Research methodology vs. research methods
The research methodology or design is the overall strategy and rationale that you used to carry out the research. Whereas, research methods are the specific tools and processes you use to gather and understand the data you need to test your hypothesis.
To further understand research methodology, let’s explore some examples of research methodology:
a. Qualitative research methodology example: A study exploring the impact of author branding on author popularity might utilize in-depth interviews to gather personal experiences and perspectives.
b. Quantitative research methodology example: A research project investigating the effects of a book promotion technique on book sales could employ a statistical analysis of profit margins and sales before and after the implementation of the method.
c. Mixed-Methods research methodology example: A study examining the relationship between social media use and academic performance might combine both qualitative and quantitative approaches. It could include surveys to quantitatively assess the frequency of social media usage and its correlation with grades, alongside focus groups or interviews to qualitatively explore students’ perceptions and experiences regarding how social media affects their study habits and academic engagement.
These examples highlight the meaning of methodology in research and how it guides the research process, from data collection to analysis, ensuring the study’s objectives are met efficiently.
When it comes to writing your study, the methodology in research papers or a dissertation plays a pivotal role. A well-crafted methodology section of a research paper or thesis not only enhances the credibility of your research but also provides a roadmap for others to replicate or build upon your work.
Wondering how to write the research methodology section? Follow these steps to create a strong methods chapter:
At the start of a research paper , you would have provided the background of your research and stated your hypothesis or research problem. In this section, you will elaborate on your research strategy.
Begin by restating your research question and proceed to explain what type of research you opted for to test it. Depending on your research, here are some questions you can consider:
a. Did you use qualitative or quantitative data to test the hypothesis?
b. Did you perform an experiment where you collected data or are you writing a dissertation that is descriptive/theoretical without data collection?
c. Did you use primary data that you collected or analyze secondary research data or existing data as part of your study?
These questions will help you establish the rationale for your study on a broader level, which you will follow by elaborating on the specific methods you used to collect and understand your data.
Now that you have told your reader what type of research you’ve undertaken for the dissertation, it’s time to dig into specifics. State what specific methods you used and explain the conditions and variables involved. Explain what the theoretical framework behind the method was, what samples you used for testing it, and what tools and materials you used to collect the data.
Once you have explained the data collection process, explain how you analyzed and studied the data. Here, your focus is simply to explain the methods of analysis rather than the results of the study.
Here are some questions you can answer at this stage:
a. What tools or software did you use to analyze your results?
b. What parameters or variables did you consider while understanding and studying the data you’ve collected?
c. Was your analysis based on a theoretical framework?
Your mode of analysis will change depending on whether you used a quantitative or qualitative research methodology in your study. If you’re working within the hard sciences or physical sciences, you are likely to use a quantitative research methodology (relying on numbers and hard data). If you’re doing a qualitative study, in the social sciences or humanities, your analysis may rely on understanding language and socio-political contexts around your topic. This is why it’s important to establish what kind of study you’re undertaking at the onset.
Now that you have gone through your research process in detail, you’ll also have to make a case for it. Justify your choice of methodology and methods, explaining why it is the best choice for your research question. This is especially important if you have chosen an unconventional approach or you’ve simply chosen to study an existing research problem from a different perspective. Compare it with other methodologies, especially ones attempted by previous researchers, and discuss what contributions using your methodology makes.
No matter how thorough a methodology is, it doesn’t come without its hurdles. This is a natural part of scientific research that is important to document so that your peers and future researchers are aware of it. Writing in a research paper about this aspect of your research process also tells your evaluator that you have actively worked to overcome the pitfalls that came your way and you have refined the research process.
1. Remember who you are writing for. Keeping sight of the reader/evaluator will help you know what to elaborate on and what information they are already likely to have. You’re condensing months’ work of research in just a few pages, so you should omit basic definitions and information about general phenomena people already know.
2. Do not give an overly elaborate explanation of every single condition in your study.
3. Skip details and findings irrelevant to the results.
4. Cite references that back your claim and choice of methodology.
5. Consistently emphasize the relationship between your research question and the methodology you adopted to study it.
To sum it up, what is methodology in research? It’s the blueprint of your research, essential for ensuring that your study is systematic, rigorous, and credible. Whether your focus is on qualitative research methodology, quantitative research methodology, or a combination of both, understanding and clearly defining your methodology is key to the success of your research.
Once you write the research methodology and complete writing the entire research paper, the next step is to edit your paper. As experts in research paper editing and proofreading services , we’d love to help you perfect your paper!
Here are some other articles that you might find useful:
What does research methodology mean, what types of research methodologies are there, what is qualitative research methodology, how to determine sample size in research methodology, what is action research methodology.
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This is very simplified and direct. Very helpful to understand the research methodology section of a dissertation
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Research methodology is a crucial aspect of any investigative process, serving as the blueprint for the entire research journey. If you are stuck in the methodology section of your research paper , then this blog will guide you on what is a research methodology, its types and how to successfully conduct one.
Table of Contents
Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings.
Research methodology is not confined to a singular approach; rather, it encapsulates a diverse range of methods tailored to the specific requirements of the research objectives.
Here is why Research methodology is important in academic and professional settings.
Research methodology forms the backbone of rigorous inquiry. It provides a structured approach that aids researchers in formulating precise thesis statements , selecting appropriate methodologies, and executing systematic investigations. This, in turn, enhances the quality and credibility of the research outcomes.
In both academic and professional contexts, the ability to reproduce research outcomes is paramount. A well-defined research methodology establishes clear procedures, making it possible for others to replicate the study. This not only validates the findings but also contributes to the cumulative nature of knowledge.
In professional settings, decisions often hinge on reliable data and insights. Research methodology equips professionals with the tools to gather pertinent information, analyze it rigorously, and derive meaningful conclusions.
This informed decision-making is instrumental in achieving organizational goals and staying ahead in competitive environments.
For academic researchers, adherence to robust research methodology is a hallmark of excellence. Institutions value research that adheres to high standards of methodology, fostering a culture of academic rigour and intellectual integrity. Furthermore, it prepares students with critical skills applicable beyond academia.
Research methodology instills a problem-solving mindset by encouraging researchers to approach challenges systematically. It equips individuals with the skills to dissect complex issues, formulate hypotheses , and devise effective strategies for investigation.
In the pursuit of knowledge and discovery, understanding the fundamentals of research methodology is paramount.
Research, in its essence, is a systematic and organized process of inquiry aimed at expanding our understanding of a particular subject or phenomenon. It involves the exploration of existing knowledge, the formulation of hypotheses, and the collection and analysis of data to draw meaningful conclusions.
Research is a dynamic and iterative process that contributes to the continuous evolution of knowledge in various disciplines.
Research takes on various forms, each tailored to the nature of the inquiry. Broadly classified, research can be categorized into two main types:
To conduct effective research, one must go through the different components of research methodology. These components form the scaffolding that supports the entire research process, ensuring its coherence and validity.
Research design serves as the blueprint for the entire research project. It outlines the overall structure and strategy for conducting the study. The three primary types of research design are:
Choosing the right data collection methods is crucial for obtaining reliable and relevant information. Common methods include:
Once data is collected, analysis becomes imperative to derive meaningful conclusions. Different methodologies exist for quantitative and qualitative data:
Selecting an appropriate research method is a critical decision in the research process. It determines the approach, tools, and techniques that will be used to answer the research questions.
Quantitative research involves the collection and analysis of numerical data, providing a structured and objective approach to understanding and explaining phenomena.
Experimental research involves manipulating variables to observe the effect on another variable under controlled conditions. It aims to establish cause-and-effect relationships.
Key Characteristics:
Applications: Commonly used in scientific studies and psychology to test hypotheses and identify causal relationships.
Survey research gathers information from a sample of individuals through standardized questionnaires or interviews. It aims to collect data on opinions, attitudes, and behaviours.
Applications: Widely employed in social sciences, marketing, and public opinion research to understand trends and preferences.
Descriptive research seeks to portray an accurate profile of a situation or phenomenon. It focuses on answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.
Applications: Useful in situations where researchers want to understand and describe a phenomenon without altering it, common in social sciences and education.
Qualitative research emphasizes exploring and understanding the depth and complexity of phenomena through non-numerical data.
A case study is an in-depth exploration of a particular person, group, event, or situation. It involves detailed, context-rich analysis.
Applications: Common in social sciences, psychology, and business to investigate complex and specific instances.
Ethnography involves immersing the researcher in the culture or community being studied to gain a deep understanding of their behaviours, beliefs, and practices.
Applications: Widely used in anthropology, sociology, and cultural studies to explore and document cultural practices.
Grounded theory aims to develop theories grounded in the data itself. It involves systematic data collection and analysis to construct theories from the ground up.
Applications: Commonly applied in sociology, nursing, and management studies to generate theories from empirical data.
Research design is the structural framework that outlines the systematic process and plan for conducting a study. It serves as the blueprint, guiding researchers on how to collect, analyze, and interpret data.
Exploratory design.
Exploratory research design is employed when a researcher aims to explore a relatively unknown subject or gain insights into a complex phenomenon.
Applications: Valuable in the early stages of investigation, especially when the researcher seeks a deeper understanding of a subject before formalizing research questions.
Descriptive research design focuses on portraying an accurate profile of a situation, group, or phenomenon.
Applications: Widely used in social sciences, marketing, and educational research to provide detailed and objective descriptions.
Explanatory research design aims to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how’ behind observed relationships.
Applications: Commonly employed in scientific studies and social sciences to delve into the underlying reasons behind observed patterns.
Cross-sectional design.
Cross-sectional designs collect data from participants at a single point in time.
Applications: Suitable for studying characteristics or behaviours that are stable or not expected to change rapidly.
Longitudinal designs involve the collection of data from the same participants over an extended period.
Applications: Ideal for studying developmental processes, trends, or the impact of interventions over time.
Experimental design.
Experimental designs involve manipulating variables under controlled conditions to observe the effect on another variable.
Applications: Commonly used in scientific studies, psychology, and medical research to establish causal relationships.
Non-experimental designs observe and describe phenomena without manipulating variables.
Applications: Suitable for studying complex phenomena in real-world settings where manipulation may not be ethical or feasible.
Effective data collection is fundamental to the success of any research endeavour.
Objective Design:
Structured Format:
Pilot Testing:
Sampling Strategy:
Establishing Rapport:
Open-Ended Questions:
Active Listening:
Ethical Considerations:
1. participant observation.
Immersive Participation:
Field Notes:
Ethical Awareness:
Objective Observation:
Data Reliability:
Contextual Understanding:
1. using existing data.
Identifying Relevant Archives:
Data Verification:
Ethical Use:
Incomplete or Inaccurate Archives:
Temporal Bias:
Access Limitations:
Conducting research is a complex and dynamic process, often accompanied by a myriad of challenges. Addressing these challenges is crucial to ensure the reliability and validity of research findings.
Sampling bias:.
Measurement error:.
Timeline pressures:.
Selection bias:.
Conducting successful research relies not only on the application of sound methodologies but also on strategic planning and effective collaboration. Here are some tips to enhance the success of your research methodology:
Well-defined research objectives guide the entire research process. Clearly articulate the purpose of your study, outlining specific research questions or hypotheses.
A thorough literature review provides a foundation for understanding existing knowledge and identifying gaps. Invest time in reviewing relevant literature to inform your research design and methodology.
A detailed plan serves as a roadmap, ensuring all aspects of the research are systematically addressed. Develop a detailed research plan outlining timelines, milestones, and tasks.
Ethical practices are fundamental to maintaining the integrity of research. Address ethical considerations early, obtain necessary approvals, and ensure participant rights are safeguarded.
Research methodologies evolve, and staying updated is essential for employing the most effective techniques. Engage in continuous learning by attending workshops, conferences, and reading recent publications.
Unforeseen challenges may arise during research, necessitating adaptability in methods. Be flexible and willing to modify your approach when needed, ensuring the integrity of the study.
Research is often an iterative process, and refining methods based on ongoing findings enhance the study’s robustness. Regularly review and refine your research design and methods as the study progresses.
What is the research methodology.
Research methodology is the systematic process of planning, executing, and evaluating scientific investigation. It encompasses the techniques, tools, and procedures used to collect, analyze, and interpret data, ensuring the reliability and validity of research findings.
Research methodologies include qualitative and quantitative approaches. Qualitative methods involve in-depth exploration of non-numerical data, while quantitative methods use statistical analysis to examine numerical data. Mixed methods combine both approaches for a comprehensive understanding of research questions.
To write a research methodology, clearly outline the study’s design, data collection, and analysis procedures. Specify research tools, participants, and sampling methods. Justify choices and discuss limitations. Ensure clarity, coherence, and alignment with research objectives for a robust methodology section.
In the methodology section of a research paper, describe the study’s design, data collection, and analysis methods. Detail procedures, tools, participants, and sampling. Justify choices, address ethical considerations, and explain how the methodology aligns with research objectives, ensuring clarity and rigour.
Mixed research methodology combines both qualitative and quantitative research approaches within a single study. This approach aims to enhance the details and depth of research findings by providing a more comprehensive understanding of the research problem or question.
Mediating variables explain the relationship, while moderating variables influence its strength or direction under different conditions.
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Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.
Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.
It should include:
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How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.
Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .
It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.
You can start by introducing your overall approach to your research. You have two options here.
What research problem or question did you investigate?
And what type of data did you need to achieve this aim?
Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?
Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .
In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.
Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.
Surveys Describe where, when, and how the survey was conducted.
Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.
Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.
The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.
The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.
Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.
In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.
Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)
Interviews or focus groups Describe where, when, and how the interviews were conducted.
Participant observation Describe where, when, and how you conducted the observation or ethnography .
Existing data Explain how you selected case study materials for your analysis.
In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.
Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.
Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.
Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.
Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.
Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.
In quantitative research , your analysis will be based on numbers. In your methods section, you can include:
In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).
Specific methods might include:
Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.
Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.
In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .
Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.
The methodology section should clearly show why your methods suit your objectives and convince the reader that you chose the best possible approach to answering your problem statement and research questions .
Your methodology can be strengthened by referencing existing research in your field. This can help you to:
Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.
Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.
Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.
Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).
In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .
Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.
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.
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Research methodology involves a systematic and well-structured approach to conducting scholarly or scientific inquiries. Knowing the significance of research methodology and its different components is crucial as it serves as the basis for any study.
Typically, your research topic will start as a broad idea you want to investigate more thoroughly. Once you’ve identified a research problem and created research questions , you must choose the appropriate methodology and frameworks to address those questions effectively.
Research methodology is the process or the way you intend to execute your study. The methodology section of a research paper outlines how you plan to conduct your study. It covers various steps such as collecting data, statistical analysis, observing participants, and other procedures involved in the research process
The methods section should give a description of the process that will convert your idea into a study. Additionally, the outcomes of your process must provide valid and reliable results resonant with the aims and objectives of your research. This thumb rule holds complete validity, no matter whether your paper has inclinations for qualitative or quantitative usage.
Studying research methods used in related studies can provide helpful insights and direction for your own research. Now easily discover papers related to your topic on SciSpace and utilize our AI research assistant, Copilot , to quickly review the methodologies applied in different papers.
While deciding on your approach towards your research, the reason or factors you weighed in choosing a particular problem and formulating a research topic need to be validated and explained. A research methodology helps you do exactly that. Moreover, a good research methodology lets you build your argument to validate your research work performed through various data collection methods, analytical methods, and other essential points.
Just imagine it as a strategy documented to provide an overview of what you intend to do.
While undertaking any research writing or performing the research itself, you may get drifted in not something of much importance. In such a case, a research methodology helps you to get back to your outlined work methodology.
A research methodology helps in keeping you accountable for your work. Additionally, it can help you evaluate whether your work is in sync with your original aims and objectives or not. Besides, a good research methodology enables you to navigate your research process smoothly and swiftly while providing effective planning to achieve your desired results.
Usually, you must ensure to include the following stated aspects while deciding over the basic structure of your research methodology:
Explain what research methods you’re going to use. Whether you intend to proceed with quantitative or qualitative, or a composite of both approaches, you need to state that explicitly. The option among the three depends on your research’s aim, objectives, and scope.
Based on logic and reason, let your readers know why you have chosen said research methodologies. Additionally, you have to build strong arguments supporting why your chosen research method is the best way to achieve the desired outcome.
The mechanism encompasses the research methods or instruments you will use to develop your research methodology. It usually refers to your data collection methods. You can use interviews, surveys, physical questionnaires, etc., of the many available mechanisms as research methodology instruments. The data collection method is determined by the type of research and whether the data is quantitative data(includes numerical data) or qualitative data (perception, morale, etc.) Moreover, you need to put logical reasoning behind choosing a particular instrument.
The results will be available once you have finished experimenting. However, you should also explain how you plan to use the data to interpret the findings. This section also aids in understanding the problem from within, breaking it down into pieces, and viewing the research problem from various perspectives.
Anything that you feel must be explained to spread more awareness among readers and focus groups must be included and described in detail. You should not just specify your research methodology on the assumption that a reader is aware of the topic.
All the relevant information that explains and simplifies your research paper must be included in the methodology section. If you are conducting your research in a non-traditional manner, give a logical justification and list its benefits.
Include information about the sample and sample space in the methodology section. The term "sample" refers to a smaller set of data that a researcher selects or chooses from a larger group of people or focus groups using a predetermined selection method. Let your readers know how you are going to distinguish between relevant and non-relevant samples. How you figured out those exact numbers to back your research methodology, i.e. the sample spacing of instruments, must be discussed thoroughly.
For example, if you are going to conduct a survey or interview, then by what procedure will you select the interviewees (or sample size in case of surveys), and how exactly will the interview or survey be conducted.
This part, which is frequently assumed to be unnecessary, is actually very important. The challenges and limitations that your chosen strategy inherently possesses must be specified while you are conducting different types of research.
You must have observed that all research papers, dissertations, or theses carry a chapter entirely dedicated to research methodology. This section helps maintain your credibility as a better interpreter of results rather than a manipulator.
A good research methodology always explains the procedure, data collection methods and techniques, aim, and scope of the research. In a research study, it leads to a well-organized, rationality-based approach, while the paper lacking it is often observed as messy or disorganized.
You should pay special attention to validating your chosen way towards the research methodology. This becomes extremely important in case you select an unconventional or a distinct method of execution.
Curating and developing a strong, effective research methodology can assist you in addressing a variety of situations, such as:
As a researcher, you must choose which tools or data collection methods that fit best in terms of the relevance of your research. This decision has to be wise.
There exists many research equipments or tools that you can use to carry out your research process. These are classified as:
An interview aimed to get your desired research outcomes can be undertaken in many different ways. For example, you can design your interview as structured, semi-structured, or unstructured. What sets them apart is the degree of formality in the questions. On the other hand, in a group interview, your aim should be to collect more opinions and group perceptions from the focus groups on a certain topic rather than looking out for some formal answers.
In surveys, you are in better control if you specifically draft the questions you seek the response for. For example, you may choose to include free-style questions that can be answered descriptively, or you may provide a multiple-choice type response for questions. Besides, you can also opt to choose both ways, deciding what suits your research process and purpose better.
Similar to the group interviews, here, you can select a group of individuals and assign them a topic to discuss or freely express their opinions over that. You can simultaneously note down the answers and later draft them appropriately, deciding on the relevance of every response.
If your research domain is humanities or sociology, observations are the best-proven method to draw your research methodology. Of course, you can always include studying the spontaneous response of the participants towards a situation or conducting the same but in a more structured manner. A structured observation means putting the participants in a situation at a previously decided time and then studying their responses.
Of all the tools described above, it is you who should wisely choose the instruments and decide what’s the best fit for your research. You must not restrict yourself from multiple methods or a combination of a few instruments if appropriate in drafting a good research methodology.
A research methodology exists in various forms. Depending upon their approach, whether centered around words, numbers, or both, methodologies are distinguished as qualitative, quantitative, or an amalgamation of both.
When a research methodology primarily focuses on words and textual data, then it is generally referred to as qualitative research methodology. This type is usually preferred among researchers when the aim and scope of the research are mainly theoretical and explanatory.
The instruments used are observations, interviews, and sample groups. You can use this methodology if you are trying to study human behavior or response in some situations. Generally, qualitative research methodology is widely used in sociology, psychology, and other related domains.
If your research is majorly centered on data, figures, and stats, then analyzing these numerical data is often referred to as quantitative research methodology. You can use quantitative research methodology if your research requires you to validate or justify the obtained results.
In quantitative methods, surveys, tests, experiments, and evaluations of current databases can be advantageously used as instruments If your research involves testing some hypothesis, then use this methodology.
As the name suggests, the amalgam methodology uses both quantitative and qualitative approaches. This methodology is used when a part of the research requires you to verify the facts and figures, whereas the other part demands you to discover the theoretical and explanatory nature of the research question.
The instruments for the amalgam methodology require you to conduct interviews and surveys, including tests and experiments. The outcome of this methodology can be insightful and valuable as it provides precise test results in line with theoretical explanations and reasoning.
The amalgam method, makes your work both factual and rational at the same time.
If you have kept your sincerity and awareness intact with the aims and scope of research well enough, you must have got an idea of which research methodology suits your work best.
Before deciding which research methodology answers your research question, you must invest significant time in reading and doing your homework for that. Taking references that yield relevant results should be your first approach to establishing a research methodology.
Moreover, you should never refrain from exploring other options. Before setting your work in stone, you must try all the available options as it explains why the choice of research methodology that you finally make is more appropriate than the other available options.
You should always go for a quantitative research methodology if your research requires gathering large amounts of data, figures, and statistics. This research methodology will provide you with results if your research paper involves the validation of some hypothesis.
Whereas, if you are looking for more explanations, reasons, opinions, and public perceptions around a theory, you must use qualitative research methodology.The choice of an appropriate research methodology ultimately depends on what you want to achieve through your research.
1. how to write a research methodology.
You can always provide a separate section for research methodology where you should specify details about the methods and instruments used during the research, discussions on result analysis, including insights into the background information, and conveying the research limitations.
There generally exists four types of research methodology i.e.
The set of techniques or procedures followed to discover and analyze the information gathered to validate or justify a research outcome is generally called Research Methodology.
Your research methodology directly reflects the validity of your research outcomes and how well-informed your research work is. Moreover, it can help future researchers cite or refer to your research if they plan to use a similar research methodology.
I f you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!
In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.
Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how a researcher systematically designs a study to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:
Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just what methodological choices were made, but also explains why they were made. In other words, the methodology chapter should justify the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions.
So, it’s the same as research design?
Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .
Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.
Let’s take a closer look.
Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.
It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president.
Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .
As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.
Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).
How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study. There are many different sampling methods you can choose from, but the two overarching categories are probability sampling and non-probability sampling .
Probability sampling involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable to the entire population.
Non-probability sampling , on the other hand, doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .
To learn more about sampling methods, be sure to check out the video below.
As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:
The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.
Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative (words-based) or quantitative (numbers-based).
Popular data analysis methods in qualitative research include:
Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some common qualitative analysis methods, along with practical examples.
As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.
If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis).
Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).
Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components.
In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .
Triangulation is one of the best ways to enhance the credibility of your research. Learn about the different options here.
Learn everything you need to know about research limitations (AKA limitations of the study). Includes practical examples from real studies.
Learn about in vivo coding, a popular qualitative coding technique ideal for studies where the nuances of language are central to the aims.
Learn about process coding, a popular qualitative coding technique ideal for studies exploring processes, actions and changes over time.
Inductive, Deductive & Abductive Coding Qualitative Coding Approaches Explained...
📄 FREE TEMPLATES
Research Topic Ideation
Proposal Writing
Literature Review
Methodology & Analysis
Academic Writing
Referencing & Citing
Apps, Tools & Tricks
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I am writing a APA Format paper . I using questionnaire with 120 STDs teacher for my participant. Can you write me mthology for this research. Send it through email sent. Just need a sample as an example please. My topic is ” impacts of overcrowding on students learning
Thanks for your comment.
We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.
All the best with your research.
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Thanks for the feedback, Matobela. Good luck with your research methodology.
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Thanks for the kind words, Edward. Good luck with your research!
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Great to hear that, Ngwisa. Good luck with your research methodology!
Thank you for keeping your presentation simples and short and covering key information for research methodology. My key takeaway: Start with defining your research objective the other will depend on the aims of your research question.
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Sure. You’re welcome to book an initial consultation with one of our Research Coaches to discuss how we can assist – https://gradcoach.com/book/new/ .
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how do i reference this?
MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.
APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/
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The methods section of a research paper provides the information by which a study’s validity is judged. The method section answers two main questions: 1) How was the data collected or generated? 2) How was it analyzed? The writing should be direct and precise and written in the past tense.
You must explain how you obtained and analyzed your results for the following reasons:
Bem, Daryl J. Writing the Empirical Journal Article . Psychology Writing Center. University of Washington; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.
I. Groups of Research Methods
There are two main groups of research methods in the social sciences:
II. Content
An effectively written methodology section should:
NOTE : Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic.
III. Problems to Avoid
Irrelevant Detail The methodology section of your paper should be thorough but to the point. Don’t provide any background information that doesn’t directly help the reader to understand why a particular method was chosen, how the data was gathered or obtained, and how it was analyzed. Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. NOTE: An exception to this rule is if you select an unconventional approach to doing the method; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall research process. Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose. Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].
It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.
Azevedo, L.F. et al. How to Write a Scientific Paper: Writing the Methods Section. Revista Portuguesa de Pneumologia 17 (2011): 232-238; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section . The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Writing the Experimental Report: Methods, Results, and Discussion . The Writing Lab and The OWL. Purdue University; Methods and Materials . The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.
Statistical Designs and Tests? Do Not Fear Them!
Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.
Knowing the Relationship Between Theories and Methods
There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.
Introspectively engage in an ongoing dialectic between theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.
Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics. Part 1, Chapter 3. Boise State University; The Theory-Method Relationship . S-Cool Revision. United Kingdom.
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The methods section of a research paper provides the information by which a study's validity is judged. Therefore, it requires a clear and precise description of how an experiment was done, and the rationale for why specific experimental procedures were chosen. The methods section should describe what was done to answer the research question, describe how it was done, justify the experimental design, and explain how the results were analyzed. Scientific writing is direct and orderly. Therefore, the methods section structure should: describe the materials used in the study, explain how the materials were prepared for the study, describe the research protocol, explain how measurements were made and what calculations were performed, and state which statistical tests were done to analyze the data. Once all elements of the methods section are written, subsequent drafts should focus on how to present those elements as clearly and logically as possibly. The description of preparations, measurements, and the protocol should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. Material in each section should be organized by topic from most to least important.
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Home » Research Methods – Types, Examples and Guide
Table of Contents
Definition:
Research Methods refer to the techniques, procedures, and processes used by researchers to collect , analyze, and interpret data in order to answer research questions or test hypotheses. The methods used in research can vary depending on the research questions, the type of data that is being collected, and the research design.
Types of Research Methods are as follows:
Qualitative research methods are used to collect and analyze non-numerical data. This type of research is useful when the objective is to explore the meaning of phenomena, understand the experiences of individuals, or gain insights into complex social processes. Qualitative research methods include interviews, focus groups, ethnography, and content analysis.
Quantitative research methods are used to collect and analyze numerical data. This type of research is useful when the objective is to test a hypothesis, determine cause-and-effect relationships, and measure the prevalence of certain phenomena. Quantitative research methods include surveys, experiments, and secondary data analysis.
Mixed Method Research refers to the combination of both qualitative and quantitative research methods in a single study. This approach aims to overcome the limitations of each individual method and to provide a more comprehensive understanding of the research topic. This approach allows researchers to gather both quantitative data, which is often used to test hypotheses and make generalizations about a population, and qualitative data, which provides a more in-depth understanding of the experiences and perspectives of individuals.
The following Table shows the key differences between Quantitative, Qualitative and Mixed Research Methods
Research Method | Quantitative | Qualitative | Mixed Methods |
---|---|---|---|
To measure and quantify variables | To understand the meaning and complexity of phenomena | To integrate both quantitative and qualitative approaches | |
Typically focused on testing hypotheses and determining cause and effect relationships | Typically exploratory and focused on understanding the subjective experiences and perspectives of participants | Can be either, depending on the research design | |
Usually involves standardized measures or surveys administered to large samples | Often involves in-depth interviews, observations, or analysis of texts or other forms of data | Usually involves a combination of quantitative and qualitative methods | |
Typically involves statistical analysis to identify patterns and relationships in the data | Typically involves thematic analysis or other qualitative methods to identify themes and patterns in the data | Usually involves both quantitative and qualitative analysis | |
Can provide precise, objective data that can be generalized to a larger population | Can provide rich, detailed data that can help understand complex phenomena in depth | Can combine the strengths of both quantitative and qualitative approaches | |
May not capture the full complexity of phenomena, and may be limited by the quality of the measures used | May be subjective and may not be generalizable to larger populations | Can be time-consuming and resource-intensive, and may require specialized skills | |
Typically focused on testing hypotheses and determining cause-and-effect relationships | Surveys, experiments, correlational studies | Interviews, focus groups, ethnography | Sequential explanatory design, convergent parallel design, explanatory sequential design |
Examples of Research Methods are as follows:
Qualitative Research Example:
A researcher wants to study the experience of cancer patients during their treatment. They conduct in-depth interviews with patients to gather data on their emotional state, coping mechanisms, and support systems.
Quantitative Research Example:
A company wants to determine the effectiveness of a new advertisement campaign. They survey a large group of people, asking them to rate their awareness of the product and their likelihood of purchasing it.
Mixed Research Example:
A university wants to evaluate the effectiveness of a new teaching method in improving student performance. They collect both quantitative data (such as test scores) and qualitative data (such as feedback from students and teachers) to get a complete picture of the impact of the new method.
Research methods are used in various fields to investigate, analyze, and answer research questions. Here are some examples of how research methods are applied in different fields:
Research methods serve several purposes, including:
Research methods are used when you need to gather information or data to answer a question or to gain insights into a particular phenomenon.
Here are some situations when research methods may be appropriate:
Research methods provide several advantages, including:
Researcher, Academic Writer, Web developer
Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.
The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.
A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.
Having a good research methodology in place has the following advantages: 3
Types of research methodology.
There are three types of research methodology based on the type of research and the data required. 1
Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.
In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:
During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.
Qualitative research 5
Quantitative research 6
What are data analysis methods.
The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.
Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.
Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:
Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:
Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:
Here are some important factors to consider when choosing a research methodology: 8
How to write a research methodology .
A research methodology should include the following components: 3,9
The methods section is a critical part of the research papers, allowing researchers to use this to understand your findings and replicate your work when pursuing their own research. However, it is usually also the most difficult section to write. This is where Paperpal can help you overcome the writer’s block and create the first draft in minutes with Paperpal Copilot, its secure generative AI feature suite.
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Q1. What are the key components of research methodology?
A1. A good research methodology has the following key components:
Q2. Why is ethical consideration important in research methodology?
A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10
Q3. What is the difference between methodology and method?
A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.
Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.
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Speaker 1: After the title page and abstract, the reader's first true interaction with your research paper is the introduction. Your introduction will establish the foundation upon which your readers approach your work, and if you use the tips we discuss in this video, these readers should be able to logically apply the rules set in your introduction to all parts of your paper, all the way through the conclusion. What exactly is the purpose of the introduction? Think about your paper as a chronological story. It will begin at point A, the introduction, and move in time towards point B, the discussion and conclusion. Since your introduction includes content about the gaps in knowledge that your study aims to fill, the results you elaborate on in your discussion section should therefore be somewhat familiar to the reader, as you have already touched upon them in the introduction section. The introduction must answer two main questions. Why was this particular study needed to fill the gaps in knowledge? And why does this particular gap need filling? Imagine our entire plane of knowledge as an incomplete puzzle. The pieces snapped together are what is established, or what is known. The missing piece is the gap in knowledge, or what is currently unknown. This is what your study will be helping to explain. So the context you provide in the introduction must first identify that there is a knowledge gap in what it is, it must explain why it needs to be filled, and then briefly summarize how this study intends to fill that gap and why. The introduction is one of the most compact parts of the research paper, since it is not very long but needs to essentially give a complete overview of the context in which your study is taking place, and your specific reasons for doing the study. Most tend to be around 10% of the total length of your paper. The introduction consists of background information about a topic being studied, the rationale for undertaking the study, or for filling the gap with this particular information, key references to preliminary work or closely related papers appearing elsewhere, a clarification of important terms, definitions, or abbreviations to be used in the paper, and a review of related studies in which you give a brief but incisive analysis of work that heavily concerns your study. It could be a very similar study or one that supports the findings of your new study. So how should you structure your introduction? As you can see in this figure, your introduction should start broadly and then narrow until it reaches your hypothesis. The first thing you want to do is state your area of research and then immediately show what is already known. This is also known as background information. Then move on to what is unknown, the problem or gap you want to resolve. Finally, you should discuss how you will resolve this problem using a clear hypothesis. In step one, you will show what is already known. Start with a strong statement that reflects your research subject area and ask questions or post statements to frame the problems your study explores. You can ask general questions here to guide your readers to the problem and show them what we already know. For instance, what do we know about breathing capability of bottlenose dolphins? Use keywords from your title, the exact language of your study that is, to zero in on the problem at hand and show the relevance of your work. Avoid stating background information that is too broad in nature. You don't need to state too many obvious facts that your readers would know. If you are writing about bottlenose dolphins, for instance, you probably don't need to explain to them that mammals breathe oxygen. At the beginning of the introduction, you should also be sure to cite all of the sources that you use for background information and support. Only provide the necessary background information. Don't focus extensively on background, but use it to set up the context for doing this study. You should also review only relevant, up-to-date primary literature that supports your explanation of our current base of knowledge. In the second part of your introduction, you should answer the question, what is the knowledge gap? Here you will highlight areas where too little information is available. Explain how and why we should fill in that gap. What does this missing information do to impede our understanding of a process or system? And you should identify what logical next steps can be developed based on existing research. By showing you have examined current data and devised a method to find new applications and make new inferences, you're showing your peers that you are aware of the direction your research is moving in, and you're showing confidence in your decision to pursue this paper study. In the last part of your introduction, you will show how your study fills in the knowledge gap. This is where you state your purpose and give a clear hypothesis or objective of the study. The hypothesis is a very short 1-2 sentence supposition or explanation of what will happen in your study. This is quite often written as an if-then format. If X and Y are present, then Z will occur. Here you should also try to answer the question, if we fill this gap, what useful information will the readers gain? Many researchers have difficulty when it comes to deciding when to write their introduction. It is important to consider the order you draft your research paper, for as you recall, everything else in the research paper must flow from the introduction. Therefore, because it is one of the most difficult sections to nail down, consider writing the introduction second to last, after the materials and methods, results, and discussion section, and just before the conclusion. This will ensure you effectively lay a groundwork for the rest of your paper, and you can use the research you have already compiled to ensure that everything in your introduction is pertinent and accurate. In addition to content and organization, writers of research papers should also be aware of grammar and style issues that directly affect the readability and strength of their printed work. Here are some guidelines for writing the introduction section. Try and write in the active voice when possible. This will shorten your sentences and enhance the impact of your information. Always strive for concise sentences. This will allow you to get in all of the necessary information in this compact introduction section. Use stronger verbs when possible. This also impacts sentence length and strength of writing. Be careful not to overuse first-person pronouns such as I and we, and always organize your thoughts from the broad to the specific, as we have seen in our model. A strong introduction will encourage readers to read your entire research paper and help get your work published in scientific journals. For more information and tips on manuscript writing and journal submissions, visit the resources page at wordvice.com.
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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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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:
Carefully consider your timeframe and word limit: be realistic, and plan enough time to research, write, and edit.
The AI-powered Citation Checker helps you avoid common mistakes such as:
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:
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.
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.
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:
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.
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.
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.
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:
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 :
There are four main considerations when it comes to the second draft.
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 .
Check the content of each paragraph, making sure that:
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 .
Scribbr’s professional editors can help with the revision process with our award-winning proofreading services.
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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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Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research. Our analysis of a selection of questionable GPT-fabricated scientific papers found in Google Scholar shows that many are about applied, often controversial topics susceptible to disinformation: the environment, health, and computing. The resulting enhanced potential for malicious manipulation of society’s evidence base, particularly in politically divisive domains, is a growing concern.
Swedish School of Library and Information Science, University of Borås, Sweden
Department of Arts and Cultural Sciences, Lund University, Sweden
Division of Environmental Communication, Swedish University of Agricultural Sciences, Sweden
The use of ChatGPT to generate text for academic papers has raised concerns about research integrity. Discussion of this phenomenon is ongoing in editorials, commentaries, opinion pieces, and on social media (Bom, 2023; Stokel-Walker, 2024; Thorp, 2023). There are now several lists of papers suspected of GPT misuse, and new papers are constantly being added. 1 See for example Academ-AI, https://www.academ-ai.info/ , and Retraction Watch, https://retractionwatch.com/papers-and-peer-reviews-with-evidence-of-chatgpt-writing/ . While many legitimate uses of GPT for research and academic writing exist (Huang & Tan, 2023; Kitamura, 2023; Lund et al., 2023), its undeclared use—beyond proofreading—has potentially far-reaching implications for both science and society, but especially for their relationship. It, therefore, seems important to extend the discussion to one of the most accessible and well-known intermediaries between science, but also certain types of misinformation, and the public, namely Google Scholar, also in response to the legitimate concerns that the discussion of generative AI and misinformation needs to be more nuanced and empirically substantiated (Simon et al., 2023).
Google Scholar, https://scholar.google.com , is an easy-to-use academic search engine. It is available for free, and its index is extensive (Gusenbauer & Haddaway, 2020). It is also often touted as a credible source for academic literature and even recommended in library guides, by media and information literacy initiatives, and fact checkers (Tripodi et al., 2023). However, Google Scholar lacks the transparency and adherence to standards that usually characterize citation databases. Instead, Google Scholar uses automated crawlers, like Google’s web search engine (Martín-Martín et al., 2021), and the inclusion criteria are based on primarily technical standards, allowing any individual author—with or without scientific affiliation—to upload papers to be indexed (Google Scholar Help, n.d.). It has been shown that Google Scholar is susceptible to manipulation through citation exploits (Antkare, 2020) and by providing access to fake scientific papers (Dadkhah et al., 2017). A large part of Google Scholar’s index consists of publications from established scientific journals or other forms of quality-controlled, scholarly literature. However, the index also contains a large amount of gray literature, including student papers, working papers, reports, preprint servers, and academic networking sites, as well as material from so-called “questionable” academic journals, including paper mills. The search interface does not offer the possibility to filter the results meaningfully by material type, publication status, or form of quality control, such as limiting the search to peer-reviewed material.
To understand the occurrence of ChatGPT (co-)authored work in Google Scholar’s index, we scraped it for publications, including one of two common ChatGPT responses (see Appendix A) that we encountered on social media and in media reports (DeGeurin, 2024). The results of our descriptive statistical analyses showed that around 62% did not declare the use of GPTs. Most of these GPT-fabricated papers were found in non-indexed journals and working papers, but some cases included research published in mainstream scientific journals and conference proceedings. 2 Indexed journals mean scholarly journals indexed by abstract and citation databases such as Scopus and Web of Science, where the indexation implies journals with high scientific quality. Non-indexed journals are journals that fall outside of this indexation. More than half (57%) of these GPT-fabricated papers concerned policy-relevant subject areas susceptible to influence operations. To avoid increasing the visibility of these publications, we abstained from referencing them in this research note. However, we have made the data available in the Harvard Dataverse repository.
The publications were related to three issue areas—health (14.5%), environment (19.5%) and computing (23%)—with key terms such “healthcare,” “COVID-19,” or “infection”for health-related papers, and “analysis,” “sustainable,” and “global” for environment-related papers. In several cases, the papers had titles that strung together general keywords and buzzwords, thus alluding to very broad and current research. These terms included “biology,” “telehealth,” “climate policy,” “diversity,” and “disrupting,” to name just a few. While the study’s scope and design did not include a detailed analysis of which parts of the articles included fabricated text, our dataset did contain the surrounding sentences for each occurrence of the suspicious phrases that formed the basis for our search and subsequent selection. Based on that, we can say that the phrases occurred in most sections typically found in scientific publications, including the literature review, methods, conceptual and theoretical frameworks, background, motivation or societal relevance, and even discussion. This was confirmed during the joint coding, where we read and discussed all articles. It became clear that not just the text related to the telltale phrases was created by GPT, but that almost all articles in our sample of questionable articles likely contained traces of GPT-fabricated text everywhere.
Evidence hacking and backfiring effects
Generative pre-trained transformers (GPTs) can be used to produce texts that mimic scientific writing. These texts, when made available online—as we demonstrate—leak into the databases of academic search engines and other parts of the research infrastructure for scholarly communication. This development exacerbates problems that were already present with less sophisticated text generators (Antkare, 2020; Cabanac & Labbé, 2021). Yet, the public release of ChatGPT in 2022, together with the way Google Scholar works, has increased the likelihood of lay people (e.g., media, politicians, patients, students) coming across questionable (or even entirely GPT-fabricated) papers and other problematic research findings. Previous research has emphasized that the ability to determine the value and status of scientific publications for lay people is at stake when misleading articles are passed off as reputable (Haider & Åström, 2017) and that systematic literature reviews risk being compromised (Dadkhah et al., 2017). It has also been highlighted that Google Scholar, in particular, can be and has been exploited for manipulating the evidence base for politically charged issues and to fuel conspiracy narratives (Tripodi et al., 2023). Both concerns are likely to be magnified in the future, increasing the risk of what we suggest calling evidence hacking —the strategic and coordinated malicious manipulation of society’s evidence base.
The authority of quality-controlled research as evidence to support legislation, policy, politics, and other forms of decision-making is undermined by the presence of undeclared GPT-fabricated content in publications professing to be scientific. Due to the large number of archives, repositories, mirror sites, and shadow libraries to which they spread, there is a clear risk that GPT-fabricated, questionable papers will reach audiences even after a possible retraction. There are considerable technical difficulties involved in identifying and tracing computer-fabricated papers (Cabanac & Labbé, 2021; Dadkhah et al., 2023; Jones, 2024), not to mention preventing and curbing their spread and uptake.
However, as the rise of the so-called anti-vaxx movement during the COVID-19 pandemic and the ongoing obstruction and denial of climate change show, retracting erroneous publications often fuels conspiracies and increases the following of these movements rather than stopping them. To illustrate this mechanism, climate deniers frequently question established scientific consensus by pointing to other, supposedly scientific, studies that support their claims. Usually, these are poorly executed, not peer-reviewed, based on obsolete data, or even fraudulent (Dunlap & Brulle, 2020). A similar strategy is successful in the alternative epistemic world of the global anti-vaccination movement (Carrion, 2018) and the persistence of flawed and questionable publications in the scientific record already poses significant problems for health research, policy, and lawmakers, and thus for society as a whole (Littell et al., 2024). Considering that a person’s support for “doing your own research” is associated with increased mistrust in scientific institutions (Chinn & Hasell, 2023), it will be of utmost importance to anticipate and consider such backfiring effects already when designing a technical solution, when suggesting industry or legal regulation, and in the planning of educational measures.
Recommendations
Solutions should be based on simultaneous considerations of technical, educational, and regulatory approaches, as well as incentives, including social ones, across the entire research infrastructure. Paying attention to how these approaches and incentives relate to each other can help identify points and mechanisms for disruption. Recognizing fraudulent academic papers must happen alongside understanding how they reach their audiences and what reasons there might be for some of these papers successfully “sticking around.” A possible way to mitigate some of the risks associated with GPT-fabricated scholarly texts finding their way into academic search engine results would be to provide filtering options for facets such as indexed journals, gray literature, peer-review, and similar on the interface of publicly available academic search engines. Furthermore, evaluation tools for indexed journals 3 Such as LiU Journal CheckUp, https://ep.liu.se/JournalCheckup/default.aspx?lang=eng . could be integrated into the graphical user interfaces and the crawlers of these academic search engines. To enable accountability, it is important that the index (database) of such a search engine is populated according to criteria that are transparent, open to scrutiny, and appropriate to the workings of science and other forms of academic research. Moreover, considering that Google Scholar has no real competitor, there is a strong case for establishing a freely accessible, non-specialized academic search engine that is not run for commercial reasons but for reasons of public interest. Such measures, together with educational initiatives aimed particularly at policymakers, science communicators, journalists, and other media workers, will be crucial to reducing the possibilities for and effects of malicious manipulation or evidence hacking. It is important not to present this as a technical problem that exists only because of AI text generators but to relate it to the wider concerns in which it is embedded. These range from a largely dysfunctional scholarly publishing system (Haider & Åström, 2017) and academia’s “publish or perish” paradigm to Google’s near-monopoly and ideological battles over the control of information and ultimately knowledge. Any intervention is likely to have systemic effects; these effects need to be considered and assessed in advance and, ideally, followed up on.
Our study focused on a selection of papers that were easily recognizable as fraudulent. We used this relatively small sample as a magnifying glass to examine, delineate, and understand a problem that goes beyond the scope of the sample itself, which however points towards larger concerns that require further investigation. The work of ongoing whistleblowing initiatives 4 Such as Academ-AI, https://www.academ-ai.info/ , and Retraction Watch, https://retractionwatch.com/papers-and-peer-reviews-with-evidence-of-chatgpt-writing/ . , recent media reports of journal closures (Subbaraman, 2024), or GPT-related changes in word use and writing style (Cabanac et al., 2021; Stokel-Walker, 2024) suggest that we only see the tip of the iceberg. There are already more sophisticated cases (Dadkhah et al., 2023) as well as cases involving fabricated images (Gu et al., 2022). Our analysis shows that questionable and potentially manipulative GPT-fabricated papers permeate the research infrastructure and are likely to become a widespread phenomenon. Our findings underline that the risk of fake scientific papers being used to maliciously manipulate evidence (see Dadkhah et al., 2017) must be taken seriously. Manipulation may involve undeclared automatic summaries of texts, inclusion in literature reviews, explicit scientific claims, or the concealment of errors in studies so that they are difficult to detect in peer review. However, the mere possibility of these things happening is a significant risk in its own right that can be strategically exploited and will have ramifications for trust in and perception of science. Society’s methods of evaluating sources and the foundations of media and information literacy are under threat and public trust in science is at risk of further erosion, with far-reaching consequences for society in dealing with information disorders. To address this multifaceted problem, we first need to understand why it exists and proliferates.
Finding 1: 139 GPT-fabricated, questionable papers were found and listed as regular results on the Google Scholar results page. Non-indexed journals dominate.
Most questionable papers we found were in non-indexed journals or were working papers, but we did also find some in established journals, publications, conferences, and repositories. We found a total of 139 papers with a suspected deceptive use of ChatGPT or similar LLM applications (see Table 1). Out of these, 19 were in indexed journals, 89 were in non-indexed journals, 19 were student papers found in university databases, and 12 were working papers (mostly in preprint databases). Table 1 divides these papers into categories. Health and environment papers made up around 34% (47) of the sample. Of these, 66% were present in non-indexed journals.
Indexed journals* | 5 | 3 | 4 | 7 | 19 |
Non-indexed journals | 18 | 18 | 13 | 40 | 89 |
Student papers | 4 | 3 | 1 | 11 | 19 |
Working papers | 5 | 3 | 2 | 2 | 12 |
Total | 32 | 27 | 20 | 60 | 139 |
Finding 2: GPT-fabricated, questionable papers are disseminated online, permeating the research infrastructure for scholarly communication, often in multiple copies. Applied topics with practical implications dominate.
The 20 papers concerning health-related issues are distributed across 20 unique domains, accounting for 46 URLs. The 27 papers dealing with environmental issues can be found across 26 unique domains, accounting for 56 URLs. Most of the identified papers exist in multiple copies and have already spread to several archives, repositories, and social media. It would be difficult, or impossible, to remove them from the scientific record.
As apparent from Table 2, GPT-fabricated, questionable papers are seeping into most parts of the online research infrastructure for scholarly communication. Platforms on which identified papers have appeared include ResearchGate, ORCiD, Journal of Population Therapeutics and Clinical Pharmacology (JPTCP), Easychair, Frontiers, the Institute of Electrical and Electronics Engineer (IEEE), and X/Twitter. Thus, even if they are retracted from their original source, it will prove very difficult to track, remove, or even just mark them up on other platforms. Moreover, unless regulated, Google Scholar will enable their continued and most likely unlabeled discoverability.
Environment | researchgate.net (13) | orcid.org (4) | easychair.org (3) | ijope.com* (3) | publikasiindonesia.id (3) |
Health | researchgate.net (15) | ieee.org (4) | twitter.com (3) | jptcp.com** (2) | frontiersin.org (2) |
A word rain visualization (Centre for Digital Humanities Uppsala, 2023), which combines word prominences through TF-IDF 5 Term frequency–inverse document frequency , a method for measuring the significance of a word in a document compared to its frequency across all documents in a collection. scores with semantic similarity of the full texts of our sample of GPT-generated articles that fall into the “Environment” and “Health” categories, reflects the two categories in question. However, as can be seen in Figure 1, it also reveals overlap and sub-areas. The y-axis shows word prominences through word positions and font sizes, while the x-axis indicates semantic similarity. In addition to a certain amount of overlap, this reveals sub-areas, which are best described as two distinct events within the word rain. The event on the left bundles terms related to the development and management of health and healthcare with “challenges,” “impact,” and “potential of artificial intelligence”emerging as semantically related terms. Terms related to research infrastructures, environmental, epistemic, and technological concepts are arranged further down in the same event (e.g., “system,” “climate,” “understanding,” “knowledge,” “learning,” “education,” “sustainable”). A second distinct event further to the right bundles terms associated with fish farming and aquatic medicinal plants, highlighting the presence of an aquaculture cluster. Here, the prominence of groups of terms such as “used,” “model,” “-based,” and “traditional” suggests the presence of applied research on these topics. The two events making up the word rain visualization, are linked by a less dominant but overlapping cluster of terms related to “energy” and “water.”
The bar chart of the terms in the paper subset (see Figure 2) complements the word rain visualization by depicting the most prominent terms in the full texts along the y-axis. Here, word prominences across health and environment papers are arranged descendingly, where values outside parentheses are TF-IDF values (relative frequencies) and values inside parentheses are raw term frequencies (absolute frequencies).
Finding 3: Google Scholar presents results from quality-controlled and non-controlled citation databases on the same interface, providing unfiltered access to GPT-fabricated questionable papers.
Google Scholar’s central position in the publicly accessible scholarly communication infrastructure, as well as its lack of standards, transparency, and accountability in terms of inclusion criteria, has potentially serious implications for public trust in science. This is likely to exacerbate the already-known potential to exploit Google Scholar for evidence hacking (Tripodi et al., 2023) and will have implications for any attempts to retract or remove fraudulent papers from their original publication venues. Any solution must consider the entirety of the research infrastructure for scholarly communication and the interplay of different actors, interests, and incentives.
We searched and scraped Google Scholar using the Python library Scholarly (Cholewiak et al., 2023) for papers that included specific phrases known to be common responses from ChatGPT and similar applications with the same underlying model (GPT3.5 or GPT4): “as of my last knowledge update” and/or “I don’t have access to real-time data” (see Appendix A). This facilitated the identification of papers that likely used generative AI to produce text, resulting in 227 retrieved papers. The papers’ bibliographic information was automatically added to a spreadsheet and downloaded into Zotero. 6 An open-source reference manager, https://zotero.org .
We employed multiple coding (Barbour, 2001) to classify the papers based on their content. First, we jointly assessed whether the paper was suspected of fraudulent use of ChatGPT (or similar) based on how the text was integrated into the papers and whether the paper was presented as original research output or the AI tool’s role was acknowledged. Second, in analyzing the content of the papers, we continued the multiple coding by classifying the fraudulent papers into four categories identified during an initial round of analysis—health, environment, computing, and others—and then determining which subjects were most affected by this issue (see Table 1). Out of the 227 retrieved papers, 88 papers were written with legitimate and/or declared use of GPTs (i.e., false positives, which were excluded from further analysis), and 139 papers were written with undeclared and/or fraudulent use (i.e., true positives, which were included in further analysis). The multiple coding was conducted jointly by all authors of the present article, who collaboratively coded and cross-checked each other’s interpretation of the data simultaneously in a shared spreadsheet file. This was done to single out coding discrepancies and settle coding disagreements, which in turn ensured methodological thoroughness and analytical consensus (see Barbour, 2001). Redoing the category coding later based on our established coding schedule, we achieved an intercoder reliability (Cohen’s kappa) of 0.806 after eradicating obvious differences.
The ranking algorithm of Google Scholar prioritizes highly cited and older publications (Martín-Martín et al., 2016). Therefore, the position of the articles on the search engine results pages was not particularly informative, considering the relatively small number of results in combination with the recency of the publications. Only the query “as of my last knowledge update” had more than two search engine result pages. On those, questionable articles with undeclared use of GPTs were evenly distributed across all result pages (min: 4, max: 9, mode: 8), with the proportion of undeclared use being slightly higher on average on later search result pages.
To understand how the papers making fraudulent use of generative AI were disseminated online, we programmatically searched for the paper titles (with exact string matching) in Google Search from our local IP address (see Appendix B) using the googlesearch – python library(Vikramaditya, 2020). We manually verified each search result to filter out false positives—results that were not related to the paper—and then compiled the most prominent URLs by field. This enabled the identification of other platforms through which the papers had been spread. We did not, however, investigate whether copies had spread into SciHub or other shadow libraries, or if they were referenced in Wikipedia.
We used descriptive statistics to count the prevalence of the number of GPT-fabricated papers across topics and venues and top domains by subject. The pandas software library for the Python programming language (The pandas development team, 2024) was used for this part of the analysis. Based on the multiple coding, paper occurrences were counted in relation to their categories, divided into indexed journals, non-indexed journals, student papers, and working papers. The schemes, subdomains, and subdirectories of the URL strings were filtered out while top-level domains and second-level domains were kept, which led to normalizing domain names. This, in turn, allowed the counting of domain frequencies in the environment and health categories. To distinguish word prominences and meanings in the environment and health-related GPT-fabricated questionable papers, a semantically-aware word cloud visualization was produced through the use of a word rain (Centre for Digital Humanities Uppsala, 2023) for full-text versions of the papers. Font size and y-axis positions indicate word prominences through TF-IDF scores for the environment and health papers (also visualized in a separate bar chart with raw term frequencies in parentheses), and words are positioned along the x-axis to reflect semantic similarity (Skeppstedt et al., 2024), with an English Word2vec skip gram model space (Fares et al., 2017). An English stop word list was used, along with a manually produced list including terms such as “https,” “volume,” or “years.”
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This research has been supported by Mistra, the Swedish Foundation for Strategic Environmental Research, through the research program Mistra Environmental Communication (Haider, Ekström, Rödl) and the Marcus and Amalia Wallenberg Foundation [2020.0004] (Söderström).
The authors declare no competing interests.
The research described in this article was carried out under Swedish legislation. According to the relevant EU and Swedish legislation (2003:460) on the ethical review of research involving humans (“Ethical Review Act”), the research reported on here is not subject to authorization by the Swedish Ethical Review Authority (“etikprövningsmyndigheten”) (SRC, 2017).
This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author and source are properly credited.
All data needed to replicate this study are available at the Harvard Dataverse: https://doi.org/10.7910/DVN/WUVD8X
The authors wish to thank two anonymous reviewers for their valuable comments on the article manuscript as well as the editorial group of Harvard Kennedy School (HKS) Misinformation Review for their thoughtful feedback and input.
15 Pages Posted: 30 Aug 2024
Nanchang Hangkong University
affiliation not provided to SSRN
There are still some challenges in the computation speed and reproduction quality of holographic display. In this paper, a method is proposed to realize a high quality 3D holographic display by using a complex value convolutional neural network. Firstly, the layer-based method is used to cut and layer the object. The amplitude and phase of each layer of the object are calculated by a complex value network at the same time. Then, the output of the complex value type of the network is converted into a phase-only hologram, and each layer of the hologram is superimposed to reproduce the complete 3D object. In addition, a novel color convolutional neural network is used to generate R, G and B three-color holograms simultaneously, reducing the time required for three-channel recalculation of holograms. The proposed method only takes 0.02s to generate a hologram from single-layer object, the average peak signal-to-noise ratio of the reconstructed image is 28dB, and the structural similarity exceeds 0.99, which realizes a high-quality dynamic holographic display. The experimental results confirm the feasibility of the proposed method and provide a new method for real-time holographic display of 3D object.
Keywords: convolutional neural network, 3D holography, high quality display, real-time display
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Nanchang hangkong university ( email ).
Nanchang China
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The methods section is a fundamental section of any paper since it typically discusses the 'what', 'how', 'which', and 'why' of the study, which is necessary to arrive at the final conclusions. In a research article, the introduction, which serves to set the foundation for comprehending the background and results is usually ...
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Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research and your dissertation topic.
Research papers in the social and natural sciences often follow APA style. This article focuses on reporting quantitative research methods. In your APA methods section, you should report enough information to understand and replicate your study, including detailed information on the sample, measures, and procedures used.
I. Groups of Research Methods. There are two main groups of research methods in the social sciences: The empirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences.This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured.
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3. Follow the order of the results: To improve the readability and flow of your manuscript, match the order of specific methods to the order of the results that were achieved using those methods. 4. Use subheadings: Dividing the Methods section in terms of the experiments helps the reader to follow the section better.
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Learn how to write a strong methodology chapter that allows readers to evaluate the reliability and validity of the research. A good methodology chapter incl...
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 section of your paper describes how your research was conducted. This information allows readers to check whether your approach is accurate and dependable. A good methodology can help increase the reader's trust in your findings. First, we will define and differentiate quantitative and qualitative research.
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Abstract. The methods section of a research paper provides the information by which a study's validity is judged. Therefore, it requires a clear and precise description of how an experiment was done, and the rationale for why specific experimental procedures were chosen. The methods section should describe what was done to answer the research ...
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Speaker 1: After the title page and abstract, the reader's first true interaction with your research paper is the introduction. Your introduction will establish the foundation upon which your readers approach your work, and if you use the tips we discuss in this video, these readers should be able to logically apply the rules set in your introduction to all parts of your paper, all the way ...
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Academic journals, archives, and repositories are seeing an increasing number of questionable research papers clearly produced using generative AI. They are often created with widely available, general-purpose AI applications, most likely ChatGPT, and mimic scientific writing. Google Scholar easily locates and lists these questionable papers alongside reputable, quality-controlled research.
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