how to write a research setting

Research Setting and Methodology

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Chapter 3 Research Setting and Methodology describes the research setting and the methods of research. It details the methodological framework of the study as the baseline description in obtaining the research materials. This section begins with the explanation of organizational ethnography as an approach to my research.

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Except in 1974, there was social movement against foreign direct investment especially concerning Japanese corporations (see also Research Background).

German Organization ONE was established in 1997 in Indonesia.

The city of Bumi Serpong Damai (BSD) is a prestigious and integrated location in South Tangerang (Province of Banten). BSD city has been developing over the last 20 years. This ambitious urban planning scheme combines housing, business and commercial properties and encompasses a total area of circa 6,000 hectares. About a quarter of the available land has been developed, and its current population is approximately 120,000. German Centre was one of the first buildings in the Central Business District (CBD) in the center of BSD. Also, an International German School and Swiss-German University are located in BSD.

The administrative unit below kecamatan (sub-district). It is also similar to desa (village, rural settlement, countryside). The term kelurahan refers to the village administrative office in the city or sub-urban areas while the term desa is used in rural settlement areas.

A small watchman’s hut built in rice paddies, but in this context the term saung refers to the meeting point for employees.

See the section Communication in the theoretical framework.

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Aang Koswara

Public Relations Studies, Padjadjaran University, Bandung, Indonesia

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Koswara, A. (2022). Research Setting and Methodology. In: Corporate Culture Practices of German Corporations in the Host Country Indonesia. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-39289-5_3

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Basic Steps in the Research Process

The following steps outline a simple and effective strategy for writing a research paper. Depending on your familiarity with the topic and the challenges you encounter along the way, you may need to rearrange these steps.

Step 1: Identify and develop your topic

Selecting a topic can be the most challenging part of a research assignment. Since this is the very first step in writing a paper, it is vital that it be done correctly. Here are some tips for selecting a topic:

• Select a topic within the parameters set by the assignment. Many times your instructor will give you clear guidelines as to what you can and cannot write about. Failure to work within these guidelines may result in your proposed paper being deemed unacceptable by your instructor.
• Select a topic of personal interest to you and learn more about it. The research for and writing of a paper will be more enjoyable if you are writing about something that you find interesting.
• Select a topic for which you can find a manageable amount of information. Do a preliminary search of information sources to determine whether existing sources will meet your needs. If you find too much information, you may need to narrow your topic; if you find too little, you may need to broaden your topic.
• Be original. Your instructor reads hundreds of research papers every year, and many of them are on the same topics (topics in the news at the time, controversial issues, subjects for which there is ample and easily accessed information). Stand out from your classmates by selecting an interesting and off-the-beaten-path topic.
• Still can't come up with a topic to write about? See your instructor for advice.

Once you have identified your topic, it may help to state it as a question. For example, if you are interested in finding out about the epidemic of obesity in the American population, you might pose the question "What are the causes of obesity in America ?" By posing your subject as a question you can more easily identify the main concepts or keywords to be used in your research.

Step 2 : Do a preliminary search for information

Before beginning your research in earnest, do a preliminary search to determine whether there is enough information out there for your needs and to set the context of your research. Look up your keywords in the appropriate titles in the library's Reference collection (such as encyclopedias and dictionaries) and in other sources such as our catalog of books, periodical databases, and Internet search engines. Additional background information may be found in your lecture notes, textbooks, and reserve readings. You may find it necessary to adjust the focus of your topic in light of the resources available to you.

Step 3: Locate materials

With the direction of your research now clear to you, you can begin locating material on your topic. There are a number of places you can look for information:

If you are looking for books, do a subject search in One Search . A Keyword search can be performed if the subject search doesn't yield enough information. Print or write down the citation information (author, title,etc.) and the location (call number and collection) of the item(s). Note the circulation status. When you locate the book on the shelf, look at the books located nearby; similar items are always shelved in the same area. The Aleph catalog also indexes the library's audio-visual holdings.

Use the library's  electronic periodical databases  to find magazine and newspaper articles. Choose the databases and formats best suited to your particular topic; ask at the librarian at the Reference Desk if you need help figuring out which database best meets your needs. Many of the articles in the databases are available in full-text format.

Use search engines ( Google ,  Yahoo , etc.) and subject directories to locate materials on the Internet. Check the  Internet Resources  section of the NHCC Library web site for helpful subject links.

Step 4: Evaluate your sources

See the  CARS Checklist for Information Quality   for tips on evaluating the authority and quality of the information you have located. Your instructor expects that you will provide credible, truthful, and reliable information and you have every right to expect that the sources you use are providing the same. This step is especially important when using Internet resources, many of which are regarded as less than reliable.

Step 5: Make notes

Consult the resources you have chosen and note the information that will be useful in your paper. Be sure to document all the sources you consult, even if you there is a chance you may not use that particular source. The author, title, publisher, URL, and other information will be needed later when creating a bibliography.

Step 6: Write your paper

Begin by organizing the information you have collected. The next step is the rough draft, wherein you get your ideas on paper in an unfinished fashion. This step will help you organize your ideas and determine the form your final paper will take. After this, you will revise the draft as many times as you think necessary to create a final product to turn in to your instructor.

Step 7: Cite your sources properly

Give credit where credit is due; cite your sources.

Citing or documenting the sources used in your research serves two purposes: it gives proper credit to the authors of the materials used, and it allows those who are reading your work to duplicate your research and locate the sources that you have listed as references. The  MLA  and the  APA  Styles are two popular citation formats.

Failure to cite your sources properly is plagiarism. Plagiarism is avoidable!

Step 8: Proofread

The final step in the process is to proofread the paper you have created. Read through the text and check for any errors in spelling, grammar, and punctuation. Make sure the sources you used are cited properly. Make sure the message that you want to get across to the reader has been thoroughly stated.

Additional research tips:

• Work from the general to the specific -- find background information first, then use more specific sources.
• Don't forget print sources -- many times print materials are more easily accessed and every bit as helpful as online resources.
• The library has books on the topic of writing research papers at call number area LB 2369.
• If you have questions about the assignment, ask your instructor.
• If you have any questions about finding information in the library, ask the librarian.

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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

Prevent plagiarism, run a free check.

Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

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 analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are 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.

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Article Contents

Primacy of the research question, structure of the paper, writing a research article: advice to beginners.

• Article contents
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• Supplementary Data

Thomas V. Perneger, Patricia M. Hudelson, Writing a research article: advice to beginners, International Journal for Quality in Health Care , Volume 16, Issue 3, June 2004, Pages 191–192, https://doi.org/10.1093/intqhc/mzh053

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Writing research papers does not come naturally to most of us. The typical research paper is a highly codified rhetorical form [ 1 , 2 ]. Knowledge of the rules—some explicit, others implied—goes a long way toward writing a paper that will get accepted in a peer-reviewed journal.

A good research paper addresses a specific research question. The research question—or study objective or main research hypothesis—is the central organizing principle of the paper. Whatever relates to the research question belongs in the paper; the rest doesn’t. This is perhaps obvious when the paper reports on a well planned research project. However, in applied domains such as quality improvement, some papers are written based on projects that were undertaken for operational reasons, and not with the primary aim of producing new knowledge. In such cases, authors should define the main research question a posteriori and design the paper around it.

Generally, only one main research question should be addressed in a paper (secondary but related questions are allowed). If a project allows you to explore several distinct research questions, write several papers. For instance, if you measured the impact of obtaining written consent on patient satisfaction at a specialized clinic using a newly developed questionnaire, you may want to write one paper on the questionnaire development and validation, and another on the impact of the intervention. The idea is not to split results into ‘least publishable units’, a practice that is rightly decried, but rather into ‘optimally publishable units’.

What is a good research question? The key attributes are: (i) specificity; (ii) originality or novelty; and (iii) general relevance to a broad scientific community. The research question should be precise and not merely identify a general area of inquiry. It can often (but not always) be expressed in terms of a possible association between X and Y in a population Z, for example ‘we examined whether providing patients about to be discharged from the hospital with written information about their medications would improve their compliance with the treatment 1 month later’. A study does not necessarily have to break completely new ground, but it should extend previous knowledge in a useful way, or alternatively refute existing knowledge. Finally, the question should be of interest to others who work in the same scientific area. The latter requirement is more challenging for those who work in applied science than for basic scientists. While it may safely be assumed that the human genome is the same worldwide, whether the results of a local quality improvement project have wider relevance requires careful consideration and argument.

Once the research question is clearly defined, writing the paper becomes considerably easier. The paper will ask the question, then answer it. The key to successful scientific writing is getting the structure of the paper right. The basic structure of a typical research paper is the sequence of Introduction, Methods, Results, and Discussion (sometimes abbreviated as IMRAD). Each section addresses a different objective. The authors state: (i) the problem they intend to address—in other terms, the research question—in the Introduction; (ii) what they did to answer the question in the Methods section; (iii) what they observed in the Results section; and (iv) what they think the results mean in the Discussion.

In turn, each basic section addresses several topics, and may be divided into subsections (Table 1 ). In the Introduction, the authors should explain the rationale and background to the study. What is the research question, and why is it important to ask it? While it is neither necessary nor desirable to provide a full-blown review of the literature as a prelude to the study, it is helpful to situate the study within some larger field of enquiry. The research question should always be spelled out, and not merely left for the reader to guess.

Typical structure of a research paper

The Methods section should provide the readers with sufficient detail about the study methods to be able to reproduce the study if so desired. Thus, this section should be specific, concrete, technical, and fairly detailed. The study setting, the sampling strategy used, instruments, data collection methods, and analysis strategies should be described. In the case of qualitative research studies, it is also useful to tell the reader which research tradition the study utilizes and to link the choice of methodological strategies with the research goals [ 3 ].

The Results section is typically fairly straightforward and factual. All results that relate to the research question should be given in detail, including simple counts and percentages. Resist the temptation to demonstrate analytic ability and the richness of the dataset by providing numerous tables of non-essential results.

The Discussion section allows the most freedom. This is why the Discussion is the most difficult to write, and is often the weakest part of a paper. Structured Discussion sections have been proposed by some journal editors [ 4 ]. While strict adherence to such rules may not be necessary, following a plan such as that proposed in Table 1 may help the novice writer stay on track.

References should be used wisely. Key assertions should be referenced, as well as the methods and instruments used. However, unless the paper is a comprehensive review of a topic, there is no need to be exhaustive. Also, references to unpublished work, to documents in the grey literature (technical reports), or to any source that the reader will have difficulty finding or understanding should be avoided.

Having the structure of the paper in place is a good start. However, there are many details that have to be attended to while writing. An obvious recommendation is to read, and follow, the instructions to authors published by the journal (typically found on the journal’s website). Another concerns non-native writers of English: do have a native speaker edit the manuscript. A paper usually goes through several drafts before it is submitted. When revising a paper, it is useful to keep an eye out for the most common mistakes (Table 2 ). If you avoid all those, your paper should be in good shape.

Common mistakes seen in manuscripts submitted to this journal

Huth EJ . How to Write and Publish Papers in the Medical Sciences , 2nd edition. Baltimore, MD: Williams & Wilkins, 1990 .

Browner WS . Publishing and Presenting Clinical Research . Baltimore, MD: Lippincott, Williams & Wilkins, 1999 .

Devers KJ , Frankel RM. Getting qualitative research published. Educ Health 2001 ; 14 : 109 –117.

Docherty M , Smith R. The case for structuring the discussion of scientific papers. Br Med J 1999 ; 318 : 1224 –1225.

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Introduction

Before beginning your paper, you need to decide how you plan to design the study .

The research design refers to the overall strategy and analytical approach that you have chosen in order to integrate, in a coherent and logical way, the different components of the study, thus ensuring that the research problem will be thoroughly investigated. It constitutes the blueprint for the collection, measurement, and interpretation of information and data. Note that the research problem determines the type of design you choose, not the other way around!

De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Trochim, William M.K. Research Methods Knowledge Base. 2006.

General Structure and Writing Style

The function of a research design is to ensure that the evidence obtained enables you to effectively address the research problem logically and as unambiguously as possible . In social sciences research, obtaining information relevant to the research problem generally entails specifying the type of evidence needed to test the underlying assumptions of a theory, to evaluate a program, or to accurately describe and assess meaning related to an observable phenomenon.

With this in mind, a common mistake made by researchers is that they begin their investigations before they have thought critically about what information is required to address the research problem. Without attending to these design issues beforehand, the overall research problem will not be adequately addressed and any conclusions drawn will run the risk of being weak and unconvincing. As a consequence, the overall validity of the study will be undermined.

The length and complexity of describing the research design in your paper can vary considerably, but any well-developed description will achieve the following :

• Identify the research problem clearly and justify its selection, particularly in relation to any valid alternative designs that could have been used,
• Review and synthesize previously published literature associated with the research problem,
• Clearly and explicitly specify hypotheses [i.e., research questions] central to the problem,
• Effectively describe the information and/or data which will be necessary for an adequate testing of the hypotheses and explain how such information and/or data will be obtained, and
• Describe the methods of analysis to be applied to the data in determining whether or not the hypotheses are true or false.

The research design is usually incorporated into the introduction of your paper . You can obtain an overall sense of what to do by reviewing studies that have utilized the same research design [e.g., using a case study approach]. This can help you develop an outline to follow for your own paper.

NOTE: Use the SAGE Research Methods Online and Cases and the SAGE Research Methods Videos databases to search for scholarly resources on how to apply specific research designs and methods . The Research Methods Online database contains links to more than 175,000 pages of SAGE publisher's book, journal, and reference content on quantitative, qualitative, and mixed research methodologies. Also included is a collection of case studies of social research projects that can be used to help you better understand abstract or complex methodological concepts. The Research Methods Videos database contains hours of tutorials, interviews, video case studies, and mini-documentaries covering the entire research process.

Creswell, John W. and J. David Creswell. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 5th edition. Thousand Oaks, CA: Sage, 2018; De Vaus, D. A. Research Design in Social Research . London: SAGE, 2001; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Leedy, Paul D. and Jeanne Ellis Ormrod. Practical Research: Planning and Design . Tenth edition. Boston, MA: Pearson, 2013; Vogt, W. Paul, Dianna C. Gardner, and Lynne M. Haeffele. When to Use What Research Design . New York: Guilford, 2012.

Action Research Design

Definition and Purpose

The essentials of action research design follow a characteristic cycle whereby initially an exploratory stance is adopted, where an understanding of a problem is developed and plans are made for some form of interventionary strategy. Then the intervention is carried out [the "action" in action research] during which time, pertinent observations are collected in various forms. The new interventional strategies are carried out, and this cyclic process repeats, continuing until a sufficient understanding of [or a valid implementation solution for] the problem is achieved. The protocol is iterative or cyclical in nature and is intended to foster deeper understanding of a given situation, starting with conceptualizing and particularizing the problem and moving through several interventions and evaluations.

What do these studies tell you ?

• This is a collaborative and adaptive research design that lends itself to use in work or community situations.
• Design focuses on pragmatic and solution-driven research outcomes rather than testing theories.
• When practitioners use action research, it has the potential to increase the amount they learn consciously from their experience; the action research cycle can be regarded as a learning cycle.
• Action research studies often have direct and obvious relevance to improving practice and advocating for change.
• There are no hidden controls or preemption of direction by the researcher.

What these studies don't tell you ?

• It is harder to do than conducting conventional research because the researcher takes on responsibilities of advocating for change as well as for researching the topic.
• Action research is much harder to write up because it is less likely that you can use a standard format to report your findings effectively [i.e., data is often in the form of stories or observation].
• Personal over-involvement of the researcher may bias research results.
• The cyclic nature of action research to achieve its twin outcomes of action [e.g. change] and research [e.g. understanding] is time-consuming and complex to conduct.
• Advocating for change usually requires buy-in from study participants.

Coghlan, David and Mary Brydon-Miller. The Sage Encyclopedia of Action Research . Thousand Oaks, CA:  Sage, 2014; Efron, Sara Efrat and Ruth Ravid. Action Research in Education: A Practical Guide . New York: Guilford, 2013; Gall, Meredith. Educational Research: An Introduction . Chapter 18, Action Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Gorard, Stephen. Research Design: Creating Robust Approaches for the Social Sciences . Thousand Oaks, CA: Sage, 2013; Kemmis, Stephen and Robin McTaggart. “Participatory Action Research.” In Handbook of Qualitative Research . Norman Denzin and Yvonna S. Lincoln, eds. 2nd ed. (Thousand Oaks, CA: SAGE, 2000), pp. 567-605; McNiff, Jean. Writing and Doing Action Research . London: Sage, 2014; Reason, Peter and Hilary Bradbury. Handbook of Action Research: Participative Inquiry and Practice . Thousand Oaks, CA: SAGE, 2001.

Case Study Design

A case study is an in-depth study of a particular research problem rather than a sweeping statistical survey or comprehensive comparative inquiry. It is often used to narrow down a very broad field of research into one or a few easily researchable examples. The case study research design is also useful for testing whether a specific theory and model actually applies to phenomena in the real world. It is a useful design when not much is known about an issue or phenomenon.

• Approach excels at bringing us to an understanding of a complex issue through detailed contextual analysis of a limited number of events or conditions and their relationships.
• A researcher using a case study design can apply a variety of methodologies and rely on a variety of sources to investigate a research problem.
• Design can extend experience or add strength to what is already known through previous research.
• Social scientists, in particular, make wide use of this research design to examine contemporary real-life situations and provide the basis for the application of concepts and theories and the extension of methodologies.
• The design can provide detailed descriptions of specific and rare cases.
• A single or small number of cases offers little basis for establishing reliability or to generalize the findings to a wider population of people, places, or things.
• Intense exposure to the study of a case may bias a researcher's interpretation of the findings.
• Design does not facilitate assessment of cause and effect relationships.
• Vital information may be missing, making the case hard to interpret.
• The case may not be representative or typical of the larger problem being investigated.
• If the criteria for selecting a case is because it represents a very unusual or unique phenomenon or problem for study, then your interpretation of the findings can only apply to that particular case.

Case Studies. Writing@CSU. Colorado State University; Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 4, Flexible Methods: Case Study Design. 2nd ed. New York: Columbia University Press, 1999; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Greenhalgh, Trisha, editor. Case Study Evaluation: Past, Present and Future Challenges . Bingley, UK: Emerald Group Publishing, 2015; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Stake, Robert E. The Art of Case Study Research . Thousand Oaks, CA: SAGE, 1995; Yin, Robert K. Case Study Research: Design and Theory . Applied Social Research Methods Series, no. 5. 3rd ed. Thousand Oaks, CA: SAGE, 2003.

Causal Design

Causality studies may be thought of as understanding a phenomenon in terms of conditional statements in the form, “If X, then Y.” This type of research is used to measure what impact a specific change will have on existing norms and assumptions. Most social scientists seek causal explanations that reflect tests of hypotheses. Causal effect (nomothetic perspective) occurs when variation in one phenomenon, an independent variable, leads to or results, on average, in variation in another phenomenon, the dependent variable.

Conditions necessary for determining causality:

• Empirical association -- a valid conclusion is based on finding an association between the independent variable and the dependent variable.
• Appropriate time order -- to conclude that causation was involved, one must see that cases were exposed to variation in the independent variable before variation in the dependent variable.
• Nonspuriousness -- a relationship between two variables that is not due to variation in a third variable.
• Causality research designs assist researchers in understanding why the world works the way it does through the process of proving a causal link between variables and by the process of eliminating other possibilities.
• Replication is possible.
• There is greater confidence the study has internal validity due to the systematic subject selection and equity of groups being compared.
• Not all relationships are causal! The possibility always exists that, by sheer coincidence, two unrelated events appear to be related [e.g., Punxatawney Phil could accurately predict the duration of Winter for five consecutive years but, the fact remains, he's just a big, furry rodent].
• Conclusions about causal relationships are difficult to determine due to a variety of extraneous and confounding variables that exist in a social environment. This means causality can only be inferred, never proven.
• If two variables are correlated, the cause must come before the effect. However, even though two variables might be causally related, it can sometimes be difficult to determine which variable comes first and, therefore, to establish which variable is the actual cause and which is the  actual effect.

Beach, Derek and Rasmus Brun Pedersen. Causal Case Study Methods: Foundations and Guidelines for Comparing, Matching, and Tracing . Ann Arbor, MI: University of Michigan Press, 2016; Bachman, Ronet. The Practice of Research in Criminology and Criminal Justice . Chapter 5, Causation and Research Designs. 3rd ed. Thousand Oaks, CA: Pine Forge Press, 2007; Brewer, Ernest W. and Jennifer Kubn. “Causal-Comparative Design.” In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 125-132; Causal Research Design: Experimentation. Anonymous SlideShare Presentation; Gall, Meredith. Educational Research: An Introduction . Chapter 11, Nonexperimental Research: Correlational Designs. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007; Trochim, William M.K. Research Methods Knowledge Base. 2006.

Cohort Design

Often used in the medical sciences, but also found in the applied social sciences, a cohort study generally refers to a study conducted over a period of time involving members of a population which the subject or representative member comes from, and who are united by some commonality or similarity. Using a quantitative framework, a cohort study makes note of statistical occurrence within a specialized subgroup, united by same or similar characteristics that are relevant to the research problem being investigated, rather than studying statistical occurrence within the general population. Using a qualitative framework, cohort studies generally gather data using methods of observation. Cohorts can be either "open" or "closed."

• Open Cohort Studies [dynamic populations, such as the population of Los Angeles] involve a population that is defined just by the state of being a part of the study in question (and being monitored for the outcome). Date of entry and exit from the study is individually defined, therefore, the size of the study population is not constant. In open cohort studies, researchers can only calculate rate based data, such as, incidence rates and variants thereof.
• Closed Cohort Studies [static populations, such as patients entered into a clinical trial] involve participants who enter into the study at one defining point in time and where it is presumed that no new participants can enter the cohort. Given this, the number of study participants remains constant (or can only decrease).
• The use of cohorts is often mandatory because a randomized control study may be unethical. For example, you cannot deliberately expose people to asbestos, you can only study its effects on those who have already been exposed. Research that measures risk factors often relies upon cohort designs.
• Because cohort studies measure potential causes before the outcome has occurred, they can demonstrate that these “causes” preceded the outcome, thereby avoiding the debate as to which is the cause and which is the effect.
• Cohort analysis is highly flexible and can provide insight into effects over time and related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
• Either original data or secondary data can be used in this design.
• In cases where a comparative analysis of two cohorts is made [e.g., studying the effects of one group exposed to asbestos and one that has not], a researcher cannot control for all other factors that might differ between the two groups. These factors are known as confounding variables.
• Cohort studies can end up taking a long time to complete if the researcher must wait for the conditions of interest to develop within the group. This also increases the chance that key variables change during the course of the study, potentially impacting the validity of the findings.
• Due to the lack of randominization in the cohort design, its external validity is lower than that of study designs where the researcher randomly assigns participants.

Healy P, Devane D. “Methodological Considerations in Cohort Study Designs.” Nurse Researcher 18 (2011): 32-36; Glenn, Norval D, editor. Cohort Analysis . 2nd edition. Thousand Oaks, CA: Sage, 2005; Levin, Kate Ann. Study Design IV: Cohort Studies. Evidence-Based Dentistry 7 (2003): 51–52; Payne, Geoff. “Cohort Study.” In The SAGE Dictionary of Social Research Methods . Victor Jupp, editor. (Thousand Oaks, CA: Sage, 2006), pp. 31-33; Study Design 101. Himmelfarb Health Sciences Library. George Washington University, November 2011; Cohort Study. Wikipedia.

Cross-Sectional Design

Cross-sectional research designs have three distinctive features: no time dimension; a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation. The cross-sectional design can only measure differences between or from among a variety of people, subjects, or phenomena rather than a process of change. As such, researchers using this design can only employ a relatively passive approach to making causal inferences based on findings.

• Cross-sectional studies provide a clear 'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
• Unlike an experimental design, where there is an active intervention by the researcher to produce and measure change or to create differences, cross-sectional designs focus on studying and drawing inferences from existing differences between people, subjects, or phenomena.
• Entails collecting data at and concerning one point in time. While longitudinal studies involve taking multiple measures over an extended period of time, cross-sectional research is focused on finding relationships between variables at one moment in time.
• Groups identified for study are purposely selected based upon existing differences in the sample rather than seeking random sampling.
• Cross-section studies are capable of using data from a large number of subjects and, unlike observational studies, is not geographically bound.
• Can estimate prevalence of an outcome of interest because the sample is usually taken from the whole population.
• Because cross-sectional designs generally use survey techniques to gather data, they are relatively inexpensive and take up little time to conduct.
• Finding people, subjects, or phenomena to study that are very similar except in one specific variable can be difficult.
• Results are static and time bound and, therefore, give no indication of a sequence of events or reveal historical or temporal contexts.
• Studies cannot be utilized to establish cause and effect relationships.
• This design only provides a snapshot of analysis so there is always the possibility that a study could have differing results if another time-frame had been chosen.
• There is no follow up to the findings.

Bethlehem, Jelke. "7: Cross-sectional Research." In Research Methodology in the Social, Behavioural and Life Sciences . Herman J Adèr and Gideon J Mellenbergh, editors. (London, England: Sage, 1999), pp. 110-43; Bourque, Linda B. “Cross-Sectional Design.” In  The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman, and Tim Futing Liao. (Thousand Oaks, CA: 2004), pp. 230-231; Hall, John. “Cross-Sectional Survey Design.” In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 173-174; Helen Barratt, Maria Kirwan. Cross-Sectional Studies: Design Application, Strengths and Weaknesses of Cross-Sectional Studies. Healthknowledge, 2009. Cross-Sectional Study. Wikipedia.

Descriptive Design

Descriptive research designs help provide answers to the questions of who, what, when, where, and how associated with a particular research problem; a descriptive study cannot conclusively ascertain answers to why. Descriptive research is used to obtain information concerning the current status of the phenomena and to describe "what exists" with respect to variables or conditions in a situation.

• The subject is being observed in a completely natural and unchanged natural environment. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject [a.k.a., the Heisenberg effect whereby measurements of certain systems cannot be made without affecting the systems].
• Descriptive research is often used as a pre-cursor to more quantitative research designs with the general overview giving some valuable pointers as to what variables are worth testing quantitatively.
• If the limitations are understood, they can be a useful tool in developing a more focused study.
• Descriptive studies can yield rich data that lead to important recommendations in practice.
• Appoach collects a large amount of data for detailed analysis.
• The results from a descriptive research cannot be used to discover a definitive answer or to disprove a hypothesis.
• Because descriptive designs often utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
• The descriptive function of research is heavily dependent on instrumentation for measurement and observation.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 5, Flexible Methods: Descriptive Research. 2nd ed. New York: Columbia University Press, 1999; Given, Lisa M. "Descriptive Research." In Encyclopedia of Measurement and Statistics . Neil J. Salkind and Kristin Rasmussen, editors. (Thousand Oaks, CA: Sage, 2007), pp. 251-254; McNabb, Connie. Descriptive Research Methodologies. Powerpoint Presentation; Shuttleworth, Martyn. Descriptive Research Design, September 26, 2008; Erickson, G. Scott. "Descriptive Research Design." In New Methods of Market Research and Analysis . (Northampton, MA: Edward Elgar Publishing, 2017), pp. 51-77; Sahin, Sagufta, and Jayanta Mete. "A Brief Study on Descriptive Research: Its Nature and Application in Social Science." International Journal of Research and Analysis in Humanities 1 (2021): 11; K. Swatzell and P. Jennings. “Descriptive Research: The Nuts and Bolts.” Journal of the American Academy of Physician Assistants 20 (2007), pp. 55-56; Kane, E. Doing Your Own Research: Basic Descriptive Research in the Social Sciences and Humanities . London: Marion Boyars, 1985.

Experimental Design

A blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment. In doing this, the researcher attempts to determine or predict what may occur. Experimental research is often used where there is time priority in a causal relationship (cause precedes effect), there is consistency in a causal relationship (a cause will always lead to the same effect), and the magnitude of the correlation is great. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable. Subsequent experimental designs have used more groups and more measurements over longer periods. True experiments must have control, randomization, and manipulation.

• Experimental research allows the researcher to control the situation. In so doing, it allows researchers to answer the question, “What causes something to occur?”
• Permits the researcher to identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
• Experimental research designs support the ability to limit alternative explanations and to infer direct causal relationships in the study.
• Approach provides the highest level of evidence for single studies.
• The design is artificial, and results may not generalize well to the real world.
• The artificial settings of experiments may alter the behaviors or responses of participants.
• Experimental designs can be costly if special equipment or facilities are needed.
• Some research problems cannot be studied using an experiment because of ethical or technical reasons.
• Difficult to apply ethnographic and other qualitative methods to experimentally designed studies.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 7, Flexible Methods: Experimental Research. 2nd ed. New York: Columbia University Press, 1999; Chapter 2: Research Design, Experimental Designs. School of Psychology, University of New England, 2000; Chow, Siu L. "Experimental Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 448-453; "Experimental Design." In Social Research Methods . Nicholas Walliman, editor. (London, England: Sage, 2006), pp, 101-110; Experimental Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Kirk, Roger E. Experimental Design: Procedures for the Behavioral Sciences . 4th edition. Thousand Oaks, CA: Sage, 2013; Trochim, William M.K. Experimental Design. Research Methods Knowledge Base. 2006; Rasool, Shafqat. Experimental Research. Slideshare presentation.

Exploratory Design

An exploratory design is conducted about a research problem when there are few or no earlier studies to refer to or rely upon to predict an outcome . The focus is on gaining insights and familiarity for later investigation or undertaken when research problems are in a preliminary stage of investigation. Exploratory designs are often used to establish an understanding of how best to proceed in studying an issue or what methodology would effectively apply to gathering information about the issue.

The goals of exploratory research are intended to produce the following possible insights:

• Familiarity with basic details, settings, and concerns.
• Well grounded picture of the situation being developed.
• Generation of new ideas and assumptions.
• Development of tentative theories or hypotheses.
• Determination about whether a study is feasible in the future.
• Issues get refined for more systematic investigation and formulation of new research questions.
• Direction for future research and techniques get developed.
• Design is a useful approach for gaining background information on a particular topic.
• Exploratory research is flexible and can address research questions of all types (what, why, how).
• Provides an opportunity to define new terms and clarify existing concepts.
• Exploratory research is often used to generate formal hypotheses and develop more precise research problems.
• In the policy arena or applied to practice, exploratory studies help establish research priorities and where resources should be allocated.
• Exploratory research generally utilizes small sample sizes and, thus, findings are typically not generalizable to the population at large.
• The exploratory nature of the research inhibits an ability to make definitive conclusions about the findings. They provide insight but not definitive conclusions.
• The research process underpinning exploratory studies is flexible but often unstructured, leading to only tentative results that have limited value to decision-makers.
• Design lacks rigorous standards applied to methods of data gathering and analysis because one of the areas for exploration could be to determine what method or methodologies could best fit the research problem.

Cuthill, Michael. “Exploratory Research: Citizen Participation, Local Government, and Sustainable Development in Australia.” Sustainable Development 10 (2002): 79-89; Streb, Christoph K. "Exploratory Case Study." In Encyclopedia of Case Study Research . Albert J. Mills, Gabrielle Durepos and Eiden Wiebe, editors. (Thousand Oaks, CA: Sage, 2010), pp. 372-374; Taylor, P. J., G. Catalano, and D.R.F. Walker. “Exploratory Analysis of the World City Network.” Urban Studies 39 (December 2002): 2377-2394; Exploratory Research. Wikipedia.

Field Research Design

Sometimes referred to as ethnography or participant observation, designs around field research encompass a variety of interpretative procedures [e.g., observation and interviews] rooted in qualitative approaches to studying people individually or in groups while inhabiting their natural environment as opposed to using survey instruments or other forms of impersonal methods of data gathering. Information acquired from observational research takes the form of “ field notes ” that involves documenting what the researcher actually sees and hears while in the field. Findings do not consist of conclusive statements derived from numbers and statistics because field research involves analysis of words and observations of behavior. Conclusions, therefore, are developed from an interpretation of findings that reveal overriding themes, concepts, and ideas. More information can be found HERE .

• Field research is often necessary to fill gaps in understanding the research problem applied to local conditions or to specific groups of people that cannot be ascertained from existing data.
• The research helps contextualize already known information about a research problem, thereby facilitating ways to assess the origins, scope, and scale of a problem and to gage the causes, consequences, and means to resolve an issue based on deliberate interaction with people in their natural inhabited spaces.
• Enables the researcher to corroborate or confirm data by gathering additional information that supports or refutes findings reported in prior studies of the topic.
• Because the researcher in embedded in the field, they are better able to make observations or ask questions that reflect the specific cultural context of the setting being investigated.
• Observing the local reality offers the opportunity to gain new perspectives or obtain unique data that challenges existing theoretical propositions or long-standing assumptions found in the literature.

What these studies don't tell you

• A field research study requires extensive time and resources to carry out the multiple steps involved with preparing for the gathering of information, including for example, examining background information about the study site, obtaining permission to access the study site, and building trust and rapport with subjects.
• Requires a commitment to staying engaged in the field to ensure that you can adequately document events and behaviors as they unfold.
• The unpredictable nature of fieldwork means that researchers can never fully control the process of data gathering. They must maintain a flexible approach to studying the setting because events and circumstances can change quickly or unexpectedly.
• Findings can be difficult to interpret and verify without access to documents and other source materials that help to enhance the credibility of information obtained from the field  [i.e., the act of triangulating the data].
• Linking the research problem to the selection of study participants inhabiting their natural environment is critical. However, this specificity limits the ability to generalize findings to different situations or in other contexts or to infer courses of action applied to other settings or groups of people.
• The reporting of findings must take into account how the researcher themselves may have inadvertently affected respondents and their behaviors.

Historical Design

The purpose of a historical research design is to collect, verify, and synthesize evidence from the past to establish facts that defend or refute a hypothesis. It uses secondary sources and a variety of primary documentary evidence, such as, diaries, official records, reports, archives, and non-textual information [maps, pictures, audio and visual recordings]. The limitation is that the sources must be both authentic and valid.

• The historical research design is unobtrusive; the act of research does not affect the results of the study.
• The historical approach is well suited for trend analysis.
• Historical records can add important contextual background required to more fully understand and interpret a research problem.
• There is often no possibility of researcher-subject interaction that could affect the findings.
• Historical sources can be used over and over to study different research problems or to replicate a previous study.
• The ability to fulfill the aims of your research are directly related to the amount and quality of documentation available to understand the research problem.
• Since historical research relies on data from the past, there is no way to manipulate it to control for contemporary contexts.
• Interpreting historical sources can be very time consuming.
• The sources of historical materials must be archived consistently to ensure access. This may especially challenging for digital or online-only sources.
• Original authors bring their own perspectives and biases to the interpretation of past events and these biases are more difficult to ascertain in historical resources.
• Due to the lack of control over external variables, historical research is very weak with regard to the demands of internal validity.
• It is rare that the entirety of historical documentation needed to fully address a research problem is available for interpretation, therefore, gaps need to be acknowledged.

Howell, Martha C. and Walter Prevenier. From Reliable Sources: An Introduction to Historical Methods . Ithaca, NY: Cornell University Press, 2001; Lundy, Karen Saucier. "Historical Research." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor. (Thousand Oaks, CA: Sage, 2008), pp. 396-400; Marius, Richard. and Melvin E. Page. A Short Guide to Writing about History . 9th edition. Boston, MA: Pearson, 2015; Savitt, Ronald. “Historical Research in Marketing.” Journal of Marketing 44 (Autumn, 1980): 52-58;  Gall, Meredith. Educational Research: An Introduction . Chapter 16, Historical Research. 8th ed. Boston, MA: Pearson/Allyn and Bacon, 2007.

Longitudinal Design

A longitudinal study follows the same sample over time and makes repeated observations. For example, with longitudinal surveys, the same group of people is interviewed at regular intervals, enabling researchers to track changes over time and to relate them to variables that might explain why the changes occur. Longitudinal research designs describe patterns of change and help establish the direction and magnitude of causal relationships. Measurements are taken on each variable over two or more distinct time periods. This allows the researcher to measure change in variables over time. It is a type of observational study sometimes referred to as a panel study.

• Longitudinal data facilitate the analysis of the duration of a particular phenomenon.
• Enables survey researchers to get close to the kinds of causal explanations usually attainable only with experiments.
• The design permits the measurement of differences or change in a variable from one period to another [i.e., the description of patterns of change over time].
• Longitudinal studies facilitate the prediction of future outcomes based upon earlier factors.
• The data collection method may change over time.
• Maintaining the integrity of the original sample can be difficult over an extended period of time.
• It can be difficult to show more than one variable at a time.
• This design often needs qualitative research data to explain fluctuations in the results.
• A longitudinal research design assumes present trends will continue unchanged.
• It can take a long period of time to gather results.
• There is a need to have a large sample size and accurate sampling to reach representativness.

Anastas, Jeane W. Research Design for Social Work and the Human Services . Chapter 6, Flexible Methods: Relational and Longitudinal Research. 2nd ed. New York: Columbia University Press, 1999; Forgues, Bernard, and Isabelle Vandangeon-Derumez. "Longitudinal Analyses." In Doing Management Research . Raymond-Alain Thiétart and Samantha Wauchope, editors. (London, England: Sage, 2001), pp. 332-351; Kalaian, Sema A. and Rafa M. Kasim. "Longitudinal Studies." In Encyclopedia of Survey Research Methods . Paul J. Lavrakas, ed. (Thousand Oaks, CA: Sage, 2008), pp. 440-441; Menard, Scott, editor. Longitudinal Research . Thousand Oaks, CA: Sage, 2002; Ployhart, Robert E. and Robert J. Vandenberg. "Longitudinal Research: The Theory, Design, and Analysis of Change.” Journal of Management 36 (January 2010): 94-120; Longitudinal Study. Wikipedia.

Meta-Analysis Design

Meta-analysis is an analytical methodology designed to systematically evaluate and summarize the results from a number of individual studies, thereby, increasing the overall sample size and the ability of the researcher to study effects of interest. The purpose is to not simply summarize existing knowledge, but to develop a new understanding of a research problem using synoptic reasoning. The main objectives of meta-analysis include analyzing differences in the results among studies and increasing the precision by which effects are estimated. A well-designed meta-analysis depends upon strict adherence to the criteria used for selecting studies and the availability of information in each study to properly analyze their findings. Lack of information can severely limit the type of analyzes and conclusions that can be reached. In addition, the more dissimilarity there is in the results among individual studies [heterogeneity], the more difficult it is to justify interpretations that govern a valid synopsis of results. A meta-analysis needs to fulfill the following requirements to ensure the validity of your findings:

• Clearly defined description of objectives, including precise definitions of the variables and outcomes that are being evaluated;
• A well-reasoned and well-documented justification for identification and selection of the studies;
• Assessment and explicit acknowledgment of any researcher bias in the identification and selection of those studies;
• Description and evaluation of the degree of heterogeneity among the sample size of studies reviewed; and,
• Justification of the techniques used to evaluate the studies.
• Can be an effective strategy for determining gaps in the literature.
• Provides a means of reviewing research published about a particular topic over an extended period of time and from a variety of sources.
• Is useful in clarifying what policy or programmatic actions can be justified on the basis of analyzing research results from multiple studies.
• Provides a method for overcoming small sample sizes in individual studies that previously may have had little relationship to each other.
• Can be used to generate new hypotheses or highlight research problems for future studies.
• Small violations in defining the criteria used for content analysis can lead to difficult to interpret and/or meaningless findings.
• A large sample size can yield reliable, but not necessarily valid, results.
• A lack of uniformity regarding, for example, the type of literature reviewed, how methods are applied, and how findings are measured within the sample of studies you are analyzing, can make the process of synthesis difficult to perform.
• Depending on the sample size, the process of reviewing and synthesizing multiple studies can be very time consuming.

Beck, Lewis W. "The Synoptic Method." The Journal of Philosophy 36 (1939): 337-345; Cooper, Harris, Larry V. Hedges, and Jeffrey C. Valentine, eds. The Handbook of Research Synthesis and Meta-Analysis . 2nd edition. New York: Russell Sage Foundation, 2009; Guzzo, Richard A., Susan E. Jackson and Raymond A. Katzell. “Meta-Analysis Analysis.” In Research in Organizational Behavior , Volume 9. (Greenwich, CT: JAI Press, 1987), pp 407-442; Lipsey, Mark W. and David B. Wilson. Practical Meta-Analysis . Thousand Oaks, CA: Sage Publications, 2001; Study Design 101. Meta-Analysis. The Himmelfarb Health Sciences Library, George Washington University; Timulak, Ladislav. “Qualitative Meta-Analysis.” In The SAGE Handbook of Qualitative Data Analysis . Uwe Flick, editor. (Los Angeles, CA: Sage, 2013), pp. 481-495; Walker, Esteban, Adrian V. Hernandez, and Micheal W. Kattan. "Meta-Analysis: It's Strengths and Limitations." Cleveland Clinic Journal of Medicine 75 (June 2008): 431-439.

Mixed-Method Design

• Narrative and non-textual information can add meaning to numeric data, while numeric data can add precision to narrative and non-textual information.
• Can utilize existing data while at the same time generating and testing a grounded theory approach to describe and explain the phenomenon under study.
• A broader, more complex research problem can be investigated because the researcher is not constrained by using only one method.
• The strengths of one method can be used to overcome the inherent weaknesses of another method.
• Can provide stronger, more robust evidence to support a conclusion or set of recommendations.
• May generate new knowledge new insights or uncover hidden insights, patterns, or relationships that a single methodological approach might not reveal.
• Produces more complete knowledge and understanding of the research problem that can be used to increase the generalizability of findings applied to theory or practice.
• A researcher must be proficient in understanding how to apply multiple methods to investigating a research problem as well as be proficient in optimizing how to design a study that coherently melds them together.
• Can increase the likelihood of conflicting results or ambiguous findings that inhibit drawing a valid conclusion or setting forth a recommended course of action [e.g., sample interview responses do not support existing statistical data].
• Because the research design can be very complex, reporting the findings requires a well-organized narrative, clear writing style, and precise word choice.
• Design invites collaboration among experts. However, merging different investigative approaches and writing styles requires more attention to the overall research process than studies conducted using only one methodological paradigm.
• Concurrent merging of quantitative and qualitative research requires greater attention to having adequate sample sizes, using comparable samples, and applying a consistent unit of analysis. For sequential designs where one phase of qualitative research builds on the quantitative phase or vice versa, decisions about what results from the first phase to use in the next phase, the choice of samples and estimating reasonable sample sizes for both phases, and the interpretation of results from both phases can be difficult.
• Due to multiple forms of data being collected and analyzed, this design requires extensive time and resources to carry out the multiple steps involved in data gathering and interpretation.

Burch, Patricia and Carolyn J. Heinrich. Mixed Methods for Policy Research and Program Evaluation . Thousand Oaks, CA: Sage, 2016; Creswell, John w. et al. Best Practices for Mixed Methods Research in the Health Sciences . Bethesda, MD: Office of Behavioral and Social Sciences Research, National Institutes of Health, 2010Creswell, John W. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . 4th edition. Thousand Oaks, CA: Sage Publications, 2014; Domínguez, Silvia, editor. Mixed Methods Social Networks Research . Cambridge, UK: Cambridge University Press, 2014; Hesse-Biber, Sharlene Nagy. Mixed Methods Research: Merging Theory with Practice . New York: Guilford Press, 2010; Niglas, Katrin. “How the Novice Researcher Can Make Sense of Mixed Methods Designs.” International Journal of Multiple Research Approaches 3 (2009): 34-46; Onwuegbuzie, Anthony J. and Nancy L. Leech. “Linking Research Questions to Mixed Methods Data Analysis Procedures.” The Qualitative Report 11 (September 2006): 474-498; Tashakorri, Abbas and John W. Creswell. “The New Era of Mixed Methods.” Journal of Mixed Methods Research 1 (January 2007): 3-7; Zhanga, Wanqing. “Mixed Methods Application in Health Intervention Research: A Multiple Case Study.” International Journal of Multiple Research Approaches 8 (2014): 24-35 .

Observational Design

This type of research design draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment. There are two general types of observational designs. In direct observations, people know that you are watching them. Unobtrusive measures involve any method for studying behavior where individuals do not know they are being observed. An observational study allows a useful insight into a phenomenon and avoids the ethical and practical difficulties of setting up a large and cumbersome research project.

• Observational studies are usually flexible and do not necessarily need to be structured around a hypothesis about what you expect to observe [data is emergent rather than pre-existing].
• The researcher is able to collect in-depth information about a particular behavior.
• Can reveal interrelationships among multifaceted dimensions of group interactions.
• You can generalize your results to real life situations.
• Observational research is useful for discovering what variables may be important before applying other methods like experiments.
• Observation research designs account for the complexity of group behaviors.
• Reliability of data is low because seeing behaviors occur over and over again may be a time consuming task and are difficult to replicate.
• In observational research, findings may only reflect a unique sample population and, thus, cannot be generalized to other groups.
• There can be problems with bias as the researcher may only "see what they want to see."
• There is no possibility to determine "cause and effect" relationships since nothing is manipulated.
• Sources or subjects may not all be equally credible.
• Any group that is knowingly studied is altered to some degree by the presence of the researcher, therefore, potentially skewing any data collected.

Atkinson, Paul and Martyn Hammersley. “Ethnography and Participant Observation.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, eds. (Thousand Oaks, CA: Sage, 1994), pp. 248-261; Observational Research. Research Methods by Dummies. Department of Psychology. California State University, Fresno, 2006; Patton Michael Quinn. Qualitiative Research and Evaluation Methods . Chapter 6, Fieldwork Strategies and Observational Methods. 3rd ed. Thousand Oaks, CA: Sage, 2002; Payne, Geoff and Judy Payne. "Observation." In Key Concepts in Social Research . The SAGE Key Concepts series. (London, England: Sage, 2004), pp. 158-162; Rosenbaum, Paul R. Design of Observational Studies . New York: Springer, 2010;Williams, J. Patrick. "Nonparticipant Observation." In The Sage Encyclopedia of Qualitative Research Methods . Lisa M. Given, editor.(Thousand Oaks, CA: Sage, 2008), pp. 562-563.

Philosophical Design

Understood more as an broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study. This approach uses the tools of argumentation derived from philosophical traditions, concepts, models, and theories to critically explore and challenge, for example, the relevance of logic and evidence in academic debates, to analyze arguments about fundamental issues, or to discuss the root of existing discourse about a research problem. These overarching tools of analysis can be framed in three ways:

• Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
• Epistemology -- the study that explores the nature of knowledge; for example, by what means does knowledge and understanding depend upon and how can we be certain of what we know?
• Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?
• Can provide a basis for applying ethical decision-making to practice.
• Functions as a means of gaining greater self-understanding and self-knowledge about the purposes of research.
• Brings clarity to general guiding practices and principles of an individual or group.
• Philosophy informs methodology.
• Refine concepts and theories that are invoked in relatively unreflective modes of thought and discourse.
• Beyond methodology, philosophy also informs critical thinking about epistemology and the structure of reality (metaphysics).
• Offers clarity and definition to the practical and theoretical uses of terms, concepts, and ideas.
• Limited application to specific research problems [answering the "So What?" question in social science research].
• Analysis can be abstract, argumentative, and limited in its practical application to real-life issues.
• While a philosophical analysis may render problematic that which was once simple or taken-for-granted, the writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
• There are limitations in the use of metaphor as a vehicle of philosophical analysis.
• There can be analytical difficulties in moving from philosophy to advocacy and between abstract thought and application to the phenomenal world.

Burton, Dawn. "Part I, Philosophy of the Social Sciences." In Research Training for Social Scientists . (London, England: Sage, 2000), pp. 1-5; Chapter 4, Research Methodology and Design. Unisa Institutional Repository (UnisaIR), University of South Africa; Jarvie, Ian C., and Jesús Zamora-Bonilla, editors. The SAGE Handbook of the Philosophy of Social Sciences . London: Sage, 2011; Labaree, Robert V. and Ross Scimeca. “The Philosophical Problem of Truth in Librarianship.” The Library Quarterly 78 (January 2008): 43-70; Maykut, Pamela S. Beginning Qualitative Research: A Philosophic and Practical Guide . Washington, DC: Falmer Press, 1994; McLaughlin, Hugh. "The Philosophy of Social Research." In Understanding Social Work Research . 2nd edition. (London: SAGE Publications Ltd., 2012), pp. 24-47; Stanford Encyclopedia of Philosophy . Metaphysics Research Lab, CSLI, Stanford University, 2013.

Sequential Design

• The researcher has a limitless option when it comes to sample size and the sampling schedule.
• Due to the repetitive nature of this research design, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• This is a useful design for exploratory studies.
• There is very little effort on the part of the researcher when performing this technique. It is generally not expensive, time consuming, or workforce intensive.
• Because the study is conducted serially, the results of one sample are known before the next sample is taken and analyzed. This provides opportunities for continuous improvement of sampling and methods of analysis.
• The sampling method is not representative of the entire population. The only possibility of approaching representativeness is when the researcher chooses to use a very large sample size significant enough to represent a significant portion of the entire population. In this case, moving on to study a second or more specific sample can be difficult.
• The design cannot be used to create conclusions and interpretations that pertain to an entire population because the sampling technique is not randomized. Generalizability from findings is, therefore, limited.
• Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Betensky, Rebecca. Harvard University, Course Lecture Note slides; Bovaird, James A. and Kevin A. Kupzyk. "Sequential Design." In Encyclopedia of Research Design . Neil J. Salkind, editor. (Thousand Oaks, CA: Sage, 2010), pp. 1347-1352; Cresswell, John W. Et al. “Advanced Mixed-Methods Research Designs.” In Handbook of Mixed Methods in Social and Behavioral Research . Abbas Tashakkori and Charles Teddle, eds. (Thousand Oaks, CA: Sage, 2003), pp. 209-240; Henry, Gary T. "Sequential Sampling." In The SAGE Encyclopedia of Social Science Research Methods . Michael S. Lewis-Beck, Alan Bryman and Tim Futing Liao, editors. (Thousand Oaks, CA: Sage, 2004), pp. 1027-1028; Nataliya V. Ivankova. “Using Mixed-Methods Sequential Explanatory Design: From Theory to Practice.” Field Methods 18 (February 2006): 3-20; Bovaird, James A. and Kevin A. Kupzyk. “Sequential Design.” In Encyclopedia of Research Design . Neil J. Salkind, ed. Thousand Oaks, CA: Sage, 2010; Sequential Analysis. Wikipedia.

Systematic Review

• A systematic review synthesizes the findings of multiple studies related to each other by incorporating strategies of analysis and interpretation intended to reduce biases and random errors.
• The application of critical exploration, evaluation, and synthesis methods separates insignificant, unsound, or redundant research from the most salient and relevant studies worthy of reflection.
• They can be use to identify, justify, and refine hypotheses, recognize and avoid hidden problems in prior studies, and explain data inconsistencies and conflicts in data.
• Systematic reviews can be used to help policy makers formulate evidence-based guidelines and regulations.
• The use of strict, explicit, and pre-determined methods of synthesis, when applied appropriately, provide reliable estimates about the effects of interventions, evaluations, and effects related to the overarching research problem investigated by each study under review.
• Systematic reviews illuminate where knowledge or thorough understanding of a research problem is lacking and, therefore, can then be used to guide future research.
• The accepted inclusion of unpublished studies [i.e., grey literature] ensures the broadest possible way to analyze and interpret research on a topic.
• Results of the synthesis can be generalized and the findings extrapolated into the general population with more validity than most other types of studies .
• Systematic reviews do not create new knowledge per se; they are a method for synthesizing existing studies about a research problem in order to gain new insights and determine gaps in the literature.
• The way researchers have carried out their investigations [e.g., the period of time covered, number of participants, sources of data analyzed, etc.] can make it difficult to effectively synthesize studies.
• The inclusion of unpublished studies can introduce bias into the review because they may not have undergone a rigorous peer-review process prior to publication. Examples may include conference presentations or proceedings, publications from government agencies, white papers, working papers, and internal documents from organizations, and doctoral dissertations and Master's theses.

Denyer, David and David Tranfield. "Producing a Systematic Review." In The Sage Handbook of Organizational Research Methods .  David A. Buchanan and Alan Bryman, editors. ( Thousand Oaks, CA: Sage Publications, 2009), pp. 671-689; Foster, Margaret J. and Sarah T. Jewell, editors. Assembling the Pieces of a Systematic Review: A Guide for Librarians . Lanham, MD: Rowman and Littlefield, 2017; Gough, David, Sandy Oliver, James Thomas, editors. Introduction to Systematic Reviews . 2nd edition. Los Angeles, CA: Sage Publications, 2017; Gopalakrishnan, S. and P. Ganeshkumar. “Systematic Reviews and Meta-analysis: Understanding the Best Evidence in Primary Healthcare.” Journal of Family Medicine and Primary Care 2 (2013): 9-14; Gough, David, James Thomas, and Sandy Oliver. "Clarifying Differences between Review Designs and Methods." Systematic Reviews 1 (2012): 1-9; Khan, Khalid S., Regina Kunz, Jos Kleijnen, and Gerd Antes. “Five Steps to Conducting a Systematic Review.” Journal of the Royal Society of Medicine 96 (2003): 118-121; Mulrow, C. D. “Systematic Reviews: Rationale for Systematic Reviews.” BMJ 309:597 (September 1994); O'Dwyer, Linda C., and Q. Eileen Wafford. "Addressing Challenges with Systematic Review Teams through Effective Communication: A Case Report." Journal of the Medical Library Association 109 (October 2021): 643-647; Okoli, Chitu, and Kira Schabram. "A Guide to Conducting a Systematic Literature Review of Information Systems Research."  Sprouts: Working Papers on Information Systems 10 (2010); Siddaway, Andy P., Alex M. Wood, and Larry V. Hedges. "How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, Meta-analyses, and Meta-syntheses." Annual Review of Psychology 70 (2019): 747-770; Torgerson, Carole J. “Publication Bias: The Achilles’ Heel of Systematic Reviews?” British Journal of Educational Studies 54 (March 2006): 89-102; Torgerson, Carole. Systematic Reviews . New York: Continuum, 2003.

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What really matters for successful research environments? A realist synthesis

Rola ajjawi.

1 Centre for Research in Assessment and Digital Learning (CRADLE), Deakin University, Geelong, Victoria, Australia

Paul E S Crampton

2 Research Department of Medical Education, University College London, London, UK

3 Monash Centre for Scholarship in Health Education (MCSHE), Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia

Charlotte E Rees

Associated data.

Table S2. MeSH terms and a selection of key terms utilised in the database searches.

Table S3. Inclusion and exclusion criteria with respect to topic, recentness and type of article.

Table S4. Refined inclusion and exclusion criteria to include contextual parameters.

Table S5. Studies by type: qualitative, quantitative and mixed‐methods.

Research environments, or cultures, are thought to be the most influential predictors of research productivity. Although several narrative and systematic reviews have begun to identify the characteristics of research‐favourable environments, these reviews have ignored the contextual complexities and multiplicity of environmental characteristics.

The current synthesis adopts a realist approach to explore what interventions work for whom and under what circumstances.

We conducted a realist synthesis of the international literature in medical education, education and medicine from 1992 to 2016, following five stages: (i) clarifying the scope; (ii) searching for evidence; (iii) assessing quality; (iv) extracting data, and (v) synthesising data.

We identified numerous interventions relating to research strategy, people, income, infrastructure and facilities (IIF), and collaboration. These interventions resulted in positive or negative outcomes depending on the context and mechanisms fired. We identified diverse contexts at the individual and institutional levels, but found that disciplinary contexts were less influential. There were a multiplicity of positive and negative mechanisms, along with three cross‐cutting mechanisms that regularly intersected: time; identity, and relationships. Outcomes varied widely and included both positive and negative outcomes across subjective (e.g. researcher identity) and objective (e.g. research quantity and quality) domains.

Conclusions

The interplay among mechanisms and contexts is central to understanding the outcomes of specific interventions, bringing novel insights to the literature. Researchers, research leaders and research organisations should prioritise the protection of time for research, enculturate researcher identities, and develop collaborative relationships to better foster successful research environments. Future research should further explore the interplay among time, identity and relationships.

Short abstract

This realist review shows when and why interventions related to research strategy; people; income, infrastructure and facilities; and collaboration result in positive or negative research environments. Findings indicate that protected time, researcher identities and collaborative relationships are important for fostering successful research environments.

Introduction

Research environments matter. Environmental considerations such as robust cultures of research quality and support for researchers are thought to be the most influential predictors of research productivity. 1 , 2 Over 25 years ago, Bland and Ruffin 1 identified 12 characteristics of research‐favourable environments in the international academic medicine literature spanning the period from the mid‐1960s to 1990 (Box 1 ). Although these characteristics are aspirational in flavour, how they interplay to influence research productivity within increasingly complex institutional structures is not yet known. Indeed, although existing reviews have begun to help us better understand what makes for successful research environments, this research has typically ignored the contextual complexities and multiplicity of environmental characteristics 1 , 3 , 4 , 5 , 6 , 7 and has focused on narrow markers of productivity such as the quantity of research outputs (e.g. ref. 7 ) The current realist synthesis, therefore, aims to address this gap in the research literature by reviewing more recent literature ( 1992–2016 ) and exploring the features of successful research environments in terms of which interventions work, for whom, how and in what circumstances.

Characteristics of successful research environments 1

• Clear organisational research goals
• Research productivity as a priority and at least equal priority to other activities
• A robust research culture with shared research values
• A positive group climate
• Participative governance structures
• Non‐hierarchical and decentralised structures
• Good communication and professionally meaningful relationships between team members
• Decent resources such as people, funding, research facilities and time
• Larger group size, moderately established teams and diversity
• Rewards for research success
• Recruitment and selection of talented researchers
• Research‐oriented leaders with research expertise and skill

The contextual background for understanding successful research environments

Against a backdrop of the mass production of education, reduced government funding for research and ‘new managerialist’ cultures in higher education, 8 , 9 increased scrutiny of the quantity and quality of research, the research environments in which research is produced and the impacts of research has become inevitable. 10 Indeed, in higher education institutions (HEIs) globally, research productivity is being measured as part of individual researcher and research group key performance indicators. 7 In many countries, such as Australia, Hong Kong, New Zealand and the UK, 11 HEI research is measured on a national scale through government‐led research assessments. Such research measurement has contributed to the allocation of funding to universities and differentiation of universities in the competitive marketplace, with some solidifying their institutional identities as ‘research‐intensive’ and others emphasising their relative ‘newcomer‐to‐research’ status (e.g. previously ‘teaching‐intensive’ universities). 9 , 12 , 13 Such institutional differentiation also parallels that of individual academics within universities, who are increasingly encouraged to take either ‘research‐active’ or ‘education‐focused’ career pathways. 8 , 9 It is these broader national and institutional constraints that inevitably impact on research environments at the level of units, centres, departments and schools within universities (the level of ‘research environment’ that we focus on in this paper). Table S1 provides definitions of key terms.

Key features of research environments identified in previous reviews

Evans defines a research environment as including: ‘shared values, assumptions, beliefs, rituals and other forms of behaviour whose central focus is the acceptance and recognition of research practice and output as valued, worthwhile and pre‐eminent activity.’ 14 Previous reviews have tended to focus on interventions aimed at individual researchers, such as research capacity building, 4 , 5 , 7 and with individual‐level outcomes, such as increased numbers of grants or publications. 4 , 5 , 7 These reviews have typically concluded that research capacity‐building interventions lead to positive research outcomes. 4 , 5 , 7 Furthermore, the reviews have identified both individual and institutional enablers to research. Individual enablers included researchers’ intrinsic motivation to conduct research. 6 , 7 Institutional enablers included peer support, encouragement and review, 7 mentoring and collaboration, 4 , 5 research leadership, 5 , 6 institutional structures, processes and systems supporting research, such as clear strategy, 5 , 6 protected time and financial support. 5 Although these reviews have begun to shed light on the features of successful research environments, they have significant limitations: (i) they either include studies of low to moderate quality 4 , 5 or fail to check the quality of studies included, 7 and (ii) they do not explore what works for whom and under what circumstances, but instead focus on what works and ignore the influence of the context in which interventions are implemented and ‘how’ outcomes come about. Indeed, Mazmanian et al. 4 concluded in their review: ‘…little is known about what works best and in what situations.’

Conceptual framework: a realist approach

Given the gaps in the research literature and the importance of promoting successful research environments for individuals’ careers, institutional prestige and the knowledge base of the community, we thought a realist synthesis would be most likely to elucidate how multiple complex interventions can influence success. Realism assumes the existence of an external reality (a real world), but one that is filtered (i.e. perceived, interpreted and responded to) through human senses, volitions, language and culture. 15 A realist approach enables the development and testing of theory for why interventions may or may not work, for whom and under what circumstances. 16 It does this through recognising that interventions do not directly cause outcomes; instead, participants’ reactions and responses to the opportunities provided by the intervention trigger outcomes. This approach can allow researchers to identify causal links in complex situations, such as those between interventions and the contexts in which they work, how they work (mechanisms) and their outcomes. 17 Although the context–mechanism–outcome (CMO) approach is not necessarily linear, it can help to provide explanations that privilege contextual variability. 18

Aligned with the goals of realist research, this synthesis aims to address the following research question: What are the features of successful research environments, for whom, how and in what circumstances?

We followed five stages of realist synthesis: (i) clarifying scope; (ii) searching for evidence; (iii) assessing quality; (iv) extracting data, and (v) synthesising data. 19 Our methods also follow the RAMESES ( r ealist a nd m eta‐narrative e vidence s ynthesis: e volving s tandards) reporting guidelines. 20

Clarifying the scope

We first clarified the scope of our realist synthesis by identifying relevant interventions based on the Research Excellence Framework (REF) 2014 environment assessment criteria. The REF is a national exercise assessing the quality of research produced by UK HEIs, its impact beyond academia, and the environment that supports research. The assessment criteria indicated in the REF2014 environment template included the unit's research strategy , its people (including staffing strategy, staff development and research students), its income, infrastructure and facilities (IIF), as well as features of collaboration . 21 These guided our search terms (see stage 2 below). We chose to use these quality markers as they informed the UK national assessment exercise, upon which other national exercises are often based. In addition, these criteria were explicit, considered and implementable, and were developed through consensus. Like other realist syntheses, 18 , 22 , 23 ours considered a multiplicity of different interventions rather than just one and some of the papers we reviewed combined multiple interventions.

Based on previous reviews, 1 , 4 , 5 , 7 our initial programme theory speculated that interventions aligned to having an explicit research strategy, staff development opportunities, funding and establishing research networks would be effective for creating successful research environments (Fig. ​ (Fig.1 1 gives further details of our initial programme theory).

Initial programme theory

Searching for empirical evidence

We devised search terms as a team and refined these iteratively with the help of a health librarian experienced in searching. We split the research question into three key concepts: (i) research environment; (ii) discipline, and (iii) research indicator (i.e. positive or negative). We then used variations of these terms to search the most relevant databases including MEDLINE, ProQuest, Scopus, CINAHL (Cumulative Index to Nursing and Allied Health Literature) and Web of Science. Table S2 illustrates the MeSH terms and provides a selection of key terms utilised in the database searches.

We were interested in comparing research cultures across the disciplines of medical education, education and medicine for two key reasons. Firstly, the discipline of medical education consists of a rich tapestry of epistemological approaches including biomedical sciences, social sciences and education, and medicine. 24 , 25 Secondly, there have been disciplinary arguments in the literature about whether medical education should be constructed as medicine or social science. 24 , 26

We agreed various inclusion and exclusion criteria with respect to topic, recentness and type of article (Table S3 ), as well as refined criteria to include contextual parameters (Table S4 ). We chose 1992 as the start date for our search period as 1992 saw the first published literature review about productive research environments in the academic medicine literature. 1

Study selection

The first top‐level search elicited 8527 journal articles across all databases. Once duplicate results had been removed, and ‘topic’ and ‘recentness’ study parameters reinforced, 420 articles remained. The searching and selection process is summarised in a PRISMA ( p referred r eporting i tems for s ystematic reviews and m eta‐ a nalyses) diagram (Fig. ​ (Fig.2). 2 ). Three research assistants and one of the authors (PESC) initially assessed relevance by reviewing abstracts using preliminary inclusion criteria. If any ambiguities were found by any of the reviewers, abstracts were checked by one of the other two researchers (RA and CER). Where divergent views existed, researchers discussed the reasons why and agreed on whether to include or exclude. A 10% sample of these 420 abstracts were double‐checked by an additional two researchers, including a number of articles previously excluded, for quality control purposes.

PRISMA flow diagram of the selection process

Assessment of quality

We assessed the journal articles for relevance and rigour. 20 We defined an article's relevance according to ‘whether it can contribute to theory building and/or testing’. 20 Following the relevance check and ‘type’ exclusions to original research papers, 100 articles remained, which were then assessed for rigour. Although we chose to narrow down to original research, we kept relevant articles such as systematic reviews and opinion pieces to inform the introduction and discussion sections of this paper.

We defined rigour as determining ‘whether the method used to generate the particular piece of data is credible and trustworthy’. 20 We used two pre‐validated tools to assess study quality: the Medical Education Research Study Quality Instrument (MERSQI) to assess the quality of quantitative research, 27 , 28 and the Critical Appraisal Skills Programme (CASP) qualitative checklist for qualitative and mixed‐method studies. 29 Both tools are used to consider the rigour of study design, sampling, type of data, data analysis and outcomes/findings, and have been employed in previous reviews. 23 , 30

Following the quality assessment, 47 articles remained and were then subjected to data extraction and synthesis. Five papers were excluded as they did not contribute to our theory building or lacked CMO configurations (CMOCs). We kept notes of the reasons for excluding studies and resolved doubts through discussion (Fig. ​ (Fig.2 2 ).

Data extraction

Two data‐rich articles containing multiple CMOCs were inductively and deductively (based on the initial programme theory) coded by all of us to ensure consistency. We then discussed any similarities and differences in our coding. As is inherent in the challenges of realist approaches, we found differences in our identifications of CMOCs, which often related to how one particular component (e.g. time) could be an outcome at one moment and a mechanism the next. This alerted us to overlapping constructs, which we then explored as we coded remaining papers. To collect data across all remaining papers, we extracted information relating to: study design, methods and sample size; study setting; intervention focus; contexts of the intervention; mechanisms generated in the results, and outcomes. The key CMOCs in all 42 articles were identified primarily from the results sections of the papers. The process of data extraction and analysis was iterative with repeated discussion among the researchers of the demi‐regularities (i.e. patterns of CMOCs) in relation to the initial programme theory and negotiations of any differences of opinion.

Data synthesis

Finally, we interrogated our data extraction to look for patterns across our data/papers. We used an interpretative approach to consider how our data compared with our initial programme theory in order to develop our modified programme theory.

Characteristics of the studies

The 42 papers represented the following disciplines: medical education ( n = 4, 10%); 31 , 32 , 33 , 34 education ( n = 18, 43%), 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 and medicine ( n = 20, 48%). 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 There were 26 (62%) qualitative studies, 11 (26%) quantitative studies and five (12%) mixed‐methods studies (Table S5 ). The studies were from countries across the globe, including Australia ( n = 10, 24%), the USA ( n = 7, 17%), the UK ( n = 6, 14%), Canada ( n = 4, 10%), South Africa ( n = 4, 10%), Denmark ( n = 2, 5%), Turkey ( n = 2, 5%) and others ( n = 7, 17%) (e.g. Belgium, China, Germany, New Zealand and the Philippines). The research designs varied but common approaches included qualitative interviews, surveys, documentary/bibliographic analysis, case studies and mixed‐methods studies. Study participants included academics, teachers, health care professionals, senior directors, PhD students, early‐career researchers (ECRs) and senior researchers. Table S6 lists the individual contexts, interventions, mechanisms and outcomes identified from individual papers.

Extending our initial programme theory

A key finding from our realist synthesis was that the same interventions fired either positive or negative mechanisms leading to positive or negative outcomes, respectively, depending on context. Surprisingly, the CMOCs were mostly consistent across the three disciplines (i.e. medical education, education and medicine) with local contexts seemingly interplaying more strongly with outcomes. Therefore, we present these disciplinary contexts here as merged, but we highlight any differences by disciplinary context where relevant.

Having a research strategy promoted a successful research environment when it enabled appropriate resources (including time) and valuing of research; however, it had negative consequences when it too narrowly focused on outputs, incentives and rewards. In terms of people , individual researchers needed to be internally motivated and to have a sense of belonging, and protected time and access to capacity‐building activities in order to produce research. Lack of knowledge, researcher identity, networks and time, plus limited leadership support, acted as mechanisms leading to negative research outcomes. The presence of IIF was overwhelmingly indicated as necessary for successful research environments and their absence was typically detrimental. Interestingly, a few papers reported that external funding could have negative consequences because short‐term contracts, reduced job security and the use of temporary junior staff can lead to weak research environments. 40 , 67 , 71 Finally, collaboration was crucial for successful research mediated through trusting respectful relationships, supportive leadership and belongingness. Poor communication and competitive cultures, however, worked to undermine collaboration, leading to isolation and low self‐esteem, plus decreased research engagement and productivity. Table ​ Table1 1 highlights illustrative CMOCs for each intervention extending our initial programme theory.

Positive and negative context–mechanism–outcome configurations (CMOCs) for each intervention

CMOCs indicated in bold highlight the three cross‐cutting themes of time, identity and relationships.

ECRs = early‐career researchers.

Key cross‐cutting mechanisms: time, identity and relationships

As Table ​ Table1 1 shows, the same intervention can lead to positive or negative outcomes depending on the particular contexts and mechanisms triggered. This highlights greater complexity than is evident at first glance. Cross‐cutting these four interventions were three mechanisms that were regularly identified as critical to the success (or not) of a research environment: time; researcher identities, and relationships. We now present key findings for each of these cross‐cutting mechanisms and discuss how their inter‐relations lead to our modified programme theory (Fig. ​ (Fig.3). 3 ). Note that although we have tried to separate these three mechanisms for ease of reading, they were often messily entangled. Table ​ Table2 2 presents quotes illustrating the way in which each mechanism mediates outcomes within particular circumstances.

Modified programme theory. ECR = early‐career researcher

Time, identity and relationships as cross‐cutting mechanisms mediating successful research environments

Time was identified as an important mechanism for mobilising research outcomes across our three disciplines. Time was conceptualised severally including as: protected time; workload pressures influencing time available; efficient use of time; flexible use of time; making time, and time in career. The two most commonly considered aspects were protected time and workload implications. Protected time was largely talked about in the negative across a variety of contexts and disciplines, with lack of protected time leading to lack of researcher engagement or inactivity and reduced research productivity. 32 , 35 , 37 , 41 , 44 , 47 , 49 , 61 , 62 , 63 , 67 Also across a variety of contexts and disciplines, and acting as a positive mechanism, available protected time was found to lead to increased research productivity and active research engagement. 31 , 36 , 40 , 48 , 49 , 63 , 65 With regard to workload, limitations on the time available for research imposed by excessive other workloads led to reduced research activity, lower research productivity, poor‐quality research and reduced opportunity to attend research training. 40 , 41 , 47 , 49 , 60 , 67 Juggling of multiple responsibilities, such as clinical, teaching, administrative and leadership roles, also inhibited research productivity by diminishing the time available for research. 35 , 40 , 49 The alignment of research with other non‐research work was described as driving efficiencies in the use of time leading to greater research productivity (Table ​ (Table2, 2 , quote 1).

Identity was also an important mechanism for mobilising research outcomes across our three disciplines. Interpretations included personal identities (e.g. gender), professional identity (e.g. as a primary practitioner or a primary researcher), and social identity (e.g. sense of belongingness). Researcher identity was often referred to in relation to first‐career practitioners (and therefore second‐career researchers). Sharp et al. 48 defined these as participants recruited into higher education not directly from doctoral study but on the basis of their extensive ‘first‐order’ knowledge and pedagogical expertise. These were also practitioners conducting research in schools or hospitals. Identities were also referenced in relation to early, mid‐career or senior researchers. Academic staff working in academic institutions needed to develop a sense of researcher identity, belongingness, self‐efficacy for research and autonomy to increase their satisfaction, competence and research activity. 39 , 40 , 44 , 46 , 51 , 67 For first‐career practitioners (i.e. teachers, doctors), the research needed to be highly relevant and aligned to their primary identity work in order to motivate them. 53 , 59 , 62 , 65 This alignment was described as having a strong research–teaching nexus. 40 , 48 Linked to this concept was the need for first‐career practitioners to see the impact of research in relation to their primary work (e.g. patient‐ or student‐oriented) to facilitate motivation and to develop a researcher identity (Table ​ (Table2, 2 , quote 2). 36 , 37 , 41 , 49 , 53 , 54 , 67 Where research was seen as irrelevant to primary identity work (e.g. English language teaching, general practice), there was research disengagement. 37 , 48 , 52 , 59 , 67

Relationships

For all researchers and across our three disciplines, relationships were important in the mediating of successful research environments. 31 , 34 , 38 , 39 , 41 , 44 , 57 , 60 , 66 , 67 Positive research relationships were characterised by mutual trust and respect, 40 , 41 , 42 , 43 , 54 , 66 , 72 whereas others described them as friendships that take time to develop. 51 Mutually supportive relationships seemed to be particularly relevant to ECRs in terms of developing confidence, self‐esteem and research capacity and making identity transitions. 35 , 43 , 48 , 58 , 67 Relationships in the form of networks were considered to improve the quality of research through multicentre research and improved collaboration. 33 , 60 Supportive leadership as a particular form of relationship was an important mechanism in promoting a successful research environment. Supportive leaders needed to monitor workloads, set the vision, raise awareness of the value of research, and provide positive role‐modelling, thereby leading to increased productivity, promoting researcher identities and creating thriving research environments (Table ​ (Table2, 2 , quote 3). 31 , 34 , 37 , 38 , 40 , 41 , 43 , 44 , 46 , 48 , 49 , 53 , 55 , 62 Research leadership, however, could be influenced negatively by the context of compliance and counting in current university cultures damaging relationships, creating a loss of motivation, and raising feelings of devalue. Indeed, the failure of leaders to recognise researcher identities led to negative research productivity. 36 , 37 , 38 , 43 , 46 , 48 , 49

Intersections between time, identity and relationships within successful research environments

Time and identity.

Time and identity intersected in interesting ways. Firstly, time was a necessary enabler for the development of a researcher identity. 37 , 38 , 41 , 48 , 49 , 54 , 59 , 61 , 63 , 65 , 67 , 69 Secondly, those who identified as researchers (thus holding primary researcher identities) used their time efficiently to favour research activity outcomes despite a lack of protected time. 35 , 43 Conversely, for other professors who lacked personal determination and resilience for research, having protected time did not lead to better research activity. 43 This highlights the fact that time alone is insufficient to support a successful research environment, and that it is how time is utilised and prioritised by researchers that really matters (Table ​ (Table2, 2 , quote 4).

Identity and relationships

Interventions aimed at developing researcher identity consistently focused on relationship building across the three disciplines. The interventions that supported identity transitions into research included formal research training, 44 , 48 , 52 , 68 mentoring, 41 , 48 , 57 , 65 , 72 writing groups, 72 and collaboration with peers and other researchers, 39 , 41 , 43 operating through multiple mechanisms including relationships. The mechanisms included self‐esteem/confidence, increased networks, external recognition as a researcher, belongingness, and self‐efficacy. 35 , 41 , 43 , 44 , 45 , 52 , 57 Furthermore, our data suggest that leadership can be an enabler to the development of a researcher identity. In particular, leadership enabled research autonomy, recognition and empowerment, and fostered supportive mentoring environments, leading to researcher identity development and research productivity (Table ​ (Table2, 2 , quote 5). 34 , 38 , 46 , 48

Time and relationships

Relationships were developed and sustained over time (Table ​ (Table2, 2 , quote 6). Across the three disciplines, the role of leaders (managers, directors, deans) was to acknowledge and raise awareness of research, and then to prioritise time for research against competing demands, leading to effective research networks, cohesion and collaboration. 31 , 34 , 38 , 43 , 46 , 48 , 49 , 50 , 53 , 55 , 70 Second‐career PhD students who did not invest time in establishing relationships with researchers in their new disciplines (as they already had strong supportive networks in their original disciplines) found that they had limited research networks following graduation. 48

Summary of key findings

Our initial programme theory was based on previous literature reviews 1 , 4 , 5 , 6 , 7 and on the REF2014 criteria. 10 , 21 However, we were able to develop a modified programme theory on the basis of our realist synthesis, which highlights novel findings in terms of what really matters for successful research environments. Firstly, we found that key interventions led to both positive (subjective and objective) and negative (subjective and objective) outcomes in various contexts. Interestingly, we did not identify any outcomes relating to research impact despite impact nowadays being considered a prominent marker of research success, alongside quantitative metrics such as number of publications, grant income and h‐indices. 21 Secondly, we found that disciplinary contexts appeared to be less influential than individual, local and institutional contexts. Finally, our modified programme theory demonstrates a complex interplay among three cross‐cutting mechanisms (time, researcher identity and relationships) as mechanisms underpinning both successful and unsuccessful research environments.

Key findings and comparisons with the existing literature

Our research supports the findings of earlier reviews 1 , 5 , 6 , 7 regarding the importance of having a clear research strategy, an organisation that values research, research‐oriented leadership, access to resources (such as people, funding, research facilities and time), and meaningful relationships. However, our research extends these findings considerably by flagging up the indication that a clear linear relationship, whereby the presence of these interventions will necessarily result in a successful research environment, does not exist. For example, instituting a research strategy can have negative effects if the indicators are seen as overly narrow in focus or output‐oriented. 38 , 40 , 46 , 47 , 64 Similarly, project money can lead to the employment of more part‐time staff on fixed‐term contracts, which results in instability, turnover and lack of research team expertise. 40 , 67 , 71

Our findings indicate that the interplays among time, identity and relationships are important considerations when implementing interventions promoting research environments. Although time was identified as an important mechanism affecting research outcomes within the majority of papers, researcher identity positively affected research outcomes even in time‐poor situations. Indeed, we found that identity acted as a mechanism for research productivity that could overcome limited time through individuals efficiently finding time to prioritise research through their motivation and resilience. 35 , 43 Time was therefore more than just time spent doing research, but also included investment in developing a researcher identity and relationships with other researchers over time. 37 , 38 , 41 , 48 , 49 , 54 , 59 , 61 , 63 , 67 , 69 Relationship‐building interventions were also found to be effective in supporting difficult identity transitions into research faced by ECRs and those with first‐career practitioner backgrounds. Supportive leadership, as a particular form of relationship, could be seen as an enabler to the provision of protected time and a reasonable workload, allowing time for research and for researcher identity formation. 34 , 38 , 46 , 48 Indeed, our realist synthesis findings highlight the central importance of researcher identity and thus offer a novel explanation for why research environments may not flourish even in the presence of a research strategy, resources (e.g. time) and valuing of research.

Researcher identity is complex and intersects with other identities such as those of practitioner, teacher, leader and so on. Brew et al. 39 , 73 , 74 explored researcher identification and productivity by asking researchers if they considered themselves to be ‘research‐active’ and part of a research team. Those who identified as researchers prioritised their work differently: those who were highly productive prioritised research, whereas those in the low‐productivity group prioritised teaching. 73 Interestingly, highly productive researchers tended to view research as a social phenomenon with publications, presentations and grants being ‘traded’ in academic networks. Brew et al. 39 explain that: ‘…the trading view relates to a self‐generating researcher identity. Researcher identity develops in the act of publication, networks, collaborations and peer review. These activities support a person's identification as a researcher. They also, in turn, influence performance measures and metrics.’ Although the relationships among identity, identification and productivity are clearly complex, we explored a broader range of metrics in our realist synthesis than just productivity.

Methodological strengths and limitations

This is the first study to explore this important topic using realist synthesis to better understand the influence of context and how particular interventions lead to outcomes. We followed RAMESES 20 guidelines and adopted a rigorous team‐based approach to each analytic stage, conducting regular quality checks. The search was not exhaustive as we could have ‘exploded’ the interventions and performed a comprehensive review of each in its own right (e.g. mentoring). However, for pragmatic reasons and to answer our broad research questions, we chose not to do this, as suggested by Wong et al. 20 Although all members of the team had been involved in realist syntheses previously, the process remained messy as we dealt with complex phenomena. The messiness often lies in untangling CMOCs and identifying recurrent patterns in the large amounts of literature reviewed.

Implications for education and research

Our findings suggest that interventions related to research strategy, people, IIF and collaboration are supported under the ‘right’ conditions. We need to focus on time, identity and relationships (including leadership) in order to better mobilise the interventions to promote successful research environments.

Individuals need to reflect on how and why they identify as researchers, including their conceptions of research and their working towards the development of a researcher identity such that research is internally motivated rather than just externally driven. Those who are second‐career researchers or those with significant teaching or practitioner roles could seek to align research with their practice while they establish wider research networks.

We recommend that research leaders support individuals to develop their researcher identity, be seen to value research, recognise that research takes time, and provide access to opportunities promoting research capacity building, strong relationships and collaboration. Leaders, for example, may introduce interventions that promote researcher identities and build research relationships (e.g. collaborations, networking, mentoring, research groups etc.), paying attention to the ways in which competitive or collaborative cultures are fostered. Browne et al. 75 recently recommended discussions around four categories for promoting identity transition: reflection on self (values, experiences and expectations); consideration of the situation (circumstances, concerns); support (what is available and what is needed), and strategies (personal strategies to cope with change and thrive). With the professionalisation of medical education, 76 research units are increasingly likely to contain a mixture of first‐ and second‐career researchers, and our review suggests that discussions about conceptions of research and researcher identity would be valuable.

Finally, organisations need to value research and provide access to resources and research capacity‐building activities. Within the managerialist cultures of HEIs, compliance and counting have already become dominant discourses in terms of promotion and success. Policymakers should therefore consider ways in which HEIs recognise, incentivise and reward research in all its forms (including subjective and objective measures of quantity, quality and impact) to determine the full effects of their policies on research environments.

Future research would benefit from further exploration of the interplay among time, identities and relationships (including leadership) in different contexts using realist evaluation. 77 Specifically, as part of realist approaches, longitudinal audio‐diaries 78 could be employed to explore researcher identity transitions over time, particularly for first‐career practitioners transitioning into second‐career researchers.

Contributors

RA and CER were responsible for the conception of the synthesis. All authors contributed to the protocol development. RA and PESC carried out the database searches. All authors sifted for relevance and rigour, analysed the papers and contributed to the writing of the article. All authors approved the final manuscript for publication.

Conflicts of interest

Ethical approval.

not required.

Supporting information

Table S1. Definitions of key terms.

Table S6. Contexts, interventions, mechanisms and outcomes identified in individual studies.

Acknowledgements

we thank Andy Jackson, Learning and Teaching Librarian, University of Dundee, Dundee, UK, for his advice and help in developing our literature searches. We also thank Laura McDonald, Paul McLean and Eilidh Dear, who were medical students at the University of Dundee, for their help with database searches and with sifting papers for relevance and rigour. We would also like to thank Chau Khuong, Australian Regenerative Medicine Institute, Monash University, Melbourne, Victoria, Australia, for her work in designing Figs ​ Figs1 1 and ​ and3 3 .

How to Choose, Develop, & Research a Setting: Part 1

Setting is far more than the backdrop of a novel. It’s the environment that breathes life into a story. It can paint hues of emotion, provide necessary backstory, enhance characterization, and serve as a tool to unfold significant plot elements.

When a writer prepares to write a book, they should spend just as much time researching and developing a setting as they do with their characters. In fact, setting should be treated with much attention as if it were a character in itself.

Think of your favorite book. How would the plot differ if it were set in the snow-capped mountains of Colorado? Or in a dry desert of New Mexico?

When a writer accurately portrays a believable setting for their novel, the reader becomes sucked into the story. This should be done in a way so that the story would not be the same if it were set in another location.

For example: The setting is a crucial element in the movie The Titanic . It would be impossible to set that story in another location; the entire plot would unravel.

Readers fall in love with books that present well-developed settings and story worlds. What would The Chronicles of Narnia be without Narnia? Or Anne of Green Gables without Green Gables?

When choosing a setting, ask yourself:

•  What is the mood and theme of this story? What kind of location—a small town, big city, etc.—would best portray this?
•  How will the setting affect the plot of the story?
•  Will I use a real town or invent one?
•  What cities—including my hometown— am I familiar with? Out of those, which one am I most passionate about?
•  How can I weave symbolism into this setting?
•  How does the setting influence my protagonist? What is his/her attitude toward this location? 
(This is a great way to unravel backstory — through showing the memories tied to her surroundings.)

I chose Lake Lure, NC for the setting of Purple Moon for the following reasons:

•  I realized I had yet to read a YA novel that was set in the Blue Ridge mountains of North Carolina.
•  I knew I wanted to set the story in the south since I am from SC.
•  I came across a photograph of the mountains outlining a lake. This inspired me to do a Google search of lakes in North Carolina.
•  After I found a list, I chose Lake Lure because the name reflected a theme in the novel.
•  Since my protagonist is an artist, the mountains tucked into the lake keeps her inspired and reflects her personality.

If you want your readers to become swept away in your story, it’s crucial that you spend necessary time researching your setting before you begin to write.

It’s important to research your setting for the following reasons:

• Believability
•  So your readers can feel as if they have stepped into 
the pages of your book. You want to give them the sense 
that they are living in the story.
•  To prevent your story from unfolding in front of a “closed 
curtain”.

In the next post, we’ll discuss how to go about researching your setting and how to filter it through the eyes of your protagonist.

What is your favorite story setting? How does it enhance the plot, theme, mood, and protagonist of the novel?

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How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

Need a helping hand?

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications . If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

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Can you help me with a full paper template for this Abstract:

Background: Energy and sports drinks have gained popularity among diverse demographic groups, including adolescents, athletes, workers, and college students. While often used interchangeably, these beverages serve distinct purposes, with energy drinks aiming to boost energy and cognitive performance, and sports drinks designed to prevent dehydration and replenish electrolytes and carbohydrates lost during physical exertion.

Objective: To assess the nutritional quality of energy and sports drinks in Egypt.

Material and Methods: A cross-sectional study assessed the nutrient contents, including energy, sugar, electrolytes, vitamins, and caffeine, of sports and energy drinks available in major supermarkets in Cairo, Alexandria, and Giza, Egypt. Data collection involved photographing all relevant product labels and recording nutritional information. Descriptive statistics and appropriate statistical tests were employed to analyze and compare the nutritional values of energy and sports drinks.

Results: The study analyzed 38 sports drinks and 42 energy drinks. Sports drinks were significantly more expensive than energy drinks, with higher net content and elevated magnesium, potassium, and vitamin C. Energy drinks contained higher concentrations of caffeine, sugars, and vitamins B2, B3, and B6.

Conclusion: Significant nutritional differences exist between sports and energy drinks, reflecting their intended uses. However, these beverages’ high sugar content and calorie loads raise health concerns. Proper labeling, public awareness, and responsible marketing are essential to guide safe consumption practices in Egypt.

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How to Write a Research Paper

If you already have a headache trying to understand what research paper is all about, we have created an ultimate guide for you on how to write a research paper. You will find all the answers to your questions regarding structure, planning, doing investigation, finding the topic that appeals to you. Plus, you will find out the secret to an excellent paper. Are you at the edge of your seat? Let us start with the basics then.

• What is a Research Paper
• Reasons for Writing a Research Paper
• Report Papers and Thesis Papers
• How to Start a Research Paper
• How to Choose a Topic for a Research Paper
• How to Write a Proposal for a Research Paper
• How to Write a Research Plan
• How to Do Research
• How to Write an Outline for a Research Paper
• How to Write a Thesis Statement for a Research Paper
• How to Write a Research Paper Rough Draft
• How to Write an Introduction for a Research Paper
• How to Write a Body of a Research Paper
• How to Write a Conclusion for a Research Paper
• How to Write an Abstract for a Research Paper
• How to Revise and Edit a Research Paper
• How to Write a Bibliography for a Research Paper
• What Makes a Good Research Paper

Research Paper Writing Services

What is a research paper.

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You probably know the saying ‘the devil is not as black as he is painted’. This particular saying is absolutely true when it comes to writing a research paper. Your feet are cold even with the thought of this assignment. You have heard terrifying stories from older students. You have never done this before, so certainly you are scared. What is a research paper? How should I start? What are all these requirements about?

Luckily, you have a friend in need. That is our writing service. First and foremost, let us clarify the definition. A research paper is a piece of academic writing that provides information about a particular topic that you’ve researched . In other words, you choose a topic: about historical events, the work of some artist, some social issues etc. Then you collect data on the given topic and analyze it. Finally, you put your analysis on paper. See, it is not as scary as it seems. If you are still having doubts, whether you can handle it yourself, we are here to help you. Our team of writers can help you choose the topic, or give you advice on how to plan your work, or how to start, or craft a paper for you. Just contact us 24/7 and see everything yourself.

5 Reasons for Writing a Research Paper

Why should I spend my time writing some academic paper? What is the use of it? Is not some practical knowledge more important? The list of questions is endless when it comes to a research paper. That is why we have outlined 5 main reasons why writing a research paper is a good thing.

• You will learn how to organize your time

If you want to write a research paper, you will have to learn how to manage your time. This type of assignment cannot be done overnight. It requires careful planning and you will need to learn how to do it. Later, you will be able to use these time-managing skills in your personal life, so why not developing them?

• You will discover your writing skills

You cannot know something before you try it. This rule relates to writing as well. You cannot claim that you cannot write until you try it yourself. It will be really difficult at the beginning, but then the words will come to your head themselves.

• You will improve your analytical skills

Writing a research paper is all about investigation and analysis. You will need to collect data, examine and classify it. These skills are needed in modern life more than anything else is.

• You will gain confidence

Once you do your own research, it gives you the feeling of confidence in yourself. The reason is simple human brain likes solving puzzles and your assignment is just another puzzle to be solved.

• You will learn how to persuade the reader

When you write your paper, you should always remember that you are writing it for someone to read. Moreover, you want this someone to believe in your ideas. For this reason, you will have to learn different convincing methods and techniques. You will learn how to make your writing persuasive. In turns, you will be able to use these methods in real life.

What is the Difference between Report and Thesis Papers?

A common question is ‘what is the difference between a report paper and a thesis paper?’ The difference lies in the aim of these two assignments. While the former aims at presenting the information, the latter aims at providing your opinion on the matter. In other words, in a report paper you have to summarize your findings. In a thesis paper, you choose some issue and defend your point of view by persuading the reader. It is that simple.

A thesis paper is a more common assignment than a report paper. This task will help a professor to evaluate your analytical skills and skills to present your ideas logically. These skills are more important than just the ability to collect and summarize data.

How to Write a Research Paper Step by Step

Research comes from the French word  rechercher , meaning “to seek out.” Writing a research paper requires you to seek out information about a subject, take a stand on it, and back it up with the opinions, ideas, and views of others. What results is a printed paper variously known as a term paper or library paper, usually between five and fifteen pages long—most instructors specify a minimum length—in which you present your views and findings on the chosen subject.

It is not a secret that the majority of students hate writing a research paper. The reason is simple it steals your time and energy. Not to mention, constant anxiety that you will not be able to meet the deadline or that you will forget about some academic requirement.

We will not lie to you; a research paper is a difficult assignment. You will have to spend a lot of time. You will need to read, to analyze, and to search for the material. You will probably be stuck sometimes. However, if you organize your work smart, you will gain something that is worth all the effort – knowledge, experience, and high grades.

The reason why many students fail writing a research paper is that nobody explained them how to start and how to plan their work. Luckily, you have found our writing service and we are ready to shed the light on this dark matter.

We have created a step by step guide for you on how to write a research paper. We will dwell upon the structure, the writing tips, the writing strategies as well as academic requirements. Read this whole article and you will see that you can handle writing this assignment and our team of writers is here to assist you.

How to Start a Research Paper?

It all starts with the assignment. Your professor gives you the task. It may be either some general issue or specific topic to write about. Your assignment is your first guide to success. If you understand what you need to do according to the assignment, you are on the road to high results. Do not be scared to clarify your task if you need to. There is nothing wrong in asking a question if you want to do something right. You can ask your professor or you can ask our writers who know a thing or two in academic writing.

It is essential to understand the assignment. A good beginning makes a good ending, so start smart.

Learn how to start a research paper .

Choosing a Topic for a Research Paper

We have already mentioned that it is not enough to do great research. You need to persuade the reader that you have made some great research. What convinces better that an eye-catching topic? That is why it is important to understand how to choose a topic for a research paper.

First, you need to delimit the general idea to a more specific one. Secondly, you need to find what makes this topic interesting for you and for the academia. Finally, you need to refine you topic. Remember, it is not something you will do in one day. You can be reshaping your topic throughout your whole writing process. Still, reshaping not changing it completely. That is why keep in your head one main idea: your topic should be precise and compelling .

Learn how to choose a topic for a research paper .

How to Write a Proposal for a Research Paper?

If you do not know what a proposal is, let us explain it to you. A proposal should answer three main questions:

• What is the main aim of your investigation?
• Why is your investigation important?
• How are you going to achieve the results?

In other words, proposal should show why your topic is interesting and how you are going to prove it. As to writing requirements, they may differ. That is why make sure you find out all the details at your department. You can ask your departmental administrator or find information online at department’s site. It is crucial to follow all the administrative requirements, as it will influence your grade.

Learn how to write a proposal for a research paper .

How to Write a Research Plan?

The next step is writing a plan. You have already decided on the main issues, you have chosen the bibliography, and you have clarified the methods. Here comes the planning. If you want to avoid writer’s block, you have to structure you work. Discuss your strategies and ideas with your instructor. Think thoroughly why you need to present some data and ideas first and others second. Remember that there are basic structure elements that your research paper should include:

• Thesis Statement
• Introduction
• Bibliography

You should keep in mind this skeleton when planning your work. This will keep your mind sharp and your ideas will flow logically.

Learn how to write a research plan .

How to Do Research?

Your research will include three stages: collecting data, reading and analyzing it, and writing itself.

First, you need to collect all the material that you will need for you investigation: films, documents, surveys, interviews, and others. Secondly, you will have to read and analyze. This step is tricky, as you need to do this part smart. It is not enough just to read, as you cannot keep in mind all the information. It is essential that you make notes and write down your ideas while analyzing some data. When you get down to the stage number three, writing itself, you will already have the main ideas written on your notes. Plus, remember to jot down the reference details. You will then appreciate this trick when you will have to write the bibliography.

If you do your research this way, it will be much easier for you to write the paper. You will already have blocks of your ideas written down and you will just need to add some material and refine your paper.

Learn how to do research .

How to Write an Outline for a Research Paper?

To make your paper well organized you need to write an outline. Your outline will serve as your guiding star through the writing process. With a great outline you will not get sidetracked, because you will have a structured plan to follow. Both you and the reader will benefit from your outline. You present your ideas logically and you make your writing coherent according to your plan. As a result, this outline guides the reader through your paper and the reader enjoys the way you demonstrate your ideas.

Learn how to write an outline for a research paper . See research paper outline examples .

How to Write a Thesis Statement for a Research Paper?

Briefly, the thesis is the main argument of your research paper. It should be precise, convincing and logical. Your thesis statement should include your point of view supported by evidence or logic. Still, remember it should be precise. You should not beat around the bush, or provide all the possible evidence you have found. It is usually a single sentence that shows your argument. In on sentence you should make a claim, explain why it significant and convince the reader that your point of view is important.

Learn how to write a thesis statement for a research paper . See research paper thesis statement examples .

Should I Write a Rough Draft for a Research Paper?

Do you know any writer who put their ideas on paper, then never edited them and just published? Probably, no writer did so. Writing a research paper is no exception. It is impossible to cope with this assignment without writing a rough draft.

Your draft will help you understand what you need to polish to make your paper perfect. All the requirements, academic standards make it difficult to do everything flawlessly at the first attempt. Make sure you know all the formatting requirements: margins, words quantity, reference requirements, formatting styles etc.

Learn how to write a rough draft for a research paper .

How to Write an Introduction for a Research Paper?

Let us make it more vivid for you. We have narrowed down the tips on writing an introduction to the three main ones:

• Include your thesis in your introduction

Remember to include the thesis statement in your introduction. Usually, it goes at the end of the first paragraph.

• Present the main ideas of the body

You should tell the main topics you are going to discuss in the main body. For this reason, before writing this part of introduction, make sure you know what is your main body is going to be about. It should include your main ideas.

• Polish your thesis and introduction

When you finish the main body of your paper, come back to the thesis statement and introduction. Restate something if needed. Just make it perfect; because introduction is like the trailer to your paper, it should make the reader want to read the whole piece.

Learn how to write an introduction for a research paper . See research paper introduction examples .

How to Write a Body of a Research Paper?

A body is the main part of your research paper. In this part, you will include all the needed evidence; you will provide the examples and support your argument.

It is important to structure your paragraphs thoroughly. That is to say, topic sentence and the evidence supporting the topic. Stay focused and do not be sidetracked. You have your outline, so follow it.

Here are the main tips to keep in head when writing a body of a research paper:

• Let the ideas flow logically
• Include only relevant information
• Provide the evidence
• Structure the paragraphs
• Make the coherent transition from one paragraph to another

See? When it is all structured, it is not as scary as it seemed at the beginning. Still, if you have doubts, you can always ask our writers for help.

Learn how to write a body of a research paper . See research paper transition examples .

How to Write a Conclusion for a Research Paper?

Writing a good conclusion is important as writing any other part of the paper. Remember that conclusion is not a summary of what you have mentioned before. A good conclusion should include your last strong statement.

If you have written everything according to the plan, the reader already knows why your investigation is important. The reader has already seen the evidence. The only thing left is a strong concluding thought that will organize all your findings.

Never include any new information in conclusion. You need to conclude, not to start a new discussion.

Learn how to write a conclusion for a research paper .

How to Write an Abstract for a Research Paper?

An abstract is a brief summary of your paper, usually 100-200 words. You should provide the main gist of your paper in this short summary. An abstract can be informative, descriptive or proposal. Depending on the type of abstract, you need to write, the requirements will differ.

To write an informative abstract you have to provide the summary of the whole paper. Informative summary. In other words, you need to tell about the main points of your work, the methods used, the results and the conclusion of your research.

To write a descriptive abstract you will not have to provide any summery. You should write a short teaser of your paper. That is to say, you need to write an overview of your paper. The aim of a descriptive abstract is to interest the reader.

Finally, to write a proposal abstract you will need to write the basic summary as for the informative abstract. However, the difference is the following: you aim at persuading someone to let you write on the topic. That is why, a proposal abstract should present your topic as the one worth investigating.

Learn how to write an abstract for a research paper .

Should I Revise and Edit a Research Paper?

Revising and editing your paper is essential if you want to get high grades. Let us help you revise your paper smart:

• Check your paper for spelling and grammar mistakes
• Sharpen the vocabulary
• Make sure there are no slang words in your paper
• Examine your paper in terms of structure
• Compare your topic, thesis statement to the whole piece
• Check your paper for plagiarism

If you need assistance with proofreading and editing your paper, you can turn to the professional editors at our service. They will help you polish your paper to perfection.

Learn how to revise and edit a research paper .

How to Write a Bibliography for a Research Paper?

First, let us make it clear that bibliography and works cited are two different things. Works cited are those that you cited in your paper. Bibliography should include all the materials you used to do your research. Still, remember that bibliography requirements differ depending on the formatting style of your paper. For this reason, make sure you ask you professor all the requirements you need to meet to avoid any misunderstanding.

Learn how to write a bibliography for a research paper .

The Key Secret to a Good Research Paper

Now when you know all the stages of writing a research paper, you are ready to find the key to a good research paper:

• Choose the topic that really interests you
• Make the topic interesting for you even if it is not at the beginning
• Follow the step by step guide and do not get sidetracked
• Be persistent and believe in yourself
• Really do research and write your paper from scratch
• Learn the convincing writing techniques and use them
• Follow the requirements of your assignment
• Ask for help if needed from real professionals

Feeling more confident about your paper now? We are sure you do. Still, if you need help, you can always rely on us 24/7.

We hope we have made writing a research paper much easier for you. We realize that it requires lots of time and energy. We believe when you say that you cannot handle it anymore. For this reason, we have been helping students like you for years. Our professional team of writers is ready to tackle any challenge.

All our authors are experienced writers crafting excellent academic papers. We help students meet the deadline and get the top grades they want. You can see everything yourself. All you need to do is to place your order online and we will contact you. Writing a research paper with us is truly easy, so why do not you check it yourself?

Additional Resources for Research Paper Writing:

• Anthropology Research
• Career Research
• Communication Research
• Criminal Justice Research
• Health Research
• Political Science Research
• Psychology Research
• Sociology Research

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This vidcast talks about how to set goals and how to maintain motivation for long writing tasks. When setting goals for a writing project, it is important to think about goals for the entire project and also goals for specific writing times. These latter goals should be specific, measurable, and manageable within the time allotted for writing. The section on motivation shares ideas for boosting motivation over the course of a long writing project. The handouts on goal-setting and staying productive, as well as the scholarly writing inventory, complement the material in this vidcast and should be used in conjunction with it. 

Note: Closed-captioning and a full  transcript  are available for this vidcast. 

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Goal-Setting for your Personal Intensive Writing Experience (IWE) | [PDF]

This handout guides writers through the important process of goal-setting for the personal Intensive Writing Experience. Specifically, it talks about how to (1) formulate specific, measurable, and reasonable writing goals, (2) set an overall IWE goal, (3) break up the overall goal into smaller, daily goals, and (4) break up daily goals into smaller goals for individual writing sessions. Writers are prompted to clear their head of distracting thoughts before each writing session and, after each session, to debrief on their progress and recalibrate goals as needed. 

Scholarly Writing Inventory (PDF) 

This questionnaire helps writers identify and inventory their personal strengths and weaknesses as scholarly writers. Specifically, writers are prompted to answer questions pertaining to (1) the emotional/psychological aspects of writing, (2) writing routines, (3) research, (4) organization, (5) citation, (6) mechanics, (7) social support, and (8) access to help. By completing this questionnaire, scholarly writers will find themselves in a better position to build upon their strengths and address their weaknesses. 

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This resource offers some practical tips and tools to assist writers in staying productive for extended periods of time in the face of common challenges like procrastination. It discusses how the process of writing is more than putting words on a page and offers suggestions for addressing negative emotions towards writing, such as anxiety. The handout also lays out helpful methods for staying productive for long writing tasks: (1) time-based methods, (2) social-based methods, (3) output-based methods, (4) reward-based methods, and (5) mixed methods. 

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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How to Write a Research Essay

Last Updated: January 12, 2023 Fact Checked

This article was co-authored by Michelle Golden, PhD . Michelle Golden is an English teacher in Athens, Georgia. She received her MA in Language Arts Teacher Education in 2008 and received her PhD in English from Georgia State University in 2015. There are 11 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 385,879 times.

Research essays are extremely common assignments in high school, college, and graduate school, and are not unheard of in middle school. If you are a student, chances are you will sooner or later be faced with the task of researching a topic and writing a paper about it. Knowing how to efficiently and successfully do simple research, synthesize information, and clearly present it in essay form will save you many hours and a lot of frustration.

Researching a Topic

• Be sure to stay within the guidelines you are given by your teacher or professor. For example, if you are free to choose a topic but the general theme must fall under human biology, do not write your essay on plant photosynthesis.
• Stick with topics that are not overly complicated, especially if the subject is not something you plan to continue studying. There's no need to make things harder on yourself!

• Specialty books; these can be found at your local public or school library. A book published on your topic is a great resource and will likely be one of your most reliable options for finding quality information. They also contain lists of references where you can look for more information.
• Academic journals; these are periodicals devoted to scholarly research on a specific field of study. Articles in academic journals are written by experts in that field and scrutinized by other professionals to ensure their accuracy. These are great options if you need to find detailed, sophisticated information on your topic; avoid these if you are only writing a general overview.
• Online encyclopedias; the most reliable information on the internet can be found in online encyclopedias like Encyclopedia.com and Britannica.com. While online wikis can be very helpful, they sometimes contain unverified information that you should probably not rely upon as your primary resources.
• Expert interviews; if possible, interview an expert in the subject of your research. Experts can be professionals working in the field you are studying, professors with advanced degrees in the subject of interest, etc.

• Organize your notes by sub-topic to keep them orderly and so you can easily find references when you are writing.
• If you are using books or physical copies of magazines or journals, use sticky tabs to mark pages or paragraphs where you found useful information. You might even want to number these tabs to correspond with numbers on your note sheet for easy reference.
• By keeping your notes brief and simple, you can make them easier to understand and reference while writing. Don't make your notes so long and detailed that they essentially copy what's already written in your sources, as this won't be helpful to you.

• Sometimes the objective of your research will be obvious to you before you even begin researching the topic; other times, you may have to do a bit of reading before you can determine the direction you want your essay to take.
• If you have an objective in mind from the start, you can incorporate this into online searches about your topic in order to find the most relevant resources. For example, if your objective is to outline the environmental hazards of hydraulic fracturing practices, search for that exact phrase rather than just "hydraulic fracturing."

• Avoid asking your teacher to give you a topic. Unless your topic was assigned to you in the first place, part of the assignment is for you to choose a topic relevant to the broader theme of the class or unit. By asking your teacher to do this for you, you risk admitting laziness or incompetence.
• If you have a few topics in mind but are not sure how to develop objectives for some of them, your teacher can help with this. Plan to discuss your options with your teacher and come to a decision yourself rather than having him or her choose the topic for you from several options.

Organizing your Essay

• Consider what background information is necessary to contextualize your research topic. What questions might the reader have right out of the gate? How do you want the reader to think about the topic? Answering these kinds of questions can help you figure out how to set up your argument.
• Match your paper sections to the objective(s) of your writing. For example, if you are trying to present two sides of a debate, create a section for each and then divide them up according to the aspects of each argument you want to address.

• An outline can be as detailed or general as you want, so long as it helps you figure out how to construct the essay. Some people like to include a few sentences under each heading in their outline to create a sort of "mini-essay" before they begin writing. Others find that a simple ordered list of topics is sufficient. Do whatever works best for you.
• If you have time, write your outline a day or two before you start writing and come back to it several times. This will give you an opportunity to think about how the pieces of your essay will best fit together. Rearrange things in your outline as many times as you want until you have a structure you are happy with.

• Style guides tell you exactly how to quote passages, cite references, construct works cited sections, etc. If you are assigned a specific format, you must take care to adhere to guidelines for text formatting and citations.
• Some computer programs (such as EndNote) allow you to construct a library of resources which you can then set to a specific format type; then you can automatically insert in-text citations from your library and populate a references section at the end of the document. This is an easy way to make sure your citations match your assigned style format.

• You may wish to start by simply assigning yourself a certain number of pages per day. Divide the number of pages you are required to write by the number of days you have to finish the essay; this is the number of pages (minimum) that you must complete each day in order to pace yourself evenly.
• If possible, leave a buffer of at least one day between finishing your paper and the due date. This will allow you to review your finished product and edit it for errors. This will also help in case something comes up that slows your writing progress.

Writing your Essay

• Keep your introduction relatively short. For most papers, one or two paragraphs will suffice. For really long essays, you may need to expand this.
• Don't assume your reader already knows the basics of the topic unless it truly is a matter of common knowledge. For example, you probably don't need to explain in your introduction what biology is, but you should define less general terms such as "eukaryote" or "polypeptide chain."

• You may need to include a special section at the beginning of the essay body for background information on your topic. Alternatively, you can consider moving this to the introductory section, but only if your essay is short and only minimal background discussion is needed.
• This is the part of your paper where organization and structure are most important. Arrange sections within the body so that they flow logically and the reader is introduced to ideas and sub-topics before they are discussed further.
• Depending upon the length and detail of your paper, the end of the body might contain a discussion of findings. This kind of section serves to wrap up your main findings but does not explicitly state your conclusions (which should come in the final section of the essay).
• Avoid repetition in the essay body. Keep your writing concise, yet with sufficient detail to address your objective(s) or research question(s).

• Always use quotation marks when using exact quotes from another source. If someone already said or wrote the words you are using, you must quote them this way! Place your in-text citation at the end of the quote.
• To include someone else's ideas in your essay without directly quoting them, you can restate the information in your own words; this is called paraphrasing. Although this does not require quotation marks, it should still be accompanied by an in-text citation.

• Except for very long essays, keep your conclusion short and to the point. You should aim for one or two paragraphs, if possible.
• Conclusions should directly correspond to research discussed in the essay body. In other words, make sure your conclusions logically connect to the rest of your essay and provide explanations when necessary.
• If your topic is complex and involves lots of details, you should consider including a brief summary of the main points of your research in your conclusion.

• Making changes to the discussion and conclusion sections instead of the introduction often requires a less extensive rewrite. Doing this also prevents you from removing anything from the beginning of your essay that could accidentally make subsequent portions of your writing seem out of place.
• It is okay to revise your thesis once you've finished the first draft of your essay! People's views often change once they've done research on a topic. Just make sure you don't end up straying too far from your assigned topic if you do this.
• You don't necessarily need to wait until you've finished your entire draft to do this step. In fact, it is a good idea to revisit your thesis regularly as you write. This can save you a lot of time in the end by helping you keep your essay content on track.

• Computer software such as EndNote is available for making citation organization as easy and quick as possible. You can create a reference library and link it to your document, adding in-text citations as you write; the program creates a formatted works cited section at the end of your document.
• Be aware of the formatting requirements of your chosen style guide for works cited sections and in-text citations. Reference library programs like EndNote have hundreds of pre-loaded formats to choose from.

• Create a catchy title. Waiting until you have finished your essay before choosing a title ensures that it will closely match the content of your essay. Research papers don't always take on the shape we expect them to, and it's easier to match your title to your essay than vice-versa.
• Read through your paper to identify and rework sentences or paragraphs that are confusing or unclear. Each section of your paper should have a clear focus and purpose; if any of yours seem not to meet these expectations, either rewrite or discard them.
• Review your works cited section (at the end of your essay) to ensure that it conforms to the standards of your chosen or assigned style format. You should at least make sure that the style is consistent throughout this section.
• Run a spell checker on your entire document to catch any spelling or grammar mistakes you may not have noticed during your read-through. All modern word processing programs include this function.

• Note that revising your draft is not the same as proofreading it. Revisions are done to make sure the content and substantive ideas are solid; editing is done to check for spelling and grammar errors. Revisions are arguably a more important part of writing a good paper.
• You may want to have a friend, classmate, or family member read your first draft and give you feedback. This can be immensely helpful when trying to decide how to improve upon your first version of the essay.
• Except in extreme cases, avoid a complete rewrite of your first draft. This will most likely be counterproductive and will waste a lot of time. Your first draft is probably already pretty good -- it likely just needs some tweaking before it is ready to submit.

Community Q&A

• Avoid use of the word "I" in research essay writing, even when conveying your personal opinion about a subject. This makes your writing sound biased and narrow in scope. Thanks Helpful 0 Not Helpful 0
• Even if there is a minimum number of paragraphs, always do 3 or 4 more paragraphs more than needed, so you can always get a good grade. Thanks Helpful 0 Not Helpful 0

• Never plagiarize the work of others! Passing off others' writing as your own can land you in a lot of trouble and is usually grounds for failing an assignment or class. Thanks Helpful 12 Not Helpful 1

You Might Also Like

• ↑ https://owl.purdue.edu/owl/general_writing/common_writing_assignments/research_papers/choosing_a_topic.html
• ↑ https://libguides.mit.edu/select-topic
• ↑ https://www.indeed.com/career-advice/career-development/research-objectives
• ↑ https://www.hunter.cuny.edu/rwc/handouts/the-writing-process-1/organization/Organizing-an-Essay
• ↑ https://www.lynchburg.edu/academics/writing-center/wilmer-writing-center-online-writing-lab/the-writing-process/organizing-your-paper/
• ↑ https://www.mla.org/MLA-Style
• ↑ http://www.apastyle.org/
• ↑ https://writing.wisc.edu/Handbook/PlanResearchPaper.html
• ↑ https://owl.purdue.edu/owl/research_and_citation/apa6_style/apa_formatting_and_style_guide/in_text_citations_the_basics.html
• ↑ https://opentextbc.ca/writingforsuccess/chapter/chapter-12-peer-review-and-final-revisions/
• ↑ https://openoregon.pressbooks.pub/wrd/back-matter/creating-a-works-cited-page/

About This Article

The best way to write a research essay is to find sources, like specialty books, academic journals, and online encyclopedias, about your topic. Take notes as you research, and make sure you note which page and book you got your notes from. Create an outline for the paper that details your argument, various sections, and primary points for each section. Then, write an introduction, build the body of the essay, and state your conclusion. Cite your sources along the way, and follow the assigned format, like APA or MLA, if applicable. To learn more from our co-author with an English Ph.D. about how to choose a thesis statement for your research paper, keep reading! Did this summary help you? Yes No

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How to Write a Research Paper | A Beginner's Guide

A research paper is a piece of academic writing that provides analysis, interpretation, and argument based on in-depth independent research.

Research papers are similar to academic essays , but they are usually longer and more detailed assignments, designed to assess not only your writing skills but also your skills in scholarly research. Writing a research paper requires you to demonstrate a strong knowledge of your topic, engage with a variety of sources, and make an original contribution to the debate.

This step-by-step guide takes you through the entire writing process, from understanding your assignment to proofreading your final draft.

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Table of contents

Understand the assignment, choose a research paper topic, conduct preliminary research, develop a thesis statement, create a research paper outline, write a first draft of the research paper, write the introduction, write a compelling body of text, write the conclusion, the second draft, the revision process, research paper checklist, free lecture slides.

Completing a research paper successfully means accomplishing the specific tasks set out for you. Before you start, make sure you thoroughly understanding the assignment task sheet:

• Read it carefully, looking for anything confusing you might need to clarify with your professor.
• Identify the assignment goal, deadline, length specifications, formatting, and submission method.
• Make a bulleted list of the key points, then go back and cross completed items off as you’re writing.

Carefully consider your timeframe and word limit: be realistic, and plan enough time to research, write, and edit.

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There are many ways to generate an idea for a research paper, from brainstorming with pen and paper to talking it through with a fellow student or professor.

You can try free writing, which involves taking a broad topic and writing continuously for two or three minutes to identify absolutely anything relevant that could be interesting.

You can also gain inspiration from other research. The discussion or recommendations sections of research papers often include ideas for other specific topics that require further examination.

Once you have a broad subject area, narrow it down to choose a topic that interests you, m eets the criteria of your assignment, and i s possible to research. Aim for ideas that are both original and specific:

• A paper following the chronology of World War II would not be original or specific enough.
• A paper on the experience of Danish citizens living close to the German border during World War II would be specific and could be original enough.

Note any discussions that seem important to the topic, and try to find an issue that you can focus your paper around. Use a variety of sources , including journals, books, and reliable websites, to ensure you do not miss anything glaring.

Do not only verify the ideas you have in mind, but look for sources that contradict your point of view.

• Is there anything people seem to overlook in the sources you research?
• Are there any heated debates you can address?
• Do you have a unique take on your topic?
• Have there been some recent developments that build on the extant research?

In this stage, you might find it helpful to formulate some research questions to help guide you. To write research questions, try to finish the following sentence: “I want to know how/what/why…”

A thesis statement is a statement of your central argument — it establishes the purpose and position of your paper. If you started with a research question, the thesis statement should answer it. It should also show what evidence and reasoning you’ll use to support that answer.

The thesis statement should be concise, contentious, and coherent. That means it should briefly summarize your argument in a sentence or two, make a claim that requires further evidence or analysis, and make a coherent point that relates to every part of the paper.

You will probably revise and refine the thesis statement as you do more research, but it can serve as a guide throughout the writing process. Every paragraph should aim to support and develop this central claim.

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A research paper outline is essentially a list of the key topics, arguments, and evidence you want to include, divided into sections with headings so that you know roughly what the paper will look like before you start writing.

A structure outline can help make the writing process much more efficient, so it’s worth dedicating some time to create one.

Your first draft won’t be perfect — you can polish later on. Your priorities at this stage are as follows:

• Maintaining forward momentum — write now, perfect later.
• Paying attention to clear organization and logical ordering of paragraphs and sentences, which will help when you come to the second draft.
• Expressing your ideas as clearly as possible, so you know what you were trying to say when you come back to the text.

You do not need to start by writing the introduction. Begin where it feels most natural for you — some prefer to finish the most difficult sections first, while others choose to start with the easiest part. If you created an outline, use it as a map while you work.

Do not delete large sections of text. If you begin to dislike something you have written or find it doesn’t quite fit, move it to a different document, but don’t lose it completely — you never know if it might come in useful later.

Paragraph structure

Paragraphs are the basic building blocks of research papers. Each one should focus on a single claim or idea that helps to establish the overall argument or purpose of the paper.

Example paragraph

George Orwell’s 1946 essay “Politics and the English Language” has had an enduring impact on thought about the relationship between politics and language. This impact is particularly obvious in light of the various critical review articles that have recently referenced the essay. For example, consider Mark Falcoff’s 2009 article in The National Review Online, “The Perversion of Language; or, Orwell Revisited,” in which he analyzes several common words (“activist,” “civil-rights leader,” “diversity,” and more). Falcoff’s close analysis of the ambiguity built into political language intentionally mirrors Orwell’s own point-by-point analysis of the political language of his day. Even 63 years after its publication, Orwell’s essay is emulated by contemporary thinkers.

Citing sources

It’s also important to keep track of citations at this stage to avoid accidental plagiarism . Each time you use a source, make sure to take note of where the information came from.

You can use our free citation generators to automatically create citations and save your reference list as you go.

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The research paper introduction should address three questions: What, why, and how? After finishing the introduction, the reader should know what the paper is about, why it is worth reading, and how you’ll build your arguments.

What? Be specific about the topic of the paper, introduce the background, and define key terms or concepts.

Why? This is the most important, but also the most difficult, part of the introduction. Try to provide brief answers to the following questions: What new material or insight are you offering? What important issues does your essay help define or answer?

How? To let the reader know what to expect from the rest of the paper, the introduction should include a “map” of what will be discussed, briefly presenting the key elements of the paper in chronological order.

The major struggle faced by most writers is how to organize the information presented in the paper, which is one reason an outline is so useful. However, remember that the outline is only a guide and, when writing, you can be flexible with the order in which the information and arguments are presented.

One way to stay on track is to use your thesis statement and topic sentences . Check:

• topic sentences against the thesis statement;
• topic sentences against each other, for similarities and logical ordering;
• and each sentence against the topic sentence of that paragraph.

Be aware of paragraphs that seem to cover the same things. If two paragraphs discuss something similar, they must approach that topic in different ways. Aim to create smooth transitions between sentences, paragraphs, and sections.

The research paper conclusion is designed to help your reader out of the paper’s argument, giving them a sense of finality.

Trace the course of the paper, emphasizing how it all comes together to prove your thesis statement. Give the paper a sense of finality by making sure the reader understands how you’ve settled the issues raised in the introduction.

You might also discuss the more general consequences of the argument, outline what the paper offers to future students of the topic, and suggest any questions the paper’s argument raises but cannot or does not try to answer.

You should not :

• Offer new arguments or essential information
• Take up any more space than necessary
• Begin with stock phrases that signal you are ending the paper (e.g. “In conclusion”)

There are four main considerations when it comes to the second draft.

• Check how your vision of the paper lines up with the first draft and, more importantly, that your paper still answers the assignment.
• Identify any assumptions that might require (more substantial) justification, keeping your reader’s perspective foremost in mind. Remove these points if you cannot substantiate them further.
• Be open to rearranging your ideas. Check whether any sections feel out of place and whether your ideas could be better organized.
• If you find that old ideas do not fit as well as you anticipated, you should cut them out or condense them. You might also find that new and well-suited ideas occurred to you during the writing of the first draft — now is the time to make them part of the paper.

The goal during the revision and proofreading process is to ensure you have completed all the necessary tasks and that the paper is as well-articulated as possible. You can speed up the proofreading process by using the AI proofreader .

Global concerns

• Confirm that your paper completes every task specified in your assignment sheet.
• Check for logical organization and flow of paragraphs.
• Check paragraphs against the introduction and thesis statement.

Fine-grained details

Check the content of each paragraph, making sure that:

• each sentence helps support the topic sentence.
• no unnecessary or irrelevant information is present.
• all technical terms your audience might not know are identified.

Next, think about sentence structure , grammatical errors, and formatting . Check that you have correctly used transition words and phrases to show the connections between your ideas. Look for typos, cut unnecessary words, and check for consistency in aspects such as heading formatting and spellings .

Finally, you need to make sure your paper is correctly formatted according to the rules of the citation style you are using. For example, you might need to include an MLA heading  or create an APA title page .

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Checklist: Research paper

I have followed all instructions in the assignment sheet.

My introduction presents my topic in an engaging way and provides necessary background information.

My introduction presents a clear, focused research problem and/or thesis statement .

My paper is logically organized using paragraphs and (if relevant) section headings .

Each paragraph is clearly focused on one central idea, expressed in a clear topic sentence .

Each paragraph is relevant to my research problem or thesis statement.

I have used appropriate transitions  to clarify the connections between sections, paragraphs, and sentences.

My conclusion provides a concise answer to the research question or emphasizes how the thesis has been supported.

My conclusion shows how my research has contributed to knowledge or understanding of my topic.

My conclusion does not present any new points or information essential to my argument.

I have provided an in-text citation every time I refer to ideas or information from a source.

I have included a reference list at the end of my paper, consistently formatted according to a specific citation style .

I have thoroughly revised my paper and addressed any feedback from my professor or supervisor.

I have followed all formatting guidelines (page numbers, headers, spacing, etc.).

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Elephants use the tips of their trunks to grasp things with great precision – how this can help robotic design

PhD Candidate at MECADEV (Centre National de la Recherche Scientifique/Muséum national d'Histoire naturelle), Sorbonne Université

Disclosure statement

Pauline Costes receives funding from the IBEES Initiative of Sorbonne Université (E. Pouydebat).

Sorbonne Université provides funding as a founding partner of The Conversation FR.

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An elephant uses its trunk for eating, drinking water, communicating, exploring the environment, social behaviour, and making and using tools. The trunk, which contains six muscle groups, is not only very strong – it can uproot a tree – but can be used with great precision. Elephants use a number of techniques to grasp objects, including suction, pinching with the two “fingers” at the tip of the trunk and wrapping the trunk around the object.

Researcher Pauline Costes was part of a group of scientists who tested six female African savannah elephants in a zoo to see how much force their trunk tips exerted and which part of the trunk tip was strongest. She explains how these findings will be used to improve the ability of robots to grip and handle objects.

What did you set out to study and why?

In this research project , we studied the maximum pinching force exerted by the tip of the trunk of African savannah elephants. The elephant’s trunk is mainly composed of muscles, has no rigid structure (no bones), and has many nerves, giving it great power, precision and sensibility.

Previous studies have measured the force of the entire trunk when elephants wrap it around an object. We focused on how forceful the trunk tip is. The tip of an elephant’s trunk comprises two finger-like protuberances: a pointy one at the top and a more rounded and shorter one underneath. We also studied how the position of the trunk influenced the force exerted by the elephant.

Read more: Fish fins are teaching us the secret to flexible robots and new shape-changing materials

Electronic engineers who design robots have tried to mimic the flexibility and way in which natural biological tissue can twist or turn when it performs different tasks. This is known as bio-inspired technology. For the past 20 years, the elephant’s trunk has inspired this research, especially in the robotics of grasping and manipulation.

Our research aimed to find out how strong the trunk tip’s pinching grasp is. This kind of grasping allows small objects to be picked up with high precision. This is particularly useful in soft robotics, which focuses on the design and manufacture of robots using flexible and deformable materials, inspired by biology.

What were your key findings?

We measured a maximum pinch force of 86.4 Newton. A newton, the international unit for measuring force, corresponds to the force that gives a mass of one kilogram an acceleration of one metre per second squared. By comparison, the maximum pinch force between the thumb and index finger in humans is between 49 and 68 Newton .

We found that the trunk tip is used to grasp objects with high precision but without great force. This is useful information for the future development of the soft grippers of robots. Some robots have to be able to grasp objects if they are to carry out routine activities. Soft grippers – the tool on the end of the robot’s arm – are the most important component of grasping.

Read more: How we made an octopus-inspired surgical robot using coffee

Soft grippers based on the elephant’s trunk also adapt to cluttered and unpredictable environments by reconfiguring their shape. In other words, they adapt their elastic bodies to the objects they interact with.

More research means better grippers. Here are a few examples of how soft robots can be used:

Medicine: Use of robots for minimally invasive surgical procedures.

Industry: Handling fragile or irregularly shaped objects on production lines.

Research and exploration: Development of robots capable of navigating in difficult or inaccessible environments.

Agriculture: Harvesting delicate fruit and vegetables without damaging them.

We also found a difference in force between the elephant’s two “fingers”. This had never been studied before.

How did you discover this?

We created a device to measure the pinching force of an elephant’s trunk tip. This was a box fitted with two force sensors connected to an electronic system. The system recorded the force of the pinch and automatically released apples as a reward .

An apple was released when the elephant managed to pinch strongly enough to cross a predefined threshold. The trunk then had to pinch harder the next time to release the next apple. This was repeated until the elephants reached the maximum force they could manage.

By placing the sensors vertically and then horizontally on the box, we could see how the elephants would grip them in these different orientations. This showed us how the position of the trunk influences the force it exerts.

The equipment itself took us some time to set up and get the elephants ready for it through training. Tests were carried out with the sensors alone, then various prototypes of the box were tested until the final box was functional and fairly solid. After this initial test phase, conducted by several researchers of our team, I spent three months at the zoo to collect the data needed for this work.

How did your research benefit elephants?

The first direct benefit was keeping the captive elephants stimulated through enriching activities.

Our research also examined how the trunk grasping techniques differ between different groups of elephants living in several habitats and the relationship with the density and size of the vegetation. This new knowledge is beneficial for elephant conservation, helping scientists to figure out how climate change, which changes elephant habitats, will affect their feeding behaviour.

The research was carried out in collaboration between France’s MECADEV and ISYEB research units at the Centre National de la Recherche Scientifique, the Muséum National d'Histoire Naturelle and ZooParc de Beauval .

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NVIDIA Sets New Generative AI Performance and Scale Records in MLPerf Training v4.0

Generative AI models have a variety of uses, such as helping write computer code, crafting stories, composing music, generating images, producing videos, and more. And, as these models continue to grow in size and are trained on even more data, they are producing even higher-quality outputs.

Building and deploying these more intelligent models is incredibly compute-intensive, requiring many high-performance processors working in parallel, orchestrated by efficient and versatile software.

For example, Meta announced that it trained its latest Llama 3 family of large language models (LLMs) using AI clusters featuring 24,576 NVIDIA H100 Tensor Core GPUs. The larger of the models, Llama 3 70B, required a total 6.4 million H100 GPU-hours to train.

When LLMs are pretrained, they can then be customized through a variety of techniques , including model fine-tuning, to achieve higher accuracy for specific tasks. As enterprises move to adopt LLMs for a wide variety of applications, LLM fine-tuning is fast becoming a core industry workload. 

AI training is a full-stack challenge, and delivering world-class end-to-end training performance requires the combination of powerful processors, fast memory, high-bandwidth and low-latency networking, and optimized software. 

MLPerf Training has emerged as the industry-standard benchmark to measure and evaluate end-to-end AI training performance. Developed by the MLCommons consortium, MLPerf Training workloads are frequently updated to reflect the latest AI use cases. During each submission round, the results undergo a rigorous peer-review process to ensure their integrity before publication.

In MLPerf Training v4.0, NVIDIA set new generative AI training performance records and continued to deliver the highest performance on every workload. This performance was delivered using the full stack of NVIDIA software and hardware:

• NVIDIA Hopper GPUs
• The latest, fourth-generation NVLink interconnect combined with the latest third-generation NVSwitch chip
• NVIDIA Quantum-2 InfiniBand networking
• NVIDIA NeMo framework
• NVIDIA Transformer Engine library
• NVIDIA cuBLAS library
• NVIDIA cuDNN library
• NVIDIA Magnum IO

Each component has been optimized further since the last round of MLPerf Training to continue delivering more performance and value to users. This post provides a closer look at these outstanding results. 

MLPerf Training v4.0 updates

This round of MLPerf saw the addition of two new tests to reflect popular industry workloads. 

The first measures how quickly Llama 2 70B can be fine-tuned using the popular low-rank adaptation (LoRA) technique. LLM fine-tuning enables enterprises to customize LLMs using their proprietary data to improve response quality for specific use cases. 

The second new test focuses on graph neural network (GNN) training, based on an implementation of RGAT (relational graph attention network). GNNs are being applied to many domains, including drug discovery, fraud detection, and recommendation systems. 

The latest MLPerf Training v4.0 test suite has the following workloads:

• LLM pre-training (GPT-3 175B) 
• LLM fine-tuning (Llama 2 70B with LoRA)
• Graph neural network (GNN)
• Text-to-image (Stable Diffusion v2)
• Recommender (DLRM-dcnv2)
• Natural language processing (BERT-Large)
• Image classification (ResNet-50)
• Lightweight object detection (RetinaNet)
• Biomedical image segmentation (3D U-Net)

As AI is a diverse and rapidly evolving field, with new models and applications being invented continuously, it’s important that industry benchmarks, such as MLPerf, cover a wide range of use cases and evolve in lock-step with industry trends. 

NVIDIA sets new LLM pretraining performance and scale records 

MLPerf incorporates an LLM pretraining benchmark based on GPT-3 175B, a 175B parameter LLM developed by OpenAI . The workload is extremely demanding and is a good test of large-scale LLM training performance, which stresses the compute, networking, and software efficiency of an accelerated computing platform. 

NVIDIA first submitted results on the GPT3-175B LLM  benchmark when it was introduced in MLPerf Training v3.0 last year. We achieved a time-to-train of 10.9 minutes using 3,584 H100 GPUs, representing both performance and scale records at the time. 

In this round of MLPerf Training, NVIDIA has more than tripled its submission scale to 11,616 H100 GPUs and more than tripled performance to 3.4 minutes to train, delivering near-linear performance scaling. These results build upon the prior records set by NVIDIA last round with 10,752 H100 GPUs that delivered a time-to-train of just 3.9 minutes.

MLPerf Training v3.1 and v4.0 results retrieved from www.mlperf.org . on June 12, 2024, from the following entries: NVIDIA 3.0-2069, NVIDIA 4.0-0059. NVIDIA A100 result with 512 A100 is not verified by MLCommons. The MLPerf name and logo are trademarks of MLCommons Association in the United States and other countries. All rights reserved. Unauthorized use strictly prohibited. See www.mlcommons.org for more information.

The exceptional results submitted by NVIDIA this round reflected both increased submission scale, as well as significant software improvements that further enhanced delivered performance at scale. 

One notable example is the first use of CUDA Graphs in NVIDIA LLM submissions. As training scales to several thousand GPUs, CPU overhead becomes more pronounced. The use of CUDA Graphs, which enables multiple GPU operations to be launched with a single CPU operation, also contributed to the performance delivered at max scale.

At a scale of 512 GPUs, H100 performance has increased by 27% in just one year, completing the workload in under an hour, with per-GPU utilization now reaching 904 TFLOP/s.

This exceptional result was enabled by numerous improvements to the NVIDIA software stack:

• Optimized FP8 kernels
• A new FP8-aware distributed optimizer
• An optimized FlashAttention implementation in cuDNN
• More effective overlapped execution of math operations and GPU-to-GPU communication operations
• Intelligent power allocation within the H100 GPUs to maximize Tensor Core throughput

Diving further into the last optimization, a notable characteristic of LLM training is its high compute intensity. Especially for smaller-scale LLM runs, math operations can make up a much greater part of the time required to perform each training step compared to operations related to GPU-to-GPU communication. This leads to high Tensor Core utilization and can result in scenarios where Tensor Core throughput is constrained by the power available to the GPU. 

In the submission with 512 H100 GPUs, we improved end-to-end performance by redirecting power from the L2 cache memory on each H100 GPU to the streaming multiprocessor (SM), which houses, among other units, NVIDIA Hopper fourth-generation Tensor Cores. This was done by setting a ratio using a boost slider managed by NVIDIA Management Libraries (NVML).

This resulted in higher GPU operating frequency within the same power budget and improved end-to-end performance by 4%. The boost slider can be set through the command nvidia-smi boost-slider –vboost <value> . For more information about this command, including how to get all possible values, run nvidia-smi boost-slider –help .

By improving performance with the same GPUs, you can either train models with similar computational requirements in less time and at a lower cost or train more computationally intensive models in a similar time with similar costs. 

NVIDIA achieves the highest LLM fine-tuning performance

The latest version of MLPerf Training includes a fine-tuning test, which applies LoRA to the Llama 2 70B model, developed by Meta. LoRA is a popular form of parameter-efficient fine-tuning, described in this post .

The NVIDIA platform excelled on this new test, delivering the fastest single-server performance as well as scalability well beyond a single GPU server.

A single DGX H100, incorporating eight H100 GPUs, delivered an outstanding performance, completing the test in just over 28 minutes. The NVIDIA H200 Tensor Core GPU, which upgrades the NVIDIA Hopper architecture with 141 GB of HBM3e memory, delivered an additional 14% speedup, reducing the time-to-train with a single node to just 24.7 minutes. 

NVIDIA submissions this round also demonstrated the ability to fine-tune LLMs using up to 1,024 H100 GPUs, delivering an outstanding result of just 1.5 minutes, establishing both performance and scale records. 

To enable efficient scaling to 1,024 H100 GPUs, NVIDIA submissions on the LLM fine-tuning benchmark leveraged the context parallelism capability available in the NVIDIA NeMo framework. To learn more about context parallelism and how to leverage it when using the NeMo framework, see this page .

In the NVIDIA LLM fine-tuning submissions this round, we used an FP8 implementation of self-attention, available through cuDNN. This improved performance by 15% at the 8-GPU scale. For more information, see Accelerating Transformers with NVIDIA cuDNN 9 .

These fantastic results complement the great performance on supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) demonstrated on NVIDIA Hopper GPUs late last year. 

These fine-tuning techniques can provide better accuracy compared to parameter-efficient methods such as LoRA, but at the cost of greater compute intensity. The NVIDIA NeMo framework supports many model customization techniques to provide you with the flexibility to choose the ones that best serve your needs. 

NVIDIA raises the bar for text-to-image generative AI training

Generative AI is transforming visual design and is being applied to a broad range of use cases, including marketing and advertising, media and entertainment, product design and prototyping, as well as architecture visualization. 

To represent visual generative AI, MLPerf Training v4.0 includes a text-to-image benchmark, based on Stable Diffusion v2. 

Building upon the record-setting NVIDIA submissions in the last round, NVIDIA submissions this round deliver up to 80% more performance at the same submission scales through extensive software enhancements:

• Use of full-iteration CUDA Graphs
• Use of distributed optimizer for Stable Diffusion
• Optimized cuDNN and cuBLAS heuristics for Stable Diffusion

MLPerf Training v3.1 and v4.0 results retrieved from www.mlperf.org . on June 12, 2024, from the following entries: NVIDIA 3.1-2050, NVIDIA 4.0-0053. The MLPerf name and logo are trademarks of MLCommons Association in the United States and other countries. All rights reserved. Unauthorized use strictly prohibited. See www.mlcommons.org for more information

NVIDIA accelerates graph neural network training

Graph neural networks (GNNs) are used for a range of applications, including social network analysis, drug discovery, fraud detection, recommenders in retail, and even molecular chemistry. The addition of a GNN benchmark to MLPerf broadens the workload coverage to cover this important class of neural networks. 

NVIDIA submitted results using 8, 64, and 512 H100 GPUs, setting a new benchmark time to train record of just 1.1 minutes in the largest-scale configuration. 

NVIDIA also submitted eight GPU results using eight H200 Tensor Core GPUs, each featuring 141 GB of HBM3e and delivering a 47% boost compared to the H100 submission at the same scale. 

Key takeaways

The NVIDIA platform continues to demonstrate the highest performance and greatest versatility for the full diversity of AI workloads, spanning both generative AI as well as more traditional AI workloads.

The NVIDIA platform is moving fast. By continuing to optimize the NVIDIA software stack, customers can enjoy more performance per GPU, which reduces the cost to train, and the ability to efficiently scale to larger numbers of GPUs to train even more demanding models. 

The NVIDIA platform continues to deliver even more performance through invention across the entire stack, including new chips and systems. The NVIDIA Blackwell platform, announced at GTC 2024, is set to democratize trillion-parameter AI, with NVIDIA GB200 NVL72 delivering up to 30x faster real-time trillion-parameter inference, and up to 4x faster trillion-parameter training compared to the same number of NVIDIA Hopper GPUs.

Related resources

• GTC session: An Intro to the MLPerf Benchmarks and New Generative AI Tests
• GTC session: How to Seamlessly Scale from Open Source to Production-Ready Generative AI
• GTC session: Generative AI Theater: Fast-Track AI Development With NVIDIA APIs and NGC Catalog
• NGC Containers: NVIDIA MLPerf Inference
• NGC Containers: GenAI SD NIM

About the Authors

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NVIDIA H200 Tensor Core GPUs and NVIDIA TensorRT-LLM Set MLPerf LLM Inference Records

New NVIDIA NeMo Framework Features and NVIDIA H200 Supercharge LLM Training Performance and Versatility

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Setting New Records at Data Center Scale Using NVIDIA H100 GPUs and NVIDIA Quantum-2 InfiniBand

Breaking MLPerf Training Records with NVIDIA H100 GPUs

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Apple Intelligence Preview

AI for the rest of us.

Coming in beta this fall *

Built into your iPhone, iPad, and Mac to help you write, express yourself, and get things done effortlessly.

Draws on your personal context while setting a brand-new standard for privacy in AI.

Write with intelligent new tools. Everywhere words matter.

Apple Intelligence powers new Writing Tools, which help you find just the right words virtually everywhere you write. With enhanced language capabilities, you can summarize an entire lecture in seconds, get the short version of a long group thread, and minimize unnecessary distractions with prioritized notifications.

Explore new features for writing, focus, and communication.

Transform how you communicate using intelligent Writing Tools that can proofread your text, rewrite different versions until the tone and wording are just right, and summarize selected text with a tap. Writing Tools are available nearly everywhere you write, including third-party apps.

Priority notifications appear at the top of the stack, letting you know what to pay attention to at a glance. And notifications are summarized, so you can scan them faster.

Priority messages in Mail elevate time-sensitive messages to the top of your inbox — like an invitation that has a deadline today or a check-in reminder for your flight this afternoon.

Tap to reveal a summary of a long email in the Mail app and cut to the chase. You can also view summaries of email right from your inbox.

Just hit record in the Notes or Phone apps to capture audio recordings and transcripts. Apple Intelligence generates summaries of your transcripts, so you can get to the most important information at a glance.

Reduce Interruptions is an all-new Focus that understands the content of your notifications and shows you the ones that might need immediate attention, like a text about picking up your child from daycare later today.

Use a Smart Reply in Mail to quickly draft an email response with all the right details. Apple Intelligence can identify questions you were asked in an email and offer relevant selections to include in your response. With a few taps you’re ready to send a reply with key questions answered.

Delightful images created just for you.

Apple Intelligence enables delightful new ways to express yourself visually. Create fun, original images and brand-new Genmoji that are truly personal to you. Turn a rough sketch into a related image that complements your notes with Image Wand. And make a custom memory movie based on the description you provide.

Create expressive images, unique Genmoji, and custom memory movies.

Produce fun, original images in seconds with the Image Playground experience right in your apps. Create an entirely new image based on a description, suggested concepts, and even a person from your Photos library. You can easily adjust the style and make changes to match a Messages thread, your Freeform board, or a slide in Keynote.

Experiment with different concepts and try out image styles like animation, illustration, and sketch in the dedicated Image Playground app . Create custom images to share with friends in other apps or on social media.

Make a brand-new Genmoji right in the keyboard to match any conversation. Provide a description to see a preview, and adjust your description until it’s perfect. You can even pick someone from your Photos library and create a Genmoji that looks like them.

Image Wand can transform your rough sketch into a related image in the Notes app. Use your finger or Apple Pencil to draw a circle around your sketch, and Image Wand will analyze the content around it to produce a complementary visual. You can even circle an empty space, and Image Wand will use the surrounding context to create a picture.

Create a custom memory movie of the story you want to see, right in Photos. Enter a description, and Apple Intelligence finds the best photos and videos that match. It then crafts a storyline with unique chapters based on themes it identifies and arranges your photos into a movie with its own narrative arc.

Search for photos and videos in the Photos app simply by describing what you’re looking for. Apple Intelligence can even find a particular moment in a video clip that fits your search description and take you right to it.

Remove distractions in your photos with the Clean Up tool in the Photos app. Apple Intelligence identifies background objects so you can remove them with a tap and perfect your shot — while staying true to the original image.

The start of a new era for Siri.

Siri draws on Apple Intelligence for all-new superpowers. With an all-new design, richer language understanding, and the ability to type to Siri whenever it’s convenient for you, communicating with Siri is more natural than ever. Equipped with awareness of your personal context, the ability to take action in and across apps, and product knowledge about your devices’ features and settings, Siri will be able to assist you like never before.

Discover an even more capable, integrated, personal Siri.

Siri has an all-new design that’s even more deeply integrated into the system experience, with an elegant, glowing light that wraps around the edge of your screen.

With a double tap on the bottom of your iPhone or iPad screen, you can type to Siri from anywhere in the system when you don’t want to speak out loud.

Tap into the expansive product knowledge Siri has about your devices’ features and settings. You can ask questions when you’re learning how to do something new on your iPhone, iPad, and Mac, and Siri can give you step-by-step directions in a flash.

Siri, set an alarm for — oh wait no, set a timer for 10 minutes. Actually, make that 5.

Richer language understanding and an enhanced voice make communicating with Siri even more natural. And when you refer to something you mentioned in a previous request, like the location of a calendar event you just created, and ask ”What will the weather be like there?” Siri knows what you’re talking about.

Apple Intelligence empowers Siri with onscreen awareness , so it can understand and take action with things on your screen. If a friend texts you their new address, you can say “Add this address to their contact card,” and Siri will take care of it.

Awareness of your personal context enables Siri to help you in ways that are unique to you. Can’t remember if a friend shared that recipe with you in a note, a text, or an email? Need your passport number while booking a flight? Siri can use its knowledge of the information on your device to help find what you’re looking for, without compromising your privacy.

Seamlessly take action in and across apps with Siri. You can make a request like “Send the email I drafted to April and Lilly” and Siri knows which email you’re referencing and which app it’s in. And Siri can take actions across apps, so after you ask Siri to enhance a photo for you by saying “Make this photo pop,” you can ask Siri to drop it in a specific note in the Notes app — without lifting a finger.

Great powers come with great privacy.

Apple Intelligence is designed to protect your privacy at every step. It’s integrated into the core of your iPhone, iPad, and Mac through on-device processing. So it’s aware of your personal information without collecting your personal information. And with groundbreaking Private Cloud Compute, Apple Intelligence can draw on larger server-based models, running on Apple silicon, to handle more complex requests for you while protecting your privacy.

Private Cloud Compute

• Your data is never stored
• Used only for your requests
• Verifiable privacy promise

ChatGPT, seamlessly integrated.

With ChatGPT from OpenAI integrated into Siri and Writing Tools, you get even more expertise when it might be helpful for you — no need to jump between tools. Siri can tap into ChatGPT for certain requests, including questions about photos or documents. And with Compose in Writing Tools, you can create and illustrate original content from scratch.

You control when ChatGPT is used and will be asked before any of your information is shared. Anyone can access ChatGPT for free, without creating an account. ChatGPT subscribers can connect accounts to access paid features within these experiences.

New possibilities for your favorite apps.

New App Intents, APIs, and frameworks make it incredibly easy for developers to integrate system-level features like Siri, Writing Tools, and Image Playground into your favorite apps.

Learn more about developing for Apple Intelligence

Apple Intelligence is compatible with these devices.

Apple Intelligence is free to use and will initially be available in U.S. English. Coming in beta this fall. *

• iPhone 15 Pro Max A17 Pro
• iPhone 15 Pro A17 Pro
• iPad Pro M1 and later
• iPad Air M1 and later
• MacBook Air M1 and later
• MacBook Pro M1 and later
• iMac M1 and later
• Mac mini M1 and later
• Mac Studio M1 Max and later
• Mac Pro M2 Ultra