types of research methods for phd

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15 kinds of research methodologies for phd. pupils, basic research.

Pure research or fundamental research or basic research zooms on enhancing scientific knowledge for the exhaustive understanding of a topic or certain natural phenomena, essentially in natural sciences; knowledge that is obtained for the purpose of knowledge it is called fundamental research.

1.Applied research

Research that covers real life applications of the natural sciences; aimed at offering an answer to particular practical issues and develops novel technologies

2.Fixed research versus flexible research

In fixed research, the design of the study is fixed prior to the main phase of data gathering; moreover, fixed designs are essentially theoretical. Variables that need to be controlled and measured need to be known in advance and they are measured quantitatively.

3.Quantitative research and qualitative research

Quantitative research denotes gauging phenomena in various grades; on the other hand, qualitative research sometimes deems Boolean measurements alone; solution can be studied qualitatively for its appropriateness. However, comparison between candidate solutions requires quantitative observation.

4.Experimental research and non-experimental research

In an experimental design , operationalize the variables to be measured; moreover, operationalize in the best manner. Consider the study expectations, outcome measurement, variable measurement, and the methods to answer research questions.

Think of the practical limitations such as the availability of data-sets and experimental set-ups that represent actual scenarios.

5.Exploratory research and confirmatory research

Confirmatory research tests a priori hypotheses—outcome predictions done prior to the measurement stage. Such a priori hypotheses are usually derived from a theory or the results of previous studies.

Exploratory research generates a posteriori hypotheses by investigating a data-set and ascertaining potential connection between variables.

6.Explanatory research or casual research

Causal research is also called explanatory research ; conducted to ascertain the extent and type of cause-effect relationships. Causal research are conducted to evaluate effects of specific changes on existing norms, various processes etc.

7.Descriptive research

Descriptive research is the available statement of affairs; researcher has no control over variable. Descriptive studies are characterised as simply an effort to ascertain, define or recognize.  Not “why it is that way” nor “how it came to be,” which is the objective of analytical research.

8.Historical research

Historical research explores and explains the meanings, phases and traits of a phenomena or process at a certain phase of time in the past; historical research is a research strategy from the research of history.

9.Casual comparative research

Also called as “ex-post facto” research (In Latin, implies “after the fact”); researchers determine the causes or consequences of differences that already exist between or among groups of individuals.

An effort to ascertain a causative relationship between an independent variable and a dependent variable; relationship between the independent variable and dependent variable are usually a suggested relationship (not proved yet) because you do not have complete control over the independent variable

10.Correlational research

Correlational research is a form of non-experimental research technique wherein a researcher measures 2 variables and assesses the statistical connection between them with no influence from any external variable.

The correlation between two variables is given through correlation coefficient, which is a statistical measure that calculates the strength of the relationship between two variables that is a value measured between -1 and +1.

11.Evaluation research method

Evaluation research technique is known as program evaluation and refers to a research purpose instead of a particular technique; objective is to assess the effect of social involvements such as new treatment techniques, innovations in services, etc.

A form of applied research to have some real-world effect. Methods such as surveys and experiments are used in evaluation research.

12.Formative and summative evaluation

While learning is in progress, formative assessment offers feedback and information; measures participant’s progress and also assess researcher’s own progress as well.

For example, when implementing a new program, you can determine whether or not the activity should be used again (or modified) with the help of observation and/or surveying.

Summative assessment happens after the learning has ended and offers info and feedback to sum up the process; essentially, no formal learning is happening at this phase other than incidental learning which might take place through the completion of program.

13.Diagnostic research

Descriptive research studies define the characteristics of a particular individual, or of a group.

Studies showing whether certain variables are linked are examples of diagnostic research.

Researcher defines what he or she wants to measure and finds adequate methods for measuring it along with a clear description of ‘population’.

Aim is to obtain complete and accurate information. And the researcher plans the procedure carefully.

14.Prognostic research

Prognostic research (specifically in clinical research) examines chosen predictive variables and risk factors; prognostic research assesses influence on the outcome of a disease. Clinicians have a better understanding of the history of the ailment.

This understanding facilitates clinical decision-making via providing apt treatment alternatives and helps to predict accurate disease outcomes.

Assessing prognostic studies involves ascertaining the internal validity of the study design and assessing the effects of bias or systemic errors.

15.Action research

A systematic inquiry for improving and/or honing researchers’ actions. Researchers find it an empowering experience.

Action research has positive result for various reasons; most important is that action research is pertinent to the research participants.

Relevance is assured because the aim of each research project is ascertained by the researchers, who are also the main beneficiaries of the research observations.

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15 Types of Research Methods

Research methods refer to the strategies, tools, and techniques used to gather and analyze data in a structured way in order to answer a research question or investigate a hypothesis (Hammond & Wellington, 2020).

Generally, we place research methods into two categories: quantitative and qualitative. Each has its own strengths and weaknesses, which we can summarize as:

• Quantitative research can achieve generalizability through scrupulous statistical analysis applied to large sample sizes.
• Qualitative research achieves deep, detailed, and nuance accounts of specific case studies, which are not generalizable.

Some researchers, with the aim of making the most of both quantitative and qualitative research, employ mixed methods, whereby they will apply both types of research methods in the one study, such as by conducting a statistical survey alongside in-depth interviews to add context to the quantitative findings.

Below, I’ll outline 15 common research methods, and include pros, cons, and examples of each .

Types of Research Methods

Research methods can be broadly categorized into two types: quantitative and qualitative.

• Quantitative methods involve systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques, providing an in-depth understanding of a specific concept or phenomenon (Schweigert, 2021). The strengths of this approach include its ability to produce reliable results that can be generalized to a larger population, although it can lack depth and detail.
• Qualitative methods encompass techniques that are designed to provide a deep understanding of a complex issue, often in a specific context, through collection of non-numerical data (Tracy, 2019). This approach often provides rich, detailed insights but can be time-consuming and its findings may not be generalizable.

These can be further broken down into a range of specific research methods and designs:

Combining the two methods above, mixed methods research mixes elements of both qualitative and quantitative research methods, providing a comprehensive understanding of the research problem . We can further break these down into:

• Sequential Explanatory Design (QUAN→QUAL): This methodology involves conducting quantitative analysis first, then supplementing it with a qualitative study.
• Sequential Exploratory Design (QUAL→QUAN): This methodology goes in the other direction, starting with qualitative analysis and ending with quantitative analysis.

Let’s explore some methods and designs from both quantitative and qualitative traditions, starting with qualitative research methods.

Qualitative Research Methods

Qualitative research methods allow for the exploration of phenomena in their natural settings, providing detailed, descriptive responses and insights into individuals’ experiences and perceptions (Howitt, 2019).

These methods are useful when a detailed understanding of a phenomenon is sought.

1. Ethnographic Research

Ethnographic research emerged out of anthropological research, where anthropologists would enter into a setting for a sustained period of time, getting to know a cultural group and taking detailed observations.

Ethnographers would sometimes even act as participants in the group or culture, which many scholars argue is a weakness because it is a step away from achieving objectivity (Stokes & Wall, 2017).

In fact, at its most extreme version, ethnographers even conduct research on themselves, in a fascinating methodology call autoethnography .

The purpose is to understand the culture, social structure, and the behaviors of the group under study. It is often useful when researchers seek to understand shared cultural meanings and practices in their natural settings.

However, it can be time-consuming and may reflect researcher biases due to the immersion approach.

Example of Ethnography

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.

2. Phenomenological Research

Phenomenological research is a qualitative method focused on the study of individual experiences from the participant’s perspective (Tracy, 2019).

It focuses specifically on people’s experiences in relation to a specific social phenomenon ( see here for examples of social phenomena ).

This method is valuable when the goal is to understand how individuals perceive, experience, and make meaning of particular phenomena. However, because it is subjective and dependent on participants’ self-reports, findings may not be generalizable, and are highly reliant on self-reported ‘thoughts and feelings’.

Example of Phenomenological Research

A phenomenological approach to experiences with technology  by Sebnem Cilesiz represents a good starting-point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

3. Historical Research

Historical research is a qualitative method involving the examination of past events to draw conclusions about the present or make predictions about the future (Stokes & Wall, 2017).

As you might expect, it’s common in the research branches of history departments in universities.

This approach is useful in studies that seek to understand the past to interpret present events or trends. However, it relies heavily on the availability and reliability of source materials, which may be limited.

Common data sources include cultural artifacts from both material and non-material culture , which are then examined, compared, contrasted, and contextualized to test hypotheses and generate theories.

Example of Historical Research

A historical research example might be a study examining the evolution of gender roles over the last century. This research might involve the analysis of historical newspapers, advertisements, letters, and company documents, as well as sociocultural contexts.

4. Content Analysis

Content analysis is a research method that involves systematic and objective coding and interpreting of text or media to identify patterns, themes, ideologies, or biases (Schweigert, 2021).

A content analysis is useful in analyzing communication patterns, helping to reveal how texts such as newspapers, movies, films, political speeches, and other types of ‘content’ contain narratives and biases.

However, interpretations can be very subjective, which often requires scholars to engage in practices such as cross-comparing their coding with peers or external researchers.

Content analysis can be further broken down in to other specific methodologies such as semiotic analysis, multimodal analysis , and discourse analysis .

Example of Content Analysis

How is Islam Portrayed in Western Media?  by Poorebrahim and Zarei (2013) employs a type of content analysis called critical discourse analysis (common in poststructuralist and critical theory research ). This study by Poorebrahum and Zarei combs through a corpus of western media texts to explore the language forms that are used in relation to Islam and Muslims, finding that they are overly stereotyped, which may represent anti-Islam bias or failure to understand the Islamic world.

5. Grounded Theory Research

Grounded theory involves developing a theory  during and after  data collection rather than beforehand.

This is in contrast to most academic research studies, which start with a hypothesis or theory and then testing of it through a study, where we might have a null hypothesis (disproving the theory) and an alternative hypothesis (supporting the theory).

Grounded Theory is useful because it keeps an open mind to what the data might reveal out of the research. It can be time-consuming and requires rigorous data analysis (Tracy, 2019).

Grounded Theory Example

Developing a Leadership Identity   by Komives et al (2005) employs a grounded theory approach to develop a thesis based on the data rather than testing a hypothesis. The researchers studied the leadership identity of 13 college students taking on leadership roles. Based on their interviews, the researchers theorized that the students’ leadership identities shifted from a hierarchical view of leadership to one that embraced leadership as a collaborative concept.

6. Action Research

Action research is an approach which aims to solve real-world problems and bring about change within a setting. The study is designed to solve a specific problem – or in other words, to take action (Patten, 2017).

This approach can involve mixed methods, but is generally qualitative because it usually involves the study of a specific case study wherein the researcher works, e.g. a teacher studying their own classroom practice to seek ways they can improve.

Action research is very common in fields like education and nursing where practitioners identify areas for improvement then implement a study in order to find paths forward.

Action Research Example

Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing   by Ellison and Drew was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

7. Natural Observational Research

Observational research can also be quantitative (see: experimental research), but in naturalistic settings for the social sciences, researchers tend to employ qualitative data collection methods like interviews and field notes to observe people in their day-to-day environments.

This approach involves the observation and detailed recording of behaviors in their natural settings (Howitt, 2019). It can provide rich, in-depth information, but the researcher’s presence might influence behavior.

While observational research has some overlaps with ethnography (especially in regard to data collection techniques), it tends not to be as sustained as ethnography, e.g. a researcher might do 5 observations, every second Monday, as opposed to being embedded in an environment.

Observational Research Example

A researcher might use qualitative observational research to study the behaviors and interactions of children at a playground. The researcher would document the behaviors observed, such as the types of games played, levels of cooperation , and instances of conflict.

8. Case Study Research

Case study research is a qualitative method that involves a deep and thorough investigation of a single individual, group, or event in order to explore facets of that phenomenon that cannot be captured using other methods (Stokes & Wall, 2017).

Case study research is especially valuable in providing contextualized insights into specific issues, facilitating the application of abstract theories to real-world situations (Patten, 2017).

However, findings from a case study may not be generalizable due to the specific context and the limited number of cases studied (Walliman, 2021).

See More: Case Study Advantages and Disadvantages

Example of a Case Study

Scholars conduct a detailed exploration of the implementation of a new teaching method within a classroom setting. The study focuses on how the teacher and students adapt to the new method, the challenges encountered, and the outcomes on student performance and engagement. While the study provides specific and detailed insights of the teaching method in that classroom, it cannot be generalized to other classrooms, as statistical significance has not been established through this qualitative approach.

Quantitative Research Methods

Quantitative research methods involve the systematic empirical investigation of observable phenomena via statistical, mathematical, or computational techniques (Pajo, 2022). The focus is on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

9. Experimental Research

Experimental research is a quantitative method where researchers manipulate one variable to determine its effect on another (Walliman, 2021).

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.

This type of research is useful in situations where researchers want to determine causal relationships between variables. However, experimental conditions may not reflect real-world conditions.

Example of Experimental Research

A researcher may conduct an experiment to determine the effects of a new educational approach on student learning outcomes. Students would be randomly assigned to either the control group (traditional teaching method) or the experimental group (new educational approach).

10. Surveys and Questionnaires

Surveys and questionnaires are quantitative methods that involve asking research participants structured and predefined questions to collect data about their attitudes, beliefs, behaviors, or characteristics (Patten, 2017).

Surveys are beneficial for collecting data from large samples, but they depend heavily on the honesty and accuracy of respondents.

They tend to be seen as more authoritative than their qualitative counterparts, semi-structured interviews, because the data is quantifiable (e.g. a questionnaire where information is presented on a scale from 1 to 10 can allow researchers to determine and compare statistical means, averages, and variations across sub-populations in the study).

Example of a Survey Study

A company might use a survey to gather data about employee job satisfaction across its offices worldwide. Employees would be asked to rate various aspects of their job satisfaction on a Likert scale. While this method provides a broad overview, it may lack the depth of understanding possible with other methods (Stokes & Wall, 2017).

11. Longitudinal Studies

Longitudinal studies involve repeated observations of the same variables over extended periods (Howitt, 2019). These studies are valuable for tracking development and change but can be costly and time-consuming.

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 a detailed analysis of change possible.

Perhaps the most relatable example of a longitudinal study is a national census, which is taken on the same day every few years, to gather comparative demographic data that can show how a nation is changing over time.

While longitudinal studies are commonly quantitative, there are also instances of qualitative ones as well, such as the famous 7 Up study from the UK, which studies 14 individuals every 7 years to explore their development over their lives.

Example of a Longitudinal Study

A national census, taken every few years, uses surveys to develop longitudinal data, which is then compared and analyzed to present accurate trends over time. Trends a census can reveal include changes in religiosity, values and attitudes on social issues, and much more.

12. Cross-Sectional Studies

Cross-sectional studies are a quantitative research method that involves analyzing data from a population at a specific point in time (Patten, 2017). They provide a snapshot of a situation but cannot determine causality.

This design is used to measure and compare the prevalence of certain characteristics or outcomes in different groups within the sampled population.

The major advantage of cross-sectional design is its ability to measure a wide range of variables simultaneously without needing to follow up with participants over time.

However, cross-sectional studies do have limitations . This design can only show if there are associations or correlations between different variables, but cannot prove cause and effect relationships, temporal sequence, changes, and trends over time.

Example of a Cross-Sectional Study

Our longitudinal study example of a national census also happens to contain cross-sectional design. One census is cross-sectional, displaying only data from one point in time. But when a census is taken once every few years, it becomes longitudinal, and so long as the data collection technique remains unchanged, identification of changes will be achievable, adding another time dimension on top of a basic cross-sectional study.

13. Correlational Research

Correlational research is a quantitative method that seeks to determine if and to what degree a relationship exists between two or more quantifiable variables (Schweigert, 2021).

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.

While correlational research can reveal relationships between variables, it cannot establish causality.

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

Example of Correlational Research

A team of researchers is interested in studying the relationship between the amount of time students spend studying and their academic performance. They gather data from a high school, measuring the number of hours each student studies per week and their grade point averages (GPAs) at the end of the semester. Upon analyzing the data, they find a positive correlation, suggesting that students who spend more time studying tend to have higher GPAs.

14. Quasi-Experimental Design Research

Quasi-experimental design research is a quantitative research method that is similar to experimental design but lacks the element of random assignment to treatment or control.

Instead, quasi-experimental designs typically rely on certain other methods to control for extraneous variables.

The term ‘quasi-experimental’ implies that the experiment resembles a true experiment, but it is not exactly the same because it doesn’t meet all the criteria for a ‘true’ experiment, specifically in terms of control and random assignment.

Quasi-experimental design is useful when researchers want to study a causal hypothesis or relationship, but practical or ethical considerations prevent them from manipulating variables and randomly assigning participants to conditions.

Example of Quasi-Experimental Design

A researcher wants to study the impact of a new math tutoring program on student performance. However, ethical and practical constraints prevent random assignment to the “tutoring” and “no tutoring” groups. Instead, the researcher compares students who chose to receive tutoring (experimental group) to similar students who did not choose to receive tutoring (control group), controlling for other variables like grade level and previous math performance.

Related: Examples and Types of Random Assignment in Research

15. Meta-Analysis Research

Meta-analysis statistically combines the results of multiple studies on a specific topic to yield a more precise estimate of the effect size. It’s the gold standard of secondary research .

Meta-analysis is particularly useful when there are numerous studies on a topic, and there is a need to integrate the findings to draw more reliable conclusions.

Some meta-analyses can identify flaws or gaps in a corpus of research, when can be highly influential in academic research, despite lack of primary data collection.

However, they tend only to be feasible when there is a sizable corpus of high-quality and reliable studies into a phenomenon.

Example of a Meta-Analysis

The power of feedback revisited (Wisniewski, Zierer & Hattie, 2020) is a meta-analysis that examines 435 empirical studies research on the effects of feedback on student learning. They use a random-effects model to ascertain whether there is a clear effect size across the literature. The authors find that feedback tends to impact cognitive and motor skill outcomes but has less of an effect on motivational and behavioral outcomes.

Choosing a research method requires a lot of consideration regarding what you want to achieve, your research paradigm, and the methodology that is most valuable for what you are studying. There are multiple types of research methods, many of which I haven’t been able to present here. Generally, it’s recommended that you work with an experienced researcher or research supervisor to identify a suitable research method for your study at hand.

Hammond, M., & Wellington, J. (2020). Research methods: The key concepts . New York: Routledge.

Howitt, D. (2019). Introduction to qualitative research methods in psychology . London: Pearson UK.

Pajo, B. (2022). Introduction to research methods: A hands-on approach . New York: Sage Publications.

Patten, M. L. (2017). Understanding research methods: An overview of the essentials . New York: Sage

Schweigert, W. A. (2021). Research methods in psychology: A handbook . Los Angeles: Waveland Press.

Stokes, P., & Wall, T. (2017). Research methods . New York: Bloomsbury Publishing.

Tracy, S. J. (2019). Qualitative research methods: Collecting evidence, crafting analysis, communicating impact . London: John Wiley & Sons.

Walliman, N. (2021). Research methods: The basics. London: Routledge.

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]

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ Social-Emotional Learning (Definition, Examples, Pros & Cons)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ What is Educational Psychology?
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ What is IQ? (Intelligence Quotient)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd/ 5 Top Tips for Succeeding at University

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What are acceptable dissertation research methods?

August 16, 2023

Reading time:  3–4 minutes

Doctoral research is the cornerstone of a PhD program .

In order to write a dissertation, you must complete extensive, detailed research. Depending on your area of study, different types of research methods will be appropriate to complete your work.

“The choice of research method depends on the questions you hope to answer with your research,” says Curtis Brant, PhD, Capella University dean of research and scholarship.

Once you’ve identified your research problem, you’ll employ the methodology best suited for solving the problem.

There are two primary dissertation research methods: qualitative and quantitative.

Qualitative

Qualitative research focuses on examining the topic via cultural phenomena, human behavior or belief systems. This type of research uses interviews, open-ended questions or focus groups to gain insight into people’s thoughts and beliefs around certain behaviors and systems.

Dr. Brant says there are several approaches to qualitative inquiry. The three most routinely used include:

Generic qualitative inquiry. The researcher focuses on people’s experiences or perceptions in the real world. This often includes, but is not limited to, subjective opinions, attitudes and beliefs .

Case study. The researcher performs an in-depth exploration of a program, event, activity or process with an emphasis on the experience of one or more individuals. The focus of this kind of inquiry must be defined and often includes more than one set of data, such as interviews and field notes, observations or other qualitative data.

Phenomenological. The researcher identifies lived experiences associated with how an individual encounters and engages with the real world .

Qualitative research questions seek to discover:

• A participant’s verbal descriptions of a phenomenon being investigated
•  A researcher’s observations of the phenomenon being investigated
• An integrated interpretation of participant’s descriptions and researchers observations

Quantitative

Quantitative research involves the empirical investigation of observable and measurable variables. It is used for theory testing, predicting outcomes or determining relationships between and among variables using statistical analysis.

According to Dr. Brant, there are two primary data sources for quantitative research.

Surveys: Surveys involve asking people a set of questions, usually testing for linear relationships, statistical differences or statistical independence. This approach is common in correlation research designs.

Archival research (secondary data analysis). Archival research involves using preexisting data to answer research questions instead of collecting data from active human participants.

Quantitative research questions seek to address:

• Descriptions of variables being investigated
• Measurements of relationships between (at least two) variables
• Differences between two or more groups’ scores on a variable or variables

Which method should you choose?

Choosing a qualitative or quantitative methodology for your research will be based on the nature of the questions you ask, the preferred method in your field, the feasibility of the approach and other factors. Many programs offer doctoral mentors and support teams that can help guide you throughout the process.

Capella University offers PhD and professional doctorate degree programs ranging from business to education and health to technology. Learn more about Capella doctoral programs and doctoral support.

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How To Choose Your Research Methodology

Qualitative vs quantitative vs mixed methods.

By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!

In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.

Overview: Choosing Your Methodology

Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research

Choosing a research methodology – Nature of the research – Research area norms – Practicalities

1. Understanding the options

Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.

Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.

Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.

• Uses an inductive approach
• Is used to build theories
• Takes a subjective approach
• Adopts an open and flexible approach
• The researcher is close to the respondents
• Interviews and focus groups are oftentimes used to collect word-based data.
• Generally, draws on small sample sizes
• Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
• Uses a deductive approach
• Is used to test theories
• Takes an objective approach
• Adopts a closed, highly planned approach
• The research is disconnected from respondents
• Surveys or laboratory equipment are often used to collect number-based data.
• Generally, requires large sample sizes
• Uses statistical analysis techniques to make sense of the data

Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.

In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.

The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job. 

Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

2. How to choose a research methodology

To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).

The three factors you need to consider are:

• The nature of your research aims, objectives and research questions
• The methodological approaches taken in the existing literature
• Practicalities and constraints

Let’s take a look at each of these.

Factor #1: The nature of your research

As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .

But, what types of research exist?

Broadly speaking, research can fall into one of three categories:

• Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
• Confirmatory – confirming a potential theory or hypothesis by testing it empirically
• A mix of both – building a potential theory or hypothesis and then testing it

As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Let’s look at an example in action.

If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.

If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .

So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.

The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.

If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.

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Factor #2: The disciplinary norms

Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.

A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .

Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.

Factor #3: Practicalities

When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.

But what constraints, you ask?

When you’re evaluating your methodological options, you need to consider the following constraints:

• Data access
• Equipment and software
• Your knowledge and skills

Let’s look at each of these.

Constraint #1: Data access

The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.

If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.

So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.

Constraint #2: Time

The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.

Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon. 

Constraint #3: Money

As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .

Some of the costs that may arise include:

• Software costs – e.g. survey hosting services, analysis software, etc.
• Promotion costs – e.g. advertising a survey to attract respondents
• Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
• Equipment rental costs – e.g. recording equipment, lab equipment, etc.
• Travel costs
• Food & beverages

These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Constraint #4: Equipment & software

Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.

Constraint #5: Your knowledge and skillset

The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.

Some of the questions you should ask yourself are:

• Am I more of a “numbers person” or a “words person”?
• How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
• How much do I know about the software and/or hardware that I’ll potentially use?
• How excited am I to learn new research skills and gain new knowledge?
• How much time do I have to learn the things I need to learn?

Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.

So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.

Recap: Choosing a methodology

In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:

• Exploratory
• Confirmatory
• Combination
• Research area norms
• Hardware and software
• Your knowledge and skillset

If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.

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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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Very useful and informative especially for beginners

Nice article! I’m a beginner in the field of cybersecurity research. I am a Telecom and Network Engineer and Also aiming for PhD scholarship.

I find the article very informative especially for my decitation it has been helpful and an eye opener.

Hi I am Anna ,

I am a PHD candidate in the area of cyber security, maybe we can link up

The Examples shows by you, for sure they are really direct me and others to knows and practices the Research Design and prepration.

I found the post very informative and practical.

I struggle so much with designs of the research for sure!

I’m the process of constructing my research design and I want to know if the data analysis I plan to present in my thesis defense proposal possibly change especially after I gathered the data already.

Thank you so much this site is such a life saver. How I wish 1-1 coaching is available in our country but sadly it’s not.

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Types of Research – Explained with Examples

• By DiscoverPhDs
• October 2, 2020

Types of Research

Research is about using established methods to investigate a problem or question in detail with the aim of generating new knowledge about it.

It is a vital tool for scientific advancement because it allows researchers to prove or refute hypotheses based on clearly defined parameters, environments and assumptions. Due to this, it enables us to confidently contribute to knowledge as it allows research to be verified and replicated.

Knowing the types of research and what each of them focuses on will allow you to better plan your project, utilises the most appropriate methodologies and techniques and better communicate your findings to other researchers and supervisors.

Classification of Types of Research

There are various types of research that are classified according to their objective, depth of study, analysed data, time required to study the phenomenon and other factors. It’s important to note that a research project will not be limited to one type of research, but will likely use several.

According to its Purpose

Theoretical research.

Theoretical research, also referred to as pure or basic research, focuses on generating knowledge , regardless of its practical application. Here, data collection is used to generate new general concepts for a better understanding of a particular field or to answer a theoretical research question.

Results of this kind are usually oriented towards the formulation of theories and are usually based on documentary analysis, the development of mathematical formulas and the reflection of high-level researchers.

Applied Research

Here, the goal is to find strategies that can be used to address a specific research problem. Applied research draws on theory to generate practical scientific knowledge, and its use is very common in STEM fields such as engineering, computer science and medicine.

This type of research is subdivided into two types:

• Technological applied research : looks towards improving efficiency in a particular productive sector through the improvement of processes or machinery related to said productive processes.
• Scientific applied research : has predictive purposes. Through this type of research design, we can measure certain variables to predict behaviours useful to the goods and services sector, such as consumption patterns and viability of commercial projects.

According to your Depth of Scope

Exploratory research.

Exploratory research is used for the preliminary investigation of a subject that is not yet well understood or sufficiently researched. It serves to establish a frame of reference and a hypothesis from which an in-depth study can be developed that will enable conclusive results to be generated.

Because exploratory research is based on the study of little-studied phenomena, it relies less on theory and more on the collection of data to identify patterns that explain these phenomena.

Descriptive Research

The primary objective of descriptive research is to define the characteristics of a particular phenomenon without necessarily investigating the causes that produce it.

In this type of research, the researcher must take particular care not to intervene in the observed object or phenomenon, as its behaviour may change if an external factor is involved.

Explanatory Research

Explanatory research is the most common type of research method and is responsible for establishing cause-and-effect relationships that allow generalisations to be extended to similar realities. It is closely related to descriptive research, although it provides additional information about the observed object and its interactions with the environment.

Correlational Research

The purpose of this type of scientific research is to identify the relationship between two or more variables. A correlational study aims to determine whether a variable changes, how much the other elements of the observed system change.

According to the Type of Data Used

Qualitative research.

Qualitative methods are often used in the social sciences to collect, compare and interpret information, has a linguistic-semiotic basis and is used in techniques such as discourse analysis, interviews, surveys, records and participant observations.

In order to use statistical methods to validate their results, the observations collected must be evaluated numerically. Qualitative research, however, tends to be subjective, since not all data can be fully controlled. Therefore, this type of research design is better suited to extracting meaning from an event or phenomenon (the ‘why’) than its cause (the ‘how’).

Quantitative Research

Quantitative research study delves into a phenomena through quantitative data collection and using mathematical, statistical and computer-aided tools to measure them . This allows generalised conclusions to be projected over time.

According to the Degree of Manipulation of Variables

Experimental research.

It is about designing or replicating a phenomenon whose variables are manipulated under strictly controlled conditions in order to identify or discover its effect on another independent variable or object. The phenomenon to be studied is measured through study and control groups, and according to the guidelines of the scientific method.

Non-Experimental Research

Also known as an observational study, it focuses on the analysis of a phenomenon in its natural context. As such, the researcher does not intervene directly, but limits their involvement to measuring the variables required for the study. Due to its observational nature, it is often used in descriptive research.

Quasi-Experimental Research

It controls only some variables of the phenomenon under investigation and is therefore not entirely experimental. In this case, the study and the focus group cannot be randomly selected, but are chosen from existing groups or populations . This is to ensure the collected data is relevant and that the knowledge, perspectives and opinions of the population can be incorporated into the study.

According to the Type of Inference

Deductive investigation.

In this type of research, reality is explained by general laws that point to certain conclusions; conclusions are expected to be part of the premise of the research problem and considered correct if the premise is valid and the inductive method is applied correctly.

Inductive Research

In this type of research, knowledge is generated from an observation to achieve a generalisation. It is based on the collection of specific data to develop new theories.

Hypothetical-Deductive Investigation

It is based on observing reality to make a hypothesis, then use deduction to obtain a conclusion and finally verify or reject it through experience.

According to the Time in Which it is Carried Out

Longitudinal study (also referred to as diachronic research).

It is the monitoring of the same event, individual or group over a defined period of time. It aims to track changes in a number of variables and see how they evolve over time. It is often used in medical, psychological and social areas .

Cross-Sectional Study (also referred to as Synchronous Research)

Cross-sectional research design is used to observe phenomena, an individual or a group of research subjects at a given time.

According to The Sources of Information

Primary research.

This fundamental research type is defined by the fact that the data is collected directly from the source, that is, it consists of primary, first-hand information.

Secondary research

Unlike primary research, secondary research is developed with information from secondary sources, which are generally based on scientific literature and other documents compiled by another researcher.

According to How the Data is Obtained

Documentary (cabinet).

Documentary research, or secondary sources, is based on a systematic review of existing sources of information on a particular subject. This type of scientific research is commonly used when undertaking literature reviews or producing a case study.

Field research study involves the direct collection of information at the location where the observed phenomenon occurs.

From Laboratory

Laboratory research is carried out in a controlled environment in order to isolate a dependent variable and establish its relationship with other variables through scientific methods.

Mixed-Method: Documentary, Field and/or Laboratory

Mixed research methodologies combine results from both secondary (documentary) sources and primary sources through field or laboratory research.

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The Top 3 Types of Dissertation Research Explained

Preparing for your doctoral dissertation takes serious perseverance. You’ve endured years of studies and professional development to get to this point. After sleepless nights and labor-intensive research, you’re ready to present the culmination of all of your hard work. Even with a strong base knowledge, it can be difficult — even daunting — to decide how you will begin writing.

By taking a wide-lens view of the dissertation research process , you can best assess the work you have ahead of you and any gaps in your current research strategy. Subsequently, you’ll begin to develop a timeline so you can work efficiently and cross that finish line with your degree in hand.

What Is a Dissertation?

A dissertation is a published piece of research on a novel topic in your chosen field. Students complete a dissertation as part of a doctoral or PhD program. For most students, a dissertation is the first substantive piece of academic research they will write. 

Because a dissertation becomes a published piece of academic literature that other academics may cite, students must defend it in front of a board of experts consisting of peers in their field, including professors, their advisor, and other industry experts. 

For many students, a dissertation is the first piece of research in a long career full of research. As such, it’s important to choose a topic that’s interesting and engaging.

Types of Dissertation Research

Dissertations can take on many forms, based on research and methods of presentation in front of a committee board of academics and experts in the field. Here, we’ll focus on the three main types of dissertation research to get you one step closer to earning your doctoral degree.

1. Qualitative

The first type of dissertation is known as a qualitative dissertation . A qualitative dissertation mirrors the qualitative research that a doctoral candidate would conduct throughout their studies. This type of research relies on non-numbers-based data collected through things like interviews, focus groups and participant observation. 

The decision to model your dissertation research according to the qualitative method will depend largely on the data itself that you are collecting. For example, dissertation research in the field of education or psychology may lend itself to a qualitative approach, depending on the essence of research. Within a qualitative dissertation research model, a candidate may pursue one or more of the following:

• Case study research
• Autoethnographies
• Narrative research 
• Grounded theory 

Although individual approaches may vary, qualitative dissertations usually include certain foundational characteristics. For example, the type of research conducted to develop a qualitative dissertation often follows an emergent design, meaning that the content and research strategy changes over time. Candidates also rely on research paradigms to further strategize how best to collect and relay their findings. These include critical theory, constructivism and interpretivism, to name a few. 

Because qualitative researchers integrate non-numerical data, their methods of collection often include unstructured interview, focus groups and participant observations. Of course, researchers still need rubrics from which to assess the quality of their findings, even though they won’t be numbers-based. To do so, they subject the data collected to the following criteria: dependability, transferability and validity. 

When it comes time to present their findings, doctoral candidates who produce qualitative dissertation research have several options. Some choose to include case studies, personal findings, narratives, observations and abstracts. Their presentation focuses on theoretical insights based on relevant data points. 

2. Quantitative

Quantitative dissertation research, on the other hand, focuses on the numbers. Candidates employ quantitative research methods to aggregate data that can be easily categorized and analyzed. In addition to traditional statistical analysis, quantitative research also hones specific research strategy based on the type of research questions. Quantitative candidates may also employ theory-driven research, replication-based studies and data-driven dissertations. 

When conducting research, some candidates who rely on quantitative measures focus their work on testing existing theories, while others create an original approach. To refine their approach, quantitative researchers focus on positivist or post-positivist research paradigms. Quantitative research designs focus on descriptive, experimental or relationship-based designs, to name a few. 

To collect the data itself, researchers focus on questionnaires and surveys, structured interviews and observations, data sets and laboratory-based methods. Then, once it’s time to assess the quality of the data, quantitative researchers measure their results against a set of criteria, including: reliability, internal/external validity and construct validity. Quantitative researchers have options when presenting their findings. Candidates convey their results using graphs, data, tables and analytical statements.

3. Mixed-Method

Many PhD candidates also use a hybrid model in which they employ both qualitative and quantitative methods of research. Mixed dissertation research models are fairly new and gaining traction. For a variety of reasons, a mixed-method approach offers candidates both versatility and credibility. It’s a more comprehensive strategy that allows for a wider capture of data with a wide range of presentation optimization. 

In the most common cases, candidates will first use quantitative methods to collect and categorize their data. Then, they’ll rely on qualitative methods to analyze that data and draw meaningful conclusions to relay to their committee panel. 

With a mixed-method approach, although you’re able to collect and analyze a more broad range of data, you run the risk of widening the scope of your dissertation research so much that you’re not able to reach succinct, sustainable conclusions. This is where it becomes critical to outline your research goals and strategy early on in the dissertation process so that the techniques you use to capture data have been thoroughly examined. 

How to Choose a Type of Dissertation Research That’s Right for You

After this overview of application and function, you may still be wondering how to go about choosing a dissertation type that’s right for you and your research proposition. In doing so, you’ll have a couple of things to consider: 

• What are your personal motivations? 
• What are your academic goals? 

It’s important to discern exactly what you hope to get out of your doctoral program . Of course, the presentation of your dissertation is, formally speaking, the pinnacle of your research. However, doctoral candidates must also consider:

• Which contributions they will make to the field
• Who they hope to collaborate with throughout their studies
• What they hope to take away from the experience personally, professionally and academically

Personal Considerations

To discern which type of dissertation research to choose, you have to take a closer look at your learning style, work ethic and even your personality. 

Quantitative research tends to be sequential and patterned-oriented. Steps move in a logical order, so it becomes clear what the next step should be at all times. For most candidates, this makes it easier to devise a timeline and stay on track. It also keeps you from getting overwhelmed by the magnitude of research involved. You’ll be able to assess your progress and make simple adjustments to stay on target. 

On the other hand, maybe you know that your research will involve many interviews and focus groups. You anticipate that you’ll have to coordinate participants’ schedules, and this will require some flexibility. Instead of creating a rigid schedule from the get-go, allowing your research to flow in a non-linear fashion may actually help you accomplish tasks more efficiently, albeit out of order. This also allows you the personal versatility of rerouting research strategy as you collect new data that leads you down other paths. 

After examining the research you need to conduct, consider more broadly: What type of student and researcher are you? In other words, What motivates you to do your best work? 

You’ll need to make sure that your methodology is conducive to the data you’re collecting, and you also need to make sure that it aligns with your work ethic so you set yourself up for success. If jumping from one task to another will cause you extra stress, but planning ahead puts you at ease, a quantitative research method may be best, assuming the type of research allows for this. 

Professional Considerations

The skills you master while working on your dissertation will serve you well beyond the day you earn your degree. Take into account the skills you’d like to develop for your academic and professional future. In addition to the hard skills you will develop in your area of expertise, you’ll also develop soft skills that are transferable to nearly any professional or academic setting. Perhaps you want to hone your ability to strategize a timeline, gather data efficiently or draw clear conclusions about the significance of your data collection. 

If you have considerable experience with quantitative analysis, but lack an extensive qualitative research portfolio, now may be your opportunity to explore — as long as you’re willing to put in the legwork to refine your skills or work closely with your mentor to develop a strategy together. 

Academic Considerations

For many doctoral candidates who hope to pursue a professional career in the world of academia, writing your dissertation is a practice in developing general research strategies that can be applied to any academic project. 

Candidates who are unsure which dissertation type best suits their research should consider whether they will take a philosophical or theoretical approach or come up with a thesis that addresses a specific problem or idea. Narrowing down this approach can sometimes happen even before the research begins. Other times, candidates begin to refine their methods once the data begins to tell a more concrete story.

Next Step: Structuring Your Dissertation Research Schedule

Once you’ve chosen which type of dissertation research you’ll pursue, you’ve already crossed the first hurdle. The next hurdle becomes when and where to fit dedicated research time and visits with your mentor into your schedule. The busyness of day-to-day life shouldn’t prevent you from making your academic dream a reality. In fact, search for programs that assist, not impede, your path to higher levels of academic success. 

Find out more about SNU’s online and on-campus education opportunities so that no matter where you are in life, you can choose the path that’s right for you.

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Public Health Doctoral Studies (PhD and DrPH): Types of Studies

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Study Definitions

Meta-Analysis

A quantitative method of combining the results of independent studies, which are drawn from the published literature, and synthesizing summaries and conclusions.

Systematic Review

A review which endeavors to consider all published and unpublished material on a specific question.  Studies that are judged methodologically sound are then combined quantitatively or qualitatively depending on their similarity.

Randomized Control Trial (RCT)

A  clinical trial involving one or more new treatments and at least one control treatment with specified outcome measures for evaluating the intervention.  The treatment may be a drug, device, or procedure. Controls are either placebo or an active treatment that is currently considered the "gold standard".  If patients are randomized via mathmatical techniques then the trial is designated as a randomized controlled trial.

Cohort Study

In cohort studies, groups of individuals, who are initially free of disease, are classified according to exposure or non-exposure to a risk factor and followed over time to determine the incidence of an outcome of interest.  In a prospective cohort study, the exposure information for the study subjects is collected at the start of the study and the new cases of disease are identified from that point on.  In a retrospective cohort study, the exposure status was measured in the past and disease identification has already begun. 

Case-Control Study

Studies that start by identifying persons with and without a disease of interest (cases and controls, respectively) and then look back in time to find differences in exposure to risk factors. 

Cross-Sectional Study

Studies in which the presence or absence of disease or other health-related variables are determined in each member of a population at one particular time. 

Levels of Evidence Pyramid

Levels of Evidence Pyramid created by Andy Puro, September 2014

Experimental vs. Observational Studies

An observational study is a study in which the investigator cannot control the assignment of treatment to subjects because the participants or conditions are not being directly assigned by the researcher.

• Examines predetermined treatments, interventions, policies, and their effects
• Four main types: case-series , case-control , cross-sectional , and cohort studies

In an experimental study , the investigators directly manipulate or assign participants to different interventions or environments.

• Controlled trials - studies in which the experimental drug or procedure is compared with another drug or procedure
• Uncontrolled trials - studies in which the investigators' experience with the experimental drug or procedure is described, but the treatment is not compared with another treatment

Formal Trials versus Observational Studies (Ravi Thadhani, Harvard Medical School)

Study Designs (Centre for Evidence Based Medicine, University of Oxford)

Learn about Clinical Studies (ClinicalTrials.gov, National Institutes of Health)

Definitions taken from: Dawson B, Trapp R.G. (2004). Chapter 2. Study Designs in Medical Research. In Dawson B, Trapp R.G. (Eds), Basic & Clinical Biostatistics, 4e Retrieved September 15, 2014 from http://accessmedicine.mhmedical.com/content.aspx?bookid=356&Sectionid=40086281.

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Choosing the Right Research Methodology: A Guide for Researchers

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Table of Contents

Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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Dissertations 4: methodology: methods.

• Introduction & Philosophy
• Methodology

Primary & Secondary Sources, Primary & Secondary Data

When describing your research methods, you can start by stating what kind of secondary and, if applicable, primary sources you used in your research. Explain why you chose such sources, how well they served your research, and identify possible issues encountered using these sources.  

Definitions  

There is some confusion on the use of the terms primary and secondary sources, and primary and secondary data. The confusion is also due to disciplinary differences (Lombard 2010). Whilst you are advised to consult the research methods literature in your field, we can generalise as follows:  

Secondary sources 

Secondary sources normally include the literature (books and articles) with the experts' findings, analysis and discussions on a certain topic (Cottrell, 2014, p123). Secondary sources often interpret primary sources.  

Primary sources 

Primary sources are "first-hand" information such as raw data, statistics, interviews, surveys, law statutes and law cases. Even literary texts, pictures and films can be primary sources if they are the object of research (rather than, for example, documentaries reporting on something else, in which case they would be secondary sources). The distinction between primary and secondary sources sometimes lies on the use you make of them (Cottrell, 2014, p123). 

Primary data 

Primary data are data (primary sources) you directly obtained through your empirical work (Saunders, Lewis and Thornhill 2015, p316). 

Secondary data 

Secondary data are data (primary sources) that were originally collected by someone else (Saunders, Lewis and Thornhill 2015, p316).   

Comparison between primary and secondary data   

Use  

Virtually all research will use secondary sources, at least as background information. 

Often, especially at the postgraduate level, it will also use primary sources - secondary and/or primary data. The engagement with primary sources is generally appreciated, as less reliant on others' interpretations, and closer to 'facts'. 

The use of primary data, as opposed to secondary data, demonstrates the researcher's effort to do empirical work and find evidence to answer her specific research question and fulfill her specific research objectives. Thus, primary data contribute to the originality of the research.    

Ultimately, you should state in this section of the methodology: 

What sources and data you are using and why (how are they going to help you answer the research question and/or test the hypothesis. 

If using primary data, why you employed certain strategies to collect them. 

What the advantages and disadvantages of your strategies to collect the data (also refer to the research in you field and research methods literature). 

Quantitative, Qualitative & Mixed Methods

The methodology chapter should reference your use of quantitative research, qualitative research and/or mixed methods. The following is a description of each along with their advantages and disadvantages. 

Quantitative research 

Quantitative research uses numerical data (quantities) deriving, for example, from experiments, closed questions in surveys, questionnaires, structured interviews or published data sets (Cottrell, 2014, p93). It normally processes and analyses this data using quantitative analysis techniques like tables, graphs and statistics to explore, present and examine relationships and trends within the data (Saunders, Lewis and Thornhill, 2015, p496). 

Qualitative research  

Qualitative research is generally undertaken to study human behaviour and psyche. It uses methods like in-depth case studies, open-ended survey questions, unstructured interviews, focus groups, or unstructured observations (Cottrell, 2014, p93). The nature of the data is subjective, and also the analysis of the researcher involves a degree of subjective interpretation. Subjectivity can be controlled for in the research design, or has to be acknowledged as a feature of the research. Subject-specific books on (qualitative) research methods offer guidance on such research designs.  

Mixed methods 

Mixed-method approaches combine both qualitative and quantitative methods, and therefore combine the strengths of both types of research. Mixed methods have gained popularity in recent years.  

When undertaking mixed-methods research you can collect the qualitative and quantitative data either concurrently or sequentially. If sequentially, you can for example, start with a few semi-structured interviews, providing qualitative insights, and then design a questionnaire to obtain quantitative evidence that your qualitative findings can also apply to a wider population (Specht, 2019, p138). 

Ultimately, your methodology chapter should state: 

Whether you used quantitative research, qualitative research or mixed methods. 

Why you chose such methods (and refer to research method sources). 

Why you rejected other methods. 

How well the method served your research. 

The problems or limitations you encountered. 

Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains mixed methods research in the following video:

LinkedIn Learning Video on Academic Research Foundations: Quantitative

The video covers the characteristics of quantitative research, and explains how to approach different parts of the research process, such as creating a solid research question and developing a literature review. He goes over the elements of a study, explains how to collect and analyze data, and shows how to present your data in written and numeric form.

Link to quantitative research video

Some Types of Methods

There are several methods you can use to get primary data. To reiterate, the choice of the methods should depend on your research question/hypothesis. 

Whatever methods you will use, you will need to consider: 

why did you choose one technique over another? What were the advantages and disadvantages of the technique you chose? 

what was the size of your sample? Who made up your sample? How did you select your sample population? Why did you choose that particular sampling strategy?) 

ethical considerations (see also tab...)  

safety considerations  

validity  

feasibility  

recording  

procedure of the research (see box procedural method...).  

Check Stella Cottrell's book  Dissertations and Project Reports: A Step by Step Guide  for some succinct yet comprehensive information on most methods (the following account draws mostly on her work). Check a research methods book in your discipline for more specific guidance.  

Experiments 

Experiments are useful to investigate cause and effect, when the variables can be tightly controlled. They can test a theory or hypothesis in controlled conditions. Experiments do not prove or disprove an hypothesis, instead they support or not support an hypothesis. When using the empirical and inductive method it is not possible to achieve conclusive results. The results may only be valid until falsified by other experiments and observations. 

For more information on Scientific Method, click here . 

Observations 

Observational methods are useful for in-depth analyses of behaviours in people, animals, organisations, events or phenomena. They can test a theory or products in real life or simulated settings. They generally a qualitative research method.  

Questionnaires and surveys 

Questionnaires and surveys are useful to gain opinions, attitudes, preferences, understandings on certain matters. They can provide quantitative data that can be collated systematically; qualitative data, if they include opportunities for open-ended responses; or both qualitative and quantitative elements. 

Interviews  

Interviews are useful to gain rich, qualitative information about individuals' experiences, attitudes or perspectives. With interviews you can follow up immediately on responses for clarification or further details. There are three main types of interviews: structured (following a strict pattern of questions, which expect short answers), semi-structured (following a list of questions, with the opportunity to follow up the answers with improvised questions), and unstructured (following a short list of broad questions, where the respondent can lead more the conversation) (Specht, 2019, p142). 

This short video on qualitative interviews discusses best practices and covers qualitative interview design, preparation and data collection methods. 

Focus groups   

In this case, a group of people (normally, 4-12) is gathered for an interview where the interviewer asks questions to such group of participants. Group interactions and discussions can be highly productive, but the researcher has to beware of the group effect, whereby certain participants and views dominate the interview (Saunders, Lewis and Thornhill 2015, p419). The researcher can try to minimise this by encouraging involvement of all participants and promoting a multiplicity of views. 

This video focuses on strategies for conducting research using focus groups.  

Check out the guidance on online focus groups by Aliaksandr Herasimenka, which is attached at the bottom of this text box. 

Case study 

Case studies are often a convenient way to narrow the focus of your research by studying how a theory or literature fares with regard to a specific person, group, organisation, event or other type of entity or phenomenon you identify. Case studies can be researched using other methods, including those described in this section. Case studies give in-depth insights on the particular reality that has been examined, but may not be representative of what happens in general, they may not be generalisable, and may not be relevant to other contexts. These limitations have to be acknowledged by the researcher.     

Content analysis 

Content analysis consists in the study of words or images within a text. In its broad definition, texts include books, articles, essays, historical documents, speeches, conversations, advertising, interviews, social media posts, films, theatre, paintings or other visuals. Content analysis can be quantitative (e.g. word frequency) or qualitative (e.g. analysing intention and implications of the communication). It can detect propaganda, identify intentions of writers, and can see differences in types of communication (Specht, 2019, p146). Check this page on collecting, cleaning and visualising Twitter data.

Extra links and resources:  

Research Methods  

A clear and comprehensive overview of research methods by Emerald Publishing. It includes: crowdsourcing as a research tool; mixed methods research; case study; discourse analysis; ground theory; repertory grid; ethnographic method and participant observation; interviews; focus group; action research; analysis of qualitative data; survey design; questionnaires; statistics; experiments; empirical research; literature review; secondary data and archival materials; data collection. 

Doing your dissertation during the COVID-19 pandemic  

Resources providing guidance on doing dissertation research during the pandemic: Online research methods; Secondary data sources; Webinars, conferences and podcasts; 

• Virtual Focus Groups Guidance on managing virtual focus groups

5 Minute Methods Videos

The following are a series of useful videos that introduce research methods in five minutes. These resources have been produced by lecturers and students with the University of Westminster's School of Media and Communication. 

Case Study Research

Research Ethics

Quantitative Content Analysis 

Sequential Analysis 

Qualitative Content Analysis 

Thematic Analysis 

Social Media Research 

Mixed Method Research 

Procedural Method

In this part, provide an accurate, detailed account of the methods and procedures that were used in the study or the experiment (if applicable!). 

Include specifics about participants, sample, materials, design and methods. 

If the research involves human subjects, then include a detailed description of who and how many participated along with how the participants were selected.  

Describe all materials used for the study, including equipment, written materials and testing instruments. 

Identify the study's design and any variables or controls employed. 

Write out the steps in the order that they were completed. 

Indicate what participants were asked to do, how measurements were taken and any calculations made to raw data collected. 

Specify statistical techniques applied to the data to reach your conclusions. 

Provide evidence that you incorporated rigor into your research. This is the quality of being thorough and accurate and considers the logic behind your research design. 

Highlight any drawbacks that may have limited your ability to conduct your research thoroughly. 

You have to provide details to allow others to replicate the experiment and/or verify the data, to test the validity of the research. 

Bibliography

Cottrell, S. (2014). Dissertations and project reports: a step by step guide. Hampshire, England: Palgrave Macmillan.

Lombard, E. (2010). Primary and secondary sources.  The Journal of Academic Librarianship , 36(3), 250-253

Saunders, M.N.K., Lewis, P. and Thornhill, A. (2015).  Research Methods for Business Students.  New York: Pearson Education. 

Specht, D. (2019).  The Media And Communications Study Skills Student Guide . London: University of Westminster Press.  

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Topic selection & proposal development, enquire now, software implementation using matlab, questionnaire designing & data analysis, chapters writing & journal papers, 5 different types of research methodology for 2024.

Research Methodology refers to the systematic process used to conduct and analyze research. It involves a set of procedures and techniques employed to gather, organize, and interpret data. Various types of research methodology , such as qualitative and quantitative methods, form the foundation for investigating and understanding diverse phenomena. 

Diverse research methodology provide a spectrum of advantages in scientific exploration. Qualitative methodologies, such as interviews and observations, delve deep into understanding human behavior and motivations. Quantitative approaches, like surveys and experiments, offer precise numerical data for statistical analysis. Mixed-methods enable a comprehensive view by merging qualitative and quantitative strengths. Experimental methods establish cause-and-effect relationships, while case studies offer in-depth insights into specific instances. Each methodology caters to different research needs, fostering a nuanced understanding of complex phenomena and contributing to the richness and depth of scholarly inquiry.

This blog is your guide to the Top 5 types of research methods that haven’t been fully tapped into yet. We’re talking about different ways to do research, the kind that hasn’t been widely used or discovered. It’s crucial to stay on top of these categories of research methodology because as the world moves forward, so does the way we study and understand things. So, we’ll be checking out the latest and coolest Research methodology types , from new technologies to fresh ways of combining different fields of study. 

Different types of methodology in research

Research methodology encompasses a variety of approaches and techniques to gather and analyze data. Here are some Different types of methodology in research:

Qualitative Methodology:

In-depth exploration of attitudes, behaviors, and motivations.

Utilizes methods like interviews, focus groups, and content analysis.

Quantitative Methodology:

Focuses on numerical data and statistical analysis.

Involves surveys, experiments, and structured observations.

Mixed-Methods Approach:

Integrates both qualitative and quantitative methods.

Offers a thorough comprehension of the research problem.

Experimental Research:

Investigates cause-and-effect relationships.

Involves controlled experiments with manipulated variables.

Survey Research:

Gathers data from a selected group through structured questionnaires.

Examines trends, attitudes, and opinions.

Case Study Methodology:

In-depth analysis of a specific instance or case.

Offers detailed insights into complex phenomena.

Action Research:

Involves collaboration between researchers and practitioners.

Aims to solve real-world problems through iterative cycles of planning, acting, observing, and reflecting.

Ethnographic Research:

Immersive study of a specific group or culture.

Requires prolonged engagement and participant observation.

Methodology 1: Neurobiological Methodology

Neurobiological Methodology stands at the forefront of methodology in research paper, bridging the realms of neuroscience and traditional research methodologies. This is one of the Research methodology types which aims to unravel the intricacies of human cognition and behavior by integrating cutting-edge brain imaging techniques with established research methods.

Key Components:

Neuroimaging Technologies: Utilizes advanced technologies such as fMRI (functional Magnetic Resonance Imaging) and EEG (Electroencephalography) for all the research methodologies including exploratory research in research methodology. Enables real-time monitoring of brain activity, offering insights into cognitive processes during various tasks.

Biometric Data Integration: Incorporates biometric data, including heart rate variability and skin conductance, to supplement neurobiological findings. Provides a comprehensive understanding of emotional responses and physiological changes related to cognitive activities.

Experimental Designs with Neural Correlates: Designs experiments that correlate specific neural activities with behavioral responses. Allows researchers to identify neural markers associated with decision-making, memory, and learning.

Cross-Disciplinary Collaboration: Encourages collaboration between neuroscientists and researchers from diverse fields. Integrates expertise from psychology, sociology, and other disciplines to ensure a holistic approach.

Applications: Neurobiological Methodology, which is a descriptive methodology in research, holds immense potential across various research domains:

In Psychology: Unraveling the neural basis of psychological disorders, emotions, and cognitive functions.

In Marketing: Understanding consumer behavior by examining the neural responses to advertisements and product choices.

In Education: Enhancing learning methodologies by identifying neural patterns associated with effective teaching strategies.

Challenges and Future Directions: Despite its promises, Neurobiological Methodology faces challenges such as data complexity and ethical considerations. Future research should focus on refining methodologies, establishing ethical guidelines, and fostering interdisciplinary collaboration to unlock the full potential of this unexplored approach. Neurobiological Methodology emerges as a groundbreaking frontier, offering a novel lens through which researchers can delve into the intricacies of human cognition and behavior. As one of the different types of methodology in research, it holds the potential to reshape our understanding of the mind and pave the way for innovative solutions across diverse fields.

Methodology 2: Augmented Reality (AR) Research Methodology

Augmented Reality (AR) Research Methodology marks an unexplored frontier, intertwining cutting-edge AR technologies with traditional research methods. This is one of the types of methodology in research which seeks to create immersive environments for data collection, offering a unique perspective on human behavior and decision-making.

Constructs simulated environments using AR technology to observe and analyze real-time human behavior.

Enables researchers to study reactions and interactions in controlled yet dynamic settings.

Integrates AR-generated data collection points within physical spaces.

Facilitates the gathering of diverse data sets by embedding virtual elements in real-world contexts.

Utilizes AR interfaces to track user interactions and responses.

Enhances the understanding of user engagement and decision-making processes within augmented scenarios.

Combines AR experiences with traditional research methods such as exploratory research in research methodology for a comprehensive approach.

Allows researchers to triangulate findings by comparing results obtained from both virtual and non-virtual settings.

Applications: AR Research Methodology, which is also a descriptive methodology in research, holds promise across various research domains:

Simulating scenarios to observe human responses to environmental changes in descriptive qualitative research methodology.

Analyzing consumer behavior within augmented retail environments for product placement and advertising strategies.

Creating interactive learning experiences to study the impact of AR on knowledge retention.

Challenges and Future Directions: Challenges such as technological constraints and the need for standardized protocols highlight the evolving nature of this Research methodology types. Future endeavors should focus on refining AR applications, establishing ethical guidelines, and exploring collaborative opportunities with AR developers. Augmented Reality Research Methodology stands as an exciting avenue among the types of methodology in research, offering a transformative approach to understanding human behavior within virtual and augmented spaces. As technology continues to advance, this methodology holds the potential to redefine the landscape of research methodologies across diverse disciplines.

Methodology 3: Predictive Analytics in Social Sciences

Predictive Analytics in Social Sciences emerges as a groundbreaking methodology in research papers, introducing advanced statistical models and machine learning algorithms to forecast social trends and behaviors. This type of exploratory research methodologies harnesses the power of predictive analytics to offer a new dimension to traditional categories of research methodology.

Advanced Statistical Models:

Applies sophisticated statistical models, including regression analysis and time-series forecasting.

Enables researchers to identify patterns and relationships within social data.

Machine Learning Algorithms:

Integrates machine learning algorithms to predict future outcomes based on historical data.

Provides a dynamic and adaptive approach to understanding social phenomena in descriptive qualitative research methodology.

Big Data Utilization:

Harnesses large datasets from diverse sources, including social media, surveys, and public records.

Facilitates the identification of trends and correlations within complex social systems.

Real-Time Analysis:

Conducts real-time analysis of social data to generate instant predictions.

Allows for timely interventions and policy adjustments based on emerging social patterns.

Applications: Predictive Analytics in Social Sciences holds immense potential across various applications:

In Sociology: Forecasting demographic shifts, social movements, and cultural trends.

In Public Policy: Informing policy decisions by predicting the potential impact of interventions.

In Market Research: Anticipating consumer behavior and market trends for strategic planning.

Challenges and Future Directions: Despite its promises, integrating predictive analytics into social sciences faces challenges such as data privacy concerns and model interpretability, which is a type of exploratory research methodologies. Future research should focus on refining models, addressing ethical considerations, and enhancing the transparency of predictive analytics methodologies.

Predictive Analytics in Social Sciences stands as a dynamic methodology, extending beyond basic research methodology to offer foresight into the complex dynamics of human societies. As we embrace the era of big data, this approach holds the potential to revolutionize how we understand and respond to social changes in real time.

Methodology 4: Quantum Research Methodology

Quantum Research Methodology represents a paradigm shift, bridging the world of quantum physics with a basic research methodology. This unexplored approach challenges the traditional classification of research methodology by harnessing the principles of quantum mechanics for data analysis.

Quantum Computing for Data Processing: Utilizes quantum computing’s parallel processing capabilities for handling complex datasets. Offers a quantum leap in computational efficiency, enabling the analysis of vast amounts of information.

Quantum Entanglement in Data Relationships: Applies the concept of quantum entanglement to identify interconnected relationships within datasets. Provides a unique perspective on the interdependence of variables in comprehensive research methodology.

Superposition for Multifaceted Analysis: Exploits quantum superposition to analyze data simultaneously from multiple perspectives. Enhances researchers’ ability to examine complex phenomena from various angles.

Quantum Algorithms for Pattern Recognition: Develops quantum algorithms for advanced pattern recognition within datasets. Enables the identification of subtle patterns that may go unnoticed with classical algorithms.

Applications: Quantum Research Methodology holds potential classification of research methodology across diverse fields:

Exploring quantum phenomena and complex physical systems with enhanced computational power.

Analyzing intricate biological datasets to uncover hidden relationships and patterns.

Enhancing predictive modeling and risk analysis with quantum algorithms.

Challenges and Future Directions: The integration of quantum principles into research methodologies presents challenges such as the need for quantum expertise and the development of quantum-safe data encryption. Future research should focus on refining quantum algorithms, expanding interdisciplinary collaborations, and addressing ethical considerations. Quantum Research Methodology offers a novel and comprehensive approach that transcends traditional classifications of research methodology. As quantum technologies continue to advance, this unexplored frontier holds the promise of revolutionizing how we conduct research, analyze data, and gain insights into the underlying structures of complex systems.

Methodology 5: Bibliometric Research Methodology

Bibliometric research methodology is a quantitative approach that analyzes patterns and trends within academic literature, utilizing bibliographic data to gain insights into the scholarly landscape in the comprehensive research methodology.

Citation Analysis:

Examines the frequency and impact of citations to understand the influence of a publication.

Identifies seminal works and measures the academic impact of research.

Co-authorship Networks:

Maps collaborations among researchers through analysis of co-authored publications.

Unveils research communities and the dynamics of collaborative efforts.

Journal Impact Factors:

Evaluates the prestige and impact of academic journals based on citation patterns.

Assists researchers in identifying reputable outlets for publication.

Keyword Co-occurrence:

Identifies prevalent themes and topics within a field by analyzing the co-occurrence of keywords.

Facilitates trend analysis and the identification of emerging research areas.

Applications:

Research Evaluation:

Assessing the impact and productivity of researchers, institutions, or journals.

Informing funding agencies and policymakers in decision-making processes.

Trend Analysis:

Identifying emerging topics and research directions within a discipline.

Assisting researchers in staying abreast of the latest developments.

Collaboration Mapping:

Facilitating the identification of potential collaborators and research networks.

Enhancing interdisciplinary research initiatives.

Challenges:

Data Quality and Availability:

Limited availability and consistency of bibliographic data.

Challenges in obtaining accurate and comprehensive citation information.

Discipline-specific Differences:

Variability in citation practices across disciplines.

Difficulty in creating standardized metrics applicable to all fields.

Self-citation Bias:

Influence of self-citations on impact metrics.

Requires careful consideration to avoid skewing results.

Future Directions:

Integration with Altmetrics:

Incorporating alternative metrics like social media mentions to provide a more comprehensive assessment of research impact.

Open Science Initiatives:

Embracing open access principles to enhance data sharing and transparency.

Facilitating broader collaboration and increasing the accessibility of research outputs.

Machine Learning Applications:

Implementing machine learning algorithms for more sophisticated analysis.

Enhancing the automation of bibliometric processes and improving accuracy.

Final Thoughts

In wrapping up our exploration of the top 5 unexplored types of research methodology for 2024, it’s like we’ve discovered a treasure chest of new ideas. These methods are like a breath of fresh air in the world of research. From understanding how our brains work to creating virtual worlds with Augmented Reality, and predicting social trends, we’re on the brink of something big. 

Quantum research and Blockchain verification bring a touch of magic, making our data analysis smarter and more secure. These aren’t just fancy trends; they’re like keys to unlock a whole new era of learning. So, in 2024, researchers, buckle up and dive into these research methodology – the journey promises to be full of surprises, discoveries, and a whole lot of new knowledge!

Educba is a website that provides researchers with a comprehensive guide to different types of research methodologies. The website offers a wide range of courses and tutorials on research methodology, which can help researchers develop their research skills and knowledge. By taking these courses, researchers can learn about different research methods and techniques, such as surveys, case studies, and experiments. 

This knowledge can help researchers design and conduct their research more effectively and efficiently. Additionally, the website provides a platform for researchers to connect with other researchers and experts in their field. This can help researchers build their professional network and find new opportunities for research and collaboration. Overall, educba.com is a valuable resource for researchers who are looking to develop their research skills and knowledge and build their professional network.

Frequently Asked Questions

What is the research methodology?

Research methodology is the systematic process used to conduct and analyze research.

What is literature review in research methodology?

Literature review in research methodology involves reviewing and analyzing existing literature on a specific topic.

What is qualitative research methodology?

Qualitative research methodology involves exploring and understanding complex phenomena through non-numerical data.

What are qualitative methodologies?

Qualitative methodologies encompass various approaches like interviews, focus groups, and content analysis.

What are research methodology types?

Research methodology types include qualitative, quantitative, mixed methods, experimental, and survey research.

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