question and the potential studies that follow from it. Such deliberations almost invariably produce a lot of enthusiasm and exhilaration – because they are fun. The researcher wants to begin collecting data or start the analysis. However, Crombie and Davies, in their chapter about “Developing the research question” state emphatically: “Don’t rush into a study”. 16 Separate from doing a pilot study, which is about the procedures of your study, you may also need to collect ancillary information before actually starting your study.

Pilot study

Even if you think you are totally certain of what you want, you should first do a pilot study, based on a brief protocol. 2 , 22 That initial protocol should be easy to write. You have already discussed the aim and design of your study. Write them down. You expect a particular type of information that is essential and that will tell the essence of your message (a particular 2-by-2 or X-by-Y table, a particular graph), which you can describe.

Pilot studies are not done to know the likely direction of the results; instead, the aim is to see whether you will be able to perform the procedures of your study – and ultimately whether that really is the study you want to do. 50 The aim is to save yourself from embarrassment: data that very surprisingly do not turn out to be what you expected, questionnaires that are misunderstood or do not deliver the answers that you need or that are not returned, laboratories that do not produce, patients who do not show up, heads of other departments who block access to their patients or materials, or yourself who needs more time to manage the complexity of the undertaking.

We have never heard of someone who was sorry for having done a pilot. Conversely, we know many persons who found out at much personal embarrassment and institutional cost that their project was unfeasible. In intermediate cases, the pilot may show the need to change questionnaires or procedures before the study goes ahead.

In principle, a pilot study should be exactly like your final study and test out all your procedures on a small number of persons. Often, it is better to approach the task piecemeal and pilot different aspects of the research one by one.

A tough question is how to do pilot studies and pilot analyses when ethical or institutional review board approval is necessary for some of the actions in a pilot study. One solution might be to avoid piloting some procedures; for example, try parts of the procedure – for example, you may not be able to randomize in a pilot, but you may be able to try out data collection procedures and forms. There is a degree of circularity about piloting, also in obtaining funding, as one may need funding for the pilot. In practice, the best step might be to ask the ethics committee or review board of your institute which aspects of the research can be piloted and under what conditions.

In Appendix E , several questions that you might ask in pilot studies are listed. They may lead to profound reassessments of your research – particularly if you are piloting the collection of new data, but also if the research involves analyses of existing data.

Ancillary information

It may be necessary to collect additional information about event rates or standard deviations of measurements to calculate the statistical precision that might be obtained. Also, sometimes you need other ways of “testing the water” like procedures to streamlining data collection from different centers in order to know whether the study is feasible. Depending on the study size and importance, such activities may become studies in themselves and actually take a lot of time and money.

Advance writing of paper: before full data collection and/or analysis

Whitesides’ advice is:

The key to efficient use of your and my time is that we start exchanging outlines and proposals as early in a project as possible. Do not, under any circumstances, wait until the collection of data is ‘complete’ before starting to write an outline. 38

After the pilot study, you have a firm grasp of all elements that are necessary for a scientific paper: introduction, materials and methods, results, and discussion. In the introduction, you explain why you have done this research. Almost always, an introduction comprises three ideas: what is the general problem? what is the particular research question? what study will you perform to answer that question? This is followed by the materials and methods section. They have been extensively discussed and have been fine-tuned in the study protocol and the pilot study. Thereafter come the results sections. By now, you know what tables or figures you want and how you can obtain them, but not what the final numbers will look like. You will also have an idea about the auxiliary tables that you might need to explain your data to others (such as a table with the baseline characteristics or an additional table with a subgroup analysis). You can now draft the layouts of all these tables. Visualizing the presentation of your results in advance is the “bare minimum” of writing in advance.

Finally, the discussion section. Can you write a discussion before you know the final data? Of course you can; you even must think ahead. In principle, there are only three possible outcomes: the study can give the results that you hoped for; it can show the inverse; or something indeterminate in between. In all instances, you can imagine how you will react. One possibility is that you are disappointed by the results of your study, and you will tend to find excuses for why it did not produce the results you hoped for. What excuses might your produce? The other possibility is that it does show what you wanted; then you may have to imagine how others will react and what their objections might be. If the results are indeterminate, everybody might be disappointed, and you will need to explain the failure of your research to give clear-cut results. When you detect a specific weakness by imagining this situation, you may wish to change aspects of your study.

As we explain in Appendix F , there is no need to write a very extensive paper as a first draft – on the contrary, it might be more useful to write a short paper, which has the advantage that others will more readily read it and comment on it.

Never be afraid to discuss your study at all stages extensively with others, not only your immediate research colleagues but also semi-outsiders and also in this advance-writing stage. If you know, or are told by others, that a particular direction of your results might not be believed and therefore draw criticism because of some potential deficiency in your study, why not remedy it at this stage? Looking at what you have written, or by discussing potential results with others, you will be able to imagine more clearly what your readers and critical colleagues might object to.

Writing a paper beforehand is the ultimate test of whether the research project is what you wanted, whether your reasoning flows logically, or whether you forgot something. The initial draft will be a yardstick for yourself and for others – whatever happens during the course of your research. This will help you to surmount surprise happenings: you have written down where you started and why, and therefore you will also know very securely when and why you have to take a detour – or even a U-turn.

Writing is difficult and time-consuming. Writing a paper can easily take 5–10 revisions, which might span a full year (inclusive of the time it takes your supervisor or your colleagues to produce comments). During the writing, you will often be obliged to go back to the data and do additional or different analyses. Since your paper will need many revisions, and this will take such a long time, why not take a head-start at the beginning of your data collection? It will save frustration and lost time at the end of your project.

Many guidelines and advices exist about writing, both about the substance (how to use words and phrases) and about the process. All beginning researchers should have a look at some books and papers about writing, and seasoned researchers can still profit from rereading them. Several reporting guidelines exist for several types of studies (RCTs, observational, diagnostic research, etc). They are often very detailed, in describing what should be in title, abstract, and so on. Although they should not be mechanically adhered to, 28 they help writing. In Appendix F , we have collected some wisdom that we particularly liked; several books on writing are listed, as well as reporting guidelines that help researchers to craft papers that are readable and contain all the information that is necessary and useful to others.

Now you can start “your research”

After the piloting and after having written your paper, you are ready to start your data collection, your analysis, or whatever is needed to “do your research”.

The work that is needed before you can start to “do your research” will take a great deal of time and effort. What will you have achieved after setting up a piece of research following the lengthy and involved precepts of this paper? You will have specified a limited research question that you will solve. You will add one little shining stone to the large mosaic of science. At the time that you do the study, you may still be too close to see its effect on the overall picture. That will come over the years.

Acknowledgments

We thank Miguel Hernán, Stuart Pocock, and Bianca De Stavola for their informative comments on an earlier draft manuscript, as well as two anonymous reviewers of Clinical Epidemiology . The Centre for Global NCDs is supported by the Wellcome Trust Institutional Strategic Support Fund (097834/Z/11/B). This work was also supported by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013 / ERC grant agreement number 668954).

The authors report no conflicts of interest in this work.

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In Tied Presidential Race, Harris and Trump Have Contrasting Strengths, Weaknesses

2. issues and the 2024 election, table of contents.

Other findings: An uncertain election outcome, the more critical candidate, Trump and the 2020 election
Voting preferences among demographic groups
Support for Harris, Trump among voters and nonvoters in recent elections
How Harris and Trump supporters see their vote
Do voters think it’s clear who will win?
Most voters cite several issues as very important to their vote
Changes in confidence in candidates on issues, following Biden’s departure from race
Do voters see the candidates as ‘too personally critical’?
Do the candidates make you feel proud, hopeful, uneasy or angry?
How the candidates make Harris and Trump supporters feel
How men and women view the impact of the candidates’ genders
Views of the candidates’ races and ethnicities
Views of the candidates’ ages among younger and older voters
Views of the values and goals of the other candidate’s supporters
Should the president work with the opposing party in Congress?
Top economic concerns: Food and consumer prices, housing costs
Acknowledgments
The American Trends Panel survey methodology

As concerns around the state of the economy and inflation continue, about eight-in-ten registered voters (81%) say the economy will be very important to their vote in the 2024 presidential election.

While the economy is the top issue among voters, a large majority (69%) cite at least five of the 10 issues asked about in the survey as very important to their vote.

Chart shows The economy is the top issue for voters in the 2024 election

There are wide differences between voters who support Harris and Trump when it comes to the issues.

Among Trump supporters, the economy (93%), immigration (82%) and violent crime (76%) are the leading issues. Just 18% of Trump supporters say racial and ethnic inequality is very important. And even fewer say climate change is very important (11%).

For Harris supporters, issues such as health care (76%) and Supreme Court appointments (73%) are of top importance. Large majorities also cite the economy (68%) and abortion (67%) as very important to their vote in the election.

Most voters cite several issues as very important to their vote this November. Very few – just 5% – say only one issue or no issues are highly important.

Chart shows About 7 in 10 voters say 5 or more issues are very important to their presidential vote

Majorities of both Harris supporters (71%) and Trump supporters (69%) say at least five of 10 issues included in the survey are very important to their vote.

Harris supporters are more likely than Trump supporters to say most of the issues included are very important. About a third of Harris supporters (32%) say at least eight of 10 issues are very important, compared with 17% of Trump supporters.

Top voting issues: 2020 versus 2024

While the economy has long been a top issue for voters – and continues to be one today – other issues have become increasingly important for voters over the past four years.

Immigration

About six-in-ten voters (61%) today say immigration is very important to their vote – a 9 percentage point increase from the 2020 presidential election and 13 points higher than during the 2022 congressional elections.

Immigration is now a much more important issue for Republican voters in particular: 82% of Trump supporters say it is very important to their vote in the 2024 election, up 21 points from 2020.

About four-in-ten Harris supporters (39%) say immigration is very important to their vote. This is 8 points higher than the share of Democratic congressional supporters who said this in 2022, but lower than the 46% of Biden supporters who cited immigration as very important four years ago.

In August 2020, fewer than half of voters (40%) said abortion was a very important issue to their vote. At the time, Trump voters (46%) were more likely than Biden voters (35%) to say it mattered a great deal.

Following the Supreme Court’s decision to overturn Roe v. Wade , opinions about abortion’s importance as a voting issue shifted. Today, 67% of Harris supporters call the issue very important – nearly double the share of Biden voters who said this four years ago, though somewhat lower than the share of midterm Democratic voters who said this in 2022 (74%). And about a third of Trump supporters (35%) now say abortion is very important to their vote – 11 points lower than in 2020.

Confidence in Harris and Trump on top issues

Chart shows Voters are more confident in Trump on economy, immigration; Harris leads on abortion, race

Voters have more confidence in Trump than Harris on economic, immigration and foreign policies. Half or more voters say they are at least somewhat confident in Trump to make good decisions in these areas, while smaller shares (45% each) say this about Harris.

In contrast, voters have more confidence in Harris than Trump to make good decisions about abortion policy and to effectively address issues around race. Just over half of voters have confidence in Harris on these issues, while 44% have confidence in Trump on these issues.

Trump holds a slight edge over Harris for handling law enforcement and criminal justice issues (51% Trump, 47% Harris). Voters are equally confident in Harris and Trump to select good nominees for the Supreme Court (50% each).

Fewer than half of voters say they are very or somewhat confident in either candidate to bring the country closer together (41% are confident in Harris, 36% in Trump). And voters express relatively little confidence in Trump (37%) or Harris (32%) to reduce the influence of money in politics.

Chart shows Voters are more confident in Harris than they were in Biden on several issues

Since Biden dropped out of the presidential race in July , there has been movement on how confident voters are in the candidates to address issues facing the country.

Abortion policy

In July, 48% of voters were confident in Biden to make good decisions about abortion policy. Today, 55% of voters are confident in Harris to do the same.

Harris currently has an 11-point advantage over Trump on voters’ confidence to handle abortion policy decisions.

Immigration policy

Voters also express more confidence in Harris to make wise decisions about immigration policy than they did for Biden before he withdrew from the race. Today, 45% are confident in Harris on this issue; in July, 35% said this about Biden.

While Trump’s advantage over Harris on immigration policy is less pronounced than it was over Biden, he continues to hold a 7-point edge. Voters are as confident in his ability to make wise decisions about immigration policy as they were in July (52%).

Foreign and economic policies

Harris has also improved over Biden in voters’ confidence to make good decisions about foreign and economic policies. Currently, 45% of voters are confident in Harris on each of these issues.

In July, 39% had confidence in Biden to make good foreign policy decisions, while a similar share (40%) had confidence in him on economic policy.

Trump holds an edge over Harris on both of these issues, though both are somewhat narrower than the advantage he had over Biden on these issues in July.

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Airstrikes Hit Syrian City Said to Be a Weapons Research Hub, Killing 18

Syria accused Israel of carrying out the attacks in and around Masyaf, where experts say missiles and unconventional weapons are developed. Israel did not comment.

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A child on a bicycle gazes at the wreckage of a burned-out vehicle on a dirt road, with some men and vehicles in the background.

By Matthew Mpoke Bigg Ephrat Livni and Thomas Fuller

Airstrikes in Syria killed at least 18 people and injured dozens of others, Syria’s state news media reported on Monday, blaming Israel for the attacks in and around a city known as a center for the development of weapons, including missiles.

The Syrian state news agency, SANA, said multiple sites were hit in and near Masyaf, a small city in northwestern Syria; most of its reports were vague about what, exactly, was struck, but some said the targets were military sites. Israeli officials declined to comment on the attack.

The Syrian Observatory for Human Rights, a group based in Britain that tracks the conflict in Syria, confirmed the strikes and said they hit an area containing a scientific research institute where work on “developing short- and medium-range precision missiles” is conducted. It cited unnamed sources in the Syrian security forces.

Independent experts, Israeli officials and the U.S. government have described that institute as a center of weapons research and development , aided by Syria’s ally Iran, with the work being done there including chemical, biological and potentially nuclear weapons as well as missiles used by Hezbollah, the powerful Iran-backed militia group in Lebanon that is fighting Israel.

Israel has struck Masyaf, about 25 miles from the Mediterranean coast, several times in the past.

The airstrikes late Sunday night and early Monday amounted to one of the deadliest attacks in Syria in months. SANA said that in addition to the 18 dead, 37 people had been injured in the strikes, including six who were in critical condition. The agency said that the strikes had damaged roads and water, power and telephone infrastructure.

The Syrian Observatory put the death toll higher, saying that at least 25 people had been killed, including Syrian combatants, people working with Iranian militias and civilians. It was not possible to confirm the reported tolls independently.

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Research: When Bonuses Backfire

Dirk Sliwka
Timo Vogelsang

How to rethink your incentive strategy and reward employees in ways that actually motivate them.

Why do bonuses sometimes backfire? It’s because each incentive design choice both signals information about your own beliefs and intentions as an employer and shapes the signaling value of employee behavior within the organization. If you don’t think through these signals carefully, you may end up approving a bonus scheme with results that are the opposite of what you intend. This article offers a way to help you align the signals your incentive scheme sends with your performance goals.

More than 30 years ago, author and lecturer Alfie Kohn, in a rather controversial but often cited HBR article , claimed that “rewards typically undermine the very processes they are intended to enhance.” Yet until recently, nearly all scientific studies that have documented such “backfiring” effects have been confined to laboratory experiments or field settings outside of the firm. This may cause some to question whether these effects are really present in commercial contexts. Our new research, which consists of two large field experiments in retail organizations, demonstrates that they do indeed occur. One of the studies showed unequivocally that the provision of a monetary attendance bonus increased absence days. The other revealed that the added value of performance review conversations was wiped out when they were combined with a monetary bonus. In both cases, a well-intentioned financial reward ultimately had crucial and costly unintended effects, largely because of signals about expected behavior given by the incentives. To understand what was going on, let’s look at the two studies in turn.

DS Dirk Sliwka is a professor of management in the Faculty of Management, Economics, and Social Sciences at the University of Cologne in Germany
TV Timo Vogelsang is an Associate Professor of Managerial Accounting at the Frankfurt School of Finance and Management in Germany

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

Qualitative vs. quantitative : Will your data take the form of words or numbers?
Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

For quantitative data, you can use statistical analysis methods to test relationships between variables.
For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .


Qualitative		to broader populations. .
Quantitative		.

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.


Primary	.	methods.
Secondary

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.


Descriptive		. .
Experimental

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Research methods for collecting data
Research method	Primary or secondary?	Qualitative or quantitative?	When to use
	Primary	Quantitative	To test cause-and-effect relationships.
	Primary	Quantitative	To understand general characteristics of a population.
Interview/focus group	Primary	Qualitative	To gain more in-depth understanding of a topic.
Observation	Primary	Either	To understand how something occurs in its natural setting.
	Secondary	Either	To situate your research in an existing body of work, or to evaluate trends within a research topic.
	Either	Either	To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study.

Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

During an experiment .
Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

Research methods for analyzing data
Research method	Qualitative or quantitative?	When to use
	Quantitative	To analyze data collected in a statistically valid manner (e.g. from experiments, surveys, and observations).
Meta-analysis	Quantitative	To statistically analyze the results of a large collection of studies. Can only be applied to studies that collected data in a statistically valid manner.
	Qualitative	To analyze data collected from interviews, , or textual sources. To understand general themes in the data and how they are communicated.
	Either	To analyze large volumes of textual or visual data collected from surveys, literature reviews, or other sources. Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words).

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

Chi square test of independence
Statistical power
Descriptive statistics
Degrees of freedom
Pearson correlation
Null hypothesis
Double-blind study
Case-control study
Research ethics
Data collection
Hypothesis testing
Structured interviews

Research bias

Hawthorne effect
Unconscious bias
Recall bias
Halo effect
Self-serving bias
Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Other students also liked, writing strong research questions | criteria & examples.

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A woman stands in front of a red sign on the wall that says "Nanoworld"

CEAS alumna at the forefront of AI chip innovation

Devika chauhan applies graduate research to develop future ai chips at intel.

During her time as a doctoral student at the University of Cincinnati, Devika Chauhan played a vital role in elevating UC's cutting-edge research on carbon nanotube synthesis and its state-of-the-art applications. Now employed by Intel Corp., she applies the knowledge from her graduate experience at UC to develop future artificial intelligence chips.

Devika Chauhan's collaborative work at UC resulted in UC's receiving two patents for work involving carbon nanotubes. Now, she works at Intel Corp. Photo/Provided

Chauhan was attracted to UC's College of Engineering and Applied Science by its variety of research programs. Her decision to come to UC was cemented, she said, when she discovered UC's vast network of professional connections and opportunities both in Cincinnati and worldwide.

"After earning my bachelor's degree in India, I was eager to broaden my skillset and explore new opportunities," Chauhan said. "What truly captivated me about UC is its extensive network of connections. The opportunity for deep academic, professional, and research-based engagement, coupled with a University Graduate Scholarship award, teaching assistantship and research assistantship positions made UC a perfect choice for my graduate studies."

Chauhan began exploring nanotechnology during a smart structures course with professor Mark Schulz during her first semester at UC. It was there that she became fascinated by the properties of carbon nanotubes and their potential applications. Her initial curiosity and prior experience with composite structures inspired her to take a tour of Nanoworld , UC's nanotechnology lab, which ultimately played a major role in her decision to pursue a doctorate after earning her master's degree.

Devika Chauhan, left, conducted research in UC's Nanoworld laboratory with Professor Mark Schulz. Photo/Provided

While working alongside experts in nanotechnology, her curiosity for carbon nanotube research knew no bounds. The lab at UC combined with the support from faculty on campus is what solidified her decision to stay at UC to pursue a doctorate.

"Deciding to pursue a Ph.D. was a straightforward choice for me. The supportive environment at UC made it feel like a family; I always felt comfortable seeking help from professors and colleagues. Even if they couldn't assist directly, they were always willing to connect me with someone who could," she said.

During her doctoral studies, Chauhan's research primarily consisted of synthesizing carbon materials and applications, improving material properties. Some of the projects she worked on included developing heat-resistant materials to protect firefighters from fire hazards, creating high-altitude radiation shielding and contributing to a collaborative project with the U.S. Army.

Her expertise in carbon nanotube synthesis and its application led her to become a principal investigator for two projects that were funded by the National Institute for Occupational Safety and Health. Accompanying her academic studies, Chauhan was a teaching assistant for multiple semesters. Her collaborative work at UC resulted in the college's receiving two patents for work involving carbon nanotubes, more than a dozen published papers and six book chapters.

"My accomplishments at UC would not have been possible without the guidance of my mentors, including Professors Mark Schulz, Henry Spitz, Vesselin Shanov and Peter Nagy," she said.

UC has given me more than I can think of. Even now, I think of Cincinnati as home.

Devika Chauhan CEAS alumna

Chauhan said her transition from academia to the professional world was easy. She landed a job at Intel in her final semester at UC.

Thanks to her experience with nanomaterials, she started off at Intel layering materials to make conductors and connectors in the development stages of these AI chips. In her role, she tackles the challenge of yield, which is making as many chips as possible from a single wafer. This process is integral to the semiconductor industry. Chauhan's work is contributing to Intel's efforts to compete in the global AI chip market.

"UC has given me more than I can think of. Even now, I think of Cincinnati as home," she said.

Featured image at top: Devika Chauhan worked in UC's Nanoworld lab as a graduate student. Photo/Provided

Interested in learning more?

Learn more about UC's involvement in training the future workforce in the semiconductor field , including the new fabrication plants under construction by Intel in Ohio.

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UC welcomes largest group of new global students ever this fall

November 19, 2021

This fall, a record number of international students arrived for the first time at the University of Cincinnati. In spite of ongoing uncertainty over global health and safety, in spite of sometimes chaotic changes to government guidelines or the availability of visa appointments, and in spite of the many complications currently entangling world travel, 1,224 new international students arrived at UC for the first time.

Georgia Tech to end China partnerships following concerns over military ties

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Forum on China-Africa Cooperation in Beijing

Reporting by Michael Martina; Editing by David Gregorio

Our Standards: The Thomson Reuters Trust Principles. , opens new tab

Top US, Chinese military officials hold first video call

The United States and China held theatre-level commander talks for the first time on Tuesday, Chinese authorities said, as the two nations look to stabilise military ties and prevent military misunderstandings.

Right wing Alternative for Germany (AfD) party protest, one week after a man killed a policeman with a knife in the city of Mannheim

Nomination Opportunity: José Vasconcelos Award 2025

URL: https://www.consejoculturalmundial.org/world-award-of-education/

The José Vasconcelos World Award of Education is granted to a renowned educator, an authority in the field of teaching, or someone who has brought about visionary development in education policy. Through their work, the individual or team should have had a significantly positive influence on the quality and reach of teaching and learning in our society. The World Award of Education acknowledges these exceptional individuals for their enduring contributions, innovations, and leadership in education, significantly enhancing the quality and accessibility of education globally.

Winners are characterized by several key attributes listed below:

Innovative Educational Practices
Global Influence in Education
Contributions to Educational Research
Commitment to Learning and Teaching
Inspiring Leadership
Development of Educational Resources
Promotion of Educational Equity and Accessibility
Interdisciplinary Approach
International Collaboration and Exchange

AWARD INFORMATION:

The World Award of Education grants a Diploma, a Commemorative medal, and an Award Cheque.

For more information about the nomination process, please consult the award website.

Nomination Deadline: Friday, November 29, 2024 by 11:59 Central European Time

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Research is the deliberate, purposeful, and systematic gathering of data, information, facts, and/or opinions for the advancement of personal, societal, or overall human knowledge. Based on this definition, we all do research all the time. Most of this research is casual research. Asking friends what they think of different restaurants, looking ...
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Issues and the 2024 election
ABOUT PEW RESEARCH CENTER Pew Research Center is a nonpartisan, nonadvocacy fact tank that informs the public about the issues, attitudes and trends shaping the world. It does not take policy positions. The Center conducts public opinion polling, demographic research, computational social science research and other data-driven research.
Airstrikes Hit Syrian City Said to Be a Weapons Research Hub, Killing
Israeli security experts at the nonprofit Alma Research and Education Center, in an August 2023 report on the Syrian research center, said it serves as a "growth engine for the development and ...
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Our new research, which consists of two large field experiments in retail organizations, demonstrates that they do indeed occur. One of the studies showed unequivocally that the provision of a ...
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Research Methods | Definitions, Types, Examples
CEAS alumna at the forefront of AI chip innovation
During her time as a graduate student at the University of Cincinnati, Devika Chauhan, PhD played a vital role in elevating UC's cutting-edge research on carbon nanotube synthesis and its state-of-the-art applications. Now employed by Intel, she applies the knowledge from her graduate experience at UC to develop future artificial intelligence (AI) chips.
Georgia Tech to end China partnerships following concerns over military
Georgia Tech is ending its research and educational partnerships in the Chinese cities of Tianjin and Shenzhen, the U.S. university said on Friday, following scrutiny from Congress over its ...
Nomination Opportunity: José Vasconcelos Award 2025
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