methodology in a dissertation

Writing the Dissertation - Guides for Success: The Methodology

• Writing the Dissertation Homepage
• Overview and Planning
• The Literature Review
• The Methodology
• The Results and Discussion
• The Conclusion
• The Abstract
• Getting Started
• What to Avoid

Overview of writing the methodology

The methodology chapter precisely outlines the research method(s) employed in your dissertation and considers any relevant decisions you made, and challenges faced, when conducting your research. Getting this right is crucial because it lays the foundation for what’s to come: your results and discussion.

Disciplinary differences

Please note: this guide is not specific to any one discipline. The methodology can vary depending on the nature of the research and the expectations of the school or department. Please adapt the following advice to meet the demands of your dissertation and the expectations of your school or department. Consult your supervisor for further guidance; you can also check out our  Writing Across Subjects guide .

Guide contents

As part of the Writing the Dissertation series, this guide covers the most common conventions found in a methodology chapter, giving you the necessary knowledge, tips and guidance needed to impress your markers!  The sections are organised as follows:

• Getting Started  - Defines the methodology and its core characteristics.
• Structure  - Provides a detailed walk-through of common subsections or components of the methodology.
• What to Avoid  - Covers a few frequent mistakes you'll want to...avoid!
• FAQs  - Guidance on first- vs. third-person, secondary literature and more.
• Checklist  - Includes a summary of key points and a self-evaluation checklist.

Training and tools

• The Academic Skills team has recorded a Writing the Dissertation workshop series to help you with each section of a standard dissertation, including a video on writing the method/methodology .
• For more on methods and methodologies, you can check out USC's methodology research guide  and Huddersfield's guide to writing the methodology of an undergraduate dissertation .
• The dissertation planner tool can help you think through the timeline for planning, research, drafting and editing.
• iSolutions offers training and a Word template to help you digitally format and structure your dissertation.

What is the methodology?

The methodology of a dissertation is like constructing a house of cards. Having strong and stable foundations for your research relies on your ability to make informed and rational choices about the design of your study. Everything from this point on – your results and discussion –  rests on these decisions, like the bottom layer of a house of cards.

The methodology is where you explicitly state, in relevant detail, how you conduced your study in direct response to your research question(s) and/or hypotheses. You should work through the linear process of devising your study to implementing it, covering the important choices you made and any potential obstacles you faced along the way.

Methods or methodology?

Some disciplines refer to this chapter as the research methods , whilst others call it the methodology . The two are often used interchangeably, but they are slightly different. The methods chapter outlines the techniques used to conduct the research and the specific steps taken throughout the research process. The methodology also outlines how the research was conducted, but is particularly interested in the philosophical underpinning that shapes the research process. As indicated by the suffix, -ology , meaning the study of something, the methodology is like the study of research, as opposed to simply stating how the research was conducted.

This guide focuses on the methodology, as opposed to the methods, although the content and guidance can be tailored to a methods chapter. Every dissertation is different and every methodology has its own nuances, so ensure you adapt the content here to your research and always consult your supervisor for more detailed guidance.

What are my markers looking for?

Your markers are looking   for your understanding of the complex process behind original (see definition) research. They are assessing your ability to...

• Demonstrate   an understanding of the impact that methodological choices can have on the reliability and validity of your findings, meaning you should engage with ‘why’ you did that, as opposed to simply ‘what’ you did.
• Make   informed methodological choices that clearly relate to your research question(s).

But what does it mean to engage in 'original' research? Originality doesn’t strictly mean you should be inventing something entirely new. Originality comes in many forms, from updating the application of a theory, to adapting a previous experiment for new purposes – it’s about making a worthwhile contribution.

Structuring your methodology

The methodology chapter should outline the research process undertaken, from selecting the method to articulating the tool or approach adopted to analyse your results. Because you are outlining this process, it's important that you structure your methodology in a linear way, showing how certain decisions have impacted on subsequent choices.

Scroll to continue reading, or click a link below to jump immediately to that section:

The 'research onion'

To ensure you write your methodology in a linear way, it can be useful to think of the methodology in terms of layers, as shown in the figure below.

Figure: 'Research onion' from Saunders et al. (2007).

You don't need to precisely follow these exact layers as some won't be relevant to your research. However, the layered 'out to in' structure developed by Saunders et al. (2007) is appropriate for any methodology chapter because it guides your reader through the process in a linear fashion, demonstrating how certain decisions impacted on others. For example, you need to state whether your research is qualitative, quantitative or mixed before articulating your precise research method. Likewise, you need to explain how you collected your data before you inform the reader of how you subsequently analysed that data.

Using this linear approach from 'outer' layer to 'inner' layer, the next sections will take you through the most common layers used to structure a methodology chapter.

Introduction and research outline

Like any chapter, you should open your methodology with an introduction. It's good to start by briefly restating the research problem, or gap, that you're addressing, along with your research question(s) and/or hypotheses. Following this, it's common to provide a very condensed statement that outlines the most important elements of your research design. Here's a short example:

This study adopted qualitative research through a series of semi-structured interviews with seven experienced industry professionals.

Like any other introduction, you can then provide a brief statement outlining what the chapter is about and how it's structured (e.g., an essay map ).

Restating the research problem (or gap) and your research question(s) and/or hypotheses creates a natural transition from your previous review of the literature - which helped you to identify the gap or problem - to how you are now going to address such a problem. Your markers are also going to assess the relevance and suitability of your method and methodological choices against your research question(s), so it's good to 'frame' the entire chapter around the research question(s) by bringing them to the fore.

Research philosophy

A research philosophy is an underlying belief that shapes the way research is conducted. For this reason, as featured in the 'research onion' above, the philosophy should be the outermost layer - the first methodological issue you deal with following the introduction and research outline - because every subsequent choice, from the method employed to the way you analyse data, is directly influenced by your philosophical stance.

You can say something about other philosophies, but it's best to directly relate this to your research and the philosophy you have selected - why the other philosophy isn't appropriate for you to adopt, for instance. Otherwise, explain to your reader the philosophy you have selected (using secondary literature), its underlying principles, and why this philosophy, therefore, is particularly relevant to your research.

The research philosophy is sometimes featured in a methodology chapter, but not always. It depends on the conventions within your school or discipline , so only include this if it's expected.

The reason for outlining the research philosophy is to show your understanding of the role that your chosen philosophy plays in shaping the design and approach of your research study. The philosophy you adopt also indicates your worldview (in the context of this research), which is an important way of highlighting the role you, the researcher, play in shaping new knowledge.

Research method

This is where you state whether you're doing qualitative, quantitative or mixed-methods research before outlining the exact instrument or strategy (see definition) adopted for research (interviews, case study, etc.). It's also important that you explain why you have chosen that particular method and strategy. You can also explain why you're not adopting an alternate form of research, or why you haven't used a particular instrument, but keep this brief and use it to reinforce why you have chosen your method and strategy.

Your research method, more than anything else, is going to directly influence how effectively you answer your research question(s). For that reason, it's crucial that you emphasise the suitability of your chosen method and instrument for the purposes of your research.                       

Data collection

The data collection part of your methodology explain the process of how you accessed and collected your data. Using an interview as a qualitative example, this might include the criteria for selecting participants, how you recruited the participants and how and where you conducted the interviews. There is often some overlap with data collection and research method, so don't worry about this. Just make sure you get the essential information across to your reader.

The details of how you accessed and collected your data are important for replicability purposes - the ability for someone to adopt the same approach and repeat the study. It's also important to include this information for reliability and consistency purposes (see  validity and reliability  on the next tab of this guide for more).

Data analysis

After describing how you collected the data, you need to identify your chosen method of data analysis. Inevitably, this will vary depending on whether your research is qualitative or quantitative (see note below).

Qualitative research tends to be narrative-based where forms of ‘coding’ are employed to categorise and group the data into meaningful themes and patterns (Bui, 2014). Quantitative deals with numerical data meaning some form of statistical approach is taken to measure the results against the research question(s).

Tell your reader which data analysis software (such as SPSS or Atlast.ti) or method you’ve used and why, using relevant literature. Again, you can mention other data analysis tools that you haven’t used, but keep this brief and relate it to your discussion of your chosen approach. This isn’t to be confused with the results and discussion chapters where you actually state and then analyse your results. This is simply a discussion of the approach taken, how you applied this approach to your data and why you opted for this method of data analysis.

Detail of how you analysed your data helps to contextualise your results and discussion chapters. This is also a validity issue (see next tab of guide), as you need to ensure that your chosen method for data analysis helps you to answer your research question(s) and/or respond to your hypotheses. To use an example from Bui (2014: 155), 'if one of the research questions asks whether the participants changed their behaviour before and after the study, then one of the procedures for data analysis needs to be a comparison of the pre- and postdata'.

Validity and reliability

Validity simply refers to whether the research method(s) and instrument(s) applied are directly suited to meet the purposes of your research – whether they help you to answer your research question(s), or allow you to formulate a response to your hypotheses.

Validity can be separated into two forms: internal and external. The difference between the two is defined by what exists inside the study (internal) and what exists outside the study (external).

• Internal validity is the extent to which ‘the results obtained can be attributed to the manipulation of the independent variable' (Salkind, 2011: 147).
• External validity refers to the application of your study’s findings outside the setting of your study. This is known as generalisability , meaning to what extent are the results applicable to a wider context or population.

Reliability

Reliability refers to the consistency with which you designed and implemented your research instrument(s). The idea behind this is to ensure that someone else could replicate your study and, by applying the instrument in the exact same way, would achieve the same results. This is crucial to quantitative and scientific based research, but isn’t strictly the case with qualitative research given the subjective nature of the data.

With qualitative data, it’s important to emphasise that data was collected in a consistent way to avoid any distortions. For example, let’s say you’ve circulated a questionnaire to participants. You would want to ensure that every participant receives the exact same questionnaire with precisely the same questions and wording, unless different questionnaires are required for different members of the sample for the purposes of the research.

Ethical considerations

Any research involving human participants needs to consider ethical factors. In response, you need to show your markers that you have implemented the necessary measures to cover the relevant ethical issues. These are some of the factors that are typically included:

• How did you gain the consent of participants, and how did you formally record this consent?
• What measures did you take to ensure participants had enough understanding of their role to make an informed decision, including the right to withdraw at any stage?
• What measures did you take to maintain the confidentiality of participants during the research and, potentially, for the write-up?
• What measures did you take to store the raw data and protect it from external access and use prior to the write-up?

These are only a few examples of the ethical factors you need to write about in your methodology. Depending on the nature of your research, ethical considerations might form a significant part of your methodology chapter, or may only constitute a few sentences. Either way, it’s imperative that you show your markers that you’ve considered the relevant ethical implications of your research.

Limitations

Don’t make the mistake of ignoring the limitations of your study (see the next tab, 'What to Avoid', for more on this) – it’s a common part of research and should be confronted. Limitations of research can be diverse, but tend to be logistical issues relating to time, scope and access . Whilst accepting that your study has certain limitations, the key is to put a positive spin on it, like the example below:

Despite having a limited sample size compared to other similar studies, the number of participants is enough to provide sufficient data, whilst the in-depth nature of the interviews facilitates detailed responses from participants.

• Bui, Y. N. (2014) How to Write a Master’s Thesis. 2dn Edtn. Thousand Oaks, CA: Sage.
• Guba, E. G. and Lincoln, Y. S. (1994) ‘Competing paradigms in qualitative research’, in Denzin, N. K. and Lincoln, N. S. (eds.) Handbook of Qualitative Research. Thousand Oaks, CA: Sage, pp. 105-117.
• Salkind, N. J. (2011) ‘Internal and external validity’, in Moutinho, L. and Hutchenson, G. D. (eds.) The SAGE Dictionary of Quantitative Management Research . Thousand Oaks, CA: Sage, pp. 147-149.
• Saunders, M., Lewis, P. and Thornhill, A. (2007) Research Methods for Business Students . 4th Edtn. Harlow: Pearson.

What to avoid

This portion of the guide will cover some common missteps you should try to avoid in writing your methodology.

Ignoring limitations

It might seem instinctive to hide any flaws or limitations with your research to protect yourself from criticism. However, you need to highlight any problems you encountered during the research phase, or any limitations with your approach. Your markers are expecting you to engage with these limitations and highlight the kind of impact they may have had on your research.

Just be careful that you don’t overstress these limitations. Doing so could undermine the reliability and validity of your results, and your credibility as a researcher.

Literature review of methods

Don’t mistake your methodology chapter as a detailed review of methods employed in other studies. This level of detail should, where relevant, be incorporated in the literature review chapter, instead (see our Writing the Literature Review guide ). Any reference to methodological choices made by other researchers should come into your methodology chapter, but only in support of the decisions you made.

Unnecessary detail

It’s important to be thorough in a methodology chapter. However, don’t include unnecessary levels of detail. You should provide enough detail that allows other researchers to replicate or adapt your study, but don’t bore your reader with obvious or extraneous detail.

Any materials or content that you think is worth including, but not essential in the chapter, could be included in an appendix (see definition). These don’t count towards your word count (unless otherwise stated), and they can provide further detail and context for your reader. For instance, it’s quite common to include a copy of a questionnaire in an appendix, or a list of interview questions.

Q: Should the methodology be in the past or present tense?

A: The past tense. The study has already been conducted and the methodological decisions have been implemented, meaning the chapter should be written in the past tense. For example...

Data was collected over the course of four weeks.

I informed participants of their right to withdraw at any time.

The surveys included ten questions about job satisfaction and ten questions about familial life (see Appendix).

Q: Should the methodology include secondary literature?

A: Yes, where relevant. Unlike the literature review, the methodology is driven by what you did rather than what other people have done. However, you should still draw on secondary sources, when necessary, to support your methodological decisions.

Q: Do you still need to write a methodology for secondary research?

A: Yes, although it might not form a chapter, as such. Including some detail on how you approached the research phase is always a crucial part of a dissertation, whether primary or secondary. However, depending on the nature of your research, you may not have to provide the same level of detail as you would with a primary-based study.

For example, if you’re analysing two particular pieces of literature, then you probably need to clarify how you approached the analysis process, how you use the texts (whether you focus on particular passages, for example) and perhaps why these texts are scrutinised, as opposed to others from the relevant literary canon.

In such cases, the methodology may not be a chapter, but might constitute a small part of the introduction. Consult your supervisor for further guidance.

Q: Should the methodology be in the first-person or third?

A: It’s important to be consistent , so you should use whatever you’ve been using throughout your dissertation. Third-person is more commonly accepted, but certain disciplines are happy with the use of first-person. Just remember that the first-person pronoun can be a distracting, but powerful device, so use it sparingly. Consult your supervisor for further guidance.

It’s important to remember that all research is different and, as such, the methodology chapter is likely to be very different from dissertation to dissertation. Whilst this guide has covered the most common and essential layers featured in a methodology, your methodology might be very different in terms of what you focus on, the depth of focus and the wording used.

What’s important to remember, however, is that every methodology chapter needs to be structured in a linear, layered way that guides the reader through the methodological process in sequential order. Through this, your marker can see how certain decisions have impacted on others, showing your understanding of the research process.

Here’s a final checklist for writing your methodology. Remember that not all of these points will be relevant for your methodology, so make sure you cover whatever’s appropriate for your dissertation. The asterisk (*) indicates any content that might not be relevant for your dissertation. You can download a copy of the checklist to save and edit via the Word document, below.

• Methodology self-evaluation checklist

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Writing a Methodology for your Dissertation | Complete Guide & Steps

What is a methodology.

The methodology is perhaps the most challenging and laborious part of the dissertation . Essentially, the methodology helps in understanding the broad, philosophical approach behind the methods of research you chose to employ in your study. The research methodology elaborates on the ‘how’ part of your research.

This means that your methodology chapter should clearly state whether you chose to use quantitative or qualitative data collection techniques or a mix of both.

Your research methodology should explain the following:

• What was the purpose of your research?
• What type of research method was used?
• What were the data-collecting methods?
• How did you analyse the data?
• What kind of resources were used in your research?
• Why did you choose these methods?

You will be required to provide justifications as to why you preferred a certain method over the others. If you are trying to figure out exactly how to write methodology or the structure of a methodology for a dissertation, this article will point you in the right direction.

Students must be sure of why they chose a certain research method over another. “I figured out” or “In my opinion” statements will not be an acceptable justification. So, you will need to come up with concrete academic reasons for your selection of research methods.

What are the Standard Contents of a Research Methodology?

The methodology generally acts as a guideline or plan for exactly how you intend to carry out your research. This is especially true for students who must submit their methodology chapter before carrying out the research.

Your methodology should link back to the literature review and clearly state why you chose certain data collection and analysis methods for your research/dissertation project.

The methodology chapter consists of the following:

• Research Design
• Philosophical Approach
• Data Collection Methods
• Research Limitations
• Ethical Considerations (If Any)
• Data Analysis Methods

For those who are submitting their dissertation as a single paper, their methodology should also touch on any modifications they had to make as their work progressed.

However, it is essential to provide academic justifications for all choices made by the researcher.

How to Choose your Dissertation Methodology and Research Design?

The theme of your research methodology chapter should be related to your literature review and research question (s).

You can visit your college or university library to find textbooks and articles that provide information about the commonly employed research methods .

An intensive reading of such books can help you devise your research philosophy and choose the appropriate methods. Any limitations or weaknesses of your chosen research approach should also be explained, as well as the strategies to overcome them.

To research well, you should read well! Read as many research articles (from reputed journals) as you can. Seeing how other researchers use methods in their studies and why will help you justify, in the long run, your own research method(s).

Regardless of the chosen research approach, you will find researchers who either support it or don’t. Use the arguments for and against articulated in the literature to clarify why you decided to choose the selected research design and why the research limitations are irrelevant to your research.

How to Structure your Dissertation Methodology?

The typical structure of the methodology chapter is as follows:

• Research Design And Strategy
• Methods Of Data Collection And Data Analysis
• Ethical Considerations, Reliability , Limitations And Generalisability

In research jargon, generalisability is termed external validity . It means how generalisable your research findings are to other contexts, places, times, people, etc. External validity is expected to be significantly high, especially in quantitative studies.

According to USC-Research Guides (2017) , a research design’s primary function is to enable the researcher to answer the research questions through evidence effectively. Generally, this section will shed light on how you collected your data.

The researcher will have to justify their choice of data collection methods, such as the one that was reviewed, the use of data tools (interviews, phone surveys, questionnaires, observation, online surveys , etc.) and the like.

Moreover, data sampling choice should also be clearly explained with a focus on how you chose the ethnicity, group, profession and age of the participants.

• What type of questions do you intend to ask the respondents?
• How will they help to answer your research questions ?
• How will they help to test the hypothesis of the dissertation?

It is recommended to prepare these questions at the start of your research. You should develop your research problem and questions. This approach can allow the room to change or modify research questions if your data collection methods do not give the desired results.

It’s a good practice to keep referring to your research questions whilst planning or writing the research design section. This will help your reader recall what the research is about; why you have done what you did. Even though this technique is recommended to be applied at the start of every section within a dissertation, it’s especially beneficial in the methodology section.

In short, you will need to make sure that the data you are going to collect relates to the topic you are exploring. The complexity and length of the research design section will vary depending on your academic subject and the scope of your research, but a well-written research design will have the following characteristics:

• It sheds light on alternative research design options and justifies why your chosen design is the best to address the research problem.
• Clearly specifies the research questions that the research aims to address or the hypothesis to validate.
• Explain how the collected data will help address the research problem and discusses your research methodology to collect the data.

Philosophical Approach Behind Writing a Methodology

This will discuss your chosen philosophy to strengthen your research and the research model. Commonly employed philosophies in academia are

• Interpretivism,
• Positivism/Post-Positivism
• Constructivism

There are several other research philosophies that you could adopt.

The choice of philosophy will depend on many factors, including your academic subject and the type and complexity of the research study. Regardless of which philosophy is used, you will be required to make different assumptions about the world.

Once you have chosen your research philosophy, the next step will describe your research context to answer all the questions, including when, where, why, how and what of your research.

Essentially, as a researcher, you will be required to decide whether you will be using a qualitative method, a quantitative method or a mix of both.

Did you know?

Using both qualitative and quantitative methods leads to the use of a mixed-methods approach. This approach also goes by another seldom-used name: eclectic approach.

The process of data collection is different for each method. Typically, you would want to decide whether you will adopt the positivist approach, defining your hypothesis and testing it against reality.

If this is the case, you will be required to take the quantitative approach, collecting numerical data at a large scale (from 30 or more respondents) and testing your hypotheses with this data.

Collecting data from at least 30 respondents/participants ensures reliable statistical analysis . This is especially true for quantitative studies. If the data contains less than 30 responses, it won’t be enough to carry out reliable statistical analyses on such data.

The other option for you would be to base your research on a qualitative approach, which will point you in a direction where you will be investigating broader areas by identifying people’s emotions and perceptions of a subject.

With a qualitative approach, you will have to collect responses from respondents and look at them in all their richness to develop theories about the field you are exploring.

Finally, you can also use a mix of qualitative and quantitative methods (which is becoming increasingly popular among researchers these days). This method is beneficial if you are interested in putting quantitative data into a real-world context or reflecting different perspectives on a subject.

Research philosophy in the ‘research onion.’

Methods of Data Collection and Data Analysis

This section will require you to clearly specify how you gathered the data and briefly discuss the tools you used to analyse it. For example, you may choose to conduct surveys and/or interviews as part of the data collection process.

Similarly, if you used software such as Excel or SPSS to process the data , you will have to justify your software choice. In this section of your methodology chapter , you will also have to explain how you arrived at your findings and how reliable they are.

It is important to note that your readers or supervisor would want to see a correlation between your findings and the hypothesis/research questions you based your study on at the very beginning.

Your supervisor or dissertation research assistant can play a key role in helping you write the methodology chapter according to established research standards. So, keep your supervisor in the loop to get their contributions and recommendations throughout the process.

In this section, you should briefly describe the methods you’ve used to analyse the data you’ve collected.

Qualitative Methods

The qualitative method includes analysing language, images, audio, videos, or any textual data (textual analysis). The following types of methods are used in textual analysis .

Discourse analysis:

Discourse analysis is an essential aspect of studying a language and its uses in day-to-day life.

Content analysis:

It is a method of studying and retrieving meaningful information from documents Thematic analysis:

It’s a method of identifying patterns of themes in the collected information, such as face-to-face interviews, texts, and transcripts.

Example: After collecting the data, it was checked thoroughly to find the missing information. The interviews were transcribed, and textual analysis was conducted. The repetitions of the text, types of colours displayed, and the tone of the speakers was measured.

Quantitative Methods

Quantitative data analysis is used for analysing numerical data. Include the following points:

• The methods of preparing data before analysing it.
• Which statistical test you have used? (one-ended test, two-ended test)
• The type of software you’ve used.

Ethical Considerations, Reliability and Limitations of a Dissertation Methodology

Other important sections of your methodology are:

Ethical Considerations

Always consider how your research will influence other individuals who are beyond the scope of the study. This is especially true for human subjects. As a researcher, you are always expected to make sure that your research and ideas do not harm anyone in any way.Discussion concerning data protection, data handling and data confidentiality will also be included in this brief segment.

• How did you ensure your participants’/respondents’ anonymity and/or confidentiality?
• Did you remove any identifiable markers after conducting the study (post-test stage) so that readers wouldn’t be able to guess the identity of the participant/respondent?
• Was personal information collected according to the purpose of the research? (For instance, asking respondents their age when it wasn’t even relevant in the study). All such ethical considerations need to be mentioned.

Even though there is no established rule to include ethical considerations and limitations within the methodology section, it’s generally recommended to include it in this section, as it makes more sense than including it, say, after the discussions section or within the conclusion.

This is mainly because limitations almost always occur in the methodology stage of research. And ethical considerations need to be taken while sampling, an important aspect of the research methodology.

Here are some examples of ethical issues that you should be mindful of

• Does your research involve participants recalling episodes of suffering and pain?
• Are you trying to find answers to questions considered culturally sensitive either by participants or the readers?
• Are your research, analysis and findings based on a specific location or a group of people?

All such issues should be categorically addressed and a justification provided for your chosen research methodology by highlighting the study’s benefits.

Reliability

Is your research study and findings reliable for other researchers in your field of work? To establish yourself as a reliable researcher, your study should be both authentic and reliable.

Reliability means the extent to which your research can yield similar results if it was replicated in another setting, at a different time, or under different circumstances. If replication occurs and different findings come to light, your (original) research would be deemed unreliable.

Limitations

Good dissertation writers will always acknowledge the limitations of their research study. Limitations in data sampling can decrease your results’ reliability.

A classic example of research limitation is collecting responses from people of a certain age group when you could have targeted a more representative cross-section of the population.Be humble and admit to your own study’s limitations. Doing so makes your referees, editors, supervisors, readers and anyone else involved in the research enterprise aware that you were also aware of the things that limited your study.

Limitations are NOT the same as implications. Sometimes, the two can be confused. Limitations lead to implications, that is, due to a certain factor being absent in the study (limitation) for instance, future research could be carried out in a setting where that factor is present (implication).

Dissertation Methodology Example

At this point, you might have a basic understanding of how to craft a well-written, organised, accurate methodology section for your dissertation. An example might help bring all the aforementioned points home. Here is a dissertation methodology example in pdf to better understand how to write methodology for a dissertation.

Sample Dissertation Methodology

Does your Research Methodology Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong.

Types of Methodologies

A scientific or lab-based study.

A methodology section for a scientific study will need to elaborate on reproducibility and meticulousness more than anything else. If your methods have obvious flaws, the readers are not going to be impressed. Therefore, it is important to ensure that your chosen research methodology is vigorous in nature.

Any information related to the procedure, setup and equipment should be clearly stated so other researchers in your field of study can work with the same method in the future if needed.

Variables that are likely to falsify your data must be taken into the equation to avoid ambiguities. It is recommended to present a comprehensive strategy to deal with these variables when gathering and analysing the data and drawing conclusions.

Statistical models employed as part of your scientific study will have to be justified, and so your methodology should include details of those statistical models.

Another scholar in the future might use any aspect of your methodology as the starting point for their research. For example, they might base their research on your methodology but analyse the data using other statistical models. Hence, this is something you should be mindful of.

Behavioural or Social Sciences-Based Dissertation

Like scientific or lab-based research, a behavioural and social sciences methodology needs to be built along the same lines. The chosen methodology should demonstrate reproducibility and firmness so other scholars can use your whole dissertation methodology or a part of it based on their research needs.

But there are additional issues that the researcher must take into consideration when working with human subjects. As a starting point, you will need to decide whether your analysis will be based on qualitative data, quantitative data or mixed-method of research, where qualitative data is used to provide contextual background to quantitative data or the other way around.

Here are some questions for you to consider:

• Will you observe the participants undertaking some activity, ask them to fill out a questionnaire, or record their responses during the interviews ?
• Will you base your research on existing evidence and datasets and avoid working with human subjects?
• What are the length, width, and reach of your data? Define its scope.
• Is the data highly explicit to the location or cultural setting you carried your study in, or can it be generalised to other situations and frameworks (reliability)? What are your reasons and justifications?

While you will be required to demonstrate that you have taken care of the above questions, it is equally important to make sure that you address your research study’s ethical issues side-by-side.

Of course, the first step in that regard will be to obtain formal approval for your research design from the ethics bodies (such as IRBs – institutional review boards), but still, there will be many more issues that could trigger a sense of grief and discomfort among some of the readers.

Humanities and Arts Dissertation Project

The rigour and dependability of the methods of research employed remain undisputed and unquestionable for humanities and arts-based dissertations as well. However, the way you convince your readers of your dissertation’s thoroughness is slightly different.

Unlike social science dissertation or a scientific study, the methodology of dissertations in arts and humanities subjects needs to be directly linked to the literature review regardless of how innovative your dissertation’s topic might be.

For example, you could demonstrate the relationship between A and B to discover a new theoretical background or use existing theories in a new framework.

The methodology section of humanities and arts-based dissertations is less complex, so there might be no need to justify it in detail. Students can achieve a seamless transition from the literature review to the analysis section.

However, like with every other type of research methodology, it is important to provide a detailed justification of your chosen methodology and relate it to the research problem.

Failing to do so could leave some readers unconvinced of your theoretical foundations’ suitability, which could potentially jeopardise your whole research.

Make sure that you are paying attention to and giving enough information about the social and historical background of the theoretical frameworks your research methodology is based on. This is especially important if there is an essential difference of opinion between your research and the research done on the subject in the past.

A justification of why opposing schools of thought disagree and why you still went ahead to use aspects of these schools of thought in your methodology should be clearly presented for the readers to understand how they would support your readings.

A Dissertation in Creative Arts

Some degree programs in the arts allow students to undertake a portfolio of artworks or creative writing rather than produce an extended dissertation research project.However, in practice, your creative research will be required to be submitted along with a comprehensive evaluative paper, including background information and an explanation that hypothesises your innovative exercise.

While this might seem like an easy thing to do, critical evaluation of someone’s work is highly complex and notorious in nature. This further reinforces the argument of developing a rigorous methodology and adhering to it.

As a scholar, you will be expected to showcase the ability to critically analyse your methodology and show that you are capable of critically evaluating your own creative work.Such an approach will help you justify your method of creating the work, which will give the readers the impression that your research is grounded in theory.

What to Avoid in Methodology?

All chapters of a dissertation paper are interconnected. This means that there will undoubtedly be some information that would overlap between the different chapters of the dissertation .

For example, some of the text material may seem appropriate to both the literature review and methodology sections; you might even end up moving information from pillar to post between different chapters as you edit and improve your dissertation .

However, make sure that you are not making the following a part of your dissertation methodology, even though it may seem appropriate to fit them in there:

A Long Review of Methods Employed by Previous Researchers

It might seem relevant to include details of the models your dissertation methodology is based on. However, a detailed review of models and precedents used by other scholars and theorists will better fit in the literature review chapter, which you can link back to. This will help the readers understand why you decided to go in favour of or against a certain tactic.

Unnecessary Details Readers Might Not be Interested In

There is absolutely no need to provide extensive details of things like lab equipment and experiment procedures. Having such information in the methodology chapter would discourage some readers who might not be interested in your equipment, setup, lab environment, etc.

Your aim as the author of the document will be to retain the readers’ interest and make the methodology chapter as readable as possible.

While it is important to get all the information relating to how others can reproduce your experiment, it is equally important to ensure your methodology section isn’t unnecessarily long. Again, additional information is better to be placed within the appendices chapter.

The methodology is not the section to provide raw data, even if you are only discussing the data collection process. All such information should be moved to the appendices section.

Even if you feel some finding or numerical data is crucial to be presented within the methodology section, you can, at most, make brief comments about such data. Its discussion, however, is only allowed in the discussions section .

What Makes your Methodology Stand Out?

The factors which can determine if your dissertation methodology is ‘great’ depend on many factors, including the level of study you are currently enrolled in.

Undergraduate dissertations are, of course, less complex and less demanding. At most universities in the UK, undergraduate students are required to exhibit the ability to conduct thorough research as they engage for the first time with theoretical and conceptual frameworks in their chosen research area.

As an undergraduate student, you will be expected to showcase the capacity to reproduce what you have learnt from theorists in your academic subject, transform your leanings into a methodology that would help you address the research problem, and test the research hypothesis, as mentioned in the introduction chapter.

A great undergraduate-level dissertation will incorporate different schools of thought and make a valuable contribution to existing knowledge. However, in general, undergraduate-level dissertations’ focus should be to show thorough desk-based and independent research skills.

Postgraduate dissertation papers are much more compound and challenging because they are expected to make a substantial contribution to existing knowledge.

Depending on the academic institute, some postgraduate students are even required to develop a project published by leading academic journals as an approval of their research skills.

It is important to recognise the importance of a postgraduate dissertation towards building your professional career, especially if your work is considered impactful in your area of study and receives citations from multiple scholars, enhancing your reputation in academic communities.

Even if some academics cite your literature review and conclusion in their own work, it is a well-known fact that your methodology framework will result in many more citations regardless of your academic subject.

Other scholars and researchers in your area of study are likely to give much more value to a well-crafted methodology, especially one they can use as the starting point for their own research.

Of course, they can alter, refine and enhance your methodology in one way or another. They can even apply your methodological framework to a new data set or apply it in a completely new situation that is irrelevant to your work.

Finally, postgraduate dissertations are expected to be highly convincing and demonstrate in-depth engagement. They should be reproducible and show rigour, so the findings and conclusions can be regarded as authentic and reliable among scientific and academic communities.

The methodology is the door to success when it comes to dissertation projects. An original methodology that takes into consideration all aspects of research is likely to have an impact on the field of study.

As a postgraduate student, you should ask yourself, Is my dissertation methodology reproducible and transferable? Producing a methodology that others can reproduce in the future is as important as answering research questions .

The methodology chapter can either make or break the grade of your research/dissertation paper. It’s one of the research elements that leave a memorable impression on your readers. So, it would help if you took your time when it comes to choosing the right design and philosophical approach for your research.

Always use authentic academic sources and discuss your plans in detail with your supervisor if you believe your research design or approach has flaws in it.

Did this article help you learn how to write a dissertation methodology and how to structure a dissertation methodology? Let us know in your comments.

Are you struggling to create a thorough and well-rounded dissertation methodology?

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What Is a Research Methodology? | Steps & Tips

Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.

It should include:

• The type of research you conducted
• How you collected and analysed your data
• Any tools or materials you used in the research
• Why you chose these methods
• Your methodology section should generally be written in the past tense .
• Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
• Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyse?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.

Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analysing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorising and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviours, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalised beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalisable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives  and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

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

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Writing your Dissertation: Methodology

A key part of your dissertation or thesis is the methodology. This is not quite the same as ‘methods’.

The methodology describes the broad philosophical underpinning to your chosen research methods, including whether you are using qualitative or quantitative methods, or a mixture of both, and why.

You should be clear about the academic basis for all the choices of research methods that you have made. ' I was interested ' or ' I thought... ' is not enough; there must be good academic reasons for your choice.

What to Include in your Methodology

If you are submitting your dissertation in sections, with the methodology submitted before you actually undertake the research, you should use this section to set out exactly what you plan to do.

The methodology should be linked back to the literature to explain why you are using certain methods, and the academic basis of your choice.

If you are submitting as a single thesis, then the Methodology should explain what you did, with any refinements that you made as your work progressed. Again, it should have a clear academic justification of all the choices that you made and be linked back to the literature.

Common Research Methods for the Social Sciences

There are numerous research methods that can be used when researching scientific subjects, you should discuss which are the most appropriate for your research with your supervisor.

The following research methods are commonly used in social science, involving human subjects:

One of the most flexible and widely used methods for gaining qualitative information about people’s experiences, views and feelings is the interview.

An interview can be thought of as a guided conversation between a researcher (you) and somebody from whom you wish to learn something (often referred to as the ‘informant’).

The level of structure in an interview can vary, but most commonly interviewers follow a semi-structured format.  This means that the interviewer will develop a guide to the topics that he or she wishes to cover in the conversation, and may even write out a number of questions to ask.

However, the interviewer is free to follow different paths of conversation that emerge over the course of the interview, or to prompt the informant to clarify and expand on certain points. Therefore, interviews are particularly good tools for gaining detailed information where the research question is open-ended in terms of the range of possible answers.

Interviews are not particularly well suited for gaining information from large numbers of people. Interviews are time-consuming, and so careful attention needs to be given to selecting informants who will have the knowledge or experiences necessary to answer the research question.  

See our page: Interviews for Research for more information.

Observations

If a researcher wants to know what people do under certain circumstances, the most straightforward way to get this information is sometimes simply to watch them under those circumstances.

Observations can form a part of either quantitative or qualitative research.  For instance, if a researcher wants to determine whether the introduction of a traffic sign makes any difference to the number of cars slowing down at a dangerous curve, she or he could sit near the curve and count the number of cars that do and do not slow down.  Because the data will be numbers of cars, this is an example of quantitative observation.

A researcher wanting to know how people react to a billboard advertisement might spend time watching and describing the reactions of the people.  In this case, the data would be descriptive , and would therefore be qualitative.

There are a number of potential ethical concerns that can arise with an observation study. Do the people being studied know that they are under observation?  Can they give their consent?  If some people are unhappy with being observed, is it possible to ‘remove’ them from the study while still carrying out observations of the others around them?

See our page: Observational Research and Secondary Data for more information.

Questionnaires

If your intended research question requires you to collect standardised (and therefore comparable) information from a number of people, then questionnaires may be the best method to use.

Questionnaires can be used to collect both quantitative and qualitative data, although you will not be able to get the level of detail in qualitative responses to a questionnaire that you could in an interview.

Questionnaires require a great deal of care in their design and delivery, but a well-developed questionnaire can be distributed to a much larger number of people than it would be possible to interview. 

Questionnaires are particularly well suited for research seeking to measure some parameters for a group of people (e.g., average age, percentage agreeing with a proposition, level of awareness of an issue), or to make comparisons between groups of people (e.g., to determine whether members of different generations held the same or different views on immigration).

See our page: Surveys and Survey Design for more information.

Documentary Analysis

Documentary analysis involves obtaining data from existing documents without having to question people through interview, questionnaires or observe their behaviour. Documentary analysis is the main way that historians obtain data about their research subjects, but it can also be a valuable tool for contemporary social scientists.

Documents are tangible materials in which facts or ideas have been recorded.  Typically, we think of items written or produced on paper, such as newspaper articles, Government policy records, leaflets and minutes of meetings.  Items in other media can also be the subject of documentary analysis, including films, songs, websites and photographs.

Documents can reveal a great deal about the people or organisation that produced them and the social context in which they emerged. 

Some documents are part of the public domain and are freely accessible, whereas other documents may be classified, confidential or otherwise unavailable to public access.  If such documents are used as data for research, the researcher must come to an agreement with the holder of the documents about how the contents can and cannot be used and how confidentiality will be preserved.

How to Choose your Methodology and Precise Research Methods

Your methodology should be linked back to your research questions and previous research.

Visit your university or college library and ask the librarians for help; they should be able to help you to identify the standard research method textbooks in your field. See also our section on Research Methods for some further ideas.

Such books will help you to identify your broad research philosophy, and then choose methods which relate to that. This section of your dissertation or thesis should set your research in the context of its theoretical underpinnings.

The methodology should also explain the weaknesses of your chosen approach and how you plan to avoid the worst pitfalls, perhaps by triangulating your data with other methods, or why you do not think the weakness is relevant.

For every philosophical underpinning, you will almost certainly be able to find researchers who support it and those who don’t.

Use the arguments for and against expressed in the literature to explain why you have chosen to use this methodology or why the weaknesses don’t matter here.

Structuring your Methodology

It is usually helpful to start your section on methodology by setting out the conceptual framework in which you plan to operate with reference to the key texts on that approach.

You should be clear throughout about the strengths and weaknesses of your chosen approach and how you plan to address them. You should also note any issues of which to be aware, for example in sample selection or to make your findings more relevant.

You should then move on to discuss your research questions, and how you plan to address each of them.

This is the point at which to set out your chosen research methods, including their theoretical basis, and the literature supporting them. You should make clear whether you think the method is ‘tried and tested’ or much more experimental, and what kind of reliance you could place on the results. You will also need to discuss this again in the discussion section.

Your research may even aim to test the research methods, to see if they work in certain circumstances.

You should conclude by summarising your research methods, the underpinning approach, and what you see as the key challenges that you will face in your research. Again, these are the areas that you will want to revisit in your discussion.

Your methodology, and the precise methods that you choose to use in your research, are crucial to its success.

It is worth spending plenty of time on this section to ensure that you get it right. As always, draw on the resources available to you, for example by discussing your plans in detail with your supervisor who may be able to suggest whether your approach has significant flaws which you could address in some way.

Continue to: Research Methods Designing Research

See Also: Dissertation: Results and Discussion Writing a Literature Review | Writing a Research Proposal Writing a Dissertation: The Introduction

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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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Organizing Your Social Sciences Research Paper

• 6. The Methodology
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
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The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

• Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
• Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
• In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
• The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
• The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
• The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
• In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I.  Groups of Research Methods

There are two main groups of research methods in the social sciences:

• The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
• The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II.  Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

• Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
• Tools and methods used to identify and collect information, and how you identified relevant variables,
• The ways in which you processed the data and the procedures you used to analyze that data, and
• The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

• Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
• Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
• Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
• Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
• Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
• Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
• Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
• Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE :   Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE : If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE :   If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III.  Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

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Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

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

Structure of Research Methodology

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

I. Introduction

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

II. Research Design

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

III. Data Collection Methods

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

IV. Data Analysis Methods

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

V. Ethical Considerations

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

VI. Limitations

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

VII. Conclusion

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

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

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

Qualitative Research Methodology

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

Mixed-Methods Research Methodology

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

Case Study Research Methodology

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

Action Research Methodology

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

Experimental Research Methodology

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

Survey Research Methodology

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

Grounded Theory Research Methodology

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

Research Methodology Example

An Example of Research Methodology could be the following:

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

Introduction:

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

Research Design:

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

Participants:

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

Intervention :

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

Data Collection:

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

Data Analysis:

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

Ethical Considerations:

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

Data Management:

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

Limitations:

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

Conclusion:

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

How to Write Research Methodology

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

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

When to Write Research Methodology

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

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

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

Applications of Research Methodology

Here are some of the applications of research methodology:

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

Purpose of Research Methodology

Research methodology serves several important purposes, including:

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

Advantages of Research Methodology

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

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

Research Methodology Vs Research Methods

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What’s Included: Methodology Template

This template covers all the core components required in the research methodology chapter or section of a typical dissertation or thesis, including:

• The opening section
• Research philosophy
• Research type
• Research strategy
• Time horizon
• Sampling strategy
• Data collection methods
• Data analysis methods
• Conclusion & summary

The purpose of each section is explained in plain language, followed by an overview of the key elements that you need to cover. The template also includes practical examples to help you understand exactly what’s required, along with links to additional free resources (articles, videos, etc.) to help you along your research journey.

The cleanly-formatted Google Doc can be downloaded as a fully editable MS Word Document (DOCX format), so you can use it as-is or convert it to LaTeX.

PS – if you’d like a high-level template for the entire thesis, you can we’ve got that too .

What format is the template (DOC, PDF, PPT, etc.)?

The methodology chapter template is provided as a Google Doc. You can download it in MS Word format or make a copy to your Google Drive. You’re also welcome to convert it to whatever format works best for you, such as LaTeX or PDF.

What types of dissertations/theses can this template be used for?

The methodology template follows the standard format for academic research projects, which means it will be suitable for the vast majority of dissertations and theses (especially those within the sciences), whether they adopt a qualitative, quantitative, or mixed-methods approach. The template is loosely based on Saunders’ research onion , which is recommended as a methodological framework by many universities.

Keep in mind that the exact requirements for the methodology chapter/section will vary between universities and degree programs. These are typically minor, but it’s always a good idea to double-check your university’s requirements before you finalize your structure.

Is this template for an undergrad, Master or PhD-level thesis?

This template can be used for a dissertation, thesis or research project at any level of study. Doctoral-level projects typically require the methodology chapter to be more extensive/comprehensive, but the structure will typically remain the same.

How long should the methodology chapter be?

This can vary a fair deal, depending on the level of study (undergrad, Master or Doctoral), the field of research, as well as your university’s specific requirements. Therefore, it’s best to check with your university or review past dissertations from your program to get an accurate estimate. 

How detailed should my methodology be?

As a rule of thumb, you should provide enough detail for another researcher to replicate your study. This includes clear descriptions of procedures, tools, and techniques you used to collect and analyse your data, as well as your sampling approach.

How technical should my language be in this chapter?

In the methodology chapter, your language should be technical enough to accurately convey your research methods and processes, but also clear and precise to ensure it’s accessible to readers within your field.

Aim for a balance where the technical aspects of your methods are thoroughly explained without overusing jargon or overly complex language.

Should I include a pilot study in my methodology?

If you conducted a pilot study, you can include it in the methodology to demonstrate the feasibility and refinement of your methods. Be sure to obtain the necessary permissions from your research advisor before conducting any pilot studies, though. 

Can I share this template with my friends/colleagues?

Yes, you’re welcome to share this template in its original format (no editing allowed). If you want to post about it on your blog or social media, we kindly request that you reference this page as your source.

Do you have templates for the other chapters?

Yes, we do. We are constantly developing our collection of free resources to help students complete their dissertations and theses. You can view all of our template resources here .

Can Grad Coach help me with my methodology?

Yes, we can assist with your methodology chapter (or any other chapter) on a coaching basis. If you’re interested, feel free to get in touch to discuss our private coaching services .

Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

Thesis and Dissertation: Getting Started

Welcome to the Purdue OWL

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Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

The resources in this section are designed to provide guidance for the first steps of the thesis or dissertation writing process. They offer tools to support the planning and managing of your project, including writing out your weekly schedule, outlining your goals, and organzing the various working elements of your project.

Weekly Goals Sheet (a.k.a. Life Map) [Word Doc]

This editable handout provides a place for you to fill in available time blocks on a weekly chart that will help you visualize the amount of time you have available to write. By using this chart, you will be able to work your writing goals into your schedule and put these goals into perspective with your day-to-day plans and responsibilities each week. This handout also contains a formula to help you determine the minimum number of pages you would need to write per day in order to complete your writing on time.

Setting a Production Schedule (Word Doc)

This editable handout can help you make sense of the various steps involved in the production of your thesis or dissertation and determine how long each step might take. A large part of this process involves (1) seeking out the most accurate and up-to-date information regarding specific document formatting requirements, (2) understanding research protocol limitations, (3) making note of deadlines, and (4) understanding your personal writing habits.

Creating a Roadmap (PDF)

Part of organizing your writing involves having a clear sense of how the different working parts relate to one another. Creating a roadmap for your dissertation early on can help you determine what the final document will include and how all the pieces are connected. This resource offers guidance on several approaches to creating a roadmap, including creating lists, maps, nut-shells, visuals, and different methods for outlining. It is important to remember that you can create more than one roadmap (or more than one type of roadmap) depending on how the different approaches discussed here meet your needs.

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• Knowledge Base

Methodology

• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

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

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

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

Table of contents

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

• Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

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

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

• Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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

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

Operationalization

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

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

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

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

Reliability and validity

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

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

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

Sampling procedures

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

That means making decisions about things like:

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

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

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

Data management

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

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

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

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

Quantitative data analysis

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

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

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

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

Using inferential statistics , you can:

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

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

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

Qualitative data analysis

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

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

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

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

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

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

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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An overview of remote monitoring methods in biodiversity conservation

• Review Article
• Published: 05 October 2022
• Volume 29 , pages 80179–80221, ( 2022 )

Cite this article

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Conservation of biodiversity is critical for the coexistence of humans and the sustenance of other living organisms within the ecosystem. Identification and prioritization of specific regions to be conserved are impossible without proper information about the sites. Advanced monitoring agencies like the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) had accredited that the sum total of species that are now threatened with extinction is higher than ever before in the past and are progressing toward extinct at an alarming rate. Besides this, the conceptualized global responses to these crises are still inadequate and entail drastic changes. Therefore, more sophisticated monitoring and conservation techniques are required which can simultaneously cover a larger surface area within a stipulated time frame and gather a large pool of data. Hence, this study is an overview of remote monitoring methods in biodiversity conservation via a survey of evidence-based reviews and related studies, wherein the description of the application of some technology for biodiversity conservation and monitoring is highlighted. Finally, the paper also describes various transformative smart technologies like artificial intelligence (AI) and/or machine learning algorithms for enhanced working efficiency of currently available techniques that will aid remote monitoring methods in biodiversity conservation.

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Kingsly C. Beng & Richard T. Corlett

Avoid common mistakes on your manuscript.

Introduction

Biological diversity “biodiversity” entails the assortment of earthly life forms heterogeneously ranging from genetic to ecosystem level. It can embrace the evolutionary, ecological, and cultural aspects that uphold life in various forms (McQuatters-Gollop et al. 2019 ). It fosters ecological functioning that paves the path for fundamental ecosystem services comprising food, water, preservation of soil fertility, and management of pests and diseases (Avigliano et al. 2019 ; Whitehorn et al. 2019 ). The plasticity of co-existence between mankind and nature is irreversible because of the symbiotic relationship that sustains the co-survival of humans with other living organisms (Arias-Maldonado 2016 ).

Biological diversity of forest originating from gene to ecosystem, through species, supports forest habitat that gives rise to fodders and other goods and services in a wide array of diverse biophysical and socio-economic ambience. Despite the applicability and significance of biodiversity, its conservation is vaguely acknowledged. Presently, human invasions have distorted around 75% of the land-based territory and about 66% of the marine ecosystem. Further to this, over a third of the global terrestrial regions are now devoted to domestic pursuit (FAO 2019 ). Moreover, since 1970, the significance of agricultural crop yield has increased by about 300%, and harvesting of raw timber has hiked by 45%. Moreover, renewable and non-renewable resources roughly of 60 billion tons are presently extracted annually across the globe. Exploitation of land has abridged the prolificacy of 23% of the global land area, annually, up to US$577 billion in worldwide crops are in jeopardy from pollinator loss, and about 100–300 million people are at elevated threat of natural disaster due to loss of coastal habitats and protection (IPBES 2019 ). If such trends continue then by 2050, the transformative change in nature can lead to an unprecedented devastating irreversible impact on mankind, which will take centuries to recover.

These atrocities of biodiversity need to be averted through proper monitoring and conservation measures. Based on the present advancements in technology, a combination of system-based smart techniques, remote sensing, and molecular approaches will be necessary for implementation of such ambitious conservation drives. Computer-based simulation techniques such as geographic information system (GIS), active and passive radio detection and ranging (RADAR) system, and light detection and ranging (LiDAR) system are playing a crucial role for monitoring biodiversity in real time (Bouvier et al. 2017 ; Bae et al. 2019 ; Bakx et al. 2019 ). Further to this, the application of recent advancements like artificial intelligence (AI) (Kwok 2019 ) and/or machine learning algorithms (Fernandes et al. 2020 ) have also been exploited for the same (Hu et al. 2015 ). These systems are not only reliable in monitoring biodiversity globally but can also help prevent further biodiversity loss worldwide. Besides monitoring tools, conservation of individual species and genetic biodiversity as a whole will require the use of recent molecular techniques. Conservation genomics revolves around the concept that genome-scale data will meliorate the competence of resource proprietors to conserve species. Despite the decades-long utilization of genetic approaches for conservation research, it has only recently been implied for generating genome-wide data which is functional for conservation (Supple and Shapiro 2018 ). The revolutionary molecular tools like restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), random amplified polymorphic DNA (RAPD), sequence characterized amplified region (SCAR), microsatellites and mini-satellites, expressed sequence tags (ESTs), inter-simple sequence repeat (ISSR), and single nucleotide polymorphisms (SNPs) have transformed the hierarchy of biodiversity conservation to a higher level (Mosa et al. 2019 ).

Evidently, more sophisticated monitoring methods such as system-based simulation techniques, remote sensing, artificial intelligence, and geographic information system as well as molecular-based techniques facilitate the monitoring methods in biodiversity conservation and restoration. Therefore, the present study is an overview of remote monitoring methods in biodiversity conservation via a survey of evidence-based reviews and related studies, wherein the description of the application of some technology for biodiversity conservation and monitoring. Finally, the paper also describes various transformative smart technologies like artificial intelligence (AI) and/or machine learning algorithms for enhanced working efficiency of currently available techniques that will aid remote monitoring methods in biodiversity conservation.

Methodology of literature search

The relevant literature search was done electronically by using Google Search Engine, PubMed, ScienceDirect, SpringerLink, Frontiers Media, and MDPI databases. The most importantly searched keywords were biodiversity and potential threats, techniques to monitoring biodiversity, geographic information system, remote sensing, active remote sensing system, radio detection and ranging (RADAR) system, light detection and ranging (LiDAR) systems, passive remote sensing systems, techniques for identification and genetic conservation of species, restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), random amplified polymorphic DNA (RAPD), sequence characterized amplified region (SCAR), mini- and micro-satellites, expressed sequence tags (ESTs), inter-simple sequence repeat (ISSR), single nucleotide polymorphisms (SNPs), and artificial intelligence in biodiversity monitoring which were used and placed repeatedly within the text.

Biodiversity and potential threats

Biodiversity in simple terms is a heterogenic distribution of flora and fauna throughout the world or in a particular niche (Naeem et al. 2016 ). The number of species described around the world as per IUCN ( 2020 ) accounts for 2,137,939, of which 72,327 are vertebrates, 1,501,581 are invertebrates, 422,756 are plants, and 141,275 are identified as fungi and protists. It is now acknowledged that biodiversity is a major indicator of community ecosystem fluctuations and functioning (Tilman et al. 2014 ). These include provisioning of food, pollination, cultural recreation, and supporting nutrient cycling (Harrison et al. 2014 ; Bartkowski et al. 2015 ). Biodiversity as a whole is represented by two major components that are species richness and species evenness. A biogeographic region with a significant level of endemic species and with a higher loss of habitat is generally depicted as a biodiversity hotspot (Marchese 2015 ). These areas have proven themselves as a tool for establishing conservation priorities and orchestrate vital rationale in decision-making for cost-effective tactics to safeguard biodiversity in its natural conserved state. Usually, the hotspots are marked by single or multiple species-based metrics or concentrate on phylogenetic and functional diversity to shield species that sustain exclusive and inimitable functions inside the ecosystem (Marchese 2015 ).

Currently, as per the IUCN Red List of Species 2020–2021, of the 2,137,939 species around the world, about 31,030 species are categorized as “threatened” species. Among these, plants with 16,460 numbers contribute the most followed by vertebrates (9063), invertebrates (5333), and fungi and protists (174) [IUCN 2020 ]. Many of the species are still not assessed due to a lack of reliable identification tools or techniques. Biodiversity is mostly threatened by over-population, habitat and landscape modification, indiscriminate exploitation of resources, pollution, and lack of proper documentation (Marchese 2015 ; Liu et al. 2020 ; Reid et al. 2019 ). Demographic changes can be considered an imperative module for assisting the indirect drivers of biodiversity alternations specifically associated with land use patterns (Newbold et al. 2015 ). Population explosion, central demographic developments, and urbanization impact both ecosystems and the species it harbors (Mehring et al. 2020 ). As the changing demographic pattern is associated with population explosion, this may pose a pessimistic impact on food availability, restricted emission of greenhouse gases, control of invasive species and diseases, etc. (Lampert 2019 ; Manisalidis et al. 2020 ; Hoban et al. 2020 ; Reid et al. 2019 ). To generate such massive data over a stipulated time frame and process them simultaneously to extrude applicable information requires cutting-edge tools and multidisciplinary scientific input (Randin et al. 2020 ). With recent advancements in mapping software, large-scale data processors, and monitoring tools and genetics, artificial intelligence for generating accurate data over a larger area as a part of a global monitoring strategy has now become feasible (Wetzel et al. 2015 ; Randin et al. 2020 ). Hence, an assortment of the above mention techniques and tools will be essential for the conservation and restoration of biodiversity.

Techniques for monitoring biodiversity

Mapping and monitoring techniques have been frontiers in predicting and modeling anthropogenic activities, habitat use, and pattern of land use over time in a particular region. These advanced physical techniques include GIS, LiDAR, and RADAR systems (Bouvier et al. 2017 ; Bae et al. 2019 ; Bakx et al. 2019 ).

Geographic information system (GIS)

Understanding functional geography and making intelligent decisions is widely beneficial for naturalists. GIS is a popular tool for analyzing possible and current spatial-temporal distribution, location, distribution patterns, population assessment, and identification of priority areas for their conservation and management (Krigas et al. 2012 ; Salehi and Ahmadian 2017 ). Currently, development of ecological niche models based on topographic, bioclimatic, soil, and land use variables was mapped and predicted for species such as Clinopodium nepeta , Thymbra capitata , Melissa officinalis , Micromeria juliana , Origanum dictamnus , O. vulgare , O. onites , Salvia fruticosa , S. pomifera , and Satureja thymbra (Bariotakis et al. 2019 ). With the assistance of digitally integrated video and audio-GIS (DIVA-GIS), actual geographic distribution and the future potential assortments of several Zingiber sp. like Z. mioga , Z. officinale , Z. striolatum , and Z. cochleariforme were analyzed (Huang et al. 2019 ). Most recently, important climatic inconsistencies distressing the geographical dispersion of wild Akebia trifoliate based on the formation of spatial database were successfully determined with the help of GIS (Wang et al. 2020 ). However, GIS possesses certain limitations such as expensive software, hardware, capturing GIS data, and difficulty in their use (Bearman et al. 2016 ) (Fig. 1 , Table 1 ).

Application of Geographic Information Systems (GIS), remote sensing technologies like radio detection and ranging (RADAR) and satellite-based light detection and ranging (LiDAR) for wildlife monitoring in the forest ecosystem. The figure describes global forest distribution (Our World In Data 2020 ), wherein displayed GIS and different levels of GIS data, schismatic of passive remote sensing, active remote sensing segregated into primary RADAR system, and a block diagram of satellite-based LiDAR system for generation of DCHM (digital canopy height model) image and 3-D point cloud image of the whole organism is outlined. Global positioning system (GPS), Inertial measurement unit (IMU). The figure is inspired by the following sources: Omasa et al. ( 2007 ), Admin ( 2017 ), Bhatta and Priya ( 2017 ), Jahncke et al. ( 2018 ), Martone et al. ( 2018 ), Srivastava et al. ( 2020 ). The components of the figure are modifications of Portree ( 2006 ), Organikos ( 2012 ); Smithsonian’s National Zoo and Conservation Biology Institute Smithsonian’s National Zoo ( 2016 ), and Freepik ( 2021 ). Abbreviations: FP-mode, first-pulse mode; LP-mode, last-pulse mode; DEM, digital elevation model; DTM, digital terrain model

• Remote sensing

The ability to extract information about the environment without physical contact from a large distance by a sensor that reflects and/ or emits electromagnetic spectrum (visible, infrared, and microwave spectra) is defined as remote sensing. Based on the source of radiation emitted, which comes in contact with the object, remote sensing can be categorized as active or passive remote sensing systems (Höppler et al. 2020 ). Remote sensing of biodiversity can be used for habitat mapping including species area curve and habitat heterogeneity, species mapping/distribution, plant functional diversity/ traits, spectral diversity including vegetation indices and spectral species (Cavender-Bares et al. 2020 ; Wang and Gamon 2019 ).

Active remote sensing system

An active remote sensor emits energy pulses and records the return time and amplitude of the backscattered energy pulses from the object to generate the required information about it (Vogeler and Cohen 2016 ). Currently used active remote sensing technologies like RADAR and LiDAR systems can be used to determine the location, speed, and direction of any wildlife form.

Radio detection and ranging (RADAR) system

As a sub-set of the active remote sensing system, RADAR, operates in the microwave of wavelengths of 1 mm to 1 m. Additionally, the modern RADAR systems are incorporated with software routines to mathematically enhance spatial resolution and manage multiple pictures of the same object, also as Synthetic Aperture RADARs (SARs) (Fig. 1 ). These systems can be used to determine the polarization of the emitted and receive electromagnetic rays which provides a better understanding of the analyzed surface properties (Hay 2000 ; Valbuena et al. 2020 ; Barlow and O’Neill 2020 ) (Table 2 ).

There are two basic types of RADAR systems, namely, primary and secondary. In the primary system, the signal is transmitted in all directions however some of the signals are reflected back to the receiver after colliding with the target thereby defining or detecting the location of the target (Hirst 2008 ; Bhatta and Priya 2017 ). In this system, the transmitted signal needs to be of high power to ensure that the reflected signal is sufficient enough to provide accurate and precise information about the target (Bhatta and Priya 2017 ). Again, noise and signal attenuation due to some factors might disrupt the reflected signal which can also be regarded as a limitation (Bhatta and Priya 2017 ; Martone et al. 2018 ). In the secondary RADAR system, an active answering signal system has been installed for accuracy, where the transmitted signal is received by a compatible transponder that retrieves the signal and further sends a signal comprising the useful information in a coded form (Hirst 2008 ; Bhatta and Priya 2017 ). The receiver receives the coded signal, and after decryption of the code, the information about the target is transcribed, thereby providing information about the real-time spatial orientation (Bhatta and Priya 2017 ; Jahncke et al. 2018 ).

Further to this, ultra wideband (UWB) RADAR is one of the traditional methods used for life detection that analyzes the reflected/echo signal received after hitting the target. Micro-motions by humans, nearby environment, and clutter signals can modulate the reflected signal. As per evidence, it is a reasonable, effective, and complete non-invasive life detection method (Chunming and Guoliang 2012 ; Karthikeyan and Preethi 2018 ; Yin and Zhou 2019 ). With the growth of scientific innovation in the field of remote sensing, a hybrid (On-Chip Split-Ring-Based Sensor) RADAR system has emerged with high-resolution range and sensitivity. This system can easily detect multiple life forms simultaneously even across obstacles (Liu et al. 2016 ).

One of the major applications of RADAR is range detection and to date, the replacement of the sensing and detection efficiency and accuracy by RADAR has not been possible by any other electronic system (Bhatta and Priya 2017 ; Parrens et al. 2019 ). Extension of the sensing capability with respect to atmospheric conditions such as rain, snow, smoke, darkness, and fog and collecting the data makes it unexceptional and advantageous. At present, RADARs have broad areas of applications in defense and control systems, monitoring and forecast systems, astronomy, target-locating system and remote sensing, etc. (Bhatta and Priya 2017 ).

Light detection and ranging (LiDAR) systems

LiDAR is a widely recognized technology, especially the airborne laser scanner (ALS), which focuses on the emission and receipt of laser pulses. During field surveys, LiDAR technology offers the potential to establish variables, representing forest structures that are distinct from those detected or assessed. Bitemporal airborne LiDAR with field survey is widely used for systematic assessment of uncertainties in satellite imagery-based vegetation (Ma et al. 2018 ). Ground-based field survey with airborne LiDAR is applicable for daily tracking of bats on foot-to-roost trees using various radio receivers and antennas and the location of tree cavities using directional antennas and binoculars from the ground (Carr et al. 2018 ; Stephenson 2020 ) (Fig. 1 , Table 2 ).

Unmanned aerial vehicle (UAV) camera with LiDAR data is used for surveying mangrove-inundation spatial patterns in a subtropical intertidal wetland in southeast China (Zhu et al. 2019 ). With the support of artificial intelligence (AI), LiDAR remote sensing is found to be successful in predicting models for efficient biodiversity study by covering more areas with a clear database in a very span of time. LiDAR plot extracted information and Landsat pixel-based composites along with time-series were effective in modeling sets of reflectance images of forest structure across Canada’s forest-dominated ecosystem (Matasci et al. 2018 ). More advanced LiDAR technologies have now overtaken the previous ones in terms of both efficacy and accuracy. Almeida et al. ( 2019 ) in their research on three seasonal semi-deciduous natural forest cover types in the Atlantic forest biome of Southern Brazil have considered ALS with portable ground LiDAR remote sensing as a proxy for analysis of structural hallmarks of forest canopies enduring restoration. Airborne LiDAR with principal component analysis (PCA) assessed the estimation of canopy structure and biomass of Moso bamboo ( Phyllostachys pubescens ) in widely distributed subtropical forests of south China (Cao et al. 2019 ). High-resolution vertical Scheimpflug LiDAR has proven to resolve hypothesis for insects flying over Ostra Herrestad wind farm near the town Shimrishamn in southern Sweden (Jansson et al. 2020 ).

To conserve plant diversity information on various forest attributes, aboveground biomass (AGB), canopy structure, canopy cover, and leaf area index (LAI) are considered important and can be assessed most efficiently with a technique like LiDAR (Bolton et al. 2020 ). Forest canopy height could be an important indicator of biodiversity, productivity, and carbon storage (Li et al. 2020b ). LiDAR when combined with other RS techniques, i.e., high spatial resolution with hyperspectral sensors, thermal remote sensing, and satellite RS are yielding eye-catching results, particularly in biodiversity and ecosystem conservation.

Passive remote sensing systems

Passive remote sensing is often understood as a system that operates by passive sensors which can only be used for detection in presence of the natural source of energy, i.e., sunlight (visible to shortwave spectrum and infrared thermal radiation) (Srivastava et al. 2020 ). These sensors have a specialty to detect natural energy (radiation) that is either emitted or reflected from the source of energy or object (Earthdata 2021 ). Limitations of the applicability of passive remote sensing for biodiversity and ecosystem conservation are its dependency on sunlight as a source of radiation which is again dependent completely on the season, region, and climatic conditions (Fig. 1 ).

Techniques for identification and genetic conservation of species

Restriction fragment length polymorphism (rflp).

RFLP is a biallelic, polymorphic genetic marker characterized by hybrid labeled probes of DNA fragments and digested with restriction endonucleases for estimations of genetic diversity (Vignal et al. 2002 ; Amom and Nongdam 2017 ). Different restriction sites in DNA represent the genetic divergence between different populations or related species within a population. Özdil et al. ( 2018 ) demonstrated genetic diversity among 11 donkey species in Turkey by conducting PCR-RFLP of two genes. The restriction sites of DraII, MboI, and EagI on the lactoferrin gene (LTF) and PstI on the κ-casein gene (CSN3) have been validated to identify the polymorphism among the donkey population (Özdil et al. 2018 ). Meikasari et al. ( 2019 ) have also made elucidation of low genetic diversity among the seahorse ( Hippocampus comes ) found in Bintan waters. Another recent study indicates the utilization of PCR-RFLP in genetic-based sex determination of Sebastes rockfish (Vaux et al. 2020 ). The PCR-RFLP application in identification of durum ( Triticum durum L.) and bread wheat ( T. aestivum ) species has also been studied by analyzing chloroplast DNA (Haider and Nabulsi 2020 ) (Table 3 , Fig. 2A ).

Molecular techniques for conservation of biodiversity. A Restriction fragment length polymorphism; the genomic DNA extracted from different organisms is PCR amplified and subjected to restriction digestion using specific restriction enzymes, then DNA fragments are separated by electrophoresis and hybridized with radiolabeled probes (Özdil et al. 2018 ; Chaudhary and Maurya 2019 ; Panigrahi et al. 2019 ; Haider and Nabulsi 2020 ). B Amplified fragment length polymorphism; the restriction fragments of genomic DNA was ligated with compatible adapters and PCR amplified using selective primers against adapters, and the amplified fragments were separated by electrophoresis for DNA fingerprint analysis (Blears et al. 1998 ; Malik et al. 2018 ; Wu et al. 2019b ; Zimmermann et al. 2019 ; Neiber et al. 2020 ). C Random amplified polymorphic DNA; random PCR fragments were amplified from the genome of different species using primers with random sequences and separated by gel electrophoresis to determine the difference between species based on RAPD markers (Panigrahi et al. 2019 ; Saikia et al. 2019 ). D Sequence characterized amplified region; PCR products are generated using primers for RAPD markers from the genome of different varieties and separated in the gel. The polymorphic DNA band is gel extracted and processed for cloning and sequencing for getting specific amplification by designing SCAR primers (Yang et al. 2014 ; Bhagyawant 2015 ; Ganie et al. 2015 ; Cunha and Domingues 2017 ). E Micro-satellites; the microsatellite repeats were PCR amplified using primers that flank the repeated sequence and separated by gel electrophoresis. The individual bands were cloned and sequenced for analysis of genetic and population diversity (Kim 2019 ; Touma et al. 2019 ). F Expressed sequence tag-simple sequence repeat; cDNA library was prepared from cDNA synthesized from isolated mRNAs, and then end sequencing of cDNA library was performed by EST primers followed by its assembly. The SSR regions were amplified in assembled ESTs using specific primers and the products were analyzed in gel (Rudd 2003 ; Sun et al. 2019 ; Wagutu et al. 2020 ). G Inter-simple sequence repeat; the isolated genomic DNA from organisms was subjected to PCR amplification using primers specific to microsatellite, and the PCR products were separated by electrophoresis for analysis (Sarwat 2012 ; El Hentati et al. 2019 ; Tiwari et al. 2020 ). H Single nucleotide polymorphism; the genomic DNA from different samples was digested with suitable restriction enzyme followed by adapter ligation and PCR amplification using selective primers. Further to this, PCR products were fragmented with DNase I and labeled with fluorescent probes followed by hybridization in an SNP array. The wells were scanned and data were analyzed (Alsolami et al. 2013 ; Scionti et al. 2018 ; Cendron et al. 2020 ; Kyrkjeeide et al. 2020 )

Amplified fragment length polymorphism (AFLP)

AFLP is considered an effective means of detecting polymorphism in DNA without having any prior information regarding the genome. Being a dominant marker, it can analyze multiple loci through amplification of DNA performing PCR reaction (Bryan et al. 2017 ). The method employs restriction digestion of DNA and amplification of fragments through ligation of adapters on both ends and using primers specific to adapters (Malik et al. 2018 ). Genetic differences can be identified from the disparity in the number and length of bands on electrophoretic separation. Its application ranges from the assessment of genetic diversity within species to generate of genetic maps for disease diagnosis and phylogenetic studies. AFLP data analysis study represents the genetic diversity in E. tangutorum population contributed by geographical and environmental factors (Wu et al. 2019b ). The phylogenetic relationships and genetic distances among A. platensis populations and other distinct related species such as A. georginae and A. ludwigi in southern Brazil were also investigated through AFLP (Zimmermann et al. 2019 ). Population structure and differentiation among Melanopsis etrusca were clearly distinct between the eastern, western, and central regions populations in Italy (Neiber et al. 2020 ) (Table 3 , Fig. 2B ).

Random amplified polymorphic DNA (RAPD)

The RAPD is a PCR-based technique in which 8–10 short nucleotides comprise both forward and reverse primers that bind arbitrary nucleotide sequences of chromosomal DNA to generate random fragments. Due to this random nature of primers, no prior knowledge about genome sequence is needed. The annealing sites of these random primers vary for different species or individual to individual. Discrimination can be identified or determined from the amplified DNA fragments (RAPD markers) separated by agarose gel electrophoresis (Freigoun et al. 2020 ). RAPD markers are dominant and involved in various applications such as genome mapping, molecular evolutionary genetics, genetic diversity analysis, and population genetics as well as determining taxonomic identity (Qamer et al. 2021 ). Saikia et al. ( 2019 ) deduced genetic variation among the different morphs of muga silkworm of Northeast India through RAPD analysis. Moreover, Sulistyahadi et al. ( 2020 ) studied the locus diversity as well as genetic polymorphism of the endemic species Rhacophorus margaritifer population by this technique. It has also been used to elucidate the genetic variation in a medicinal plant species found in the south of Jordan named Artemisia judaica (Al-Rawashdeh 2011 ) (Table 3 , Fig. 2C ).

Sequence characterized amplified region (SCAR)

SCAR markers are DNA fragments generated by PCR amplification using specific 15–30-bp long primers derived from RAPD markers through cloning and sequencing (Bhagyawant 2015 ). Usually, RAPD markers are associated with low reproducibility and are dominant in nature, making it inappropriate for species identification (Sairkar et al. 2016 ). To overcome this disadvantage, RAPD markers are converted to SCAR markers which are locus-specific and co-dominant in nature (Bhagyawant 2015 ; Feng et al. 2018 ). Due to the specificity of primers, PCR amplification of SCARs is less sensitive to reaction condition and thus are easy to perform (Yuskianti and Shiraishi 2010 ). SCAR markers provide authenticate information both for species identification and population genetic diversity analysis. Researchers have successfully developed SCAR markers for the medicinal plant V. serpens using 1135-bp long amplicon through RAPD obtained by six accessions of the plant, thereby preventing it from extinction (Jha et al. 2020 ) (Table 3 , Fig. 2D ).

Mini- and micro-satellites

Mini-satellites (variable number of tandem repeats (VNTRs) 6–100 bp) and micro-satellites (1–6 bp) (simple sequence repeats (SSR) and short tandem repeats (STR)) are randomly repetitive DNA sequences widely dispersed in all eukaryotic species genomes. These multi-allelic markers are co-dominantly inherited with species-specific location and size within the genome (Vergnaud and Denoeud 2000 ; Vieira et al. 2016 ). Due to the high level of polymorphism associated with mini and microsatellites, it is extensively utilized in genetic analysis and population studies. Microsatellites are interspersed all over the genome and therefore represent high variability and their identification show great variation among species of the different population (Abdul-Muneer 2014 ). Its analysis includes PCR amplification of loci by using primers that flank the repeated sequence. By using microsatellite markers, genetic structure of Agu pigs has been elucidated along with its correlation with Ryukyu wild boar, two Chinese breeds and five European breeds (Touma et al. 2019 ). Similarly, De Góes Maciel et al. ( 2019 ) analyzed 13 microsatellite loci of 361 white-lipped peccaries for assessment of their population structure and level of genetic diversity (Table 3 , Fig. 2E ).

Expressed sequence tags (ESTs)

ESTs are small sequences of DNA usually 200 to 500 nucleotides long that act as tags for the expressed genes in certain cells, tissues, or organs. ESTs are generated by sequencing either the 3′ end or 5′ end of a segment derived from random clones from the cDNA library and long enough for the identity illustration of the expressed gene (Behera et al. 2013 ). ESTs are widely involved in gene discovery, determining the phylogenetic relationship between individuals, genetic diversity, and proteomic analysis as well as transcriptome profiling (Cai et al. 2015 ). EST-derived SSR markers are more informative than genomic SSRs for genetic diversity analysis due to several advantages such as high conserved nature, variation in coding sequence, and high heritability to closely related species (Parthiban et al. 2018 ). Sun et al. ( 2019 ) have conducted the structure analyses of expressed sequence tag-simple sequence repeat (EST-SSR) markers in Juglans sigillata and demonstrated the genetic structure based on its geographic feature. Moreover, EST-SSR analyses have provided information regarding the genetic distance between the J. regia and J. sigillata populations. By considering EST-SSRs and genotype sequencing data, they have interpreted iron walnut as the subspecies of J. regia (Sun et al. 2019 ). Investigation of evolutionary relations and genotypic relatedness are essential for the conservation of endangered species. Recently the genetic variability of an endangered species Magnolia patungensis was studied by analyzing the EST-SSR polymorphic markers (Wagutu et al. 2020 ) (Table 3 , Fig. 2F ).

Inter-simple sequence repeat (ISSR)

ISSR markers are used in diversified analyses such as species identification, evolutionary and taxonomic studies, genome mapping, genetic diversity, and gene tagging because of their high polymorphic nature (Arif et al. 2011 ; Abdelaziz et al. 2020 ). These multilocus markers are generated through PCR amplification by using microsatellites as primers. Prior sequence knowledge is not required for primer designing as repeat sequence is used to amplify these inter-microsatellite regions (Ng and Tan 2015 ). It overcomes all the limitations possessed by other markers such as RAPD and AFLP which are associated with low reproducibility (Najafzadeh et al. 2014 ). Genetic diversity and population structure analysis have been performed among 11 populations of Bergenia ciliata using 15 ISSR markers. The analysis shows a high level of polymorphism among this medicinal plant species, found in the Indian Himalayan Region (Tiwari et al. 2020 ). El Hentati et al. ( 2019 ) have studied genetic diversity and phylogenetic relationships among 20 samples of three geographical local cattle populations using ISSR primers. They found a significant variation and geographical separation among the cattle from the north, northeast, and northwest of Tunisia (Table 3 , Fig. 2G ).

Single nucleotide polymorphisms (SNPs)

Single nucleotide variation in genetic sequences defines the Single nucleotide polymorphism (SNP) among individuals, generated due to point mutation or replication errors, giving rise to different alleles within a locus (Van den Broeck et al. 2014 ). SNPs are the most common form of variation present extensively in the non-coding, coding, and inter-genic regions of DNA (Vallejos-Vidal et al. 2019 ). SNPs are mainly exploited for population structure, genetic diversity, genetic map construction, and identification of particular traits, etc. (Xia et al. 2019 ). Their abundance in coding regions makes them more attractive markers for the detection of mutations associated with diseases. SNP markers are however less polymorphic than SSR markers due to their biallelic or triallelic nature (Casci 2010 ; Mammadov et al. 2012 ). Cendron et al. ( 2020 ) demonstrated the population structure and genetic diversity of local Italian chicken breeds by using SNPs for conservation purposes which revealed lower genetic diversity among the local breeds. In another study, genetic diversity and differentiation among the D. ruyschiana populations of the Norwegian region were investigated by analyzing 96 SNPs derived from 43 sites that reported the existence of four distinct genetic groups within the population (Kyrkjeeide et al. 2020 ) (Table 3 , Fig. 2H ).

Artificial intelligence in biodiversity monitoring

With the growing performance of computing power and DL in recent years, machines had become significantly more intelligent and reliable than ever. Modern machines can handle more extensive data and more complex DL models than before (Dean 2019 ; Chen et al. 2020a ). Through this progress, machines had achieved the ability to replicate human expertise (Liu et al. 2019b ). Currently, several problems exist within our diverse planet. Researchers began to accelerate the development of several AI solutions with DL to preserve the earth for the later generations to come. In most studies, DL method’s employment provided an automated capability for machines to recognize, classify, and detect images, sounds, and behavior of animals, plants, and even humans (Abeßer 2020 ). According to Klein et al. ( 2015 ), one of the primary methods of preserving our biodiversity consists of monitoring and manual data collection. However, frequent conduct of such practices can become tedious and cause disturbances to sensitive wildlife habitats. With that said, monitoring became less reliable and brief (Table 4 ). AI-based methods have shown that even at its pre-mature level, biodiversity can have an improvement by reducing animal extinction, prolonged and in-depth monitoring of various life forms, unlocking and accessing unexplored areas, and faster and easier classification of species. With the continuing efforts in data duration, transparency, and research collaborations, these technology types may reach far beyond our expectations. These solutions, if appropriately handled, can yield a massive impact to preserve the planet and its resources without involving humans. Furthermore, the implementation of AI-based methods also extends humans’ capability to explore locations that our biological composition cannot handle, leading to discoveries of new species and life. Due to the accessibility of various capture devices, a wide range of collected data through images, videos, audio, and other forms of data fast-tracked DL and AI development. The problematic method and reliance on organic experts to perform a small to large-scale monitoring of animals, plants, and insects became less challenging as automation systems have improved significantly over a short period (Bergslien 2013 ; Buxton et al. 2018 ; Willi et al. 2018 ) (Fig. 3 ).

Application of advanced computer-added physical instruments and associated smart technologies for biodiversity monitoring. The figure describes in a conserved forest ecosystem wildlife and forest ecosystem can be monitored by using autonomous acoustic recording units, animal tracking units (GIS-based), X-ray fluorescence (XRF) analyzer, global positioning system (GPS), and camera trapping units. Configuration of these data from multiple sources and data heterogeneity can be monitored, processed, interpreted, analyzed, and distributed (encrypted) via artificial intelligence and machine-learning-based technologies. Using these technologies wildlife morphology (camera), behavior, phenology, distribution, abundance, phylogeny (acoustic), and diversity with respect to human invasion can be observed. The figure is inspired by the following sources: Bergslien ( 2013 ), Buxton et al. ( 2018 ), Willi et al. ( 2018 ). The components of the figure are modifications of The RAFOS group at the Graduate School of Oceanography, University of Rhode Island, Kingston, RI 02881 ( 2001 ), Mudgineer ( 2011 ); Leapfrog ( 2021 ), Pixabay ( 2021 ), Pngtree ( 2021 ), and Vecteezy ( 2021a , b )

Recently, a wide range of low-cost yet powerful sensors, microphones, and cameras have become available, giving aid to alleviating the problem of collecting data. Such extensive data collections from the said technologies fueled DL models to learn more patterns that generated solutions to better monitor and manage biodiversity. The common uses include automated recognition, classification, and detection of people (Kim and Moon 2016 ), animals (Verma and Gupta 2018 ), plants (Saleem et al. 2019 ), fish (Jalal et al. 2020 ), and even insects (Xia et al. 2018 ) based on their sound or image (Christin et al. 2019 ). Even with DL’s promising capabilities, it still exhibits some caveats that limit its full potential in biodiversity monitoring, specifically in real time. Monitoring wildlife through video became an exponential and popular recent development that improved interpretability with less comprehension to researchers and the like (Chen et al. 2019 ). However, it became difficult and expensive due to the challenging deployment of capable computers or capture devices to perform the task (Willi et al. 2019 ). While operating with DL models in urban areas is relatively easy due to the availability of sufficient data on infrastructure, functioning in remote areas still relies on post-monitoring systems (He et al. 2016 ; Zhang et al. 2019a ).

Researchers are also on for finding more efficient data collection techniques that will require less computational cost and fewer complexes. Currently, the computer on a hardware basis still rigorously improves and becomes more affordable and independently deployable. With that said, DL can become more efficient and reliable over time that can produce real-time wildlife monitoring in remote areas through a more visual aspect like videos without much constraint from the limited infrastructure.

Challenges and future prospects

Approximately, 1 million of the 10 million species that exist in the world are threatened with extinction (Bawa et al. 2020 ). Besides monitoring tools, a combination of efforts from varied disciplines will be essential for the safeguard of individual species and biodiversity as a whole. Computer model-based technologies like the GIS, RADAR, remote sensing, and LiDAR are actively used for the monitoring of habitats, state of threats, land uses, and conversion. Molecular approaches such as Mitochondrial DNA ( Cyt b ), SNPs, RFLP, microsatellites, etc. are also playing a pivotal role in identifying, tracking, and determining the impact of anthropogenic and environmental factors on wildlife (Krestoff et al. 2021 ; Gouda et al. 2020 ; Ridley et al. 2020 ). However, many of these techniques face challenges in form of cost-efficiency and expert handling and have single or limited focal species at the ecosystem level. Some of the possible changes and prospects in biodiversity monitoring systems that can be implemented in near future on broader aspects are discussed below.

The science of chorology with advances in GIS and remote sensing techniques in recent times has better presented the landscape as a functional unit for biodiversity management. Visualizations of spatial-temporal changes and development of biotic and abiotic threats to species also known as “threat maps” emerged as multipurpose techniques for the implementation of conservation activities at the ground level (Ridley et al. 2020 ). InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) is a newly develop modeling software with set parameters for screening and quantification of ecosystem services such as carbon stock, changes in land use, landscape, forest cover, etc. SolVES is a modern-day ArcGIS-dependent tool that provides the user with easy access to several functions of the Ecosystem Services (ES), human perceptions associated with social and cultural beliefs, socio-economic values, usage of resources, etc. even without conducting questionnaires or other ground surveys of the local people and other stakeholders (Neugarten et al. 2020 ).

ARIES (ARtificial Intelligence for Ecosystem Services) is a series of algorithm processes which are generated through detecting or recognizing and keeping the track of living systems. It is a software-based platform that solves complex and arduous social or bio-geographical dimensions by integrating biodiversity data (Silvestro et al. 2022 ). It has been successfully tested for carbon emission, climate change, water levels, and ethnic/recreational values (Bagstad et al. 2018 ). Costing Nature is another easy-to-use rapid and reliable web-based technique used for screening protected areas, land use and land cover (LULC), trends of habitation, biodiversity assessment, and possible future threats using global database. It has been used for testing ES for timber, fuel wood, grazing/fodder, and non-wood forest products (Thessen 2016 ; Dominguez-Morales et al. 2021 ; Neugarten et al. 2018 ).

As rightly pointed out by Malavasi ( 2020 ), biodiversity maps are always selective and do not necessarily display all values that are known about any given region or ecosystem. They are often inevitably affected by personal views or scientific blindness and it is therefore important to strive and rate maps not only in terms of scientific accuracy but also on their “viability.” The use of Public Participation Geographic Information Systems (PPGIS) over conventional screening systems can act as a bottom-up approach to empower concern agencies about the threats and conservation priorities by providing visual tools. Similarly, the use of a counter map can prove as a possible substitute for mitigating the loss of biodiversity in a more “systemic” manner (Schägner et al. 2013 ; Malavasi 2020 ).

Genomics models and concepts are widely applied for biodiversity sustenance, from ideal seed selection for preservation to assessing the degree of impact at community-level effects. The concept of population genomics has provided valuable information on population size, demographic history, ability of the populations to evolve and adapt to the changing environment, etc. (Miraldo et al. 2016 ; Hu et al. 2020 , 2021 ; Hohenlohe et al. 2021 ). They have been able to successfully develop large sets of markers that increase the ability to detect and quantify low levels of hybridization or admixture. Techniques such as intron sequences with assistance from Transcriptome Ortholog Alignment Sequence Tools (TOASTs), Next-Generation Sequencing (NGS), and Comparative Anchor Tagged Sequences (CATs) may represent a good proxy to assess functional adaptive potential or functional diversity in future genomic studies (Forcina et al. 2021 ).

With continuous advances in technology, more precise and reliable techniques have been designed for biodiversity conservation. However, association mapping and expanding knowledge on “omics” will help in identifying morphological traits and bring together intellectual minds to a platform for developing advanced gene traits. It also helps identify high biodiversity conservation priority areas or hotspots. Working closely with international agencies like the Convention on Biological Diversity (CBD) and UN Framework Convention on Climate Change (UNFCCC) and achieving its targets will be important for the conservation of biodiversity on the planet. Lastly, it is the human who understands the importance of coexistence and cohabitation with other forms of living beings that will help implement conservation measures and create a sense of protecting the ecosystem. Therefore, it is suggested that a combination of sophisticated monitoring methods including system-based smart techniques, transformative smart technologies, remote sensing, geographical information system, and artificial intelligence in combination with molecular approaches will smartly keep the track of living organisms and will help in biodiversity conservation and restoration.

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All data generated or analyzed during this study are included in this article.

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Department of Biotechnology, Utkal University, Vani Vihar, Bhubaneswar, Odisha, 751004, India

Rout George Kerry & Sanatan Majhi

College of Informatics and Computing Sciences, Batangas State University, Batangas, Philippines

Francis Jesmar Perez Montalbo

Department of Soil Science and Agricultural Chemistry, School of Agriculture, GIET University, Gunupur, Rayagada, Odisha, 765022, India

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RGK, FJPM, RD, and SP wrote the initial draft, GPM, GKM, VN, ABJ, KEU, RCJ, and SG edited and reviewed the whole manuscript, and SM and JRR comprehensively edited the manuscript which was then reviewed and approved by all authors.

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Kerry, R.G., Montalbo, F.J.P., Das, R. et al. An overview of remote monitoring methods in biodiversity conservation. Environ Sci Pollut Res 29 , 80179–80221 (2022). https://doi.org/10.1007/s11356-022-23242-y

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Received : 10 December 2021

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Published : 05 October 2022

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DOI : https://doi.org/10.1007/s11356-022-23242-y

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