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Definition of research

 (Entry 1 of 2)

Definition of research  (Entry 2 of 2)

transitive verb

intransitive verb

• disquisition
• examination
• exploration
• inquisition
• investigation
• delve (into)
• inquire (into)
• investigate
• look (into)

Examples of research in a Sentence

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

Word History

Middle French recerche , from recercher to go about seeking, from Old French recerchier , from re- + cerchier, sercher to search — more at search

1577, in the meaning defined at sense 3

1588, in the meaning defined at transitive sense 1

Phrases Containing research

• market research
• marketing research
• operations research

research and development

• research park
• translational research
• oppo research

Dictionary Entries Near research

Cite this entry.

“Research.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/research. Accessed 25 Mar. 2024.

Kids Definition

Kids definition of research.

Kids Definition of research  (Entry 2 of 2)

More from Merriam-Webster on research

Nglish: Translation of research for Spanish Speakers

Britannica English: Translation of research for Arabic Speakers

Britannica.com: Encyclopedia article about research

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Home Market Research

What is Research: Definition, Methods, Types & Examples

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

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

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

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

Research is conducted with a purpose to:

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

What is the purpose of research?

There are three main purposes:

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

LEARN ABOUT: Descriptive Analysis

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

LEARN ABOUT: Best Data Collection Tools

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

Here is a comparative analysis chart for a better understanding:

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

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

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

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods.

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

Types of qualitative methods include:

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

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

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

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

It is essential to ensure that your data is:

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

Gather insights

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

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

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Definition of 'research'

Video: pronunciation of research

research in British English

Research in american english, examples of 'research' in a sentence research, cobuild collocations research, trends of research.

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• resealable bag
• research a book
• research a product
• research a source
• All ENGLISH words that begin with 'R'

Related terms of research

• do research
• aid research
• cite research
• fund research
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diligent and systematic inquiry or investigation into a subject in order to discover or revise facts, theories, applications, etc.: recent research in medicine.

a particular instance or piece of research.

to make researches; investigate carefully.

to make an extensive investigation into: to research a matter thoroughly.

Origin of research

Synonym study for research, other words for research, other words from research.

• re·search·a·ble, adjective
• re·search·er, re·search·ist, noun
• pro·re·search, adjective
• un·der·re·search, verb (used with object)

Words that may be confused with research

• re-search , research

Words Nearby research

• rescue grass
• rescue mission
• research and development
• research-intensive
• research library
• research park
• research quantum

Other definitions for re-search (2 of 2)

to search or search for again.

Origin of re-search

Words that may be confused with re-search.

Dictionary.com Unabridged Based on the Random House Unabridged Dictionary, © Random House, Inc. 2024

How to use research in a sentence

The duo spent the first year in research and engaging with farmers.

Dan Finn-Foley, head of energy storage at energy research firm Wood Mackenzie Power & Renewables, compared Google’s plan to ordering eggs for breakfast.

Users will give Deep Longevity the right to conduct anonymized research using their data as part of the app’s terms and conditions, Zhavoronkov said.

There’s also the Wilhelm Reich Museum, located at “Orgonon” in Rangeley, Maine, which was previously Reich’s estate—where he conducted questionable orgone research in the later years of his career.

When we started doing research on these topics, we were too focused on political institutions.

Have you tried to access the research that your tax dollars finance, almost all of which is kept behind a paywall?

Have a look at this telling research from Pew on blasphemy and apostasy laws around the world.

And Epstein continues to steer money toward universities to advance scientific research .

The research literature, too, asks these questions, and not without reason.

We also have a growing body of biological research showing that fathers, like mothers, are hard-wired to care for children.

We find by research that smoking was the most general mode of using tobacco in England when first introduced.

This class is composed frequently of persons of considerable learning, research and intelligence.

Speaking from recollection, it appears to be a work of some research ; but I cannot say how far it is to be relied on.

Thomas Pope Blount died; an eminent English writer and a man of great learning and research .

That was long before invention became a research department full of engineers.

British Dictionary definitions for research

/ ( rɪˈsɜːtʃ , ˈriːsɜːtʃ ) /

systematic investigation to establish facts or principles or to collect information on a subject

to carry out investigations into (a subject, problem, etc)

Derived forms of research

• researchable , adjective
• researcher , noun

Collins English Dictionary - Complete & Unabridged 2012 Digital Edition © William Collins Sons & Co. Ltd. 1979, 1986 © HarperCollins Publishers 1998, 2000, 2003, 2005, 2006, 2007, 2009, 2012

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

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

Take your English to the next level

The Oxford Learner’s Thesaurus explains the difference between groups of similar words. Try it for free as part of the Oxford Advanced Learner’s Dictionary app

Research Basics

• What Is Research?
• Types of Research
• Secondary Research | Literature Review
• Developing Your Topic
• Primary vs. Secondary Sources
• Evaluating Sources
• Responsible Conduct of Research
• Additional Help

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.

So What Do We Mean By “Formal Research?”

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: Dec 21, 2023 3:49 PM
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Home » Research – Types, Methods and Examples

Research – Types, Methods and Examples

Table of Contents

Definition:

Research refers to the process of investigating a particular topic or question in order to discover new information , develop new insights, or confirm or refute existing knowledge. It involves a systematic and rigorous approach to collecting, analyzing, and interpreting data, and requires careful planning and attention to detail.

History of Research

The history of research can be traced back to ancient times when early humans observed and experimented with the natural world around them. Over time, research evolved and became more systematic as people sought to better understand the world and solve problems.

In ancient civilizations such as those in Greece, Egypt, and China, scholars pursued knowledge through observation, experimentation, and the development of theories. They explored various fields, including medicine, astronomy, and mathematics.

During the Middle Ages, research was often conducted by religious scholars who sought to reconcile scientific discoveries with their faith. The Renaissance brought about a renewed interest in science and the scientific method, and the Enlightenment period marked a major shift towards empirical observation and experimentation as the primary means of acquiring knowledge.

The 19th and 20th centuries saw significant advancements in research, with the development of new scientific disciplines and fields such as psychology, sociology, and computer science. Advances in technology and communication also greatly facilitated research efforts.

Today, research is conducted in a wide range of fields and is a critical component of many industries, including healthcare, technology, and academia. The process of research continues to evolve as new methods and technologies emerge, but the fundamental principles of observation, experimentation, and hypothesis testing remain at its core.

Types of Research

Types of Research are as follows:

• Applied Research : This type of research aims to solve practical problems or answer specific questions, often in a real-world context.
• Basic Research : This type of research aims to increase our understanding of a phenomenon or process, often without immediate practical applications.
• Experimental Research : This type of research involves manipulating one or more variables to determine their effects on another variable, while controlling all other variables.
• Descriptive Research : This type of research aims to describe and measure phenomena or characteristics, without attempting to manipulate or control any variables.
• Correlational Research: This type of research examines the relationships between two or more variables, without manipulating any variables.
• Qualitative Research : This type of research focuses on exploring and understanding the meaning and experience of individuals or groups, often through methods such as interviews, focus groups, and observation.
• Quantitative Research : This type of research uses numerical data and statistical analysis to draw conclusions about phenomena or populations.
• Action Research: This type of research is often used in education, healthcare, and other fields, and involves collaborating with practitioners or participants to identify and solve problems in real-world settings.
• Mixed Methods Research : This type of research combines both quantitative and qualitative research methods to gain a more comprehensive understanding of a phenomenon or problem.
• Case Study Research: This type of research involves in-depth examination of a specific individual, group, or situation, often using multiple data sources.
• Longitudinal Research: This type of research follows a group of individuals over an extended period of time, often to study changes in behavior, attitudes, or health outcomes.
• Cross-Sectional Research : This type of research examines a population at a single point in time, often to study differences or similarities among individuals or groups.
• Survey Research: This type of research uses questionnaires or interviews to gather information from a sample of individuals about their attitudes, beliefs, behaviors, or experiences.
• Ethnographic Research : This type of research involves immersion in a cultural group or community to understand their way of life, beliefs, values, and practices.
• Historical Research : This type of research investigates events or phenomena from the past using primary sources, such as archival records, newspapers, and diaries.
• Content Analysis Research : This type of research involves analyzing written, spoken, or visual material to identify patterns, themes, or messages.
• Participatory Research : This type of research involves collaboration between researchers and participants throughout the research process, often to promote empowerment, social justice, or community development.
• Comparative Research: This type of research compares two or more groups or phenomena to identify similarities and differences, often across different countries or cultures.
• Exploratory Research : This type of research is used to gain a preliminary understanding of a topic or phenomenon, often in the absence of prior research or theories.
• Explanatory Research: This type of research aims to identify the causes or reasons behind a particular phenomenon, often through the testing of theories or hypotheses.
• Evaluative Research: This type of research assesses the effectiveness or impact of an intervention, program, or policy, often through the use of outcome measures.
• Simulation Research : This type of research involves creating a model or simulation of a phenomenon or process, often to predict outcomes or test theories.

Data Collection Methods

• Surveys : Surveys are used to collect data from a sample of individuals using questionnaires or interviews. Surveys can be conducted face-to-face, by phone, mail, email, or online.
• Experiments : Experiments involve manipulating one or more variables to measure their effects on another variable, while controlling for other factors. Experiments can be conducted in a laboratory or in a natural setting.
• Case studies : Case studies involve in-depth analysis of a single case, such as an individual, group, organization, or event. Case studies can use a variety of data collection methods, including interviews, observation, and document analysis.
• Observational research : Observational research involves observing and recording the behavior of individuals or groups in a natural setting. Observational research can be conducted covertly or overtly.
• Content analysis : Content analysis involves analyzing written, spoken, or visual material to identify patterns, themes, or messages. Content analysis can be used to study media, social media, or other forms of communication.
• Ethnography : Ethnography involves immersion in a cultural group or community to understand their way of life, beliefs, values, and practices. Ethnographic research can use a range of data collection methods, including observation, interviews, and document analysis.
• Secondary data analysis : Secondary data analysis involves using existing data from sources such as government agencies, research institutions, or commercial organizations. Secondary data can be used to answer research questions, without collecting new data.
• Focus groups: Focus groups involve gathering a small group of people together to discuss a topic or issue. The discussions are usually guided by a moderator who asks questions and encourages discussion.
• Interviews : Interviews involve one-on-one conversations between a researcher and a participant. Interviews can be structured, semi-structured, or unstructured, and can be conducted in person, by phone, or online.
• Document analysis : Document analysis involves collecting and analyzing written documents, such as reports, memos, and emails. Document analysis can be used to study organizational communication, policy documents, and other forms of written material.

Data Analysis Methods

Data Analysis Methods in Research are as follows:

• Descriptive statistics : Descriptive statistics involve summarizing and describing the characteristics of a dataset, such as mean, median, mode, standard deviation, and frequency distributions.
• Inferential statistics: Inferential statistics involve making inferences or predictions about a population based on a sample of data, using methods such as hypothesis testing, confidence intervals, and regression analysis.
• Qualitative analysis: Qualitative analysis involves analyzing non-numerical data, such as text, images, or audio, to identify patterns, themes, or meanings. Qualitative analysis can be used to study subjective experiences, social norms, and cultural practices.
• Content analysis: Content analysis involves analyzing written, spoken, or visual material to identify patterns, themes, or messages. Content analysis can be used to study media, social media, or other forms of communication.
• Grounded theory: Grounded theory involves developing a theory or model based on empirical data, using methods such as constant comparison, memo writing, and theoretical sampling.
• Discourse analysis : Discourse analysis involves analyzing language use, including the structure, function, and meaning of words and phrases, to understand how language reflects and shapes social relationships and power dynamics.
• Network analysis: Network analysis involves analyzing the structure and dynamics of social networks, including the relationships between individuals and groups, to understand social processes and outcomes.

Research Methodology

Research methodology refers to the overall approach and strategy used to conduct a research study. It involves the systematic planning, design, and execution of research to answer specific research questions or test hypotheses. The main components of research methodology include:

• Research design : Research design refers to the overall plan and structure of the study, including the type of study (e.g., observational, experimental), the sampling strategy, and the data collection and analysis methods.
• Sampling strategy: Sampling strategy refers to the method used to select a representative sample of participants or units from the population of interest. The choice of sampling strategy will depend on the research question and the nature of the population being studied.
• Data collection methods : Data collection methods refer to the techniques used to collect data from study participants or sources, such as surveys, interviews, observations, or secondary data sources.
• Data analysis methods: Data analysis methods refer to the techniques used to analyze and interpret the data collected in the study, such as descriptive statistics, inferential statistics, qualitative analysis, or content analysis.
• Ethical considerations: Ethical considerations refer to the principles and guidelines that govern the treatment of human participants or the use of sensitive data in the research study.
• Validity and reliability : Validity and reliability refer to the extent to which the study measures what it is intended to measure and the degree to which the study produces consistent and accurate results.

Applications of Research

Research has a wide range of applications across various fields and industries. Some of the key applications of research include:

• Advancing scientific knowledge : Research plays a critical role in advancing our understanding of the world around us. Through research, scientists are able to discover new knowledge, uncover patterns and relationships, and develop new theories and models.
• Improving healthcare: Research is instrumental in advancing medical knowledge and developing new treatments and therapies. Clinical trials and studies help to identify the effectiveness and safety of new drugs and medical devices, while basic research helps to uncover the underlying causes of diseases and conditions.
• Enhancing education: Research helps to improve the quality of education by identifying effective teaching methods, developing new educational tools and technologies, and assessing the impact of various educational interventions.
• Driving innovation: Research is a key driver of innovation, helping to develop new products, services, and technologies. By conducting research, businesses and organizations can identify new market opportunities, gain a competitive advantage, and improve their operations.
• Informing public policy : Research plays an important role in informing public policy decisions. Policy makers rely on research to develop evidence-based policies that address societal challenges, such as healthcare, education, and environmental issues.
• Understanding human behavior : Research helps us to better understand human behavior, including social, cognitive, and emotional processes. This understanding can be applied in a variety of settings, such as marketing, organizational management, and public policy.

Importance of Research

Research plays a crucial role in advancing human knowledge and understanding in various fields of study. It is the foundation upon which new discoveries, innovations, and technologies are built. Here are some of the key reasons why research is essential:

• Advancing knowledge: Research helps to expand our understanding of the world around us, including the natural world, social structures, and human behavior.
• Problem-solving: Research can help to identify problems, develop solutions, and assess the effectiveness of interventions in various fields, including medicine, engineering, and social sciences.
• Innovation : Research is the driving force behind the development of new technologies, products, and processes. It helps to identify new possibilities and opportunities for improvement.
• Evidence-based decision making: Research provides the evidence needed to make informed decisions in various fields, including policy making, business, and healthcare.
• Education and training : Research provides the foundation for education and training in various fields, helping to prepare individuals for careers and advancing their knowledge.
• Economic growth: Research can drive economic growth by facilitating the development of new technologies and innovations, creating new markets and job opportunities.

When to use Research

Research is typically used when seeking to answer questions or solve problems that require a systematic approach to gathering and analyzing information. Here are some examples of when research may be appropriate:

• To explore a new area of knowledge : Research can be used to investigate a new area of knowledge and gain a better understanding of a topic.
• To identify problems and find solutions: Research can be used to identify problems and develop solutions to address them.
• To evaluate the effectiveness of programs or interventions : Research can be used to evaluate the effectiveness of programs or interventions in various fields, such as healthcare, education, and social services.
• To inform policy decisions: Research can be used to provide evidence to inform policy decisions in areas such as economics, politics, and environmental issues.
• To develop new products or technologies : Research can be used to develop new products or technologies and improve existing ones.
• To understand human behavior : Research can be used to better understand human behavior and social structures, such as in psychology, sociology, and anthropology.

Characteristics of Research

The following are some of the characteristics of research:

• Purpose : Research is conducted to address a specific problem or question and to generate new knowledge or insights.
• Systematic : Research is conducted in a systematic and organized manner, following a set of procedures and guidelines.
• Empirical : Research is based on evidence and data, rather than personal opinion or intuition.
• Objective: Research is conducted with an objective and impartial perspective, avoiding biases and personal beliefs.
• Rigorous : Research involves a rigorous and critical examination of the evidence and data, using reliable and valid methods of data collection and analysis.
• Logical : Research is based on logical and rational thinking, following a well-defined and logical structure.
• Generalizable : Research findings are often generalized to broader populations or contexts, based on a representative sample of the population.
• Replicable : Research is conducted in a way that allows others to replicate the study and obtain similar results.
• Ethical : Research is conducted in an ethical manner, following established ethical guidelines and principles, to ensure the protection of participants’ rights and well-being.
• Cumulative : Research builds on previous studies and contributes to the overall body of knowledge in a particular field.

Advantages of Research

Research has several advantages, including:

• Generates new knowledge: Research is conducted to generate new knowledge and understanding of a particular topic or phenomenon, which can be used to inform policy, practice, and decision-making.
• Provides evidence-based solutions : Research provides evidence-based solutions to problems and issues, which can be used to develop effective interventions and strategies.
• Improves quality : Research can improve the quality of products, services, and programs by identifying areas for improvement and developing solutions to address them.
• Enhances credibility : Research enhances the credibility of an organization or individual by providing evidence to support claims and assertions.
• Enables innovation: Research can lead to innovation by identifying new ideas, approaches, and technologies.
• Informs decision-making : Research provides information that can inform decision-making, helping individuals and organizations make more informed and effective choices.
• Facilitates progress: Research can facilitate progress by identifying challenges and opportunities and developing solutions to address them.
• Enhances understanding: Research can enhance understanding of complex issues and phenomena, helping individuals and organizations navigate challenges and opportunities more effectively.
• Promotes accountability : Research promotes accountability by providing a basis for evaluating the effectiveness of policies, programs, and interventions.
• Fosters collaboration: Research can foster collaboration by bringing together individuals and organizations with diverse perspectives and expertise to address complex issues and problems.

Limitations of Research

Some Limitations of Research are as follows:

• Cost : Research can be expensive, particularly when large-scale studies are required. This can limit the number of studies that can be conducted and the amount of data that can be collected.
• Time : Research can be time-consuming, particularly when longitudinal studies are required. This can limit the speed at which research findings can be generated and disseminated.
• Sample size: The size of the sample used in research can limit the generalizability of the findings to larger populations.
• Bias : Research can be affected by bias, both in the design and implementation of the study, as well as in the analysis and interpretation of the data.
• Ethics : Research can present ethical challenges, particularly when human or animal subjects are involved. This can limit the types of research that can be conducted and the methods that can be used.
• Data quality: The quality of the data collected in research can be affected by a range of factors, including the reliability and validity of the measures used, as well as the accuracy of the data entry and analysis.
• Subjectivity : Research can be subjective, particularly when qualitative methods are used. This can limit the objectivity and reliability of the findings.
• Accessibility : Research findings may not be accessible to all stakeholders, particularly those who are not part of the academic or research community.
• Interpretation : Research findings can be open to interpretation, particularly when the data is complex or contradictory. This can limit the ability of researchers to draw firm conclusions.
• Unforeseen events : Unexpected events, such as changes in the environment or the emergence of new technologies, can limit the relevance and applicability of research findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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

What Is Research, and Why Do People Do It?

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

14k Accesses

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

Abstractspiepr Abs1

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

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Part I. What Is Research?

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

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

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

Exercise 1.1

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

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

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

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

Exercise 1.2

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

Creating an Image of Scientific Inquiry

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

Descriptor 1. Experience Carefully Planned in Advance

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

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

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

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

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

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

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

Exercise 1.3

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

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

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

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

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

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

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

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

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

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

Doing Scientific Inquiry

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

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

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

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

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

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

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

Exercise 1.4

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

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

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

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

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

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

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

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

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

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

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

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

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

Exercise 1.5

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

Exercise 1.6

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

Learning from Doing Scientific Inquiry

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

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

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

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

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

Part II. Why Do Educators Do Research?

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

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

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

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

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

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

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

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

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

Exercise 1.7

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

Part III. Conducting Research as a Practice of Failing Productively

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

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

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

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

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

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

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

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

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

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

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

Exercise 1.8

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

Exercise 1.9

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

Part IV. Preview of Chap. 2

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

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

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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.

Table of contents

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 .

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.

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.

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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.

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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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Meaning of research in English

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

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What is Scientific Research and How Can it be Done?

Scientific researches are studies that should be systematically planned before performing them. In this review, classification and description of scientific studies, planning stage randomisation and bias are explained.

Research conducted for the purpose of contributing towards science by the systematic collection, interpretation and evaluation of data and that, too, in a planned manner is called scientific research: a researcher is the one who conducts this research. The results obtained from a small group through scientific studies are socialised, and new information is revealed with respect to diagnosis, treatment and reliability of applications. The purpose of this review is to provide information about the definition, classification and methodology of scientific research.

Before beginning the scientific research, the researcher should determine the subject, do planning and specify the methodology. In the Declaration of Helsinki, it is stated that ‘the primary purpose of medical researches on volunteers is to understand the reasons, development and effects of diseases and develop protective, diagnostic and therapeutic interventions (method, operation and therapies). Even the best proven interventions should be evaluated continuously by investigations with regard to reliability, effectiveness, efficiency, accessibility and quality’ ( 1 ).

The questions, methods of response to questions and difficulties in scientific research may vary, but the design and structure are generally the same ( 2 ).

Classification of Scientific Research

Scientific research can be classified in several ways. Classification can be made according to the data collection techniques based on causality, relationship with time and the medium through which they are applied.

• Observational
• Experimental
• Descriptive
• Retrospective
• Prospective
• Cross-sectional
• Social descriptive research ( 3 )

Another method is to classify the research according to its descriptive or analytical features. This review is written according to this classification method.

I. Descriptive research

• Case series
• Surveillance studies

II. Analytical research

• Observational studies: cohort, case control and cross- sectional research
• Interventional research: quasi-experimental and clinical research
• Case Report: it is the most common type of descriptive study. It is the examination of a single case having a different quality in the society, e.g. conducting general anaesthesia in a pregnant patient with mucopolysaccharidosis.
• Case Series: it is the description of repetitive cases having common features. For instance; case series involving interscapular pain related to neuraxial labour analgesia. Interestingly, malignant hyperthermia cases are not accepted as case series since they are rarely seen during historical development.
• Surveillance Studies: these are the results obtained from the databases that follow and record a health problem for a certain time, e.g. the surveillance of cross-infections during anaesthesia in the intensive care unit.

Moreover, some studies may be experimental. After the researcher intervenes, the researcher waits for the result, observes and obtains data. Experimental studies are, more often, in the form of clinical trials or laboratory animal trials ( 2 ).

Analytical observational research can be classified as cohort, case-control and cross-sectional studies.

Firstly, the participants are controlled with regard to the disease under investigation. Patients are excluded from the study. Healthy participants are evaluated with regard to the exposure to the effect. Then, the group (cohort) is followed-up for a sufficient period of time with respect to the occurrence of disease, and the progress of disease is studied. The risk of the healthy participants getting sick is considered an incident. In cohort studies, the risk of disease between the groups exposed and not exposed to the effect is calculated and rated. This rate is called relative risk. Relative risk indicates the strength of exposure to the effect on the disease.

Cohort research may be observational and experimental. The follow-up of patients prospectively is called a prospective cohort study . The results are obtained after the research starts. The researcher’s following-up of cohort subjects from a certain point towards the past is called a retrospective cohort study . Prospective cohort studies are more valuable than retrospective cohort studies: this is because in the former, the researcher observes and records the data. The researcher plans the study before the research and determines what data will be used. On the other hand, in retrospective studies, the research is made on recorded data: no new data can be added.

In fact, retrospective and prospective studies are not observational. They determine the relationship between the date on which the researcher has begun the study and the disease development period. The most critical disadvantage of this type of research is that if the follow-up period is long, participants may leave the study at their own behest or due to physical conditions. Cohort studies that begin after exposure and before disease development are called ambidirectional studies . Public healthcare studies generally fall within this group, e.g. lung cancer development in smokers.

• Case-Control Studies: these studies are retrospective cohort studies. They examine the cause and effect relationship from the effect to the cause. The detection or determination of data depends on the information recorded in the past. The researcher has no control over the data ( 2 ).

Cross-sectional studies are advantageous since they can be concluded relatively quickly. It may be difficult to obtain a reliable result from such studies for rare diseases ( 2 ).

Cross-sectional studies are characterised by timing. In such studies, the exposure and result are simultaneously evaluated. While cross-sectional studies are restrictedly used in studies involving anaesthesia (since the process of exposure is limited), they can be used in studies conducted in intensive care units.

• Quasi-Experimental Research: they are conducted in cases in which a quick result is requested and the participants or research areas cannot be randomised, e.g. giving hand-wash training and comparing the frequency of nosocomial infections before and after hand wash.
• Clinical Research: they are prospective studies carried out with a control group for the purpose of comparing the effect and value of an intervention in a clinical case. Clinical study and research have the same meaning. Drugs, invasive interventions, medical devices and operations, diets, physical therapy and diagnostic tools are relevant in this context ( 6 ).

Clinical studies are conducted by a responsible researcher, generally a physician. In the research team, there may be other healthcare staff besides physicians. Clinical studies may be financed by healthcare institutes, drug companies, academic medical centres, volunteer groups, physicians, healthcare service providers and other individuals. They may be conducted in several places including hospitals, universities, physicians’ offices and community clinics based on the researcher’s requirements. The participants are made aware of the duration of the study before their inclusion. Clinical studies should include the evaluation of recommendations (drug, device and surgical) for the treatment of a disease, syndrome or a comparison of one or more applications; finding different ways for recognition of a disease or case and prevention of their recurrence ( 7 ).

Clinical Research

In this review, clinical research is explained in more detail since it is the most valuable study in scientific research.

Clinical research starts with forming a hypothesis. A hypothesis can be defined as a claim put forward about the value of a population parameter based on sampling. There are two types of hypotheses in statistics.

• H 0 hypothesis is called a control or null hypothesis. It is the hypothesis put forward in research, which implies that there is no difference between the groups under consideration. If this hypothesis is rejected at the end of the study, it indicates that a difference exists between the two treatments under consideration.
• H 1 hypothesis is called an alternative hypothesis. It is hypothesised against a null hypothesis, which implies that a difference exists between the groups under consideration. For example, consider the following hypothesis: drug A has an analgesic effect. Control or null hypothesis (H 0 ): there is no difference between drug A and placebo with regard to the analgesic effect. The alternative hypothesis (H 1 ) is applicable if a difference exists between drug A and placebo with regard to the analgesic effect.

The planning phase comes after the determination of a hypothesis. A clinical research plan is called a protocol . In a protocol, the reasons for research, number and qualities of participants, tests to be applied, study duration and what information to be gathered from the participants should be found and conformity criteria should be developed.

The selection of participant groups to be included in the study is important. Inclusion and exclusion criteria of the study for the participants should be determined. Inclusion criteria should be defined in the form of demographic characteristics (age, gender, etc.) of the participant group and the exclusion criteria as the diseases that may influence the study, age ranges, cases involving pregnancy and lactation, continuously used drugs and participants’ cooperation.

The next stage is methodology. Methodology can be grouped under subheadings, namely, the calculation of number of subjects, blinding (masking), randomisation, selection of operation to be applied, use of placebo and criteria for stopping and changing the treatment.

I. Calculation of the Number of Subjects

The entire source from which the data are obtained is called a universe or population . A small group selected from a certain universe based on certain rules and which is accepted to highly represent the universe from which it is selected is called a sample and the characteristics of the population from which the data are collected are called variables. If data is collected from the entire population, such an instance is called a parameter . Conducting a study on the sample rather than the entire population is easier and less costly. Many factors influence the determination of the sample size. Firstly, the type of variable should be determined. Variables are classified as categorical (qualitative, non-numerical) or numerical (quantitative). Individuals in categorical variables are classified according to their characteristics. Categorical variables are indicated as nominal and ordinal (ordered). In nominal variables, the application of a category depends on the researcher’s preference. For instance, a female participant can be considered first and then the male participant, or vice versa. An ordinal (ordered) variable is ordered from small to large or vice versa (e.g. ordering obese patients based on their weights-from the lightest to the heaviest or vice versa). A categorical variable may have more than one characteristic: such variables are called binary or dichotomous (e.g. a participant may be both female and obese).

If the variable has numerical (quantitative) characteristics and these characteristics cannot be categorised, then it is called a numerical variable. Numerical variables are either discrete or continuous. For example, the number of operations with spinal anaesthesia represents a discrete variable. The haemoglobin value or height represents a continuous variable.

Statistical analyses that need to be employed depend on the type of variable. The determination of variables is necessary for selecting the statistical method as well as software in SPSS. While categorical variables are presented as numbers and percentages, numerical variables are represented using measures such as mean and standard deviation. It may be necessary to use mean in categorising some cases such as the following: even though the variable is categorical (qualitative, non-numerical) when Visual Analogue Scale (VAS) is used (since a numerical value is obtained), it is classified as a numerical variable: such variables are averaged.

Clinical research is carried out on the sample and generalised to the population. Accordingly, the number of samples should be correctly determined. Different sample size formulas are used on the basis of the statistical method to be used. When the sample size increases, error probability decreases. The sample size is calculated based on the primary hypothesis. The determination of a sample size before beginning the research specifies the power of the study. Power analysis enables the acquisition of realistic results in the research, and it is used for comparing two or more clinical research methods.

Because of the difference in the formulas used in calculating power analysis and number of samples for clinical research, it facilitates the use of computer programs for making calculations.

It is necessary to know certain parameters in order to calculate the number of samples by power analysis.

• Type-I (α) and type-II (β) error levels
• Difference between groups (d-difference) and effect size (ES)
• Distribution ratio of groups
• Direction of research hypothesis (H1)

a. Type-I (α) and Type-II (β) Error (β) Levels

Two types of errors can be made while accepting or rejecting H 0 hypothesis in a hypothesis test. Type-I error (α) level is the probability of finding a difference at the end of the research when there is no difference between the two applications. In other words, it is the rejection of the hypothesis when H 0 is actually correct and it is known as α error or p value. For instance, when the size is determined, type-I error level is accepted as 0.05 or 0.01.

Another error that can be made during a hypothesis test is a type-II error. It is the acceptance of a wrongly hypothesised H 0 hypothesis. In fact, it is the probability of failing to find a difference when there is a difference between the two applications. The power of a test is the ability of that test to find a difference that actually exists. Therefore, it is related to the type-II error level.

Since the type-II error risk is expressed as β, the power of the test is defined as 1–β. When a type-II error is 0.20, the power of the test is 0.80. Type-I (α) and type-II (β) errors can be intentional. The reason to intentionally make such an error is the necessity to look at the events from the opposite perspective.

b. Difference between Groups and ES

ES is defined as the state in which statistical difference also has clinically significance: ES≥0.5 is desirable. The difference between groups is the absolute difference between the groups compared in clinical research.

c. Allocation Ratio of Groups

The allocation ratio of groups is effective in determining the number of samples. If the number of samples is desired to be determined at the lowest level, the rate should be kept as 1/1.

d. Direction of Hypothesis (H1)

The direction of hypothesis in clinical research may be one-sided or two-sided. While one-sided hypotheses hypothesis test differences in the direction of size, two-sided hypotheses hypothesis test differences without direction. The power of the test in two-sided hypotheses is lower than one-sided hypotheses.

After these four variables are determined, they are entered in the appropriate computer program and the number of samples is calculated. Statistical packaged software programs such as Statistica, NCSS and G-Power may be used for power analysis and calculating the number of samples. When the samples size is calculated, if there is a decrease in α, difference between groups, ES and number of samples, then the standard deviation increases and power decreases. The power in two-sided hypothesis is lower. It is ethically appropriate to consider the determination of sample size, particularly in animal experiments, at the beginning of the study. The phase of the study is also important in the determination of number of subjects to be included in drug studies. Usually, phase-I studies are used to determine the safety profile of a drug or product, and they are generally conducted on a few healthy volunteers. If no unacceptable toxicity is detected during phase-I studies, phase-II studies may be carried out. Phase-II studies are proof-of-concept studies conducted on a larger number (100–500) of volunteer patients. When the effectiveness of the drug or product is evident in phase-II studies, phase-III studies can be initiated. These are randomised, double-blinded, placebo or standard treatment-controlled studies. Volunteer patients are periodically followed-up with respect to the effectiveness and side effects of the drug. It can generally last 1–4 years and is valuable during licensing and releasing the drug to the general market. Then, phase-IV studies begin in which long-term safety is investigated (indication, dose, mode of application, safety, effectiveness, etc.) on thousands of volunteer patients.

II. Blinding (Masking) and Randomisation Methods

When the methodology of clinical research is prepared, precautions should be taken to prevent taking sides. For this reason, techniques such as randomisation and blinding (masking) are used. Comparative studies are the most ideal ones in clinical research.

Blinding Method

A case in which the treatments applied to participants of clinical research should be kept unknown is called the blinding method . If the participant does not know what it receives, it is called a single-blind study; if even the researcher does not know, it is called a double-blind study. When there is a probability of knowing which drug is given in the order of application, when uninformed staff administers the drug, it is called in-house blinding. In case the study drug is known in its pharmaceutical form, a double-dummy blinding test is conducted. Intravenous drug is given to one group and a placebo tablet is given to the comparison group; then, the placebo tablet is given to the group that received the intravenous drug and intravenous drug in addition to placebo tablet is given to the comparison group. In this manner, each group receives both the intravenous and tablet forms of the drug. In case a third party interested in the study is involved and it also does not know about the drug (along with the statistician), it is called third-party blinding.

Randomisation Method

The selection of patients for the study groups should be random. Randomisation methods are used for such selection, which prevent conscious or unconscious manipulations in the selection of patients ( 8 ).

No factor pertaining to the patient should provide preference of one treatment to the other during randomisation. This characteristic is the most important difference separating randomised clinical studies from prospective and synchronous studies with experimental groups. Randomisation strengthens the study design and enables the determination of reliable scientific knowledge ( 2 ).

The easiest method is simple randomisation, e.g. determination of the type of anaesthesia to be administered to a patient by tossing a coin. In this method, when the number of samples is kept high, a balanced distribution is created. When the number of samples is low, there will be an imbalance between the groups. In this case, stratification and blocking have to be added to randomisation. Stratification is the classification of patients one or more times according to prognostic features determined by the researcher and blocking is the selection of a certain number of patients for each stratification process. The number of stratification processes should be determined at the beginning of the study.

As the number of stratification processes increases, performing the study and balancing the groups become difficult. For this reason, stratification characteristics and limitations should be effectively determined at the beginning of the study. It is not mandatory for the stratifications to have equal intervals. Despite all the precautions, an imbalance might occur between the groups before beginning the research. In such circumstances, post-stratification or restandardisation may be conducted according to the prognostic factors.

The main characteristic of applying blinding (masking) and randomisation is the prevention of bias. Therefore, it is worthwhile to comprehensively examine bias at this stage.

Bias and Chicanery

While conducting clinical research, errors can be introduced voluntarily or involuntarily at a number of stages, such as design, population selection, calculating the number of samples, non-compliance with study protocol, data entry and selection of statistical method. Bias is taking sides of individuals in line with their own decisions, views and ideological preferences ( 9 ). In order for an error to lead to bias, it has to be a systematic error. Systematic errors in controlled studies generally cause the results of one group to move in a different direction as compared to the other. It has to be understood that scientific research is generally prone to errors. However, random errors (or, in other words, ‘the luck factor’-in which bias is unintended-do not lead to bias ( 10 ).

Another issue, which is different from bias, is chicanery. It is defined as voluntarily changing the interventions, results and data of patients in an unethical manner or copying data from other studies. Comparatively, bias may not be done consciously.

In case unexpected results or outliers are found while the study is analysed, if possible, such data should be re-included into the study since the complete exclusion of data from a study endangers its reliability. In such a case, evaluation needs to be made with and without outliers. It is insignificant if no difference is found. However, if there is a difference, the results with outliers are re-evaluated. If there is no error, then the outlier is included in the study (as the outlier may be a result). It should be noted that re-evaluation of data in anaesthesiology is not possible.

Statistical evaluation methods should be determined at the design stage so as not to encounter unexpected results in clinical research. The data should be evaluated before the end of the study and without entering into details in research that are time-consuming and involve several samples. This is called an interim analysis . The date of interim analysis should be determined at the beginning of the study. The purpose of making interim analysis is to prevent unnecessary cost and effort since it may be necessary to conclude the research after the interim analysis, e.g. studies in which there is no possibility to validate the hypothesis at the end or the occurrence of different side effects of the drug to be used. The accuracy of the hypothesis and number of samples are compared. Statistical significance levels in interim analysis are very important. If the data level is significant, the hypothesis is validated even if the result turns out to be insignificant after the date of the analysis.

Another important point to be considered is the necessity to conclude the participants’ treatment within the period specified in the study protocol. When the result of the study is achieved earlier and unexpected situations develop, the treatment is concluded earlier. Moreover, the participant may quit the study at its own behest, may die or unpredictable situations (e.g. pregnancy) may develop. The participant can also quit the study whenever it wants, even if the study has not ended ( 7 ).

In case the results of a study are contrary to already known or expected results, the expected quality level of the study suggesting the contradiction may be higher than the studies supporting what is known in that subject. This type of bias is called confirmation bias. The presence of well-known mechanisms and logical inference from them may create problems in the evaluation of data. This is called plausibility bias.

Another type of bias is expectation bias. If a result different from the known results has been achieved and it is against the editor’s will, it can be challenged. Bias may be introduced during the publication of studies, such as publishing only positive results, selection of study results in a way to support a view or prevention of their publication. Some editors may only publish research that extols only the positive results or results that they desire.

Bias may be introduced for advertisement or economic reasons. Economic pressure may be applied on the editor, particularly in the cases of studies involving drugs and new medical devices. This is called commercial bias.

In recent years, before beginning a study, it has been recommended to record it on the Web site www.clinicaltrials.gov for the purpose of facilitating systematic interpretation and analysis in scientific research, informing other researchers, preventing bias, provision of writing in a standard format, enhancing contribution of research results to the general literature and enabling early intervention of an institution for support. This Web site is a service of the US National Institutes of Health.

The last stage in the methodology of clinical studies is the selection of intervention to be conducted. Placebo use assumes an important place in interventions. In Latin, placebo means ‘I will be fine’. In medical literature, it refers to substances that are not curative, do not have active ingredients and have various pharmaceutical forms. Although placebos do not have active drug characteristic, they have shown effective analgesic characteristics, particularly in algology applications; further, its use prevents bias in comparative studies. If a placebo has a positive impact on a participant, it is called the placebo effect ; on the contrary, if it has a negative impact, it is called the nocebo effect . Another type of therapy that can be used in clinical research is sham application. Although a researcher does not cure the patient, the researcher may compare those who receive therapy and undergo sham. It has been seen that sham therapies also exhibit a placebo effect. In particular, sham therapies are used in acupuncture applications ( 11 ). While placebo is a substance, sham is a type of clinical application.

Ethically, the patient has to receive appropriate therapy. For this reason, if its use prevents effective treatment, it causes great problem with regard to patient health and legalities.

Before medical research is conducted with human subjects, predictable risks, drawbacks and benefits must be evaluated for individuals or groups participating in the study. Precautions must be taken for reducing the risk to a minimum level. The risks during the study should be followed, evaluated and recorded by the researcher ( 1 ).

After the methodology for a clinical study is determined, dealing with the ‘Ethics Committee’ forms the next stage. The purpose of the ethics committee is to protect the rights, safety and well-being of volunteers taking part in the clinical research, considering the scientific method and concerns of society. The ethics committee examines the studies presented in time, comprehensively and independently, with regard to ethics and science; in line with the Declaration of Helsinki and following national and international standards concerning ‘Good Clinical Practice’. The method to be followed in the formation of the ethics committee should be developed without any kind of prejudice and to examine the applications with regard to ethics and science within the framework of the ethics committee, Regulation on Clinical Trials and Good Clinical Practice ( www.iku.com ). The necessary documents to be presented to the ethics committee are research protocol, volunteer consent form, budget contract, Declaration of Helsinki, curriculum vitae of researchers, similar or explanatory literature samples, supporting institution approval certificate and patient follow-up form.

Only one sister/brother, mother, father, son/daughter and wife/husband can take charge in the same ethics committee. A rector, vice rector, dean, deputy dean, provincial healthcare director and chief physician cannot be members of the ethics committee.

Members of the ethics committee can work as researchers or coordinators in clinical research. However, during research meetings in which members of the ethics committee are researchers or coordinators, they must leave the session and they cannot sign-off on decisions. If the number of members in the ethics committee for a particular research is so high that it is impossible to take a decision, the clinical research is presented to another ethics committee in the same province. If there is no ethics committee in the same province, an ethics committee in the closest settlement is found.

Thereafter, researchers need to inform the participants using an informed consent form. This form should explain the content of clinical study, potential benefits of the study, alternatives and risks (if any). It should be easy, comprehensible, conforming to spelling rules and written in plain language understandable by the participant.

This form assists the participants in taking a decision regarding participation in the study. It should aim to protect the participants. The participant should be included in the study only after it signs the informed consent form; the participant can quit the study whenever required, even when the study has not ended ( 7 ).

Peer-review: Externally peer-reviewed.

Author Contributions: Concept - C.Ö.Ç., A.D.; Design - C.Ö.Ç.; Supervision - A.D.; Resource - C.Ö.Ç., A.D.; Materials - C.Ö.Ç., A.D.; Analysis and/or Interpretation - C.Ö.Ç., A.D.; Literature Search - C.Ö.Ç.; Writing Manuscript - C.Ö.Ç.; Critical Review - A.D.; Other - C.Ö.Ç., A.D.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study has received no financial support.

Research: Definition, Characteristics, Goals, Approaches

Research is an original and systematic investigation undertaken to increase existing knowledge and understanding of the unknown to establish facts and principles.

Let’s understand research:

What is Research?

Research is a voyage of discovery of new knowledge. It comprises creating ideas and generating new knowledge that leads to new and improved insights and the development of new materials, devices, products, and processes.

It should have the potential to produce sufficiently relevant results to increase and synthesize existing knowledge or correct and integrate previous knowledge.

Good reflective research produces theories and hypotheses and benefits any intellectual attempt to analyze facts and phenomena.

Where did the word Research Come from?

The word ‘research’ perhaps originates from the old French word “recerchier” which meant to ‘ search again.’ It implicitly assumes that the earlier search was not exhaustive and complete; hence, a repeated search is called for.

In practice, ‘research’ refers to a scientific process of generating an unexplored horizon of knowledge, aiming at discovering or establishing facts, solving a problem, and reaching a decision. Keeping the above points in view, we arrive at the following definition of research:

Research Definition

Research is a scientific approach to answering a research question , solving a research problem, or generating new knowledge through a systematic and orderly collection, organization, and analysis of data to make research findings useful in decision-making.

When do we call research scientific? Any research endeavor is said to be scientific if

• It is based on empirical and measurable evidence subject to specific principles of reasoning;
• It consists of systematic observations, measurement, and experimentation;
• It relies on the application of scientific methods and harnessing of curiosity;
• It provides scientific information and theories for the explanation of nature;
• It makes practical applications possible, and
• It ensures adequate analysis of data employing rigorous statistical techniques.

The chief characteristic that distinguishes the scientific method from other methods of acquiring knowledge is that scientists seek to let reality speak for itself, supporting a theory when a theory’s predictions are confirmed and challenging a theory when its predictions prove false.

Scientific research has multidimensional functions, characteristics, and objectives.

Keeping these issues in view, we assert that research in any field or discipline:

• Attempts to solve a research problem;
• Involves gathering new data from primary or first-hand sources or using existing data for a new purpose;
• is based upon observable experiences or empirical evidence;
• Demands accurate observation and description;
• Employs carefully designed procedures and rigorous analysis;
• attempts to find an objective, unbiased solution to the problem and takes great pains to validate the methods employed;
• is a deliberate and unhurried activity that is directional but often refines the problem or questions as the research progresses.

Characteristics of Research

Keeping this in mind that research in any field of inquiry is undertaken to provide information to support decision-making in its respective area, we summarize some desirable characteristics of research:

• The research should focus on priority problems.
• The research should be systematic. It emphasizes that a researcher should employ a structured procedure.
• The research should be logical. Without manipulating ideas logically, the scientific researcher cannot make much progress in any investigation.
• The research should be reductive. This means that one researcher’s findings should be made available to other researchers to prevent them from repeating the same research.
• The research should be replicable. This asserts that there should be scope to confirm previous research findings in a new environment and different settings with a new group of subjects or at a different point in time.
• The research should be generative. This is one of the valuable characteristics of research because answering one question leads to generating many other new questions.
• The research should be action-oriented. In other words, it should be aimed at solving to implement its findings.
• The research should follow an integrated multidisciplinary approach, i.e., research approaches from more than one discipline are needed.
• The research should be participatory, involving all parties concerned (from policymakers down to community members) at all stages of the study.
• The research must be relatively simple, timely, and time-bound, employing a comparatively simple design.
• The research must be as much cost-effective as possible.
• The research results should be presented in formats most useful for administrators, decision-makers, business managers, or community members.

3 Basic Operations of Research

Scientific research in any field of inquiry involves three basic operations:

• Data collection;
• Data analysis;
• Report writing .

• Data collection refers to observing, measuring, and recording data or information.
• Data analysis, on the other hand, refers to arranging and organizing the collected data so that we may be able to find out what their significance is and generalize about them.
• Report writing is the ultimate step of the study . Its purpose is to convey the information contained in it to the readers or audience .

If you note down, for example, the reading habit of newspapers of a group of residents in a community, that would be your data collection.

If you then divide these residents into three categories, ‘regular,’ ‘occasional,’ and ‘never,’ you have performed a simple data analysis. Your findings may now be presented in a report form.

A reader of your report knows what percentage of the community people never read any newspaper and so on.

Here are some examples that demonstrate what research is:

• A farmer is planting two varieties of jute side by side to compare yields;
• A sociologist examines the causes and consequences of divorce;
• An economist is looking at the interdependence of inflation and foreign direct investment;
• A physician is experimenting with the effects of multiple uses of disposable insulin syringes in a hospital;
• A business enterprise is examining the effects of advertisement of their products on the volume of sales;
• An economist is doing a cost-benefit analysis of reducing the sales tax on essential commodities;
• The Bangladesh Bank is closely observing and monitoring the performance of nationalized and private banks;
• Based on some prior information, Bank Management plans to open new counters for female customers.
• Supermarket Management is assessing the satisfaction level of the customers with their products.

The above examples are all researching whether the instrument is an electronic microscope, hospital records, a microcomputer, a questionnaire , or a checklist.

Research Motivation – What makes one motivated to do research?

A person may be motivated to undertake research activities because

• He might have genuine interest and curiosity in the existing body of knowledge and understanding of the problem;
• He is looking for answers to questions that have remained unanswered so far and trying to unfold the truth;
• The existing tools and techniques are accessible to him, and others may need modification and change to suit the current needs.

One might research ensuring.

• Better livelihood;
• Better career development;
• Higher position, prestige, and dignity in society;
• Academic achievement leading to higher degrees;
• Self-gratification.

At the individual level, the results of the research are used by many:

• A villager is drinking water from an arsenic-free tube well;
• A rural woman is giving more green vegetables to her child than before;
• A cigarette smoker is actively considering quitting smoking;
• An old man is jogging for cardiovascular fitness;
• A sociologist is using newly suggested tools and techniques in poverty measurement.

The above activities are all outcomes of the research.

All involved in the above processes will benefit from the research results. There is hardly any action in everyday life that does not depend upon previous research.

Research in any field of inquiry provides us with the knowledge and skills to solve problems and meet the challenges of a fast-paced decision-making environment.

9 Qualities of Research

Good research generates dependable data. It is conducted by professionals and can be used reliably for decision-making. It is thus of crucial importance that research should be made acceptable to the audience for which research should possess some desirable qualities in terms of.

9 qualities of research are;

Purpose clearly defined

Research process detailed, research design planner, ethical issues considered, limitations revealed, adequate analysis ensured, findings unambiguously presented, conclusions and recommendations justified..

We enumerate below a few qualities that good research should possess.

Good research must have its purposes clearly and unambiguously defined.

The problem involved or the decision to be made should be sharply delineated as clearly as possible to demonstrate the credibility of the research.

The research procedures should be described in sufficient detail to permit other researchers to repeat the research later.

Failure to do so makes it difficult or impossible to estimate the validity and reliability of the results. This weakens the confidence of the readers.

Any recommendations from such research justifiably get little attention from the policymakers and implementation.

The procedural design of the research should be carefully planned to yield results that are as objective as possible.

In doing so, care must be taken so that the sample’s representativeness is ensured, relevant literature has been thoroughly searched, experimental controls, whenever necessary, have been followed, and the personal bias in selecting and recording data has been minimized.

A research design should always safeguard against causing mental and physical harm not only to the participants but also those who belong to their organizations.

Careful consideration must also be given to research situations when there is a possibility for exploitation, invasion of privacy, and loss of dignity of all those involved in the study.

The researcher should report with complete honesty and frankness any flaws in procedural design; he followed and provided estimates of their effects on the findings.

This enhances the readers’ confidence and makes the report acceptable to the audience. One can legitimately question the value of research where no limitations are reported.

Adequate analysis reveals the significance of the data and helps the researcher to check the reliability and validity of his estimates.

Data should, therefore, be analyzed with proper statistical rigor to assist the researcher in reaching firm conclusions.

When statistical methods have been employed, the probability of error should be estimated, and criteria of statistical significance applied.

The presentation of the results should be comprehensive, easily understood by the readers, and organized so that the readers can readily locate the critical and central findings.

Proper research always specifies the conditions under which the research conclusions seem valid.

Therefore, it is important that any conclusions drawn and recommendations made should be solely based on the findings of the study.

No inferences or generalizations should be made beyond the data. If this were not followed, the objectivity of the research would tend to decrease, resulting in confidence in the findings.

The researcher’s experiences were reflected.

The research report should contain information about the qualifications of the researchers .

If the researcher is experienced, has a good reputation in research, and is a person of integrity, his report is likely to be highly valued. The policymakers feel confident in implementing the recommendations made in such reports.

4 Goals of Research

The primary goal or purpose of research in any field of inquiry; is to add to what is known about the phenomenon under investigation by applying scientific methods. Though each research has its own specific goals, we may enumerate the following 4 broad goals of scientific research:

Exploration and Explorative Research

Description and descriptive research, causal explanation and causal research, prediction and predictive research.

The link between the 4 goals of research and the questions raised in reaching these goals.

Let’s try to understand the 4 goals of the research.

Exploration is finding out about some previously unexamined phenomenon. In other words, an explorative study structures and identifies new problems.

The explorative study aims to gain familiarity with a phenomenon or gain new insights into it.

Exploration is particularly useful when researchers lack a clear idea of the problems they meet during their study.

Through exploration, researchers attempt to

• Develop concepts more clearly;
• Establish priorities among several alternatives;
• Develop operational definitions of variables;
• Formulate research hypotheses and sharpen research objectives;
• Improve the methodology and modify (if needed) the research design .

Exploration is achieved through what we call exploratory research.

The end of an explorative study comes when the researchers are convinced that they have established the major dimensions of the research task.

Many research activities consist of gathering information on some topic of interest. The description refers to these data-based information-gathering activities. Descriptive studies portray precisely the characteristics of a particular individual, situation, or group.

Here, we attempt to describe situations and events through studies, which we refer to as descriptive research.

Such research is undertaken when much is known about the problem under investigation.

Descriptive studies try to discover answers to the questions of who, what, when, where, and sometimes how.

Such research studies may involve the collection of data and the creation of distribution of the number of times the researcher observes a single event or characteristic, known as a research variable.

A descriptive study may also involve the interaction of two or more variables and attempts to observe if there is any relationship between the variables under investigation .

Research that examines such a relationship is sometimes called a correlational study. It is correlational because it attempts to relate (i.e., co-relate) two or more variables.

A descriptive study may be feasible to answer the questions of the following types:

• What are the characteristics of the people who are involved in city crime ? Are they young? Middle-aged? Poor? Muslim? Educated?
• Who are the potential buyers of the new product? Men or women? Urban people or rural people?
• Are rural women more likely to marry earlier than their urban counterparts?
• Does previous experience help an employee to get a higher initial salary?

Although the data description in descriptive research is factual, accurate, and systematic, the research cannot describe what caused a situation.

Thus, descriptive research cannot be used to create a causal relationship where one variable affects another.

In other words, descriptive research can be said to have a low requirement for internal validity . In sum, descriptive research deals with everything that can be counted and studied.

But there are always restrictions on that. All research must impact the lives of the people around us.

For example, finding the most frequent disease that affects the people of a community falls under descriptive research.

But the research readers will have the hunch to know why this has happened and what to do to prevent that disease so that more people will live healthy lives.

It dictates that we need a causal explanation of the situation under reference and a causal study vis-a-vis causal research .

Explanation reveals why and how something happens.

An explanatory study goes beyond description and attempts to establish a cause-and-effect relationship between variables. It explains the reason for the phenomenon that the descriptive study observed.

Thus, if a researcher finds that communities with larger family sizes have higher child deaths or that smoking correlates with lung cancer, he is performing a descriptive study.

If he explains why it is so and tries to establish a cause-and-effect relationship, he is performing explanatory or causal research . The researcher uses theories or at-least hypotheses to account for the factors that caused a certain phenomenon.

Look at the following examples that fit causal studies:

• Why are people involved in crime? Can we explain this as a consequence of the present job market crisis or lack of parental care?
• Will the buyers be motivated to purchase the new product in a new container ? Can an attractive advertisement motivate them to buy a new product?
• Why has the share market shown the steepest-ever fall in stock prices? Is it because of the IMF’s warnings and prescriptions on the commercial banks’ exposure to the stock market or because of an abundant increase in the supply of new shares?

Prediction seeks to answer when and in what situations will occur if we can provide a plausible explanation for the event in question.

However, the precise nature of the relationship between explanation and prediction has been a subject of debate.

One view is that explanation and prediction are the same phenomena, except that prediction precedes the event while the explanation takes place after the event has occurred.

Another view is that explanation and prediction are fundamentally different processes.

We need not be concerned with this debate here but can simply state that in addition to being able to explain an event after it has occurred, we would also be able to predict when it will occur.

Research Approaches

There are two main approaches to doing research.

The first is the basic approach, which mostly pertains to academic research. Many people view this as pure research or fundamental research.

The research implemented through the second approach is variously known as applied research, action research, operations research, or contract research.

Also, the third category of research, evaluative research, is important in many applications. All these approaches have different purposes influencing the nature of the respective research.

Lastly, precautions in research are required for thorough research.

So, 4 research approaches are;

• Basic Research .
• Applied Research .
• Evaluative Research .
• Precautions in Research.

Areas of Research

The most important fields or areas of research, among others, are;

• Social Research .
• Health Research .
• Population Research .
• Business Research .
• Marketing Research .
• Agricultural Research .
• Biomedical Research.
• Clinical Research .
• Outcomes Research.
• Internet Research.
• Archival Research.
• Empirical Research.
• Legal Research .
• Education Research .
• Engineering Research .
• Historical Research.

Check out our article describing all 16 areas of research .

Precautions in Research

Whether a researcher is doing applied or basic research or research of any other form, he or she must take necessary precautions to ensure that the research he or she is doing is relevant, timely, efficient, accurate, and ethical .

The research is considered relevant if it anticipates the kinds of information that decision-makers, scientists, or policymakers will require.

Timely research is completed in time to influence decisions.

• Research is efficient when it is of the best quality for the minimum expenditure and the study is appropriate to the research context.
• Research is considered accurate or valid when the interpretation can account for both consistencies and inconsistencies in the data.
• Research is ethical when it can promote trust, exercise care, ensure standards, and protect the rights of the participants in the research process.

After discussing the research definition and knowing the characteristics, goals, and approaches, it’s time to delve into the research fundamentals. For a comprehensive understanding, refer to our detailed research and methodology concepts guide .

Research should be relevant, timely, efficient, accurate, and ethical. It should anticipate the information required by decision-makers, be completed in time to influence decisions, be of the best quality for the minimum expenditure, and protect the rights of participants in the research process.

The two main approaches to research are the basic approach, often viewed as pure or fundamental research, and the applied approach, which includes action research, operations research, and contract research.

Having touched upon research, take next steps with our comprehensive resources on research and research methodology concepts .

• Hypothesis Testing: Definition, Examples
• Computer-Assisted Personal Interviewing (CAPI)
• Stapel Scale: Definition, Example
• Health Research: Definition, Examples
• Research Hypothesis: Elements, Format, Types
• Standard Error of Measurement
• Business Research: Definition, Examples
• Simple Category Scale: Definition, Example
• How to Write an Evaluation Report
• How to Select an Appropriate Evaluator
• Variables: Definition, Examples, Types of Variables in Research
• Content Analysis Method in Research
• Research Objectives: Meaning, Types
• Research Proposal: Components, Structure, Sample, Example
• Data Analysis and Interpretation

What is Research?

Research is a process of systematic inquiry that entails collection of data; documentation of critical information; and analysis and interpretation of that data/information, in accordance with suitable methodologies set by specific professional fields and academic disciplines.

Research is conducted to...

• Evaluate the validity of a hypothesis or an interpretive framework.
• To assemble a body of substantive knowledge and findings for sharing them in appropriate manners.
• To help generate questions for further inquiries.

If you would like further examples of specific ways different schools at Hampshire think about research, see: School Definitions of Research » What is "research" that needs to be reviewed and approved by the Institutional Review Board at Hampshire before proceeding?  Research should be reviewed by the IRB only when human subjects are involved, and the term research should be considered under a more narrow definition. Specifically, when the researcher is conducting research as outlined above AND has direct interaction with participants or data linked to personal identifiers , it should always fall under the purview of the IRB. Even if you have not directly collected the data yourself, as the researcher, your research may fall under the purview of the IRB. In reviewing such research, the IRB is concerned with the methodology of data collection in the "field" (e.g. collection, experimentation, interview, participant observation, etc.) and the use of the data.  The broader validity of the hypotheses or research questions, and the quality of inferences that may result (unless, of course, the research methodologies severely compromise the data collection and data usage directly), is not something they will be evaluating.

What if I am using information that is already available?

If you are doing research that is limited to secondary analysis of data, records, or specimens that are either publicly available, de-identified, or otherwise impossible to be linked to personal identities, you may still need IRB approval to do your project. Sometimes a data use agreement between the researcher and the data custodian may still be required to verify that the researcher will not have access to identifying codes.  This "de-linking" of data from personal identifiers  allows the IRB to make this determination. Regardless, you should submit an IRB proposal so the IRB can determine whether your project needs IRB review, and if so, the type of review required. For specifics of what research should be reviewed by the IRB and the category of review required, see the flow chart and examples provided .

Table of Contents

Collaboration, information literacy, writing process.

• © 2023 by Joseph M. Moxley - University of South Florida

Research refers to a systematic investigation carried out to discover new knowledge , expand existing knowledge , solve practical problems , and develop new products, apps, and services. This article explores why different research communities have different ideas about what research is and how to conduct it. Learn about the different epistemological assumptions that undergird  informal , qualitative , quantitative , textual , and mixed research methods .

What is Research?

Research may refer to

• For most researchers, the first step in any research project involves strategic searching to learn what the current and best research, theory, and scholarship is on a topic .
• scholars create knowledge by engaging in textual research , interpretation , and hermeneutics .
• Ethnography
• Participant Observation
• Survey Research
• “a systematic application of knowledge toward the production of useful materials, devices, and systems or methods, including design, development, and improvement of prototypes and new processes” (NSF n.d.)
• a process,  a research methodology , that follows  the principles of lean design .

Key Words: Research Community ; Research Methodology ; Research Methods ; Epistemology

Why Does Research Matter?

Overall, research is essential for advancing knowledge, solving problems, informing decision-making, fostering innovation, and promoting critical thinking. It plays a crucial role in shaping the world we live in and the future we create.

• Research allows us to better understand the world around us, from the fundamental workings of the universe to the intricacies of human behavior. By conducting research, scholars can uncover new information, develop new theories and models, and identify gaps in existing knowledge that need to be filled. This knowledge can help students and teachers to better understand the world around them and develop new solutions to the problems facing society.
• Research helps us identify and solve problems. It can help us find ways to improve our health, protect the environment, reduce poverty, and develop new technologies.
• Research provides important information that can inform policy decisions, business strategies, and individual choices. By studying trends, analyzing data, and conducting experiments, researchers can help us make better-informed decisions.
• Research often leads to new technologies, products, and services. By pushing the boundaries of what is currently possible, researchers can inspire and fuel innovation.
• Research teaches us to question assumptions, evaluate evidence, and think critically. These skills are important for students to develop because they enable them to become more informed and engaged citizens, able to make more informed decisions and contribute to society in meaningful ways.
• Research experience can be an asset in many career fields, including academia, business, government, and nonprofit organizations. By conducting research as an undergraduate student, students can develop valuable skills and experience that can help them to succeed in their future careers.

Types of Research

The choice of research methods depends on the epistemological assumptions of the researchers and the practices of a particular methodological community , the research question , the type of data needed, and the resources available.

Epistemology and Research Communities

Investigators across academic disciplines — the humanities, social sciences, sciences, and the arts — share some common methods and values. For instance, in both workplace writing and academic writing , investigators are careful

• to cite sources , particularly sources that have changed the conversation on a topic
• to provide evidence for claims (as opposed to opinion or other forms of anecdotal knowledge .

Yet it is also important to note that different research communities also develop unique approaches to exploring and solving problems in their knowledge domains. Research communities develop different ways of conducting research because they face different problems and because they may have different epistemological assumptions about what knowledge is and how to measure it. For example, if a researcher believes that knowledge can only be gained through observation and empirical evidence , they may choose to use quantitative research methods such as experiments or surveys . Conversely, if a researcher believes that knowledge can also be gained through subjective experience and interpretation , they may choose to use qualitative research methods such as case study , ethnography or participant observation

While there are many nuanced definitions of epistemology , scholars have identified three major epistemological perspectives that inform the works of three research communities

• The Scholars – aka Scholarship
• The Positivists – aka Positivism
• The Postpositivists – aka Postpositivism

Research & Mindset

Researchers are curious about the world. They embrace openness , a growth mindset , and collaboration . They undertake research projects in order to review existing knowledge and generate original knowledge claims about the topic , thesis, research question they are investigating. Research finds evidence.

Research Ethics

Researchers and consumers of research are wise to view research claims and research plans from an ethical perspective. Given human nature — such as the tendency to look for confirming evidence and ignore disconfirming evidence and to allow emotions to cloud reasoning — it’s foolhardy to disregard critical literacy practices when consuming the research of others.

Ethics are important to undergraduate students as researchers because ethics provide a framework for conducting research that is responsible, respectful, and accountable :

• Ethics ensure that participants in research are treated with respect and dignity, and that their rights and well-being are protected. As a student researcher, it is important to obtain informed consent from participants, ensure their confidentiality, and minimize any potential harm or discomfort.
• Ethics ensure that research is conducted with integrity and honesty. This means that data is collected and analyzed accurately, and that findings are reported truthfully and transparently.
• Ethics help to build trust between researchers and the public. When research is conducted ethically, participants and the wider community are more likely to trust the findings and the researchers themselves.
• Adhering to ethical standards in research can help students to develop important professional skills, such as critical thinking, problem-solving, and communication . These skills can be useful in a wide range of career fields, including academia, healthcare, and government.
• Ethical research is a professional obligation. By conducting research ethically, students are fulfilling their obligations to the wider research community.

Research as an Iterative, Recursive, Chaotic Process

Research is commonly depicted on websites and textbooks on research methods as systematic work (see, e.g., Wikipedia’s Research page).

Depicting research as systematic work is certainly valid, especially in natural and social science research. For instance, scientists in the lab working with a virus like COVID-19 or Ebola aren’t going to play around. Their professionalism and safety is tied to rigorously following research protocols.

That said, it’s an oversimplification to suggest research processes are invariably systematic. Discoveries have emerged from basic research that have been wildly popular and useful real-world applications . (See, for example, 24 Unintended Scientific Discoveries — the video below). Scientists may begin researching hypothesis A but rewrite that hypothesis multiple times until they find hypothesis Z — something that explains the data. Then they go back and repackage their investigation, following ethical standards, for a wider audience.

Ultimately, because research is such an iterative process, the thesis or hypothesis a researcher began with may not be the one the researcher ends up with. The takeaway here is that research is a learning process. Research efforts can lead to unpredictable applications and insights. Research finds evidence. Ultimately, research is about curiosity and openness. The question that initiates a research effort may morph into other questions as researchers

• dig deeper into the literature on the topic and become more conversant
• endeavor to make sense of the data/information they have gathered during the conduct of the study.

Related Concepts

Research methods.

Research results— knowledge claims -—are important. But, how researchers claim to know what they know—their research methods and research methodology —are equally important.

During the early stages of a writing project, you can identify research questions worth asking by engaging in Information Literacy practices.

Using Evidence

Learn to summarize,  paraphrase , and  cite sources . Weave others’ ideas and words into your texts in ways that support your  thesis/research question ,  information ,  rhetorical stance .

Hale, J. (2018). Understanding research methodology 5: Applied and basic research, PsychCentral . https://psychcentral.com/blog/understanding-research-methodology-5-applied-and-basic-research/

Related Articles:

Applied Research, Basic Research

Research Methodology

Scholarship

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Understand the difference between Applied Research and Basic Research.

As an investigator be sure to protect your research subjects and follow ethical standards. As a consumer of research, be mindful of when investigators may be exaggerating results, making claims...

Not all research methods are equal or produce the same kind of knowledge. Learn about the philosophies, the epistemologies, that inform qualitative, quantitative, mixed, and textual research methods.

Understand how to identify appropriate research methods for particular methodological communities, rhetorical situations, and research questions.

Scholarship is not just about memorizing facts or regurgitating information. It’s about developing a deep understanding of a subject, making connections across disciplines, and contributing to the ongoing conversation about...

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Is globalization in retreat? Here is what a new study shows

Sebastian franco bedoya.

The debate is raging: Is globalization in retreat or not? If yes, to what extent, and what are the implications for global prosperity and poverty reduction? These aren’t easy questions to answer, largely because there are different definitions of globalization, which give rise to different ways of measuring it. Recent research at the World Bank, based on a new definition, suggests that globalization is alive and well.

But first, some context. For more than 50 years, globalization has been a catalyst for economic development, trade integration, and prosperity building. It has helped lift more than 1 billion people out of poverty. Since the 1990s, it has become a pathway for businesses in emerging economies to enter global value chains and nearly double their share of exports. Breathtaking advances in communications, transportation, and information technology have made it easier and cheaper for countries on opposite sides of the world to transact business, tap into each other’s markets, and share resources, knowhow, and technology. On the other hand, some critics in advanced economies blame globalization for the loss of manufacturing jobs, and others point to it as a source of greenhouse gas emissions.

Recently, the COVID-19 pandemic, the war in Ukraine, and China-US tensions have led countries and companies to rethink global strategies. But to what extent is globalization actually retreating?  Some studies find little systematic evidence that it is, while others conclude that “trade openness” has recently fallen in some regions, coinciding with a slower pace of trade reforms and posing a threat to growth. This isn’t just an academic exercise. Accurately measuring globalization is necessary to understand the impact of the current challenges on the world economy. Economic policy cannot risk either overestimating deglobalization or underestimating the costs of such a scenario. For this reason, we need a clear definition with precise empirical applications that can guide economic policy.

The trade-to-GDP ratio — which calculates the relative importance of a country’s imports and exports to its economy — is one way to measure “openness” to trade  . This ratio steadily rose until 2008, then suffered a sudden drop in 2009 following the global financial crisis. By 2011 it had recovered, but it lacked the same vigor as before the crisis, suggesting to some that globalization was waning.

Some economists continue to the use trade-to-GDP ratio as a measure of openness, although many others argue that it is an inadequate yardstick and doesn’t necessarily imply that high trade barriers exist. Instead, it could reflect factors such as the size or structure of the economy or its geographic proximity to trading partners.

So globalization is better understood as an extension beyond national borders of the same market forces operating at all levels of economic activity. Using this definition, we measured the intensity of globalization as the growth of international trade relative to domestic trade. For instance, automakers sell some cars in the domestic market and export the rest. Comparing the evolution of the exports of cars with domestic sales offers a better measure of globalization dynamics than the trade-to-GDP ratio.  The model used to capture the relative dynamics of international and domestic trade is what economists call a structural gravity model. It allows for comparisons across countries and over time, capturing more intuitive globalization dynamics than the trade-to-GDP ratio. Among other factors, the reduction in trade barriers and advances in information technology make international trade grow faster than domestic trade, with the world becoming more globalized and with greater economic connectivity and cooperation among countries.

Based on this research, there is no evidence that the world economy has entered an era of deglobalization.  China’s trade-to-GDP ratio, for example, has trended downward since 2006 and is now below both the world average and the level in 2001, when China entered the World Trade Organization. Yet even considering recent trade tensions with the United States, it would be difficult to argue that the Chinese economy is drastically less “open,” as the trade-to-GDP ratio would suggest. A better explanation is that trade has become less important to China’s GDP as its domestic economy has boomed.

A globalization analysis consistent with economic theory requires the study of sector-specific dynamics. For instance, manufacturing has traditionally been a more trade-intensive sector, but information and communication technology (ICT) advances seem to be making services more tradable, pointing to more globalization opportunities in the future. Figure 1 plots the main results of our research. It shows that globalization dynamics in manufacturing were already strong in 1965, while agriculture and services “took off” in the late 1970s and 1990s, respectively. There is no sign of a deglobalization trend post-2008.

Figure 1. Globalization took off at various times, depending on the sector and country.

Figure 1 (b) investigates manufacturing dynamics across countries. These results uncover differing dynamics, situating China as a globalization leader starting in the 1980s, outperforming the world economy significantly during the entire period. This story is different from the one told by the trade-to-GDP ratio. Other results also offer deep insights by illustrating how countries like India, while lagging in manufacturing globalization, have outperformed the world economy in services.

The debate on globalization uses various terms --  slowbalization, deglobalization, reglobalization. Each tells a very different story about changes in the world economy. Our research contributes to these debates by offering a globalization toolkit to understand where the world economy stands today  and helping us to prepare for future dynamics.

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How Does Strengths-Based Therapy Work?

Why it can help to focus on your abilities rather than deficits

Dr. Amy Marschall is an autistic clinical psychologist with ADHD, working with children and adolescents who also identify with these neurotypes among others. She is certified in TF-CBT and telemental health.

Dr. Sabrina Romanoff, PsyD, is a licensed clinical psychologist and a professor at Yeshiva University’s clinical psychology doctoral program.

Renata Angerami / Getty Images

• Effectiveness
• Getting Started

Strengths-based therapy is an approach to psychotherapy treatment based in positive psychology . It focuses on a person's existing resources, resilience, and positive qualities, then uses these abilities to improve their quality of life and reduce problematic symptoms.

Learning the goals and techniques of this type of therapy can help you know what to expect. It's also beneficial to understand what conditions strengths-based therapy can help with, the benefits it provides, and what research says about its effectiveness so you know whether it may be a good option for you.

Goal of Strengths-Based Therapy

Strengths-based therapy aims to improve a person's mindset and instill a positive worldview. It enables them to see themselves as resourceful and resilient when experiencing adverse conditions or hardships.

What makes this approach different is its focus on identifying factors that might be holding back a person’s growth. It empowers participants to be an agent of change by creating an environment that promotes the change they need or desire.

Strengths-Based Therapy Techniques

In all therapeutic approaches, the therapist chooses their techniques based on the client’s unique needs. Techniques a strengths-based therapist might use in their sessions include:

• Reviewing a strengths list : The therapist provides a list of strengths with definitions and works with the client to identify which strengths apply to them. Clients can use the list as a starting point to identify their strengths.
• Asking open-ended questions : This technique involves asking questions such as, “What are you good at?” Asking open-ended questions is less structured, allowing the client to identify strengths that might not have been included on the list.
• Reframing weaknesses : A strengths-based therapist encourages the client to examine their weaknesses and identify ways these qualities can be reframed as strengths . For example, someone who worries about what others are thinking might be very compassionate and caring. This is used as a starting point to identify how these behaviors or qualities can be used to improve the client’s mindset or quality of life.
• Strengths journaling : When using this technique, the therapist asks the client to keep a journal tracking their strengths. This helps them learn to identify their strengths, and also identify situations where the strengths benefit them. Journaling improves mindfulness and helps the client notice existing strengths in their daily life.
• Maximizing strengths usage : A strengths-based therapist may also ask questions to help the client identify how and when a strength benefits them to help channel and use that strength in the most effective way possible. These questions can include things like, “When is a time you could have used this strength?” or “When is a time that you relied too heavily on this strength?”

When Strengths-Based Therapy Can Help

Strengths-based therapy can be helpful for many different concerns. It can help boost self-esteem and confidence, for instance, with some evidence that this approach can be beneficial for individuals with depression or anxiety .

Strengths-based therapy can also help individuals recovering from trauma . Building resilience and improving worldview can help alleviate many symptoms associated with these diagnoses.

Couples and families can benefit from a strengths-based treatment as it helps reframe challenges and boost healthy communication skills . Individuals learn to recognize how their strengths contribute to the relationship while beginning to identify their partner or family member’s strengths as well.

Strengths-based therapy could also help teens with identity development and insight. For similar reasons, it also benefits career counseling and determining what kinds of jobs might be a good fit for an individual.

Strengths-based therapy may be utilized in conjunction with other types of therapy, including cognitive-behavioral therapy , humanistic therapy , and narrative therapy . Therapists might also use a strengths-based approach if they are engaging in solution-focused therapy , brief motivational interviewing , or interpersonal therapy .

Benefits of Strengths-Based Therapy

Many people find strengths-based therapy beneficial in their mental health journeys. One reason is that positive psychology changes the traditional therapy narrative from “What do we need to fix about you?” to “What is the good that is already in you, and how can we bring that out?”

Strengths-based therapy also helps build resilience by identifying strengths you've used in the past but might not have defined as strengths at the time. The approach teaches you that you are already strong, and you already have the skills needed to survive. You simply need to learn how to tap into those skills and use them intentionally in your life.

Individuals enter strengths-based therapy with strengths; the therapy simply helps amplify these strengths so they're used for the person's maximum benefit.

Effectiveness of Strengths-Based Therapy

Research surrounding strengths-based therapy has shown that it is an effective treatment for a variety of conditions, including depression and trauma. It is also beneficial as an early intervention for serious mental health issues , such as psychosis.

Although people of all ages can benefit from this approach, teenagers in particular often find strengths-based therapy effective. This is partially because of focusing on the development and utilization of resilient beliefs and behaviors instead of identifying and challenging cognitive distortions.

Strengths-based therapy can be effective for both in-person and telehealth therapy sessions . This enables participants to choose which method works best for them.

Strengths-Based Therapy Criticisms

As with all therapeutic approaches, strengths-based therapy is not an ideal fit for everyone. Critics of this therapy type include:

• The approach lends itself to toxic positivity or focusing so intensely on a positive mindset that there is no space left for negative emotions or thoughts.
• Some weaknesses might not be strengths in disguise , and clients might feel invalidated if the therapist suggests otherwise.
• Strengths-based therapy emphasizes qualities and skills that are already present , so individuals looking to make changes in their lives might not find this intervention helpful.

If this approach is not the right fit for you, that is okay. There are many therapeutic options that can help improve mental health.

How to Get Started With Strengths-Based Therapy

If you feel that a strengths-based approach may benefit you and you are currently in therapy, you can ask your therapist if they are familiar with this approach. Talk about whether these interventions might be a good fit for you. Inquire whether they offer strengths-based therapy and, if not, ask if they could refer you to someone who does.

If you do not already have a therapist, you can also search for a therapist who specializes in this approach. Therapists with training in a strengths-based approach will often indicate this on their website or profile.

During intake, the therapist will gather information about your history and symptoms. They might also have you complete a strengths-based assessment to gather more information. Then, you and your therapist will work together to create a treatment plan that focuses on your strengths and positive qualities.

Get Help Now

We've tried, tested, and written unbiased reviews of the best online therapy programs including Talkspace, BetterHelp, and ReGain. Find out which option is the best for you.

Victor PP, Teismann T, Willutzki U. A pilot evaluation of a strengths-based CBT intervention module with college students.   Behav Cogn Psychother . 2017;45(4):427-431. doi:10.1017/S1352465816000552

Gabana N. A strengths-based cognitive behavioral approach to treating depression and building resilience in collegiate athletics: the individuation of an identical twin.   Case Stud Sport Exerc Psychol . 2017;1(1):4-15. doi:10.1123/cssep.2016-0005

Block AM, Aizenman L, Saad A, et al. Peer support groups: evaluating a culturally grounded, strengths-based approach for work with refugees .  ASW . 2018;18(3):930-948. doi:10.18060/21634

Allott K, Steele P, Boyer F, et al. Cognitive strengths-based assessment and intervention in first-episode psychosis: A complementary approach to addressing functional recovery?   Clinical Psychology Review . 2020;79:101871. doi:10.1016/j.cpr.2020.101871

Yuen E, Sadhu J, Pfeffer C, et al. Accentuate the positive: Strengths-based therapy for adolescents . Adolesc Psychiatry . 2020;10(3):166-171. doi:10.2174/2210676610666200225105529

Victor P, Krug I, Vehoff C, Lyons N, Willutzki U. Strengths-based cbt: internet-based versus face-to-face therapy in a randomized controlled trial .  J Depress Anxiety . 2018;07(02):1000301. doi:10.4172/2167-1044.1000301

By Amy Marschall, PsyD Dr. Amy Marschall is an autistic clinical psychologist with ADHD, working with children and adolescents who also identify with these neurotypes among others. She is certified in TF-CBT and telemental health.

What Is Climate Change?

Climate change is a long-term change in the average weather patterns that have come to define Earth’s local, regional and global climates. These changes have a broad range of observed effects that are synonymous with the term.

Changes observed in Earth’s climate since the mid-20th century are driven by human activities, particularly fossil fuel burning, which increases heat-trapping greenhouse gas levels in Earth’s atmosphere, raising Earth’s average surface temperature. Natural processes, which have been overwhelmed by human activities, can also contribute to climate change, including internal variability (e.g., cyclical ocean patterns like El Niño, La Niña and the Pacific Decadal Oscillation) and external forcings (e.g., volcanic activity, changes in the Sun’s energy output , variations in Earth’s orbit ).

Scientists use observations from the ground, air, and space, along with computer models , to monitor and study past, present, and future climate change. Climate data records provide evidence of climate change key indicators, such as global land and ocean temperature increases; rising sea levels; ice loss at Earth’s poles and in mountain glaciers; frequency and severity changes in extreme weather such as hurricanes, heatwaves, wildfires, droughts, floods, and precipitation; and cloud and vegetation cover changes.

“Climate change” and “global warming” are often used interchangeably but have distinct meanings. Similarly, the terms "weather" and "climate" are sometimes confused, though they refer to events with broadly different spatial- and timescales.

What Is Global Warming?

Global warming is the long-term heating of Earth’s surface observed since the pre-industrial period (between 1850 and 1900) due to human activities, primarily fossil fuel burning, which increases heat-trapping greenhouse gas levels in Earth’s atmosphere. This term is not interchangeable with the term "climate change."

Since the pre-industrial period, human activities are estimated to have increased Earth’s global average temperature by about 1 degree Celsius (1.8 degrees Fahrenheit), a number that is currently increasing by more than 0.2 degrees Celsius (0.36 degrees Fahrenheit) per decade. The current warming trend is unequivocally the result of human activity since the 1950s and is proceeding at an unprecedented rate over millennia.

Weather vs. Climate

“if you don’t like the weather in new england, just wait a few minutes.” - mark twain.

Weather refers to atmospheric conditions that occur locally over short periods of time—from minutes to hours or days. Familiar examples include rain, snow, clouds, winds, floods, or thunderstorms.

Climate, on the other hand, refers to the long-term (usually at least 30 years) regional or even global average of temperature, humidity, and rainfall patterns over seasons, years, or decades.

Find Out More: A Guide to NASA’s Global Climate Change Website

This website provides a high-level overview of some of the known causes, effects and indications of global climate change:

Evidence. Brief descriptions of some of the key scientific observations that our planet is undergoing abrupt climate change.

Causes. A concise discussion of the primary climate change causes on our planet.

Effects. A look at some of the likely future effects of climate change, including U.S. regional effects.

Vital Signs. Graphs and animated time series showing real-time climate change data, including atmospheric carbon dioxide, global temperature, sea ice extent, and ice sheet volume.

Earth Minute. This fun video series explains various Earth science topics, including some climate change topics.

Other NASA Resources

Goddard Scientific Visualization Studio. An extensive collection of animated climate change and Earth science visualizations.

Sea Level Change Portal. NASA's portal for an in-depth look at the science behind sea level change.

NASA’s Earth Observatory. Satellite imagery, feature articles and scientific information about our home planet, with a focus on Earth’s climate and environmental change.

Header image is of Apusiaajik Glacier, and was taken near Kulusuk, Greenland, on Aug. 26, 2018, during NASA's Oceans Melting Greenland (OMG) field operations. Learn more here . Credit: NASA/JPL-Caltech

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