proposal penelitian research design

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base
• Starting the research process
• How to Write a Research Proposal | Examples & Templates

How to Write a Research Proposal | Examples & Templates

Published on October 12, 2022 by Shona McCombes and Tegan George. Revised on November 21, 2023.

A research proposal describes what you will investigate, why it’s important, and how you will conduct your research.

The format of a research proposal varies between fields, but most proposals will contain at least these elements:

Introduction

Literature review.

• Research design

Reference list

While the sections may vary, the overall objective is always the same. A research proposal serves as a blueprint and guide for your research plan, helping you get organized and feel confident in the path forward you choose to take.

Table of contents

Research proposal purpose, research proposal examples, research design and methods, contribution to knowledge, research schedule, other interesting articles, frequently asked questions about research proposals.

Academics often have to write research proposals to get funding for their projects. As a student, you might have to write a research proposal as part of a grad school application , or prior to starting your thesis or dissertation .

In addition to helping you figure out what your research can look like, a proposal can also serve to demonstrate why your project is worth pursuing to a funder, educational institution, or supervisor.

Research proposal length

The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.

One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.

Download our research proposal template

Prevent plagiarism. Run a free check.

Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We’ve included a few for you below.

• Example research proposal #1: “A Conceptual Framework for Scheduling Constraint Management”
• Example research proposal #2: “Medical Students as Mediators of Change in Tobacco Use”

Like your dissertation or thesis, the proposal will usually have a title page that includes:

• The proposed title of your project
• Your supervisor’s name
• Your institution and department

The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.

Your introduction should:

• Introduce your topic
• Give necessary background and context
• Outline your  problem statement  and research questions

To guide your introduction , include information about:

• Who could have an interest in the topic (e.g., scientists, policymakers)
• How much is already known about the topic
• What is missing from this current knowledge
• What new insights your research will contribute
• Why you believe this research is worth doing

As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review  shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have already done or said, but rather using existing research as a jumping-off point for your own.

In this section, share exactly how your project will contribute to ongoing conversations in the field by:

• Comparing and contrasting the main theories, methods, and debates
• Examining the strengths and weaknesses of different approaches
• Explaining how will you build on, challenge, or synthesize prior scholarship

Following the literature review, restate your main  objectives . This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.

To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.

For example, your results might have implications for:

• Improving best practices
• Informing policymaking decisions
• Strengthening a theory or model
• Challenging popular or scientific beliefs
• Creating a basis for future research

Last but not least, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use our free APA citation generator .

Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.

Here’s an example schedule to help you get started. You can also download a template at the button below.

Download our research schedule template

If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.

Make sure to check what type of costs the funding body will agree to cover. For each item, include:

• Cost : exactly how much money do you need?
• Justification : why is this cost necessary to complete the research?
• Source : how did you calculate the amount?

To determine your budget, think about:

• Travel costs : do you need to go somewhere to collect your data? How will you get there, and how much time will you need? What will you do there (e.g., interviews, archival research)?
• Materials : do you need access to any tools or technologies?
• Help : do you need to hire any research assistants for the project? What will they do, and how much will you pay them?

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.

Methodology

• Sampling methods
• 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

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.

A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.

A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.

All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.

Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.

Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. & George, T. (2023, November 21). How to Write a Research Proposal | Examples & Templates. Scribbr. Retrieved April 9, 2024, from https://www.scribbr.com/research-process/research-proposal/

Is this article helpful?

Shona McCombes

Other students also liked, how to write a problem statement | guide & examples, writing strong research questions | criteria & examples, how to write a literature review | guide, examples, & templates, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

Research Design 101

Everything You Need To Get Started (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental . 

Descriptive Research Design

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

Need a helping hand?

Experimental Research Design

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological Research Design

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

You Might Also Like:

Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology

Research Design | Step-by-Step Guide with Examples

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

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

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

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

Table of contents

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

• Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

Prevent plagiarism, run a free check.

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

Types of quantitative research designs

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

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

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

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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

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

Operationalisation

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

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

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

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

Reliability and validity

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

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

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

Sampling procedures

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

That means making decisions about things like:

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

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

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

Data management

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

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

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

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

Quantitative data analysis

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

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

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

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

Using inferential statistics , you can:

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

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

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

Qualitative data analysis

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

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

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

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

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

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

Operationalisation means turning abstract conceptual ideas into measurable observations.

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

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

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, March 20). Research Design | Step-by-Step Guide with Examples. Scribbr. Retrieved 9 April 2024, from https://www.scribbr.co.uk/research-methods/research-design/

Is this article helpful?

Shona McCombes

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Types of Research Designs
• 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
• Applying Critical Thinking
• 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?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

Introduction

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

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

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

General Structure and Writing Style

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

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

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

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

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

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

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

Action Research Design

Definition and Purpose

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

What do these studies tell you ?

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

What these studies don't tell you ?

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

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

Case Study Design

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

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

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

Causal Design

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

Conditions necessary for determining causality:

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

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

Cohort Design

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

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

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

Cross-Sectional Design

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

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

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

Descriptive Design

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

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

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

Experimental Design

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

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

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

Exploratory Design

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

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

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

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

Field Research Design

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

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

What these studies don't tell you

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

Historical Design

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

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

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

Longitudinal Design

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

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

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

Meta-Analysis Design

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

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

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

Mixed-Method Design

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

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

Observational Design

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

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

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

Philosophical Design

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

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

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

Sequential Design

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

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

Systematic Review

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

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

• << Previous: Purpose of Guide
• Next: Design Flaws to Avoid >>
• Last Updated: Apr 9, 2024 1:19 PM
• URL: https://libguides.usc.edu/writingguide

• How it works

How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 3, 2023

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the  research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

• Data type required for research
• Research resources
• Participants required for research
• Hypothesis based upon research question(s)
• Data analysis  methodologies
• Variables (Independent, dependent, and confounding)
• The location and timescale for conducting the data
• The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and  interpretation techniques.  A strong research design reflects a strong  dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a  dissertation analyzing different situations or cases will have more than one research design.

For example:

• Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
• Quantitative research is good for the  statistical part of the project, but it may not provide an in-depth understanding of the  topic .
• Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

• Do you have enough time to gather data and complete the write-up?
• Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
• Do you have in-depth knowledge about the  different statistical analysis and data collection techniques to address the research questions  or test the  hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative vs. quantitative data.

Also, see; Research methods, design, and analysis .

Need help with a thesis chapter?

• Hire an expert from ResearchProspect today!
• Statistical analysis, research methodology, discussion of the results or conclusion – our experts can help you no matter how complex the requirements are.

Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the  research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your  dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the  correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results  and  conclusion .

Read our guidelines to write a research proposal  if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The  research methodology  or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to  formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

You May Also Like

Find how to write research questions with the mentioned steps required for a perfect research question. Choose an interesting topic and begin your research.

How to write a hypothesis for dissertation,? A hypothesis is a statement that can be tested with the help of experimental or theoretical research.

Not sure how to approach a company for your primary research study? Don’t worry. Here we have some tips for you to successfully gather primary study.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

• Privacy Policy

Buy Me a Coffee

Home » How To Write A Research Proposal – Step-by-Step [Template]

How To Write A Research Proposal – Step-by-Step [Template]

Table of Contents

How To Write a Research Proposal

Writing a Research proposal involves several steps to ensure a well-structured and comprehensive document. Here is an explanation of each step:

1. Title and Abstract

• Choose a concise and descriptive title that reflects the essence of your research.
• Write an abstract summarizing your research question, objectives, methodology, and expected outcomes. It should provide a brief overview of your proposal.

2. Introduction:

• Provide an introduction to your research topic, highlighting its significance and relevance.
• Clearly state the research problem or question you aim to address.
• Discuss the background and context of the study, including previous research in the field.

3. Research Objectives

• Outline the specific objectives or aims of your research. These objectives should be clear, achievable, and aligned with the research problem.

4. Literature Review:

• Conduct a comprehensive review of relevant literature and studies related to your research topic.
• Summarize key findings, identify gaps, and highlight how your research will contribute to the existing knowledge.

5. Methodology:

• Describe the research design and methodology you plan to employ to address your research objectives.
• Explain the data collection methods, instruments, and analysis techniques you will use.
• Justify why the chosen methods are appropriate and suitable for your research.

6. Timeline:

• Create a timeline or schedule that outlines the major milestones and activities of your research project.
• Break down the research process into smaller tasks and estimate the time required for each task.

7. Resources:

• Identify the resources needed for your research, such as access to specific databases, equipment, or funding.
• Explain how you will acquire or utilize these resources to carry out your research effectively.

8. Ethical Considerations:

• Discuss any ethical issues that may arise during your research and explain how you plan to address them.
• If your research involves human subjects, explain how you will ensure their informed consent and privacy.

9. Expected Outcomes and Significance:

• Clearly state the expected outcomes or results of your research.
• Highlight the potential impact and significance of your research in advancing knowledge or addressing practical issues.

10. References:

• Provide a list of all the references cited in your proposal, following a consistent citation style (e.g., APA, MLA).

11. Appendices:

• Include any additional supporting materials, such as survey questionnaires, interview guides, or data analysis plans.

Research Proposal Format

The format of a research proposal may vary depending on the specific requirements of the institution or funding agency. However, the following is a commonly used format for a research proposal:

1. Title Page:

• Include the title of your research proposal, your name, your affiliation or institution, and the date.

2. Abstract:

• Provide a brief summary of your research proposal, highlighting the research problem, objectives, methodology, and expected outcomes.

3. Introduction:

• Introduce the research topic and provide background information.
• State the research problem or question you aim to address.
• Explain the significance and relevance of the research.
• Review relevant literature and studies related to your research topic.
• Summarize key findings and identify gaps in the existing knowledge.
• Explain how your research will contribute to filling those gaps.

5. Research Objectives:

• Clearly state the specific objectives or aims of your research.
• Ensure that the objectives are clear, focused, and aligned with the research problem.

6. Methodology:

• Describe the research design and methodology you plan to use.
• Explain the data collection methods, instruments, and analysis techniques.
• Justify why the chosen methods are appropriate for your research.

7. Timeline:

8. Resources:

• Explain how you will acquire or utilize these resources effectively.

9. Ethical Considerations:

• If applicable, explain how you will ensure informed consent and protect the privacy of research participants.

10. Expected Outcomes and Significance:

11. References:

12. Appendices:

Research Proposal Template

Here’s a template for a research proposal:

1. Introduction:

2. Literature Review:

3. Research Objectives:

4. Methodology:

5. Timeline:

6. Resources:

7. Ethical Considerations:

8. Expected Outcomes and Significance:

9. References:

10. Appendices:

Research Proposal Sample

Title: The Impact of Online Education on Student Learning Outcomes: A Comparative Study

1. Introduction

Online education has gained significant prominence in recent years, especially due to the COVID-19 pandemic. This research proposal aims to investigate the impact of online education on student learning outcomes by comparing them with traditional face-to-face instruction. The study will explore various aspects of online education, such as instructional methods, student engagement, and academic performance, to provide insights into the effectiveness of online learning.

2. Objectives

The main objectives of this research are as follows:

• To compare student learning outcomes between online and traditional face-to-face education.
• To examine the factors influencing student engagement in online learning environments.
• To assess the effectiveness of different instructional methods employed in online education.
• To identify challenges and opportunities associated with online education and suggest recommendations for improvement.

3. Methodology

3.1 Study Design

This research will utilize a mixed-methods approach to gather both quantitative and qualitative data. The study will include the following components:

3.2 Participants

The research will involve undergraduate students from two universities, one offering online education and the other providing face-to-face instruction. A total of 500 students (250 from each university) will be selected randomly to participate in the study.

3.3 Data Collection

The research will employ the following data collection methods:

• Quantitative: Pre- and post-assessments will be conducted to measure students’ learning outcomes. Data on student demographics and academic performance will also be collected from university records.
• Qualitative: Focus group discussions and individual interviews will be conducted with students to gather their perceptions and experiences regarding online education.

3.4 Data Analysis

Quantitative data will be analyzed using statistical software, employing descriptive statistics, t-tests, and regression analysis. Qualitative data will be transcribed, coded, and analyzed thematically to identify recurring patterns and themes.

4. Ethical Considerations

The study will adhere to ethical guidelines, ensuring the privacy and confidentiality of participants. Informed consent will be obtained, and participants will have the right to withdraw from the study at any time.

5. Significance and Expected Outcomes

This research will contribute to the existing literature by providing empirical evidence on the impact of online education on student learning outcomes. The findings will help educational institutions and policymakers make informed decisions about incorporating online learning methods and improving the quality of online education. Moreover, the study will identify potential challenges and opportunities related to online education and offer recommendations for enhancing student engagement and overall learning outcomes.

6. Timeline

The proposed research will be conducted over a period of 12 months, including data collection, analysis, and report writing.

The estimated budget for this research includes expenses related to data collection, software licenses, participant compensation, and research assistance. A detailed budget breakdown will be provided in the final research plan.

8. Conclusion

This research proposal aims to investigate the impact of online education on student learning outcomes through a comparative study with traditional face-to-face instruction. By exploring various dimensions of online education, this research will provide valuable insights into the effectiveness and challenges associated with online learning. The findings will contribute to the ongoing discourse on educational practices and help shape future strategies for maximizing student learning outcomes in online education settings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

How To Write A Proposal – Step By Step Guide...

Grant Proposal – Example, Template and Guide

How To Write A Business Proposal – Step-by-Step...

Business Proposal – Templates, Examples and Guide

Proposal – Types, Examples, and Writing Guide

How to choose an Appropriate Method for Research?

• Profil Usaha
• Daftar Menerbitkan Buku
• Kirim Naskah
• Cek Progess Buku
• Cek Royalti Buku
• Kerjasama Net Promoter
• Jasa Parafrase
• Jasa Pengurusan HAKI
• Konsultasi Menulis
• Kerjasama Workshop
• Program Reseller
• Promo Khusus Penulis Deepublish
• Dasar Menulis
• Cara Menerbitkan Buku
• Memasarkan Buku
• Teknik Menulis
• Writing Advice
• Writing Tools
• (NEW 2024) Kunci Sukses Publikasi
• (NEW 2024) Menulis dengan Etika untuk Hindari Plagiarisme
• (PREMIUM) Cara Praktis Menulis Buku
• (NEW) Sukses Menulis Buku Referensi
• (NEW) Panduan Ringkas Menulis Buku Monograf
• Panduan Menulis Buku Ajar (Versi Cepat Paham)
• Rahasia Menulis Buku Ajar
• Self Publishing
• Pedoman Menulis Buku Tanpa Plagiarisme

Home » Desain Penelitian: Pengertian, Jenis, dan Contoh

Desain Penelitian: Pengertian, Jenis, dan Contoh

• Maret 30, 2023
• No Comments

Agar penelitian bisa berjalan sesuai dengan pedoman dan tidak menyimpang, maka desain penelitian merupakan salah satu strategi yang bisa dilakukan. Dengan adanya desain penelitian, tujuan penelitian bisa lebih mudah dicapai

Kita dapat menerapkan desain penelitian mana yang paling cocok digunakan untuk penelitian, baik penelitian kualitatif atau kuantitatif . Pada artikel ini kita akan membahas seputar desain penelitian. Jika kamu mencari informasi yang sama, maka baca artikel selengkapnya! 

Mau menulis buku ajar tapi takut salah? Jadikan panduan ini pedoman dan Anda bisa mulai menulis buku ajar sekarang dengan benar! EBOOK GRATIS! : Panduan Menulis Buku Ajar (Versi Cepat Paham)

Apa Itu Desain Penelitian?

Mari bahas pengertian desain penelitian terlebih dahulu. Desain penelitian adalah rangkaian prosedur dan metode yang dipakai untuk menganalisis dan menghimpun data untuk menentukan variabel yang akan menjadi topik penelitian. 

Desain penelitian juga didefinisikan sebagai strategi yang dilakukan peneliti untuk menghubungkan setiap elemen penelitian dengan sistematis sehingga dalam menganalisis dan menentukan fokus penelitian menjadi lebih efektif dan efisien.

Masalah pada sebuah penelitian akan menentukan jenis apa yang cocok untuk dipilih. Hal tersebut juga menentukan alat dan cara apa yang cocok digunakan untuk mengatasi masalah dalam penelitian.

Desain Penelitian Menurut Para Ahli

Berikut pengertian desain penelitian menurut para ahli:

1. Silaen (2018) 

Menurut Silaen, desain penelitian adalah desain mengenai keseluruhan proses yang diperlukan dalam perencanaan dan pelaksanaan penelitian.

2. Umar (2007)

Menurut para ahli, desain penelitian dapat diartikan sebagai suatu rencana kerja yang terstruktur dalam hal hubungan-hubungan antara variabel secara komprehensif agar hasil risetnya dapat memberikan jawaban atas pertanyaan-pertanyaan riset.

Rencana tersebut mencakup hal-hal yang akan dilakukan preset, mulai dari membuat hipotesis dan implikasinya secara operasional sampai analisis akhir 

3. Nachmias dan Nachmias (1976)

Menurut Nachmias dan Nachmias, desain penelitian merupakan suatu rencana yang membimbing peneliti dalam proses pengumpulan, analisis, dan interpretasi observasi. Maksudnya, suatu model pembuktian logis yang memungkinkan peneliti untuk mengambil inferensi mengenai hubungan kausal antar variabel di dalam suatu penelitian.

4 Jenis Desain Penelitian

Pemilihan jenis desain penelitian didasari oleh tujuan penelitian yang akan dilakukan. Terdapat empat jenis desain penelitian yang kerap digunakan, diantaranya:

1. Desain Penelitian Eksperimental

Sesuai namanya, desain penelitian eksperimental berarti peneliti sedang melakukan penelitian eksperimental. Menurut Arifin (2009:127), penelitian eksperimen diartikan sebagai penelitian yang di dalamnya melibatkan manipulasi terhadap kondisi subjek yang diteliti, disertai upaya kontrol yang ketat terhadap faktor-faktor luar serta melibatkan subjek pembanding atau metode ilmiah yang sistematis yang dilakukan untuk membangun hubungan yang melibatkan fenomena sebab akibat.

Desain penelitian eksperimen ditentukan oleh bagaimana cara peneliti mengatur subjek ke dalam kondisi dan kelompok yang berbeda. Terdapat tiga jenis desain penelitian eksperimen, yaitu pre-eksperimental, quasi-eksperimental, dan true experimental research.

a. Desain Penelitian Pre-eksperimental

Pada desain penelitian pre-eksperimental, baik satu atau berbagai kelompok variabel terikat diamati untuk mengetahui ada tidaknya pengaruh dari aplikasi suatu variabel bebas yang sebelumnya dianggap dapat menyebabkan perubahan. Desain ini merupakan yang desain penelitian eksperimen yang paling sederhana dan tidak terdapat kelompok kontrol. Lebih lanjut lagi, desain pre-eksperimental dibagi menjadi tiga, yaitu:

1) One-shot Case Study Research Design

Dalam penelitian eksperimen jenis ini, hanya ada satu kelompok variabel terikat yang dipertimbangkan. Penelitiannya dilakukan setelah memberikan beberapa perlakuan yang sebelumnya dianggap menimbulkan perubahan, sehingga desain ini merupakan suatu posttest study.

2) One-group Pretest-posttest Research Design

Desain penelitian ini mengkombinasikan posttest dan pretest study dengan mengadakan suatu tes pada satu kelompok sebelum diberi perlakuan dan setelah diberikan perlakuan. Pretest dilakukan pada awal penelitian dan posttest diberikan saat penelitian selesai.

3) Static-group Comparison

Pada desain ini, 2 atau lebih kelompok diberikan pengawasan, dimana hanya ada satu kelompok yang diberi perlakuan. Kelompok sisanya dibiarkan statis tanpa diberi perlakuan khusus. Semua kelompok yang ada kemudian diberikan posttest, kemudian adanya perbedaan yang tampak diantara kelompok-kelompok tersebut diasumsikan sebagai hasil dari perlakuan yang diberikan.

b. Desain Penelitian Quasi-eksperimental

Kata “quasi” memiliki arti parsial, setengah, atau pseudo (palsu). Sehingga penelitian quasi-eksperimental memiliki kemiripan dengan true experimental research, tetapi tidak sama. Pada quasi-eksperimen, partisipan tidak dipilih secara acak, sehingga desain penelitian ini digunakan pada kondisi dimana randomisasi sulit atau tidak mungkin dilakukan.

c. True Experimental Research Design

Desain penelitian ini bergantung pada analisis statistik untuk menerima atau menolak hipotesis. True experimental research design merupakan desain penelitian eksperimen yang paling akurat dan dapat dilakukan dengan atau tanpa pretest pada paling tidak 2 kelompok subjek variabel terikat yang dipilih secara acak.

True experimental research design harus memiliki kelompok kontrol, variabel yang dapat dimanipulasi oleh peneliti, dan distribusinya harus secara acak atau random. Klasifikasi dari true experimental research design meliputi:

1) The Posttest-only Control Group Design

Desain ini memilih subjek secara acak atau random dan dikelompokkan menjadi 2 kelompok (kontrol dan eksperimental), dan hanya kelompok eksperimental yang diberi perlakuan. Setelah observasi mendalam, kedua kelompok diberi post-test, dan suatu kesimpulan diambil dari perbedaan yang terjadi di antara kedua kelompok.

2) The Pretest-posttest Control Group Design

Pada desain kelompok kontrol ini, subjek dipilih dan dibagi menjadi 2 kelompok secara acak, kemudian kedua kelompok diberi pretest, namun hanya kelompok eksperimental yang diberikan perlakuan. Di akhir penelitian, kedua kelompok diberi post-test untuk mengukur derajat perubahan di tiap kelompok.

3) Solomon Four-group Design

Desain ini merupakan kombinasi dari pretest-only dan pretest-posttest control groups. Dalam desain ini, subjek yang telah dipilih secara acak atau random ditempatkan menjadi 4 kelompok. Dua kelompok pertama diuji menggunakan metode posttest-only, sementara dua kelompok yang lain diuji menggunakan metode pretest-posttest.

2. Desain Penelitian Survey

Penelitian survei adalah penelitian yang dilakukan pada populasi besar maupun kecil, tetapi data yang dipelajari adalah data dari sampel yang diambil dari populasi tersebut, untuk menemukan kejadian-kejadian relatif, distribusi, dan hubungan-hubungan antar variabel sosiologis maupun psikologis.

Menurut para ahli, terdapat beberapa desain penelitian survey, yaitu desain pembagian silang atau cross sectional design dan desain survey berkepanjangan atau longitudinal survey (Widodo, 2008), sample survey, dan sensus survei (Irawan Soehartono, 2000). Dengan demikian desain penelitian survey di antaranya adalah sebagai berikut.

a. Cross Sectional Survey

Desain penelitian silang atau cross sectional survey digunakan untuk mengetahui isu-isu yang bersifat temporer melalui pengumpulan data yang dilakukan satu kali saja. Desain jenis ini paling banyak digunakan oleh peneliti.

Desain penelitian berkepanjangan atau longitudinal survey digunakan untuk memahami suatu isu secara berkelanjutan. Populasi yang digunakan dalam desain ini tidaklah banyak. Adapun pengambilan data dilakukan secara berkala. Desain jenis ini dibedakan atas kajian kecenderungan atau trend studies, studi panel atau panel studies, sosiometrik, dan desain kontekstual atau contextual design. 

b. Sample Survey

Sample survey adalah survey yang dilakukan pada sebagian populasi atau sampel.

c. Sensus Survey

Sensus survey adalah survey yang dilakukan pada seluruh populasi.

3. Desain Penelitian Longitudinal

Penelitian longitudinal merupakan penelitian yang menggunakan data dengan rentang waktu yang panjang. Berapa lamakah panjang waktu yang dimaksud bersifat sangat relatif. Namun, penekanan riset longitudinal sebenarnya pada ekstensi atau perpanjangan dari survey yang dilakukan. Perpanjangan tersebut bersifat periodik.

Jadi, penelitian longitudinal dapat pula dipahami sebagai perpanjangan penelitian survey yang bersifat periodik. Sedikitnya, survey dilakukan dua kali dengan rentang waktu yang ditentukan dari awal. Teknik pengumpulan data penelitian ini biasanya menggunakan kuesioner atau interview terstruktur. 

Desain penelitiannya pun tidak jauh berbeda dengan penelitian lain seperti survey. Sebagai contoh, kita akan melakukan penelitian tentang perubahan karakteristik kekerasan pemuda di suatu kota yang kerap terjadi tawuran.

Untuk melakukan riset longitudinal, pertama-tama kita melakukan survey dengan kuesioner dan atau wawancara terhadap anak muda yang terpilih sebagai sampel. Identitas partisipan atau anak muda tersebut kita catat baik-baik dan disimpan dengan rapi di dalam arsip. Survey pertama dilakukan dengan variabel yang telah disusun matang.

Riset ini menggunakan rentang waktu yang jelas. Misalnya, setiap lima tahun kita mendatangi anak muda yang sama untuk dilihat perubahan atau perkembangan dalam karakteristiknya. Tak ada ketentuan berapa kali partisipan didatangi kembali untuk disurvey, namun biasanya sedikitnya dua kali mereka disurvey kembali.

Hasil survei kedua, ketiga dan seterusnya akan memperlihatkan perubahan apa yang terjadi pada anak muda tersebut yang barangkali di survey yang ketiga dan seterusnya bukan lagi tergolong anak muda. Dengan desain penelitian ini, perubahan karakteristik kekerasan sebagaimana yang menjadi fokus penelitian sangat mungkin diketahui.

4. Desain Penelitian Studi Kasus

Studi kasus menjadi metode paling sesuai untuk fase penyelidikan dari sebuah penelitian karena mengedepankan survey dan proses historis sebagai jalan untuk penjelasan yang bersifat sebab musabab (kausalitas). Meskipun demikian, metode studi kasus hanya merupakan persiapan metode penelitian dan tidak dapat digunakan untuk menggambarkan atau menguji suatu masalah.

Kriteria penetapan desain penelitian studi kasus sangat berpengaruh terhadap suatu penelitian. Demikian juga untuk penelitian studi kasus. Kriteria kualitas desain penelitian berkaitan dengan:

• Validitas konstruk yakni menetapkan ukuran operasional yang benar untuk konsep-konsep yang akan diteliti. Dalam studi kasus, dapat digunakan teknik multi sumber bukti, memberikan kesempatan kepada informan kunci untuk meninjau kembali draft laporan studi kasus yang bersangkutan.
• Validitas internal merupakan hubungan sebab-akibat, dimana kondisi-kondisi tertentu diperhatikan guna mengarahkan kondisi-kondisi lain, untuk membedakan dari hubungan semu.
• Validitas eksternal yaitu menetapkan ranah dimana temuan suatu penelitian dapat divisualisasikan.
• Reliabilitas  yaitu bahwa suatu penelitian seperti prosedur pengumpulan data dapat diinterpretasikan dengan hasil yang sama pada waktu yang berbeda.
• Desain penelitian komparatif

Menurut Menurut Robert K. Yin, desain penelitian studi kasus secara umum menjadi 2 (dua) jenis, yaitu penelitian studi kasus dengan menggunakan kasus tunggal dan jamak/ banyak. Disamping itu, ia juga mengelompokkannya berdasarkan jumlah unit analisisnya, yaitu (1) penelitian studi kasus tunggal holistik (holistic) yang menggunakan satu unit analisis.(2) Desain kasus tunggal terjalin (embedded) yang menggunakan beberapa atau banyak unit analisis. 

Penelitian studi kasus disebut terpancang (embedded), karena terikat (terpancang) pada unit-unit analisisnya yang telah ditentukan. Perbedaan antara penelitian studi kasus holistik (jenis 1) dan terpancang (jenis 2) adalah pada jumlah unit analisis yang digunakan.

Contoh Desain Penelitian

1. penelitian kualitatif.

Penelitian deskriptif kualitatif ditujukan untuk mendeskripsikan dan menggambarkan fenomena-fenomena yang ada, baik bersifat alamiah maupun rekayasa manusia, yang lebih memperhatikan mengenai karakteristik, kualitas, keterkaitan antar kegiatan. Selain itu, Penelitian deskriptif tidak memberikan perlakuan, manipulasi atau pengubahan pada variabel-variabel yang diteliti, melainkan menggambarkan suatu kondisi yang apa adanya. 

Seperti contoh penelitian sebagai berikut ini: 

Judul penelitian: Mengeksplor fenomena kejujuran di SD Negeri 3 Purwodadi, Kabupaten Banyumas

Satu-satunya perlakuan yang diberikan hanyalah penelitian itu sendiri, yang dilakukan melalui observasi, wawancara, dan dokumentasi. Berdasarkan keterangan dari beberapa ahli di atas, dapat ditarik kesimpulan bahwa penelitian deskriptif kualitatif yaitu rangkaian kegiatan untuk memperoleh data yang bersifat apa adanya tanpa ada dalam kondisi tertentu yang hasilnya lebih menekankan makna. Di sini, peneliti menggunakan metode penelitian deskriptif kualitatif karena penelitian ini

mengeksplor fenomena proses pembentukan karakter peserta didik melalui penyelenggaraan kantin kejujuran di SD Negeri 3 Purwodadi Kecamatan Tambak Kabupaten Banyumas. Selain itu penelitian ini juga bersifat induktif dan hasilnya lebih menekankan makna.

2. Penelitian Eksperimen

Eksperimen dalam penelitian sosial sering digunakan untuk menemukan aspek penyebab atau penyebab fenomena sosial. Seringkali desain eksperimental digunakan sebagai dasar untuk mengimplementasikan suatu program atau kebijakan.

Misalnya, sebagai contoh sederhana dari penelitian eksperimental, peneliti ingin mengetahui efektivitas penggunaan sistem alarm rokok di ruang publik untuk mengurangi konsumsi rokok di tempat umum. Beberapa ruang publik dibangun menjadi rokok, yang lain dengan fitur yang sama tidak dilengkapi dengan alarm rokok.

Eksperimen ini akan menunjukkan hasil seberapa efektif alarm rokok dapat mengurangi konsumsi rokok di tempat umum.

3. Penelitian Kuantitatif

Desain penelitian kuantitatif membuat proyek eksperimental lebih bebas. Maka peneliti sosial umumnya menerapkan desain eksperimental untuk melakukan penelitian kuantitatif. Penelitian kuantitatif bisa dipergunakan guna membandingkan kelompok yang diperlakukan sebagai subjek eksperimen dan kontrol.

Misalnya, percobaan konsumsi vitamin C untuk meningkatkan daya tahan siswa. Beberapa subjek diminta untuk mengonsumsi vitamin C, yang lain tidak memiliki kelompok kontrol. Hasilnya adalah hasil percobaan.

Dalam pembuatan makalah ilmiah juga ada yang namanya penerapan metode penelitian. Dengan metode penelitian yang bagus, maka makalah ilmiah pun juga bisa terwujud dengan kualitas yang tinggi.

Berbicara mengenai metode penelitian makalah, sebenarnya dalam hal ini sama saja dengan metode yang digunakan pada karya ilmiah secara umum. Termasuk yang sudah disinggung dalam poin sebelumnya. Jadi, di dalamnya bisa menggunakan metode penelitian dengan pendekatan kualitatif maupun kuantitatif. Hanya saja mayoritas contoh makalah menggunakan metode kualitatif.

Selain pendekatan secara umum tersebut, dalam makalah juga biasa menerapkan metode penelitian karya ilmiah pada umumnya. Sebagaimana disebutkan di atas, yakni seperti metode deskriptif dan eksperimen. Jika kasusnya berkaitan dengan fenomena sosial pun bisa mengusung metode penelitian sosial. Dan ketiga metode tersebut selanjutnya akan dibahas secara lebih detail lagi.

Pertanyaan Seputar Desain Penelitian :

Menurut Silaen, desain penelitian adalah desain mengenai keseluruhan proses yang diperlukan dalam perencanaan dan pelaksanaan penelitian. Ketahui definisi desain penelitian menurut para ahli lainnya di artikel ini!

Desain penelitian terdapat 4 jenis, yaitu desain penelitian eksperimental, desain penelitian survey, desain penelitian longitudinal, dan desain penelitian studi kasus. Setiap jenis tersebut terbagi menjadi berbagai jenis lagi. Baca selengkapnya di artikel!

Artikel Terkait:

Instrumen Penelitian

Hipotesis Penelitian 

Pendekatan Penelitian

Responden Penelitian 

Jenis Dat a Penelitian

Tahukah Anda bahwa salah satu cara untuk meningkatkan poin KUM adalah menerbitkan buku. Aturan ini tertuang dalam PO PAK 2019.

Sayangnya, kesibukan dalam mengajar, membuat dosen lupa dengan kewajiban lainnya yaitu mengembangkan karir. Maka dari itu, Penerbit Deepublish hadir untuk membantu para dosen meningkatkan poin KUM dengan menerbitkan buku .

Kunjungi halaman Daftar Menerbitkan Buku , agar konsultan kami dapat segera menghubungi Anda.

Selain itu, kami juga mempunyai E-book Gratis Panduan Menerbitkan Buku yang bisa membantu Anda dalam menyusun buku. Berikut pilihan Ebook Gratis yang bisa Anda dapatkan:

• Download Ebook Gratis : Cara Praktis Menulis Buku (Premium!)
• Download Ebook Gratis : Sukses Menulis Buku Referensi (Baru!)
• Download Ebook Gratis: Strategi Jitu Menulis Buku Monograf (Baru!)
• Download Ebook Gratis: Pedoman Pengisian SISTER (Baru!)
• Download Ebook Gratis: Self Publishing
• Download Ebook Gratis: Rahasia Menulis Buku Ajar
• Download Ebook Gratis: Pedoman Menulis Buku tanpa Plagiarisme
• Download Ebook Gratis: Panduan Menulis Buku Ajar (Versi Cepat Paham)

Mau menulis tapi waktu Anda terbatas?

Gunakan saja layanan parafrase konversi.

Cukup siapkan naskah penelitian (skripsi, tesis, disertasi, artikel ilmiah atau naskah lainnya), kami akan mengonversikan jadi buku yang berpeluang memperoleh nomor ISBN!

Tinggalkan Balasan Batalkan balasan

Alamat email Anda tidak akan dipublikasikan. Ruas yang wajib ditandai *

Simpan nama, email, dan situs web saya pada peramban ini untuk komentar saya berikutnya.

Dapatkan informasi terbaru dari kami seputar promo spesial dan event yang akan datang

Penerbit Deepublish adalah penerbit buku yang memfokuskan penerbitannya dalam bidang pendidikan, pernah meraih penghargaan sebagai Penerbit Terbaik pada Tahun 2017 oleh Perpustakaan Nasional Republik Indonesia (PNRI).

Kritik/Saran Pelayanan  : 0811-  2846 – 130

• Menerbitkan Buku
• Pengadaan Buku
• Reseller Buku
• Mitra Net Promoter

Alamat Kantor

Jl.Rajawali G. Elang 6 No 3 RT/RW 005/033, Drono, Sardonoharjo, Ngaglik, Sleman, D.I Yogyakarta 55581

Telp/Fax kantor : (0274) 283-6082

E1 Marketing : [email protected] E2 Marketing : [email protected]

• Online Submissions
• Focus and Scope
• Editorial Board
• Peer Review Process
• Review Guidelines
• Author Guidelines
• Section Policies
• Publication Frequency
• Open Access Policy
• Publication Ethics
• Reference Management
• Plagiarism Screening
• Copyright Notice
• Privacy Statement
• Template (.doc)

Dikdaya Statistics

• Announcements

Konsep Perancangan dan Penyusunan Proposal Penelitian

Abdillah, M., Rodoni, A., Saepudin, D., Muslimin, J., Matin, U. A., Kamarusdiana, & Kusmana. (2018). Pedoman Penulisan Tesis dan Disertasi Program Magister dan Doktor. SPs UIN Syarif

Hidayatullah Jakarta.

Ghodang, H., & Hantono. (2020). Metode Penelitian Kuantitatif; Konsep Dasar & Aplikasi Analisis Regresi dan Jalur dengan SPSS. Penerbit Mitra Group.

Hani, A. A. (2019). Evaluasi Pembelajaran Pada PAUD. Jurnal Care, 7(1), 54.

Hermawan, I. (2019). Teknis Menulis Karya Ilmiah Berbasis Aplikasi dan Metodologi. Hidayatul Quran.

Hidayat, A. (2021). Menulis Narasi Kreatif dengan Model Project Based Learning dan Musik Instrumental Teori dan Praktik di Sekolah Dasar. Deepublish.

Kamayanti, A. (2021). Metodologi Penelitian Kualitatif Akuntansi: Pengantar Religiositas Keilmuan (edisi revisi). Penerbit Peneleh.

Maha, R. N., & Tupan. (2019). Analisis Referensi Pada Jurnal Ilmu Dan Teknologi Kayu Tropis Tahun 2013 – 2017. Baca: Jurnal Dokumentasi Dan Informasi, 40(1), 114.

Maharani, S., Susilowati, I., & Wahyono, S. R. (2020). Sitasi Ilmiah dan Penggunaan References Tool Manager. BuatBuku.com.

Mardawani. (2020). Praktis Penelitian Kualitatif; Teori Dasar dan Analisis Data dalam Perspektif Kualitatif. Deepublish.

Munadi, A. (2022). Belajar Menulis Bersama Guru Blogger Indonesia; Sebuah Catatan Belajar Menulis Di Kelas Online Guru Blogger Indonesia. Lakeisha.

Nasution, A. R. S. (2021). Identifikasi Permasalahan Penelitian. Alacrity: Journal of Education, 1(2), 13.

Nirmala, D., & Hendro, E. P. (2021). Petunjuk Praktis Perumusan Masalah Penelitian Kebahasaan Bagi Pemula. Jurnal Harmoni, 5(2), 52.

Nurmasitah, S., Achmad, U., Prasetyaningtyas, W., & Fatati, F. (2017). Pengembangan Model Pembelajaran Penyusunan Proposal Penelitian untuk Meningkatkan Keterampilan Penulisan Karya Ilmiah Mahasiswa. Teknoboga: Jurnal Teknologi Busana Dan Boga, 5(2), 66–73.

Oktoma, E., & Amalia, D. R. (2018). . Strategi Menulis Yang Digunakan oleh Mahasiswa dalam Esai Argumentatif. FON: Jurnal Pendidikan Bahasa Dan Sastra Indonesia, 12(1), 39.

Prajawinanti, A. (2020). Pemanfaatan buku oleh mahasiswa sebagai penunjang aktivitas akademik di era generasi milenial. Pustaka Karya, 8(1), 29.

Rahmawati, I. (2022). Pengantar Psikologi Sosial. Bumi Aksara.

Ramadhan, M. (2021). Metode Penelitian. Cipta Media Nusantara.

Ridha, N. (2017). Proses Penelitian, Masalah, Variabel, dan Paradigma Penelitian. Jurnal Hikmah, 14(1),

Sani, R. A. (2020). Kiat Menulis Karya Ilmiah Berkualitas. Intelegensia Media.

Silaswati, D. (2018). Pentingnya Penentuan Topik dalam Penulisan Karya Ilmiah pada Bidang Ilmu Akuntansi. Akurat: Jurnal Ilmiah Akuntansi, 9(1), 84.

Slameto. (2015). Penyusunan Proposal Penelitian Tindakan Kelas. Jurnal Scholaria, 5(2), 60–69.

Suadi, A. (2017). Penyelesaian Sengketa Ekonomi Syariah; Teori dan Praktik. Kencana.

Sugiarti, & Andalas, E. F. (2022). Prosa; Dari Teori, Rancangan, Hingga Penulisan Artikel Ilmiah. UMM Press.

Supriadi, I. (2020). Metode Riset Akuntansi. Deepublish.

Trygu. (2020). Study Literatur Problem Based Learning untuk masalah Motivasi bagi siswa dalam Belajar Matematika. Guepedia.

Wahyujati, B. B. (2022). Metode Perancangan; Rangkuman Teori dan Aplikasi. Sanata Dharma University Press.

Yasa, I. N. P., & Wiguna, I. G. N. H. (2020). Kewirausahaan Theopreneurship; Teori dan Kiat menjadi Wirausaha. Rajawali Press.

Zaifullah, Cikka, H., & Kahar, M. I. (2021). Strategi Guru dalam Meningkatkan Interaksi dan Minat Belajar terhadap Keberhasilan Peserta Didik dalam Menghadapi Pembelajaran Tatap Muka di Masa Pandemi Covid 19. Guru Tua: Jurnal Pendidikan Dan Pembelajaran, 4(2), 9

• There are currently no refbacks.

Desain Penelitian: Pengertian, Macam dan Contoh

Desain penelitian merupakan sebuah rute atau jalannya penelitian supaya berjalan dengan lancar sesuai dengan tujuan akhirnya. Kok bisa? Mending baca pengertian desain penelitian, macam-macam dan contoh untuk skripsi, paper atau tesis dalam artikel ini.

Desain penelitian tersebut menjadi strategi keberhasilan suatu penelitian mulai dari proses hingga setelah penelitian selesai. Dengan adanya desain penelitian, maka penelitian dapat berjalan dengan lancar dan tujuan dari penelitian tersebut bisa didapatkan dengan baik.

Desain penelitian ini juga harus dirancang sesuai dengan penelitian yang akan dilaksanakan sehingga ada keterkaitan dan berhubungan satu sama lain.

Akan tetapi, apa sebenarnya desain penelitian itu mulai dari pengertian desain penelitian, desain penelitian menurut para ahli, bagaimana macam-macam desain penelitian, hingga contoh desain penelitian akan dijelaskan secara terperinci di bawah ini.

Pengertian Desain Penelitian

Desain penelitian dilakukan sebelum peneliti melakukan tahapan atau proses penelitian. Pengertian desain penelitian merupakan rangkaian dari prosedur dan juga metode yang digunakan untuk menganalisis dan juga menghimpun berbagai data untuk menentukan variabel yang akan menjadi topik penelitian.

Desain penelitian juga dapat diartikan sebagai sebuah strategi yang dilakukan seorang peneliti untuk menghubungkan setiap elemen di dalam penelitian dan dilakukan dengan sistematis sehingga dalam menganalisis dan juga menentukan desainnya, fokus penelitian menjadi lebih efektif dan juga efisien.

Sehingga dilakukannya desain penelitian ini adalah menentukan jenis apakah yang kira-kira cocok untuk dipilih di dalam penelitian yang akan dilakukan, termasuk di dalamnya menentukan berbagai alat dan juga cara apa yang cocok digunakan untuk mengatasi berbagai permasalahan yang mungkin muncul di dalam suatu penelitian.

Desain penelitian juga menjadi strategi tepat yang dipilih oleh seorang peneliti untuk sepenuhnya dapat mengintegrasikan berbagai komponen penelitian dengan cara yang logis dan juga sistematis sehingga saat membahas atau menganalisis apa yang terjadi di dalam penelitian menjadi logis dan juga efektif dan menjadi pusat penelitian yang baik.

Dapat dipahami bahwa desain penelitian ini sebagai jembatan untuk mengintegrasikan berbagai komponen penelitian, mulai dari proyek penelitian dan seluruh komponen penelitian yang diperlukan, mulai dari pertanyaan penelitian, jenis data, metode, dan juga analisis yang harus dilakukan oleh peneliti.

Tujuan dilakukannya desain penelitian ini adalah agar peneliti mampu menentukan proyek penelitian yang baik dan sesuai. Biasanya, desain penelitian ini lebih sering digunakan di dalam jenis penelitian kuantitatif. Akan tetapi tidak menutup kemungkinan bahwa bisa dilakukan dan diterapkan pada penelitian kuantitatif.

Desain Penelitian Menurut Para Ahli

Untuk memahami lebih dalam, desain penelitian juga memiliki pengertian tersendiri menurut para ahli. Para ahli di bidang yang relevan tentu memiliki pandangannya masing-masing mengenai apa itu pengertian dari desain penelitian. Di bawah ini merupakan beberapa ahli yang memiliki pendapat mengenai pengertian dari desain penelitian.

1. Sukardi (2004: 183)

Menurut Sukardi, desain penelitian merupakan semua proses yang diperlukan dalam perencanaan dan pelaksanaan penelitian. Dalam konteks ini, komponen desain dapat mencakup semua struktur penelitian yang diawali sejak ditemukannya ide sampai diperoleh hasil penelitian.

Sementara itu, Sukardi juga mengungkapkan pengertian desain penelitian secara arti sempit yaitu desain penelitian adalah penggambaran secara jelas tentang hubungan antara variabel, pengumpulan data, dan juga analisis data,.

Sehingga dengan desain yang baik, peneliti maupun orang lain yang berkepentingan mempunyai gambaran tentang bagaimana keterkaitan antar-variabel dan bagaimana mengukurnya.

2. Nursalam (2003: 81)

Nursalam (2003), menyatakan bahwa desain penelitian adalah suatu strategi untuk mencapai tujuan penelitian yang telah ditetapkan dan berperan sebagai pedoman atau penuntun peneliti pada seluruh proses penelitian.

3. Sarwono (2006)

Sarwono (2006) memberikan penjelasan, desain penelitian bagaikan sebuah peta jalan bagi peneliti yang menuntun serta menentukan arah berlangsungnya proses penelitian secara benar dan tepat sesuai dengan tujuan yang telah ditetapkan.

Tanpa desain yang benar, seorang peneliti tidak akan dapat melakukan penelitian dengan baik karena yang bersangkutan tidak mempunyai pedoman arah yang jelas.

4. Umar (2007: 6)

Umar mengungkapkan bahwa desain penelitian dapat diartikan sebagai suatu rencana kerja yang terstruktur dalam hal hubungan-hubungan antara variabel secara komprehensif yang sedemikian rupa, agar hasil risetnya dapat memberikan jawaban atas pertanyaan-pertanyaan riset.

Berbagai rencana tersebut mencakup hal-hal yang akan dilakukan preset, mulai dari membuat hipotesis dan juga implikasinya secara operasional sampai analisis akhir yang dilakukan.

5. Silaen (2018: 23)

Menurut Silaen, desain penelitian merupakan desain mengenai keseluruhan proses yang diperlukan dalam perencanaan dan juga pelaksanaan penelitian.

6. Nachmias dan Nachmias (1976)

Nachmias dan Nachmias mengungkapkan bahwa desain penelitian adalah suatu rencana yang membimbing penelitian dalam proses pengumpulan, analisis, dan interpretasi observasi.

Artinya, suatu model pembuktian logis yang memungkinkan peneliti untuk dapat mengambil inferensi mengenai hubungan kausal antar-variabel di dalam suatu penelitian.

7. Green dan Tull

Green danTull berpendapat bahwa desain penelitian adalah spesifikasi teknik dan proses untuk mendapatkan informasi yang diperlukan. Ini adalah keseluruhan pola definisi operasional atau kerangka kerja proyek yang menyatakan data apa yang akan dikumpulkan dari sumber mana dan dengan proses seperti apa.

8. Saunders (2012)

Saunders mengungkapkan bahwa desain penelitian adalah rencana umum untuk menjawab pertanyaan penelitian. Sebagai pendekatan sistematis untuk melakukan penyelidikan ilmiah, desain penelitian akan menyatukan beberapa komponen, strategi, dan juga metode untuk mengumpulkan dan menentukan teknik analisis data.

9. McCombes (2019)

McCombes mengungkapkan bahwa desain penelitian atau yang juga disebut strategi penelitian adalah rencana untuk menjawab serangkaian pertanyaan penelitian. Pada bagian ini adalah kerangka kerja yang mencakup metode dan prosedur yang mengumpulkan, menganalisis, dan menafsirkan data.

Rekomendasi Buku Metode Penelitian (PROMO)

Dapatkan buku pendukung skripsi & penelitian lainnya di Buku penelitian

Macam-Macam Desain Penelitian

Desain penelitian dibagi menjadi beberapa kategori yang dibagi berdasarkan tujuan dari penelitian tersebut dilakukan.

Ada 4 macam desain penelitian yang bisa digunakan, yaitu desain penelitian eksperimental, desain studi kasus, penelitian longitudinal dan penelitian survei.

1. Desain Penelitian Eksperimental

Desain eksperimental ini diterapkan pada peneliti yang melakukan penelitian eksperimental. Menurut Arifin (2009), penelitian eksperimental merupakan penelitian yang di dalamnya melibatkan manipulasi terhadap kondisi subjek yang diteliti serta adanya upaya kontrol yang ketat terhadap berbagai faktor luar yang melibatkan subjek pembanding.

Desain penelitian eksperimental dijadikan sebuah metode ilmiah yang sistematis dan dilakukan untuk membangun hubungan yang melibatkan fenomena sebab-akibat. Selain itu, desain penelitian eksperimental ini juga ditentukan oleh bagaimana cara peneliti dapat mengatur subjek ke dalam kondisi dan juga kelompok yang berbeda.

Oleh sebab itu, desain pada penelitian eksperimental ini dibagi lagi menjadi tiga kelompok.

a. Desain Penelitian Pre-Eksperimental

Desain penelitian pre-eksperimental baik dari satu atau berbagai kelompok variabel terikat diamati untuk dapat mengetahui ada atau tidaknya pengaruh dari suatu aplikasi dari variabel bebas yang sebelumnya dianggap dapat atau menyebabkan perubahan. Sehingga desain ini menjadi desain penelitian eksperimental yang paling sederhana dan tidak memiliki kelompok kontrol.

Desain penelitian pre-eksperimental ini dibagi lagi menjadi tiga jenis, yaitu:

• One-shot Case Study Research Design. Hanya ada satu kelompok variabel terikat yang dipertimbangkan dan dilakukan setelah memberi perlakukan yang dianggap menimbulkan perubahan.
• One-group Pretest-posttest Research Design . Mengkombinasikan posttest dan pretest study dengan mengadakan suatu tes pada satu kelompok sebelum diberi perlakuan dan setelah diberi perlakukan.
• Static-group Comparison . Ada 2 lebih atau kelompok diberikan pengawasan dan hanya ada satu kelompok yang diberikan perlakuan, sementara kelompok lainnya dibiarkan statis.

b. True Experimental Research Design

Penelitian ini bergantung terhadap bagaimana analisis statistik untuk menerima atau menolak suatu hipotesis. True experimental research design menjadi desain penelitian eksperimen yang paling akurat dan juga dapat dilakukan dengan atau tanpa pretest pada paling tidak 2 kelompok subjek variabel terikat yang dipilih secara acak.

Penelitian ini harus memiliki kelompok kontrol dan juga variabel yang dapat dimanipulasi oleh peneliti dan distribusinya harus secara acak. Ada pun di bawah ini merupakan beberapa klasifikasi dari desain penelitian, yaitu:

• The Posttest-only Control Group Design . Desain yang memilih subjek secara acak dan kemudian dikelompokkan menjadi 2 kelompok, namun hanya kelompok eksperimental yang diberi perlakuan.
• The Pretest-posttest Control Group Design . Subjek dipilih dan dibagi menjadi 2 kelompok secara acak dan dua kelompok diberikan pretest , tetapi hanya ada satu kelompok yang diberi perlakuan.
• Solomon Four-group Design . Kombinasi dari pretest-only dan pretest-posttest control group yang subjeknya dipilih secara acak dan dibagi menjadi 4 kelompok.

c. Desain Penelitian Quasi-Eksperimental

Penelitian quasi-eksperimental ini memiliki kemiripan dengan true experimental research . Akan tetapi, pada quasi-eksperimen ini, partisipan tidak dipilih secara acak, sehingga desain penelitian ini digunakan pada kondisi yang random atau sulit bahkan tidak mungkin dilakukan.

Nah, makanya disini penting untuk mendalami mengenai penelitian terdahulu. Apa itu? pahami dalam artikel Membuat Penelitian Terdahulu .

2. Desain Penelitian Studi Kasus

Desain penelitian ini paling sesuai untuk metode penelitian yaitu fase penyelidikan atau studi kasus karena mengutamakan survei dan proses historis sebagai jalan untuk menjelaskan sebab dan kausalitas.

Meski begitu, metode ini hanya merupakan persiapan metode penelitian dan tidak dapat digunakan untuk menggambarkan atau menguji suatu masalah.

3. Desain Penelitian Longitudinal

Desain penelitian ini menggunakan data dengan rentang waktu yang paling panjang akan tetapi sifatnya tetap relatif. Meski demikian, diperlukan penekanan terhadap riset longitudinal yang dilakukan pada ekstensi atau perpanjangan dari survei yang dilakukan dan perpanjangannya sendiri bersifat periodik.

Sehingga desain ini dapat dipahami sebagai proses perpanjangan penelitian survei yang sifatnya periodik dan dapat dilakukan survei dua kali tergantung rentang waktu yang ditentukan dari awal menggunakan teknik pengumpulan data baik kuesioner maupun interview terstruktur.

Langkah pertama yang harus dilakukan dalam metode ini adalah melakukan survei dengan kuesioner atau wawancara untuk mendapat identitas dan kemudian dilakukan riset dengan variabel yang sudah disusun matang. Selanjutnya, dilakukan riset dengan rentang waktu yang jelas, tetapi tidak ada ketentuan berapa kali partisipan harus disurvei kembali.

Dan setelah dilakukan beberapa kali survei, maka terjadi perubahan karakteristik yang kemudian menjadi fokus penelitian dalam desain penelitian longitudinal.

4. Desain Penelitian Survei

Desain penelitian survei dilakukan pada populasi yang besar atau kecil dan datanya diambil dari sampel yang diambil dari populasi yang ada untuk menemukan berbagai kejadian yang relatif, distribusi, dan hubungan antara berbagai variabel sosiologis maupun psikologis.

Desain penelitian ini dibagi menjadi dua yaitu desain penelitian silang dan juga survei berkepanjangan.

Contoh Desain Penelitian

Dalam menyelesaikan penelitian ini, peneliti menggunakan pendekatan deskriptif. Artinya, data yang dikumpulkan bukan berupa data angka, melainkan data yang berasal dari naskah wawancara, catatan lapangan, dokumen pribadi, catatan atau memo peneliti dan dokumen resmi lain yang mendukung.

Tujuan menggunakan pendekatan kualitatif adalah agar peneliti dapat menggambarkan realita empiris di balik fenomena yang terjadi terkait dengan peran Dinas Kebudayaan Pariwisata dan Olahraga Kabupaten Kulon Progo dalam mengembangkan potensi pariwisata di daerahnya secara mendalam, rinci dan tuntas.

Pertimbangan peneliti menggunakan penelitian kualitatif ini sebagaimana yang diungkapkan oleh Lexy Moleong (2010 : 138).

• Menyesuaikan metode kualitatif lebih mudah apabila berhadapan dengan kenyataan ganda.
• Metode ini menyajikan secara langsung hakikat hubungan antara peneliti dan responden.
• Metode ini lebih peka dan menyesuaikan diri dengan manajemen pengaruh bersama terhadap pola-pola nilai yang dihadapi. 

Adapun jenis penelitian yang digunakan adalah penelitian deskriptif. Di sini peneliti mencari fakta tentang bagaimana peran Dinas Kebudayaan Pariwisata Pemuda dan Olahraga dalam pengembangan potensi pariwisata di Kabupaten Kulon Progo dengan interpretasi yang tepat, serta akan mempelajari masalah yang terjadi di lapangan.

Termasuk didalamnya adalah kegiatan, pandangan, sikap, serta proses yang berlangsung dalam pengembangan potensi pariwisata yang dilakukan oleh Dinas Kebudayaan Pariwisata Pemuda dan Olahraga.

• Skripsi Kuantatif
• Kerangka Teori Penelitian
• Cara Review Jurnal

Pertanyaan umum mengenai desain penelitian

Desain penelitian skripsi merupakan sebuah alur dan jalan kerja untuk melakukan penelitian supaya proses dalam menyelesaikan penelitian bisa sesuai dengan tujuan skripsi yang diangkat.

Rekomendasi Buku Penunjang SKRIPSI (Spesial)

Tinggalkan komentar Batalkan balasan

Simpan nama, email, dan situs web saya pada peramban ini untuk komentar saya berikutnya.

Got any suggestions?

We want to hear from you! Send us a message and help improve Slidesgo

Top searches

Trending searches

solar eclipse

25 templates

12 templates

north korea

7 templates

21 templates

48 templates

Research Presentation templates

Customize our free themes and templates for google slides or powerpoint and explain what your research is about. these designs are easy to edit, so that will speed things up.

Formal Research Paper Slideshow

Have you seen these slides? They are perfect for presenting your research paper! First of all, because we have included all the necessary sections of this type of work, such as hypothesis, objectives, methodology, analysis and the conclusions of the paper. The second reason is that the formal style will...

Premium template

Unlock this template and gain unlimited access

Research Project Proposal

Before embarking yourself on a new project, especially if it’s about research, you need to set out a proposal to explain its viability. Here at Slidesgo we’re offering this theme that you can actually use for any kind of project, regardless of the topic.

Nursing Capstone

In medical contexts, a capstone is often the final course in a nursing degree, a project of vital importance. It’s very demanding, so if you need help with the presentation, use this free professional template. Leave the design to us and focus on your data!

Economics Thesis

If numbers, exchange rates, money and trading are your forte, odds are you’re already working on an economics thesis for your master’s degree. Defending your dissertation is the last step and the most difficult one, but Slidesgo can help you. Here’s our new free presentation template with a focus on...

Final Year Project Thesis Defense

Download the Final Year Project Thesis Defense presentation for PowerPoint or Google Slides. Congratulations, you have finally finished your research and made it to the end of your thesis! But now comes the big moment: the thesis defense. You want to make sure you showcase your research in the best...

Project Research Infographics

Download the Project Research Infographics template for PowerPoint or Google Slides and discover the power of infographics. An infographic resource gives you the ability to showcase your content in a more visual way, which will make it easier for your audience to understand your topic. Slidesgo infographics like this set...

Vein Diseases: Obstructive Venous Syndrome - Clinical Case

Download the Vein Diseases: Obstructive Venous Syndrome - Clinical Case presentation for PowerPoint or Google Slides. A clinical case is more than just a set of symptoms and a diagnosis. It is a unique story of a patient, their experiences, and their journey towards healing. Each case is an opportunity...

Medical Collaboration Research

Download the Medical Collaboration Research presentation for PowerPoint or Google Slides. Healthcare goes beyond curing patients and combating illnesses. Raising awareness about diseases, informing people about prevention methods, discussing some good practices, or even talking about a balanced diet—there are many topics related to medicine that you could be sharing...

Pediculosis

Download the Pediculosis presentation for PowerPoint or Google Slides. Taking care of yourself and of those around you is key! By learning about various illnesses and how they are spread, people can get a better understanding of them and make informed decisions about eating, exercise, and seeking medical attention. This...

Endometrial Cancer Detection Breakthrough

Download the Endometrial Cancer Detection Breakthrough presentation for PowerPoint or Google Slides. Treating diseases involves a lot of prior research and clinical trials. But whenever there’s a new discovery, a revolutionary finding that opens the door to new treatments, vaccines or ways to prevent illnesses, it’s great news. Should there...

AP Research Defense for High School

AP, or Advanced Placement, is a North American educational program that offers a rigorous course designed to challenge and prepare high school students for their future careers and academic pursuits. It requires students to conduct independent research, write a lengthy academic paper, and present their findings to a panel of...

Cycle Diagrams Theme for a Medical Breakthrough

Download the Cycle Diagrams Theme for a Medical Breakthrough presentation for PowerPoint or Google Slides.Treating diseases involves a lot of prior research and clinical trials. But whenever there’s a new discovery, a revolutionary finding that opens the door to new treatments, vaccines or ways to prevent illnesses, it’s great news....

Data Analysis for Marketing Strategies

With the amount of data available through various digital platforms, it's easier than ever to determine the trends and preferences of your target audience. By collecting and analyzing data, marketers can create highly personalized campaigns that align with the exact needs and wants of their customers. If you're trying to...

Immunological Disorders Case Report

Download the Immunological Disorders Case Report presentation for PowerPoint or Google Slides. A clinical case is more than just a set of symptoms and a diagnosis. It is a unique story of a patient, their experiences, and their journey towards healing. Each case is an opportunity for healthcare professionals to...

Elegant Black & White Thesis Defense

Present your research findings with grace and assertiveness through this template. Available for Google Slides and PowerPoint, this design set offers minimalistic charm with its simple, gray scale elegance. The template not only provides a polished platform to showcase your thesis but also ensures seamless and efficient delivery of your...

Pregnancy Breakthrough

Giving birth to a baby is a beautiful occasion, a manifestation of love between two people. Obstetrics are key during pregnancy, so how about giving a presentation about the latest breakthrough in this field? Our free medical template will come in handy.

Research Methods Lesson

If you deal with Science, it’s important to learn more about research methods. Teach your students about them with this presentation full of illustrations and drawings related to labs. Use graphs, maps, tables and overview diagrams to support your lecture in a visual way!

SWOT Analysis Infographics

Discover the strengths, weaknesses, opportunities and threats of your own company performing a SWOT analysis. Use this basic strategic planning to evaluate your position with these new infographics created by Slidesgo.

• Page 1 of 79

New! Make quick presentations with AI

Slidesgo AI presentation maker puts the power of design and creativity in your hands, so you can effortlessly craft stunning slideshows in minutes.

Register for free and start editing online