what is research project simple definition

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What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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The What: Defining a research project

During Academic Writing Month 2018, TAA hosted a series of #AcWriChat TweetChat events focused on the five W’s of academic writing. Throughout the series we explored The What: Defining a research project ; The Where: Constructing an effective writing environment ; The When: Setting realistic timeframes for your research ; The Who: Finding key sources in the existing literature ; and The Why: Explaining the significance of your research . This series of posts brings together the discussions and resources from those events. Let’s start with The What: Defining a research project .

Before moving forward on any academic writing effort, it is important to understand what the research project is intended to understand and document. In order to accomplish this, it’s also important to understand what a research project is. This is where we began our discussion of the five W’s of academic writing.

Q1: What constitutes a research project?

According to a Rutgers University resource titled, Definition of a research project and specifications for fulfilling the requirement , “A research project is a scientific endeavor to answer a research question.” Specifically, projects may take the form of “case series, case control study, cohort study, randomized, controlled trial, survey, or secondary data analysis such as decision analysis, cost effectiveness analysis or meta-analysis”.

Hampshire College offers that “Research is a process of systematic inquiry that entails collection of data; documentation of critical information; and analysis and interpretation of that data/information, in accordance with suitable methodologies set by specific professional fields and academic disciplines.” in their online resource titled, What is research? The resource also states that “Research is conducted to evaluate the validity of a hypothesis or an interpretive framework; to assemble a body of substantive knowledge and findings for sharing them in appropriate manners; and to generate questions for further inquiries.”

TweetChat participant @TheInfoSherpa , who is currently “investigating whether publishing in a predatory journal constitutes blatant research misconduct, inappropriate conduct, or questionable conduct,” summarized these ideas stating, “At its simplest, a research project is a project which seeks to answer a well-defined question or set of related questions about a specific topic.” TAA staff member, Eric Schmieder, added to the discussion that“a research project is a process by which answers to a significant question are attempted to be answered through exploration or experimentation.”

In a learning module focused on research and the application of the Scientific Method, the Office of Research Integrity within the U.S. Department of Health and Human Services states that “Research is a process to discover new knowledge…. No matter what topic is being studied, the value of the research depends on how well it is designed and done.”

Wenyi Ho of Penn State University states that “Research is a systematic inquiry to describe, explain, predict and control the observed phenomenon.” in an online resource which further shares four types of knowledge that research contributes to education, four types of research based on different purposes, and five stages of conducting a research study. Further understanding of research in definition, purpose, and typical research practices can be found in this Study.com video resource .

Now that we have a foundational understanding of what constitutes a research project, we shift the discussion to several questions about defining specific research topics.

Q2: When considering topics for a new research project, where do you start?

A guide from the University of Michigan-Flint on selecting a topic states, “Be aware that selecting a good topic may not be easy. It must be narrow and focused enough to be interesting, yet broad enough to find adequate information.”

Schmieder responded to the chat question with his approach.“I often start with an idea or question of interest to me and then begin searching for existing research on the topic to determine what has been done already.”

@TheInfoSherpa added, “Start with the research. Ask a librarian for help. The last thing you want to do is design a study thst someone’s already done.”

The Utah State University Libraries shared a video that “helps you find a research topic that is relevant and interesting to you!”

Q2a: What strategies do you use to stay current on research in your discipline?

The California State University Chancellor’s Doctoral Incentive Program Community Commons resource offers four suggestions for staying current in your field:

• Become an effective consumer of research
• Read key publications
• Attend key gatherings
• Develop a network of colleagues

Schmieder and @TheInfoSherpa discussed ways to use databases for this purpose. Schmieder identified using “journal database searches for publications in the past few months on topics of interest” as a way to stay current as a consumer of research.

@TheInfoSherpa added, “It’s so easy to set up an alert in your favorite database. I do this for specific topics, and all the latest research gets delivered right to my inbox. Again, your academic or public #librarian can help you with this.” To which Schmieder replied, “Alerts are such useful advancements in technology for sorting through the myriad of material available online. Great advice!”

In an open access article, Keeping Up to Date: An Academic Researcher’s Information Journey , researchers Pontis, et. al. “examined how researchers stay up to date, using the information journey model as a framework for analysis and investigating which dimensions influence information behaviors.” As a result of their study, “Five key dimensions that influence information behaviors were identified: level of seniority, information sources, state of the project, level of familiarity, and how well defined the relevant community is.”

Q3: When defining a research topic, do you tend to start with a broad idea or a specific research question?

In a collection of notes on where to start by Don Davis at Columbia University, Davis tells us “First, there is no ‘Right Topic.’”, adding that “Much more important is to find something that is important and genuinely interests you.”

Schmieder shared in the chat event, “I tend to get lost in the details while trying to save the world – not sure really where I start though. :O)” @TheInfoSherpa added, “Depends on the project. The important thing is being able to realize when your topic is too broad or too narrow and may need tweaking. I use the five Ws or PICO(T) to adjust my topic if it’s too broad or too narrow.”

In an online resource , The Writing Center at George Mason University identifies the following six steps to developing a research question, noting significance in that “the specificity of a well-developed research question helps writers avoid the ‘all-about’ paper and work toward supporting a specific, arguable thesis.”

• Choose an interesting general topic
• Do some preliminary research on your general topic
• Consider your audience
• Start asking questions
• Evaluate your question
• Begin your research

USC Libraries’ research guides offer eight strategies for narrowing the research topic : Aspect, Components, Methodology, Place, Relationship, Time, Type, or a Combination of the above.

Q4: What factors help to determine the realistic scope a research topic?

The scope of a research topic refers to the actual amount of research conducted as part of the study. Often the search strategies used in understanding previous research and knowledge on a topic will impact the scope of the current study. A resource from Indiana University offers both an activity for narrowing the search strategy when finding too much information on a topic and an activity for broadening the search strategy when too little information is found.

The Mayfield Handbook of Technical & Scientific Writing identifies scope as an element to be included in the problem statement. Further when discussing problem statements, this resource states, “If you are focusing on a problem, be sure to define and state it specifically enough that you can write about it. Avoid trying to investigate or write about multiple problems or about broad or overly ambitious problems. Vague problem definition leads to unsuccessful proposals and vague, unmanageable documents. Naming a topic is not the same as defining a problem.”

Schmieder identified in the chat several considerations when determining the scope of a research topic, namely “Time, money, interest and commitment, impact to self and others.” @TheInfoSherpa reiterated their use of PICO(T) stating, “PICO(T) is used in the health sciences, but it can be used to identify a manageable scope” and sharing a link to a Georgia Gwinnett College Research Guide on PICOT Questions .

By managing the scope of your research topic, you also define the limitations of your study. According to a USC Libraries’ Research Guide, “The limitations of the study are those characteristics of design or methodology that impacted or influenced the interpretation of the findings from your research.” Accepting limitations help maintain a manageable scope moving forward with the project.

Q5/5a: Do you generally conduct research alone or with collaborative authors? What benefits/challenges do collaborators add to the research project?

Despite noting that the majority of his research efforts have been solo, Schmieder did identify benefits to collaboration including “brainstorming, division of labor, speed of execution” and challenges of developing a shared vision, defining roles and responsibilities for the collaborators, and accepting a level of dependence on the others in the group.

In a resource on group writing from The Writing Center at the University of North Carolina at Chapel Hill, both advantages and pitfalls are discussed. Looking to the positive, this resource notes that “Writing in a group can have many benefits: multiple brains are better than one, both for generating ideas and for getting a job done.”

Yale University’s Office of the Provost has established, as part of its Academic Integrity policies, Guidance on Authorship in Scholarly or Scientific Publications to assist researchers in understanding authorship standards as well as attribution expectations.

In times when authorship turns sour , the University of California, San Francisco offers the following advice to reach a resolution among collaborative authors:

• Address emotional issues directly
• Elicit the problem author’s emotions
• Acknowledge the problem author’s emotions
• Express your own emotions as “I feel …”
• Set boundaries
• Try to find common ground
• Get agreement on process
• Involve a neutral third party

Q6: What other advice can you share about defining a research project?

Schmieder answered with question with personal advice to “Choose a topic of interest. If you aren’t interested in the topic, you will either not stay motivated to complete it or you will be miserable in the process and not produce the best results from your efforts.”

For further guidance and advice, the following resources may prove useful:

• 15 Steps to Good Research (Georgetown University Library)
• Advice for Researchers and Students (Tao Xie and University of Illinois)
• Develop a research statement for yourself (University of Pennsylvania)

Whatever your next research project, hopefully these tips and resources help you to define it in a way that leads to greater success and better writing.

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How to do a research project for your academic study

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Writing a research report is part of most university degrees, so it is essential you know what one is and how to write one. This guide on how to do a research project for your university degree shows you what to do at each stage, taking you from planning to finishing the project.

What is a research project? 

The big question is: what is a research project? A research project for students is an extended essay that presents a question or statement for analysis and evaluation. During a research project, you will present your own ideas and research on a subject alongside analysing existing knowledge. 

How to write a research report 

The next section covers the research project steps necessary to producing a research paper. 

Developing a research question or statement 

Research project topics will vary depending on the course you study. The best research project ideas develop from areas you already have an interest in and where you have existing knowledge. 

The area of study needs to be specific as it will be much easier to cover fully. If your topic is too broad, you are at risk of not having an in-depth project. You can, however, also make your topic too narrow and there will not be enough research to be done. To make sure you don’t run into either of these problems, it’s a great idea to create sub-topics and questions to ensure you are able to complete suitable research. 

A research project example question would be: How will modern technologies change the way of teaching in the future? 

Finding and evaluating sources 

Secondary research is a large part of your research project as it makes up the literature review section. It is essential to use credible sources as failing to do so may decrease the validity of your research project.

Examples of secondary research include:

• Peer-reviewed journals
• Scholarly articles
• Newspapers 

Great places to find your sources are the University library and Google Scholar. Both will give you many opportunities to find the credible sources you need. However, you need to make sure you are evaluating whether they are fit for purpose before including them in your research project as you do not want to include out of date information. 

When evaluating sources, you need to ask yourself:

• Is the information provided by an expert?
• How well does the source answer the research question?
• What does the source contribute to its field?
• Is the source valid? e.g. does it contain bias and is the information up-to-date?

It is important to ensure that you have a variety of sources in order to avoid bias. A successful research paper will present more than one point of view and the best way to do this is to not rely too heavily on just one author or publication. 

Conducting research 

For a research project, you will need to conduct primary research. This is the original research you will gather to further develop your research project. The most common types of primary research are interviews and surveys as these allow for many and varied results. 

Examples of primary research include: 

• Interviews and surveys 
• Focus groups 
• Experiments 
• Research diaries 

If you are looking to study in the UK and have an interest in bettering your research skills, The University of Sheffield is a  world top 100 research university  which will provide great research opportunities and resources for your project. 

Research report format  

Now that you understand the basics of how to write a research project, you now need to look at what goes into each section. The research project format is just as important as the research itself. Without a clear structure you will not be able to present your findings concisely. 

A research paper is made up of seven sections: introduction, literature review, methodology, findings and results, discussion, conclusion, and references. You need to make sure you are including a list of correctly cited references to avoid accusations of plagiarism. 

Introduction 

The introduction is where you will present your hypothesis and provide context for why you are doing the project. Here you will include relevant background information, present your research aims and explain why the research is important. 

Literature review  

The literature review is where you will analyse and evaluate existing research within your subject area. This section is where your secondary research will be presented. A literature review is an integral part of your research project as it brings validity to your research aims. 

What to include when writing your literature review:

• A description of the publications
• A summary of the main points
• An evaluation on the contribution to the area of study
• Potential flaws and gaps in the research 

Methodology

The research paper methodology outlines the process of your data collection. This is where you will present your primary research. The aim of the methodology section is to answer two questions: 

• Why did you select the research methods you used?
• How do these methods contribute towards your research hypothesis? 

In this section you will not be writing about your findings, but the ways in which you are going to try and achieve them. You need to state whether your methodology will be qualitative, quantitative, or mixed. 

• Qualitative – first hand observations such as interviews, focus groups, case studies and questionnaires. The data collected will generally be non-numerical. 
• Quantitative – research that deals in numbers and logic. The data collected will focus on statistics and numerical patterns.
• Mixed – includes both quantitative and qualitative research.

The methodology section should always be written in the past tense, even if you have already started your data collection. 

Findings and results 

In this section you will present the findings and results of your primary research. Here you will give a concise and factual summary of your findings using tables and graphs where appropriate. 

Discussion 

The discussion section is where you will talk about your findings in detail. Here you need to relate your results to your hypothesis, explaining what you found out and the significance of the research. 

It is a good idea to talk about any areas with disappointing or surprising results and address the limitations within the research project. This will balance your project and steer you away from bias.

Some questions to consider when writing your discussion: 

• To what extent was the hypothesis supported?
• Was your research method appropriate?
• Was there unexpected data that affected your results?
• To what extent was your research validated by other sources?

Conclusion 

The conclusion is where you will bring your research project to a close. In this section you will not only be restating your research aims and how you achieved them, but also discussing the wider significance of your research project. You will talk about the successes and failures of the project, and how you would approach further study. 

It is essential you do not bring any new ideas into your conclusion; this section is used only to summarise what you have already stated in the project. 

References 

As a research project is your own ideas blended with information and research from existing knowledge, you must include a list of correctly cited references. Creating a list of references will allow the reader to easily evaluate the quality of your secondary research whilst also saving you from potential plagiarism accusations. 

The way in which you cite your sources will vary depending on the university standard.

If you are an international student looking to  study a degree in the UK , The University of Sheffield International College has a range of  pathway programmes  to prepare you for university study. Undertaking a Research Project is one of the core modules for the  Pre-Masters programme  at The University of Sheffield International College.

Frequently Asked Questions 

What is the best topic for research .

It’s a good idea to choose a topic you have existing knowledge on, or one that you are interested in. This will make the research process easier; as you have an idea of where and what to look for in your sources, as well as more enjoyable as it’s a topic you want to know more about.

What should a research project include? 

There are seven main sections to a research project, these are:

• Introduction – the aims of the project and what you hope to achieve
• Literature review – evaluating and reviewing existing knowledge on the topic
• Methodology – the methods you will use for your primary research
• Findings and results – presenting the data from your primary research
• Discussion – summarising and analysing your research and what you have found out
• Conclusion – how the project went (successes and failures), areas for future study
• List of references – correctly cited sources that have been used throughout the project. 

How long is a research project? 

The length of a research project will depend on the level study and the nature of the subject. There is no one length for research papers, however the average dissertation style essay can be anywhere from 4,000 to 15,000+ words. 

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Home » Research Process – Steps, Examples and Tips

Research Process – Steps, Examples and Tips

Table of Contents

Research Process

Definition:

Research Process is a systematic and structured approach that involves the collection, analysis, and interpretation of data or information to answer a specific research question or solve a particular problem.

Research Process Steps

Research Process Steps are as follows:

Identify the Research Question or Problem

This is the first step in the research process. It involves identifying a problem or question that needs to be addressed. The research question should be specific, relevant, and focused on a particular area of interest.

Conduct a Literature Review

Once the research question has been identified, the next step is to conduct a literature review. This involves reviewing existing research and literature on the topic to identify any gaps in knowledge or areas where further research is needed. A literature review helps to provide a theoretical framework for the research and also ensures that the research is not duplicating previous work.

Formulate a Hypothesis or Research Objectives

Based on the research question and literature review, the researcher can formulate a hypothesis or research objectives. A hypothesis is a statement that can be tested to determine its validity, while research objectives are specific goals that the researcher aims to achieve through the research.

Design a Research Plan and Methodology

This step involves designing a research plan and methodology that will enable the researcher to collect and analyze data to test the hypothesis or achieve the research objectives. The research plan should include details on the sample size, data collection methods, and data analysis techniques that will be used.

Collect and Analyze Data

This step involves collecting and analyzing data according to the research plan and methodology. Data can be collected through various methods, including surveys, interviews, observations, or experiments. The data analysis process involves cleaning and organizing the data, applying statistical and analytical techniques to the data, and interpreting the results.

Interpret the Findings and Draw Conclusions

After analyzing the data, the researcher must interpret the findings and draw conclusions. This involves assessing the validity and reliability of the results and determining whether the hypothesis was supported or not. The researcher must also consider any limitations of the research and discuss the implications of the findings.

Communicate the Results

Finally, the researcher must communicate the results of the research through a research report, presentation, or publication. The research report should provide a detailed account of the research process, including the research question, literature review, research methodology, data analysis, findings, and conclusions. The report should also include recommendations for further research in the area.

Review and Revise

The research process is an iterative one, and it is important to review and revise the research plan and methodology as necessary. Researchers should assess the quality of their data and methods, reflect on their findings, and consider areas for improvement.

Ethical Considerations

Throughout the research process, ethical considerations must be taken into account. This includes ensuring that the research design protects the welfare of research participants, obtaining informed consent, maintaining confidentiality and privacy, and avoiding any potential harm to participants or their communities.

Dissemination and Application

The final step in the research process is to disseminate the findings and apply the research to real-world settings. Researchers can share their findings through academic publications, presentations at conferences, or media coverage. The research can be used to inform policy decisions, develop interventions, or improve practice in the relevant field.

Research Process Example

Following is a Research Process Example:

Research Question : What are the effects of a plant-based diet on athletic performance in high school athletes?

Step 1: Background Research Conduct a literature review to gain a better understanding of the existing research on the topic. Read academic articles and research studies related to plant-based diets, athletic performance, and high school athletes.

Step 2: Develop a Hypothesis Based on the literature review, develop a hypothesis that a plant-based diet positively affects athletic performance in high school athletes.

Step 3: Design the Study Design a study to test the hypothesis. Decide on the study population, sample size, and research methods. For this study, you could use a survey to collect data on dietary habits and athletic performance from a sample of high school athletes who follow a plant-based diet and a sample of high school athletes who do not follow a plant-based diet.

Step 4: Collect Data Distribute the survey to the selected sample and collect data on dietary habits and athletic performance.

Step 5: Analyze Data Use statistical analysis to compare the data from the two samples and determine if there is a significant difference in athletic performance between those who follow a plant-based diet and those who do not.

Step 6 : Interpret Results Interpret the results of the analysis in the context of the research question and hypothesis. Discuss any limitations or potential biases in the study design.

Step 7: Draw Conclusions Based on the results, draw conclusions about whether a plant-based diet has a significant effect on athletic performance in high school athletes. If the hypothesis is supported by the data, discuss potential implications and future research directions.

Step 8: Communicate Findings Communicate the findings of the study in a clear and concise manner. Use appropriate language, visuals, and formats to ensure that the findings are understood and valued.

Applications of Research Process

The research process has numerous applications across a wide range of fields and industries. Some examples of applications of the research process include:

• Scientific research: The research process is widely used in scientific research to investigate phenomena in the natural world and develop new theories or technologies. This includes fields such as biology, chemistry, physics, and environmental science.
• Social sciences : The research process is commonly used in social sciences to study human behavior, social structures, and institutions. This includes fields such as sociology, psychology, anthropology, and economics.
• Education: The research process is used in education to study learning processes, curriculum design, and teaching methodologies. This includes research on student achievement, teacher effectiveness, and educational policy.
• Healthcare: The research process is used in healthcare to investigate medical conditions, develop new treatments, and evaluate healthcare interventions. This includes fields such as medicine, nursing, and public health.
• Business and industry : The research process is used in business and industry to study consumer behavior, market trends, and develop new products or services. This includes market research, product development, and customer satisfaction research.
• Government and policy : The research process is used in government and policy to evaluate the effectiveness of policies and programs, and to inform policy decisions. This includes research on social welfare, crime prevention, and environmental policy.

Purpose of Research Process

The purpose of the research process is to systematically and scientifically investigate a problem or question in order to generate new knowledge or solve a problem. The research process enables researchers to:

• Identify gaps in existing knowledge: By conducting a thorough literature review, researchers can identify gaps in existing knowledge and develop research questions that address these gaps.
• Collect and analyze data : The research process provides a structured approach to collecting and analyzing data. Researchers can use a variety of research methods, including surveys, experiments, and interviews, to collect data that is valid and reliable.
• Test hypotheses : The research process allows researchers to test hypotheses and make evidence-based conclusions. Through the systematic analysis of data, researchers can draw conclusions about the relationships between variables and develop new theories or models.
• Solve problems: The research process can be used to solve practical problems and improve real-world outcomes. For example, researchers can develop interventions to address health or social problems, evaluate the effectiveness of policies or programs, and improve organizational processes.
• Generate new knowledge : The research process is a key way to generate new knowledge and advance understanding in a given field. By conducting rigorous and well-designed research, researchers can make significant contributions to their field and help to shape future research.

Tips for Research Process

Here are some tips for the research process:

• Start with a clear research question : A well-defined research question is the foundation of a successful research project. It should be specific, relevant, and achievable within the given time frame and resources.
• Conduct a thorough literature review: A comprehensive literature review will help you to identify gaps in existing knowledge, build on previous research, and avoid duplication. It will also provide a theoretical framework for your research.
• Choose appropriate research methods: Select research methods that are appropriate for your research question, objectives, and sample size. Ensure that your methods are valid, reliable, and ethical.
• Be organized and systematic: Keep detailed notes throughout the research process, including your research plan, methodology, data collection, and analysis. This will help you to stay organized and ensure that you don’t miss any important details.
• Analyze data rigorously: Use appropriate statistical and analytical techniques to analyze your data. Ensure that your analysis is valid, reliable, and transparent.
• I nterpret results carefully : Interpret your results in the context of your research question and objectives. Consider any limitations or potential biases in your research design, and be cautious in drawing conclusions.
• Communicate effectively: Communicate your research findings clearly and effectively to your target audience. Use appropriate language, visuals, and formats to ensure that your findings are understood and valued.
• Collaborate and seek feedback : Collaborate with other researchers, experts, or stakeholders in your field. Seek feedback on your research design, methods, and findings to ensure that they are relevant, meaningful, and impactful.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Design 101

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

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 .

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).

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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.

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 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 .

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.

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 .

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15 Comments

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

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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 .

how can I put this blog as my reference(APA style) in bibliography part?

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What Is a Project? Definition, Types & Examples

What is a project, exactly? We talk a lot about specific facets of project management, but it’s sometimes valuable to start at the root and dig into the basics.

To fully understand high-level project management concepts, it’s important to know the simple answers. When you can call on this knowledge, more complicated concepts are easier to master. Whether you’re the project manager or a stakeholder, give your next project definition with these project management tips in mind.

Project Definition

A project is a set of tasks that must be completed within a defined timeline to accomplish a specific set of goals. These tasks are completed by a group of people known as the project team, which is led by a project manager, who oversees the planning , scheduling, tracking and successful completion of projects.

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Besides the project team, projects require resources such as labor, materials and equipment. Organizations and individuals manage projects with a wide range of objectives. These can take many forms, from constructing a building to planning an event and even completing a certain duty. Retailers, for example, may pursue projects that improve the way they track order fulfillment. Construction teams complete projects any time they plan and build something—and so on!

Project management software gives you the tools to manage all the parts of a project so it is delivered on time and within budget. ProjectManager is award-winning project management software with features to plan, manage and track your project in real time. Organize tasks on our robust Gantt, link all four types of task dependencies to avoid costly delays and save your project plan by setting a baseline. This allows you to track your actual progress against your planned progress to help you stay on track. Get started with ProjectManager today for free.

What Are the Characteristics of a Project?

There are certain features or characteristics that are unique to projects and differentiate them from the daily operations or other types of activities of an organization. Here are the main characteristics of a project.

1. Any Project Needs a Project Manager and a Project Team

One of the most important characteristics of a project is that it’s a team effort. While the structure of project teams might change from one organization to another, projects usually involve a project manager and a team of individuals with the necessary skills to execute the tasks that are needed.

2. Every Project Needs a Project Plan

Project team members need clear directions from the project manager and other project leaders so that they can execute the work that’s expected from them. These directions come in the form of a project plan. However, a project plan is more than just a set of instructions for the project team. It’s a comprehensive document that describes every aspect of a project, such as the project goals, project schedule and project budget among other important details.

3. All Projects Go Through the Same Project Lifecycle

The project life cycle refers to the five phases all projects must progress through, from start to finish. The five phases of a project lifecycle serve as the most basic outline that gives a project definition. These five phases are initiation, planning, execution, monitoring and closure.

4. All Projects Share the Same Project Constraints

All projects no matter their size or complexity are subject to three main constraints: time, scope and cost. This simply means that projects must be completed within a defined timeline, achieve a defined set of tasks and goals and be delivered under a certain budget .

These project constraints are known as the triple constraint or the project management triangle and are one of the most important project features to know about.

5. Every Project Needs Resources

A resource is anything necessary to complete a project, such as for example, labor, raw materials, machinery and equipment. For example, in construction, raw materials such as wood, glass or paint are essential project resources . That said, other resources — like time, labor and equipment — are just as important.

A project manager must be able to identify all of the project resources in order to create a resource plan and manage the resources accordingly. When resources are left unaccounted for, it is easy to mismanage them.

Types of Projects

Projects can take many shapes and forms, which makes classifying them into types a very difficult task that requires different approaches. Here are some of the types of projects grouped by funding source, industry and project management methodology .

Types of Projects By Funding Source

One simple way to categorize projects is to look at their source of capital.

• Private projects: Projects that are financed by businesses or private organizations.
• Public projects: Projects which are funded by Government agencies.
• Mixed projects: Projects that are financed by a public-private partnership.

Types of Projects By Industry

Projects can be executed by large or small organizations from any industry. However, some industries are more project-intensive than others. Here are some of the most common types of projects by industry.

• Construction projects: The main goal of any construction project is to make a building that can be used for different purposes such as infrastructure, residential or commercial use.
• Manufacturing projects: Manufacturing projects consist of manufacturing physical products to generate profits for a company.
• IT projects: Information technology projects consist in establishing an IT framework for the processing of data at a company-wide scale.
• Software development projects: The main goal of a software development project is to create a software product for a client.
• Business projects: The term business project could refer to creating a new business, creating a new business unit for an existing company or simply launching a new business initiative.

Types of Projects By Project Management Methodology

Besides the types of projects mentioned above, projects can also be classified by the project management methodology that’s used to plan, schedule and execute them.

• Waterfall projects: Waterfall is the most traditional project management methodology, where the project plan is defined before the project begins and each major project phase must be completed in sequence.
• Agile projects: Agile projects are planned and executed in short iterations known as sprints , where project teams plan their activities as they execute the project.

Project Examples

Now that we’ve reviewed the main characteristics of a project and the various project types that exist, let’s review some common project examples to better illustrate what a project is.

Construction Project Examples

• Construction infrastructure projects: Building a bridge, a road, a mass transportation system or a water treatment facility.
• Residential construction projects: Building a house, a residential building or an apartment complex.
• Commercial construction projects: Building a shopping mall, a parking lot or a hotel.

Manufacturing Project Examples

• Building a factory from scratch
• Manufacturing products for retail sale
• Manufacturing products for a B2B purchase order
• Improving an existing production line by acquiring new machinery and training employees

Key Project Terms to Know

No matter the project, there are universal project terms that are used regardless of project type, project size or any other factor. Know these seven terms like the back of your hand and you’ll be a step ahead before the project begins:

Project Scope

Project scope is a key aspect of the project planning stage. In many ways, it is the starting point. Determining project scope requires the project manager and their team to set goals and objectives, detail deliverables, create tasks, establish important dates and more. Project scope defines desired outcomes and all specific factors which will affect reaching them.

Project Stakeholder

A stakeholder refers to anyone and everyone involved in a project. A stakeholder can be involved at every stage of the project, or just in a certain way. Stakeholder analysis helps categorize how investors, team members, vendors, contractors and more can affect your project.

Project Deliverables

A deliverable refers to the specific outcome(s) a project creates. Deliverables can be “tangible” or “intangible,” meaning they can be a physical product or something conceptual. Typically, deliverables are the need that inspired the project in the first place. If someone contracts a builder to design and construct an office space, the office is a tangible deliverable.

Project Milestones

Milestones are predetermined achievements that help track project progress. Think of milestones as checkpoints. These checkpoints are decided on before a project begins, so the project manager and team know when they are on track to achieve deliverables. Without milestones, it’s difficult to know if the project is on the road to success or needs to reroute.

Project Dependencies

Project dependencies refer to how resources must be shared and allocated within a project. Many projects will use the same physical materials for different purposes and across different stages. Understanding this dependency is the only way to ensure there is enough resources to go around. Similarly, all projects are broken down into tasks. When one task cannot begin before another is completed, these tasks share a dependency.

What It Means to Work on a Project

Whether it’s the project manager, a team member or any other project stakeholder, they’re a member of the greater project team and their actions directly affect other team members. Like any team, you “win” or “lose” as a unit, so it’s incredibly important to communicate and listen to other team members in order to coordinate efforts and succeed. Most project mishaps and project failures are the direct results of poor communication or lack of collaboration.

Why does this matter as long as the work is getting done? Working on a project is about understanding the project as a whole just as much as it is about doing the work. The only way to see this big picture is by listening to the team and learning from one another.

What Is Project Management?

The process of project management starts with the conception of the project and continues all the way through the project lifecycle. This requires detailed knowledge of company resources and how to assign them in order to complete tasks, duties, events and other projects.

A wide range of industries relies on project management methods and tools to execute projects. A few examples of these industries are construction, IT, engineering, marketing and advertising. Any team working together to reach a shared objective is engaging in some form of project management.

What Does a Project Manager Do?

A project manager is more than just a manager, in the traditional sense. This individual is the leader of the project team and oversees every aspect of the project, from beginning to end. The project manager will typically write the project plan, run team meetings, assign tasks and do quality control tests to ensure everything is running smoothly. A project manager can’t carry the entire project on their back, though. One of their key duties, in fact, is knowing how to entrust various responsibilities to team members.

With the help of their team, project managers will create project schedules and budgets. They will also create project reports throughout the project lifecycle.

As you can see, their responsibilities are widespread, but that doesn’t mean spreading too thin. Ideally, a project manager creates the foundation of the project—like the foundation of a house. They then appoint other individuals to finish out each room.

Project Definition: Best Practices for Project Management

Regardless of the project, the size of the team, or anything else, there are practices that exponentially increase the chances of success. As vital as it is to hit goals and achieve deliverables , it’s just as important to create a positive culture within the project. These five tips may seem simple, but they make a big difference:

Set Regular Team Check-ins

It’s easy to meet with the team “as needed,” but once a project begins it gets harder to find time in everyone’s schedule. Instead, schedule regular meetings before a project even starts. These meetings serve as check-ins where team members can give each other updates, voice concerns, ask questions, make adjustments and do anything else they may need. When these check-ins are already built into the schedule, no one is waiting to meet until there’s a mishap or issue.

Part of what gives a project definition is knowing how to delegate. Whether it’s the project managers or a team member, they’ll more than likely need help with a task at some point. Now, this doesn’t mean just passing along the task to someone else. It means that every team member has equal responsibilities. Instead, the best project managers know how to relinquish some control and delegate to team members.

Know the Team

Everyone on the project management team should be familiar with each other’s strengths, weaknesses and specialties. For example, if a team member needs information from a different department, they should know exactly who to ask. This familiarity cuts down on lost time. It is especially important for a project manager to know their team extremely well.

When a project member knows these things, they can make decisions that play to their team members’ strengths, not around their weaknesses. Knowing the team is a huge aspect of creating a positive culture within a project, as it celebrates everyone’s abilities.

Celebrate Milestones

Speaking of positive culture, never underestimate the power of taking a moment to mark meeting a milestone . Reaching one means the team has made significant progress and the project is still on track. At the very least, it’s important to announce reaching milestones during team check-ins. This keeps everyone on the same page and improves team efficacy.

Choose Superior PM Tools

Project management is an extremely complex job. Without the proper tools, it’s easy to make mistakes, become disorganized and even fail to complete the project. The best way to protect your project from these missteps is by choosing tools that simplify the entire process.

The best project management software does just that. Using project management software unleashes your team’s and the project’s full potential and takes the end result to new heights. The key is finding an intuitive, user-friendly project management software that makes no compromises in functionality.

How ProjectManager Makes Managing Projects Easy

ProjectManager is an award-winning project management software that makes managing projects easier than ever. Our online software allows the entire team to work on the project while in the field or on the go, and our modern interface combines functionality with user-friendly navigation. This means no more wasted time just trying to familiarize yourself with a new tool and more time perfecting your project definition.

Plan on Gantt Charts

Plan your projects from start to finish with ProjectManager’s powerful Gantt chart feature, which allows you to map out project tasks in phases. You can even create dependencies and set milestones. Plus, you can import Excel files and Microsoft Project files, so switching over to our software is seamless.

Track on Project Dashboards

As the project team moves forward with tasks, project managers can track every status update on our real-time dashboard that you can personalize to show the most important metrics. Every change to a task is tracked and automatically updates the colorful, easy-to-read charts and graphs. Keeping an eye on your project’s progress has never been easier!

Get all these features and more when you use ProjectManager. All of these tools are available in our software to help you plan, track and report on your project in real time. See what it can do for you by taking this free 30-day trial run!

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

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

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

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

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

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 analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is 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.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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What is a Research Problem? Characteristics, Types, and Examples

A research problem is a gap in existing knowledge, a contradiction in an established theory, or a real-world challenge that a researcher aims to address in their research. It is at the heart of any scientific inquiry, directing the trajectory of an investigation. The statement of a problem orients the reader to the importance of the topic, sets the problem into a particular context, and defines the relevant parameters, providing the framework for reporting the findings. Therein lies the importance of research problem s.  

The formulation of well-defined research questions is central to addressing a research problem . A research question is a statement made in a question form to provide focus, clarity, and structure to the research endeavor. This helps the researcher design methodologies, collect data, and analyze results in a systematic and coherent manner. A study may have one or more research questions depending on the nature of the study.   

Identifying and addressing a research problem is very important. By starting with a pertinent problem , a scholar can contribute to the accumulation of evidence-based insights, solutions, and scientific progress, thereby advancing the frontier of research. Moreover, the process of formulating research problems and posing pertinent research questions cultivates critical thinking and hones problem-solving skills.   

Table of Contents

What is a Research Problem ?  

Before you conceive of your project, you need to ask yourself “ What is a research problem ?” A research problem definition can be broadly put forward as the primary statement of a knowledge gap or a fundamental challenge in a field, which forms the foundation for research. Conversely, the findings from a research investigation provide solutions to the problem .  

A research problem guides the selection of approaches and methodologies, data collection, and interpretation of results to find answers or solutions. A well-defined problem determines the generation of valuable insights and contributions to the broader intellectual discourse.  

Characteristics of a Research Problem  

Knowing the characteristics of a research problem is instrumental in formulating a research inquiry; take a look at the five key characteristics below:  

Novel : An ideal research problem introduces a fresh perspective, offering something new to the existing body of knowledge. It should contribute original insights and address unresolved matters or essential knowledge.   

Significant : A problem should hold significance in terms of its potential impact on theory, practice, policy, or the understanding of a particular phenomenon. It should be relevant to the field of study, addressing a gap in knowledge, a practical concern, or a theoretical dilemma that holds significance.  

Feasible: A practical research problem allows for the formulation of hypotheses and the design of research methodologies. A feasible research problem is one that can realistically be investigated given the available resources, time, and expertise. It should not be too broad or too narrow to explore effectively, and should be measurable in terms of its variables and outcomes. It should be amenable to investigation through empirical research methods, such as data collection and analysis, to arrive at meaningful conclusions A practical research problem considers budgetary and time constraints, as well as limitations of the problem . These limitations may arise due to constraints in methodology, resources, or the complexity of the problem.  

Clear and specific : A well-defined research problem is clear and specific, leaving no room for ambiguity; it should be easily understandable and precisely articulated. Ensuring specificity in the problem ensures that it is focused, addresses a distinct aspect of the broader topic and is not vague.  

Rooted in evidence: A good research problem leans on trustworthy evidence and data, while dismissing unverifiable information. It must also consider ethical guidelines, ensuring the well-being and rights of any individuals or groups involved in the study.

Types of Research Problems  

Across fields and disciplines, there are different types of research problems . We can broadly categorize them into three types.  

• Theoretical research problems

Theoretical research problems deal with conceptual and intellectual inquiries that may not involve empirical data collection but instead seek to advance our understanding of complex concepts, theories, and phenomena within their respective disciplines. For example, in the social sciences, research problem s may be casuist (relating to the determination of right and wrong in questions of conduct or conscience), difference (comparing or contrasting two or more phenomena), descriptive (aims to describe a situation or state), or relational (investigating characteristics that are related in some way).  

Here are some theoretical research problem examples :   

• Ethical frameworks that can provide coherent justifications for artificial intelligence and machine learning algorithms, especially in contexts involving autonomous decision-making and moral agency.  
• Determining how mathematical models can elucidate the gradual development of complex traits, such as intricate anatomical structures or elaborate behaviors, through successive generations.  
• Applied research problems

Applied or practical research problems focus on addressing real-world challenges and generating practical solutions to improve various aspects of society, technology, health, and the environment.  

Here are some applied research problem examples :   

• Studying the use of precision agriculture techniques to optimize crop yield and minimize resource waste.  
• Designing a more energy-efficient and sustainable transportation system for a city to reduce carbon emissions.  
• Action research problems

Action research problems aim to create positive change within specific contexts by involving stakeholders, implementing interventions, and evaluating outcomes in a collaborative manner.  

Here are some action research problem examples :   

• Partnering with healthcare professionals to identify barriers to patient adherence to medication regimens and devising interventions to address them.  
• Collaborating with a nonprofit organization to evaluate the effectiveness of their programs aimed at providing job training for underserved populations.  

These different types of research problems may give you some ideas when you plan on developing your own.  

How to Define a Research Problem  

You might now ask “ How to define a research problem ?” These are the general steps to follow:   

• Look for a broad problem area: Identify under-explored aspects or areas of concern, or a controversy in your topic of interest. Evaluate the significance of addressing the problem in terms of its potential contribution to the field, practical applications, or theoretical insights.
• Learn more about the problem: Read the literature, starting from historical aspects to the current status and latest updates. Rely on reputable evidence and data. Be sure to consult researchers who work in the relevant field, mentors, and peers. Do not ignore the gray literature on the subject.
• Identify the relevant variables and how they are related: Consider which variables are most important to the study and will help answer the research question. Once this is done, you will need to determine the relationships between these variables and how these relationships affect the research problem . 
• Think of practical aspects : Deliberate on ways that your study can be practical and feasible in terms of time and resources. Discuss practical aspects with researchers in the field and be open to revising the problem based on feedback. Refine the scope of the research problem to make it manageable and specific; consider the resources available, time constraints, and feasibility.
• Formulate the problem statement: Craft a concise problem statement that outlines the specific issue, its relevance, and why it needs further investigation.
• Stick to plans, but be flexible: When defining the problem , plan ahead but adhere to your budget and timeline. At the same time, consider all possibilities and ensure that the problem and question can be modified if needed.

Key Takeaways  

• A research problem concerns an area of interest, a situation necessitating improvement, an obstacle requiring eradication, or a challenge in theory or practical applications.   
• The importance of research problem is that it guides the research and helps advance human understanding and the development of practical solutions.  
• Research problem definition begins with identifying a broad problem area, followed by learning more about the problem, identifying the variables and how they are related, considering practical aspects, and finally developing the problem statement.  
• Different types of research problems include theoretical, applied, and action research problems , and these depend on the discipline and nature of the study.  
• An ideal problem is original, important, feasible, specific, and based on evidence.  

Frequently Asked Questions  

Why is it important to define a research problem?  

Identifying potential issues and gaps as research problems is important for choosing a relevant topic and for determining a well-defined course of one’s research. Pinpointing a problem and formulating research questions can help researchers build their critical thinking, curiosity, and problem-solving abilities.   

How do I identify a research problem?  

Identifying a research problem involves recognizing gaps in existing knowledge, exploring areas of uncertainty, and assessing the significance of addressing these gaps within a specific field of study. This process often involves thorough literature review, discussions with experts, and considering practical implications.  

Can a research problem change during the research process?  

Yes, a research problem can change during the research process. During the course of an investigation a researcher might discover new perspectives, complexities, or insights that prompt a reevaluation of the initial problem. The scope of the problem, unforeseen or unexpected issues, or other limitations might prompt some tweaks. You should be able to adjust the problem to ensure that the study remains relevant and aligned with the evolving understanding of the subject matter.

How does a research problem relate to research questions or hypotheses?  

A research problem sets the stage for the study. Next, research questions refine the direction of investigation by breaking down the broader research problem into manageable components. Research questions are formulated based on the problem , guiding the investigation’s scope and objectives. The hypothesis provides a testable statement to validate or refute within the research process. All three elements are interconnected and work together to guide the research.  

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• Published: 16 September 2024

From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology

• Omar S. M. El Nahhas   ORCID: orcid.org/0000-0002-2542-2117 1 , 2 ,
• Marko van Treeck 1 ,
• Georg Wölflein   ORCID: orcid.org/0000-0002-0407-7617 3 ,
• Michaela Unger 1 ,
• Marta Ligero 1 ,
• Tim Lenz 1 ,
• Sophia J. Wagner 4 , 5 ,
• Katherine J. Hewitt 1 ,
• Firas Khader 2 , 6 ,
• Sebastian Foersch 7 ,
• Daniel Truhn 2 , 6 &
• Jakob Nikolas Kather   ORCID: orcid.org/0000-0002-3730-5348 1 , 2 , 8 , 9  

Nature Protocols ( 2024 ) Cite this article

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• Bioinformatics
• Cancer imaging
• Image processing

Hematoxylin- and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-based methods in computational pathology has enabled the prediction of biomarkers directly from WSIs. However, accurately linking tissue phenotype to biomarkers at scale remains a crucial challenge for democratizing complex biomarkers in precision oncology. This protocol describes a practical workflow for solid tumor associative modeling in pathology (STAMP), enabling prediction of biomarkers directly from WSIs by using deep learning. The STAMP workflow is biomarker agnostic and allows for genetic and clinicopathologic tabular data to be included as an additional input, together with histopathology images. The protocol consists of five main stages that have been successfully applied to various research problems: formal problem definition, data preprocessing, modeling, evaluation and clinical translation. The STAMP workflow differentiates itself through its focus on serving as a collaborative framework that can be used by clinicians and engineers alike for setting up research projects in the field of computational pathology. As an example task, we applied STAMP to the prediction of microsatellite instability (MSI) status in colorectal cancer, showing accurate performance for the identification of tumors high in MSI. Moreover, we provide an open-source code base, which has been deployed at several hospitals across the globe to set up computational pathology workflows. The STAMP workflow requires one workday of hands-on computational execution and basic command line knowledge.

STAMP (solid tumor associative modeling in pathology) is a practical workflow for end-to-end weakly supervised deep learning in computational pathology, enabling prediction of biomarkers directly from whole-slide images.

This protocol differentiates itself from others by providing a collaborative framework through which clinical researchers can work with engineers to set up a complete computational pathology project.

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Artificial intelligence for digital and computational pathology

Deep learning in cancer pathology: a new generation of clinical biomarkers

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma

Data availability.

Histopathology slides and genomics data from TCGA and CPTAC were used to train and validate the models. The slides for TCGA are available at https://portal.gdc.cancer.gov/ . The slides for CPTAC are available at https://proteomics.cancer.gov/data-portal . The molecular and clinical data for TCGA and CPTAC used in the experiments are available at https://github.com/KatherLab/cancer-metadata . Source data are provided with this paper.

Code availability

The open-source STAMP software for the implementation of the MSI experiments is available on GitHub ( https://github.com/KatherLab/STAMP ).

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Acknowledgements

We thank the testers of the protocol, S. Sainath, O. L. Saldanha, L. Žigutytė, C. Kummer, G. Serna, K. Boehm and L. Shaktah, who executed the STAMP protocol on various systems at cancer centers around the world. O.S.M.E.N. is supported by the German Federal Ministry of Education and Research (BMBF) through grant 1IS23070, Software Campus 3.0 (TU Dresden), as part of the Software Campus project ’MIRACLE-AI’. J.N.K. is supported by the German Federal Ministry of Health (DEEP LIVER, ZMVI1-2520DAT111), the German Cancer Aid (DECADE, 70115166), the German Federal Ministry of Education and Research (PEARL, 01KD2104C; CAMINO, 01EO2101; SWAG, 01KD2215A; TRANSFORM LIVER, 031L0312A; TANGERINE, 01KT2302 through ERA-NET Transcan), the German Academic Exchange Service (SECAI, 57616814), the German Federal Joint Committee (TransplantKI, 01VSF21048), the European Union’s Horizon Europe and innovation programme (ODELIA, 101057091; GENIAL, 101096312) and the National Institute for Health and Care Research (NIHR, NIHR213331) Leeds Biomedical Research Centre. G.W. is supported by Lothian NHS. D.T. is supported by the German Federal Ministry of Education and Research (SWAG, 01KD2215A; TRANSFORM LIVER) and the European Union’s Horizon Europe and innovation programme (ODELIA, 101057091). S.F. is supported by the German Federal Ministry of Education and Research (SWAG, 01KD2215A), the German Cancer Aid (DECADE, 70115166) and the German Research Foundation (504101714). S.J.W. was supported by the Helmholtz Association under the joint research school ‘Munich School for Data Science – MUDS’ and the Add-on Fellowship of the Joachim Herz Foundation. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. This work was funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.

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Else Kroener Fresenius Center for Digital Health, Medical Faculty Carl Gustav Carus, Technical University Dresden, Dresden, Germany

Omar S. M. El Nahhas, Marko van Treeck, Michaela Unger, Marta Ligero, Tim Lenz, Katherine J. Hewitt & Jakob Nikolas Kather

StratifAI GmbH, Dresden, Germany

Omar S. M. El Nahhas, Firas Khader, Daniel Truhn & Jakob Nikolas Kather

School of Computer Science, University of St Andrews, St Andrews, UK

Georg Wölflein

Helmholtz Munich–German Research Center for Environment and Health, Munich, Germany

Sophia J. Wagner

School of Computation, Information and Technology, Technical University of Munich, Munich, Germany

Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany

Firas Khader & Daniel Truhn

Institute of Pathology–University Medical Center Mainz, Mainz, Germany

Sebastian Foersch

Medical Oncology, National Center for Tumor Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany

Jakob Nikolas Kather

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Contributions

O.S.M.E.N. and J.N.K. designed the protocol. O.S.M.E.N., M.v.T., G.W. and T.L. developed the software and wrote technical documentation. O.S.M.E.N., M.v.T., G.W., T.L., M.L., M.U., S.J.W., F.K., S.F. and D.T. tested the software. O.S.M.E.N., J.N.K. and K.J.H. interpreted and analyzed the data. All authors wrote and reviewed the protocol and approved the final version for submission.

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Correspondence to Jakob Nikolas Kather .

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Competing interests.

O.S.M.E.N., F.K. and D.T. hold shares in StratifAI GmbH. J.N.K. declares consulting services for Owkin, France; DoMore Diagnostics, Norway; Panakeia, UK,; Scailyte, Switzerland; Mindpeak, Germany; and Histofy, UK; furthermore, he holds shares in StratifAI GmbH, Germany, and has received honoraria for lectures by AstraZeneca, Bayer, Eisai, MSD, BMS, Roche, Pfizer and Fresenius. D.T. received honoraria for lectures by Bayer and holds shares in StratifAI GmbH, Germany. S.F. has received honoraria from MSD and BMS.

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Key references using this protocol

Wagner, S. J. et al. Cancer Cell 41 , 1650–1661.e4 (2023): https://doi.org/10.1016/j.ccell.2023.08.002

El Nahhas, O. S. M. et al. Nat. Commun . 15 , 1253 (2024): https://doi.org/10.1038/s41467-024-45589-1

Jiang, X. et al. Lancet Digit. Health 6 , e33–e43 (2024): https://doi.org/10.1016/S2589-7500(23)00208-X

Hewitt, K. J. et al. Neurooncol. Adv . 5 , vdad139 (2023): https://doi.org/10.1093/noajnl/vdad139

Saldanha, O. L. et al. npj Precis. Onc . 7 , 35 (2023): https://doi.org/10.1038/s41698-023-00365-0

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El Nahhas, O.S.M., van Treeck, M., Wölflein, G. et al. From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology. Nat Protoc (2024). https://doi.org/10.1038/s41596-024-01047-2

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Received : 17 December 2023

Accepted : 04 July 2024

Published : 16 September 2024

DOI : https://doi.org/10.1038/s41596-024-01047-2

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