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Research Methodology – Types, Examples and writing Guide

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Research methodology is the backbone of any scientific or academic study, outlining the specific strategies and tools used to collect, analyze, and interpret data. A well-defined research methodology ensures that a study is conducted systematically, yielding reliable and valid results. This article explores the concept of research methodology, its various types, practical examples, and a step-by-step guide to writing a methodology section.

Research Methodology

Research methodology refers to the systematic plan and approach employed in a study to answer research questions or test hypotheses. It defines the tools, techniques, and procedures used to collect and analyze data, ensuring the research is structured and replicable.

For example, a study exploring the impact of remote learning on student performance might use surveys to collect data and statistical analysis to evaluate the findings.

Importance of Research Methodology

Clarity and Focus: Provides a clear roadmap for the study, ensuring alignment with research objectives.
Reliability: Ensures the study’s results can be replicated and trusted.
Validity: Confirms that the methods used are appropriate for answering the research questions.
Transparency: Allows others to evaluate the study’s credibility and rigor.
Adaptability: Enables adjustments to the research process if unforeseen challenges arise.

Research Methodology Structure

1. introduction.

The introduction provides an overview of the research methodology, explaining its purpose and relevance to the study. It briefly outlines the chosen approach (qualitative, quantitative, or mixed methods) and justifies its suitability for addressing the research questions or hypotheses.

Example: “This research employs a mixed-methods approach to explore the impact of remote work on employee productivity, combining quantitative surveys and qualitative interviews to gain a comprehensive understanding of the phenomenon.”

2. Research Design

This section describes the overall framework or design of the study. Common research designs include experimental, descriptive, correlational, or exploratory. The design should align with the research objectives and questions.

Type of design (e.g., experimental, case study, longitudinal).
Justification for the selected design.
Example: “A descriptive research design was chosen to investigate patterns of online shopping behavior among millennials during the pandemic.”

3. Data Collection Methods

Detail the methods and tools used to gather data. This includes the type of data (primary or secondary) and the specific techniques employed.

Data sources (e.g., surveys, interviews, observations, archival records).
Instruments or tools used (e.g., questionnaires, scales, software).
Procedures for data collection.
Example: “Primary data was collected through structured questionnaires distributed online, while secondary data was sourced from industry reports and previous research studies.”

4. Sampling

Explain the sampling method used to select participants or data points for the study. Include the sample size, criteria for inclusion or exclusion, and sampling technique.

Sampling population.
Sampling technique (e.g., random, stratified, purposive).
Rationale for the chosen sample size.
Example: “A stratified random sampling method was employed to ensure representation across age groups. The final sample comprised 200 participants aged 18–60.”

5. Data Analysis Techniques

Describe the techniques or tools used to analyze the collected data. This section should differentiate between qualitative and quantitative data analysis methods.

Quantitative analysis: statistical tools (e.g., SPSS, regression analysis).
Qualitative analysis: thematic analysis, coding, or content analysis.
Software or tools used (e.g., NVivo, Excel, Python).
Example: “Quantitative data was analyzed using SPSS software for descriptive and inferential statistics, while qualitative data was thematically coded using NVivo to identify recurring patterns.”

6. Ethical Considerations

Discuss the ethical measures taken to ensure participant safety and data integrity. Ethical considerations reflect the study’s adherence to moral and professional standards.

Informed consent from participants.
Confidentiality and data security.
Approval from an institutional review board (IRB).
Example: “All participants provided informed consent, and their anonymity was ensured by assigning unique identification codes. The study was approved by the Institutional Review Board (IRB) at XYZ University.”

7. Limitations of the Methodology

Acknowledge any methodological limitations that may affect the validity or reliability of the results.

Constraints such as sample size, geographic scope, or time frame.
Potential biases or challenges.
Example: “The study’s primary limitation was the reliance on self-reported data, which may be subject to response bias.”

8. Justification of Methodology

Provide a rationale for choosing specific methods and tools over alternatives. This reinforces the credibility of the methodology and its alignment with research objectives.

Explanation of why chosen methods are appropriate.
Comparison with other possible methods.
Example: “The mixed-methods approach was selected to capture both numerical trends and in-depth personal experiences, ensuring a holistic understanding of the research problem.”

9. Operational Definitions (Optional)

Define key terms or concepts used in the study to ensure clarity and consistency.

Example: “For this study, ‘remote work productivity’ refers to the number of tasks completed within standard working hours, as self-reported by participants.”

Types of Research Methodology

1. qualitative research methodology.

Qualitative methodology focuses on understanding human experiences, behaviors, and social phenomena. It uses non-numerical data and is often exploratory.

Subjective and descriptive.
Data collected through interviews, focus groups, or observations.
Analyzes themes, patterns, and narratives.
Example: A study exploring teachers’ perceptions of remote learning challenges during the COVID-19 pandemic.

2. Quantitative Research Methodology

Quantitative methodology focuses on measuring and analyzing numerical data to test hypotheses or answer research questions. It is often used for studies requiring statistical analysis.

Objective and structured.
Data collected through surveys, experiments, or secondary datasets.
Statistical methods used for data analysis.
Example: Examining the relationship between study hours and academic performance among high school students.

3. Mixed Methods Research Methodology

Mixed methods combine qualitative and quantitative approaches to provide a comprehensive understanding of a research problem.

Integrates numerical data with detailed narratives.
Offers both breadth and depth in analysis.
Often uses sequential or concurrent designs.
Example: Investigating how healthcare workers perceive telemedicine (qualitative) and evaluating patient satisfaction scores (quantitative).

4. Descriptive Research Methodology

Descriptive research aims to describe characteristics, phenomena, or trends in a specific population or setting.

Non-experimental.
Data collected through surveys, case studies, or observations.
Focuses on “what” rather than “why” or “how.”
Example: Surveying college students to understand their preferred learning platforms.

5. Experimental Research Methodology

Experimental research investigates cause-and-effect relationships by manipulating variables and observing outcomes.

Involves control and experimental groups.
Uses randomization to reduce bias.
Common in natural and social sciences.
Example: Testing the effectiveness of a new drug on reducing symptoms compared to a placebo.

6. Correlational Research Methodology

Correlational research examines the relationship between two or more variables without manipulating them.

Identifies positive, negative, or no correlation.
Cannot establish causation.
Data often collected through surveys or secondary datasets.
Example: Analyzing the correlation between screen time and sleep quality among teenagers.

Examples of Research Methodology

1. education.

Topic: The effectiveness of project-based learning on student engagement.
Methodology: Mixed methods involving student surveys (quantitative) and teacher interviews (qualitative).

2. Healthcare

Topic: The impact of physical activity on managing type 2 diabetes.
Methodology: Quantitative approach using clinical trials to measure blood glucose levels.

3. Business

Topic: Factors influencing employee job satisfaction in remote work environments.
Methodology: Descriptive research using online surveys to collect data from employees across industries.

4. Environmental Studies

Topic: The effect of urbanization on local biodiversity.
Methodology: Descriptive research involving field observations and quantitative data analysis of species populations.

How to Write the Methodology Section

Step 1: provide an overview.

Begin by explaining the overall research approach (qualitative, quantitative, or mixed methods) and justifying its suitability for addressing the research questions.

Example: “This study employs a mixed-methods approach to explore the impact of remote work on employee productivity. The combination of quantitative surveys and qualitative interviews provides a comprehensive understanding of the phenomenon.”

Step 2: Describe the Research Design

Outline the specific design used, such as experimental, descriptive, or correlational, and explain why it was chosen.

Example: “A correlational design was selected to analyze the relationship between screen time and sleep quality among high school students.”

Step 3: Detail the Data Collection Methods

Explain how data was collected, including tools, instruments, and procedures.

Example: “Data was collected using an online survey distributed to 500 participants. The survey included closed-ended questions measuring job satisfaction and open-ended questions capturing employee experiences.”

Step 4: Specify the Sampling Method

Describe the sampling strategy, including sample size, selection criteria, and sampling technique (e.g., random, stratified, convenience).

Example: “A stratified sampling technique was employed to ensure representation across different age groups. The final sample included 200 respondents aged 18–60.”

Step 5: Describe Data Analysis Techniques

Explain the methods used to analyze the data, whether statistical or thematic.

Example: “Quantitative data was analyzed using SPSS software, employing descriptive statistics and regression analysis. Qualitative data from interviews was thematically coded to identify patterns and themes.”

Step 6: Address Ethical Considerations

Discuss ethical measures such as informed consent, confidentiality, and data security.

Example: “All participants provided informed consent, and data was anonymized to maintain confidentiality. Ethical approval was obtained from the institutional review board.”

Step 7: Justify Your Choices

Provide a rationale for selecting the chosen methods and explain their relevance to the research objectives.

Example: “The use of surveys allowed for efficient data collection from a large sample, while interviews provided in-depth insights into individual experiences.”

Tips for Writing a Strong Methodology Section

Be Detailed and Specific: Provide enough detail to allow replication of your study.
Maintain Objectivity: Use neutral language and avoid subjective statements.
Link to Objectives: Ensure all methods align with the study’s research questions or hypotheses.
Use Subheadings: Organize the section into clear subsections for readability.
Cite Sources: Reference any tools, instruments, or previous studies that informed your methodology.

Common Mistakes to Avoid

Lack of Clarity: Ambiguous descriptions can confuse readers and undermine credibility.
Insufficient Detail: Omitting key steps or procedures can make the study irreproducible.
Ignoring Limitations: Failing to acknowledge methodological limitations reduces transparency.
Misalignment with Objectives: Methods that do not address the research questions weaken the study’s validity.

The research methodology is a vital component of any study, laying the foundation for credible and reliable results. By selecting the appropriate type—whether qualitative, quantitative, or mixed methods—and providing a clear, detailed explanation of the processes involved, researchers can ensure that their work is both rigorous and replicable. Following the writing guide and addressing common mistakes will help create a robust methodology section, contributing to the overall strength and impact of the research.

Creswell, J. W. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches . Sage Publications.
Babbie, E. (2020). The Practice of Social Research . Cengage Learning.
Bryman, A. (2016). Social Research Methods . Oxford University Press.
Patton, M. Q. (2015). Qualitative Research & Evaluation Methods: Integrating Theory and Practice . Sage Publications.
Flick, U. (2018). An Introduction to Qualitative Research . Sage Publications.

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Muhammad Hassan

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Tio Gabunia (B.Arch, M.Arch)

Tio Gabunia is an academic writer and architect based in Tbilisi. He has studied architecture, design, and urban planning at the Georgian Technical University and the University of Lisbon. He has worked in these fields in Georgia, Portugal, and France. Most of Tio’s writings concern philosophy. Other writings include architecture, sociology, urban planning, and economics.

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Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

Research methodologies can roughly be categorized into three group: quantitative, qualitative, and mixed-methods.

Qualitative Research : This methodology is based on obtaining deep, contextualized, non-numerical data. It can occur, for example, through open-ended questioning of research particiapnts in order to understand human behavior. It’s all about describing and analyzing subjective phenomena such as emotions or experiences.
Quantitative Research: This methodology is rationally-based and relies heavily on numerical analysis of empirical data . With quantitative research, you aim for objectivity by creating hypotheses and testing them through experiments or surveys, which allow for statistical analyses.
Mixed-Methods Research: Mixed-methods research combines both previous types into one project. We have more flexibility when designing our research study with mixed methods since we can use multiple approaches depending on our needs at each time. Using mixed methods can help us validate our results and offer greater predictability than just either type of methodology alone could provide.

Below are research methodologies that fit into each category.

Qualitative Research Methodologies

1. case study.

Conducts an in-depth examination of a specific case, individual, or event to understand a phenomenon.

Instead of examining a whole population for numerical trend data, case study researchers seek in-depth explanations of one event.

The benefit of case study research is its ability to elucidate overlooked details of interesting cases of a phenomenon (Busetto, Wick & Gumbinger, 2020). It offers deep insights for empathetic, reflective, and thoughtful understandings of that phenomenon.

However, case study findings aren’t transferrable to new contexts or for population-wide predictions. Instead, they inform practitioner understandings for nuanced, deep approaches to future instances (Liamputtong, 2020).

2. Grounded Theory

Grounded theory involves generating hypotheses and theories through the collection and interpretation of data (Faggiolani, n.d.). Its distinguishing features is that it doesn’t test a hypothesis generated prior to analysis, but rather generates a hypothesis or ‘theory’ that emerges from the data.

It also involves the application of inductive reasoning and is often contrasted with the hypothetico-deductive model of scientific research. This research methodology was developed by Barney Glaser and Anselm Strauss in the 1960s (Glaser & Strauss, 2009).

The basic difference between traditional scientific approaches to research and grounded theory is that the latter begins with a question, then collects data, and the theoretical framework is said to emerge later from this data.

By contrast, scientists usually begin with an existing theoretical framework , develop hypotheses, and only then start collecting data to verify or falsify the hypotheses.

3. Ethnography

In ethnographic research , the researcher immerses themselves within the group they are studying, often for long periods of time.

This type of research aims to understand the shared beliefs, practices, and values of a particular community by immersing the researcher within the cultural group.

Although ethnographic research cannot predict or identify trends in an entire population, it can create detailed explanations of cultural practices and comparisons between social and cultural groups.

When a person conducts an ethnographic study of themselves or their own culture, it can be considered autoethnography .

Its strength lies in producing comprehensive accounts of groups of people and their interactions.

Common methods researchers use during an ethnographic study include participant observation , thick description, unstructured interviews, and field notes vignettes. These methods can provide detailed and contextualized descriptions of their subjects.

Example Study

Liquidated: An Ethnography of Wall Street by Karen Ho involves an anthropologist who embeds herself with Wall Street firms to study the culture of Wall Street bankers and how this culture affects the broader economy and world.

4. Phenomenology

Phenomenology to understand and describe individuals’ lived experiences concerning a specific phenomenon.

As a research methodology typically used in the social sciences , phenomenology involves the study of social reality as a product of intersubjectivity (the intersection of people’s cognitive perspectives) (Zahavi & Overgaard, n.d.).

This philosophical approach was first developed by Edmund Husserl.

5. Narrative Research

Narrative research explores personal stories and experiences to understand their meanings and interpretations.

It is also known as narrative inquiry and narrative analysis(Riessman, 1993).

This approach to research uses qualitative material like journals, field notes, letters, interviews, texts, photos, etc., as its data.

It is aimed at understanding the way people create meaning through narratives (Clandinin & Connelly, 2004).

6. Discourse Analysis

A discourse analysis examines the structure, patterns, and functions of language in context to understand how the text produces social constructs.

This methodology is common in critical theory , poststructuralism , and postmodernism. Its aim is to understand how language constructs discourses (roughly interpreted as “ways of thinking and constructing knowledge”).

As a qualitative methodology , its focus is on developing themes through close textual analysis rather than using numerical methods. Common methods for extracting data include semiotics and linguistic analysis.

7. Action Research

Action research involves researchers working collaboratively with stakeholders to address problems, develop interventions, and evaluate effectiveness.

Action research is a methodology and philosophy of research that is common in the social sciences.

The term was first coined in 1944 by Kurt Lewin, a German-American psychologist who also introduced applied research and group communication (Altrichter & Gstettner, 1993).

Lewin originally defined action research as involving two primary processes: taking action and doing research (Lewin, 1946).

Action research involves planning, action, and information-seeking about the result of the action.

Since Lewin’s original formulation, many different theoretical approaches to action research have been developed. These include action science, participatory action research, cooperative inquiry, and living educational theory among others.

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing (Ellison & Drew, 2019) is a study conducted by a school teacher who used video games to help teach his students English. It involved action research, where he interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience, and iterated on his teaching style based on their feedback (disclaimer: I am the second author of this study).

See More: Examples of Qualitative Research

Quantitative Research Methodologies

8. experimental design.

As the name suggests, this type of research is based on testing hypotheses in experimental settings by manipulating variables and observing their effects on other variables.

The main benefit lies in its ability to manipulate specific variables to determine their effect on outcomes which is a great method for those looking for causational links in their research.

This is common, for example, in high-school science labs, where students are asked to introduce a variable into a setting in order to examine its effect.

9. Non-Experimental Design

Non-experimental design observes and measures associations between variables without manipulating them.

It can take, for example, the form of a ‘fly on the wall’ observation of a phenomenon, allowing researchers to examine authentic settings and changes that occur naturally in the environment.

10. Cross-Sectional Design

Cross-sectional design involves analyzing variables pertaining to a specific time period and at that exact moment.

This approach allows for an extensive examination and comparison of distinct and independent subjects, thereby offering advantages over qualitative methodologies such as case studies or surveys.

While cross-sectional design can be extremely useful in taking a ‘snapshot in time’, as a standalone method, it is not useful for examining changes in subjects after an intervention. The next methodology addresses this issue.

The prime example of this type of study is a census. A population census is mailed out to every house in the country, and each household must complete the census on the same evening. This allows the government to gather a snapshot of the nation’s demographics, beliefs, religion, and so on.

11. Longitudinal Design

Longitudinal research gathers data from the same subjects over an extended period to analyze changes and development.

In contrast to cross-sectional tactics, longitudinal designs examine variables more than once, over a pre-determined time span, allowing for multiple data points to be taken at different times.

A cross-sectional design is also useful for examining cohort effects , by comparing differences or changes in multiple different generations’ beliefs over time.

With multiple data points collected over extended periods ,it’s possible to examine continuous changes within things like population dynamics or consumer behavior. This makes detailed analysis of change possible.

12. Quasi-Experimental Design

Quasi-experimental design involves manipulating variables for analysis, but uses pre-existing groups of subjects rather than random groups.

Because the groups of research participants already exist, they cannot be randomly assigned to a cohort as with a true experimental design study. This makes inferring a causal relationship more difficult, but is nonetheless often more feasible in real-life settings.

Quasi-experimental designs are generally considered inferior to true experimental designs.

13. Correlational Research

Correlational research examines the relationships between two or more variables, determining the strength and direction of their association.

Similar to quasi-experimental methods, this type of research focuses on relationship differences between variables.

This approach provides a fast and easy way to make initial hypotheses based on either positive or negative correlation trends that can be observed within dataset.

Methods used for data analysis may include statistic correlations such as Pearson’s or Spearman’s.

Mixed-Methods Research Methodologies

14. sequential explanatory design (quan→qual).

This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.

It begins by collecting quantitative data that is then analyzed to determine any significant patterns or trends.

Secondly, qualitative methods are employed. Their intent is to help interpret and expand the quantitative results.

This offers greater depth into understanding both large and smaller aspects of research questions being addressed.

The rationale behind this approach is to ensure that your data collection generates richer context for gaining insight into the particular issue across different levels, integrating in one study, qualitative exploration as well as statistical procedures.

15. Sequential Exploratory Design (QUAL→QUAN)

This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

It starts with qualitative research that delves deeps into complex areas and gathers rich information through interviewing or observing participants.

After this stage of exploration comes to an end, quantitative techniques are used to analyze the collected data through inferential statistics.

The idea is that a qualitative study can arm the researchers with a strong hypothesis testing framework, which they can then apply to a larger sample size using qualitative methods.

When I first took research classes, I had a lot of trouble distinguishing between methodologies and methods.

The key is to remember that the methodology sets the direction, while the methods are the specific tools to be used. A good analogy is transport: first you need to choose a mode (public transport, private transport, motorized transit, non-motorized transit), then you can choose a tool (bus, car, bike, on foot).

While research methodologies can be split into three types, each type has many different nuanced methodologies that can be chosen, before you then choose the methods – or tools – to use in the study. Each has its own strengths and weaknesses, so choose wisely!

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