concept paper example quantitative research

Concept Papers in Research: Deciphering the blueprint of brilliance

Concept papers hold significant importance as a precursor to a full-fledged research proposal in academia and research. Understanding the nuances and significance of a concept paper is essential for any researcher aiming to lay a strong foundation for their investigation.

Table of Contents

What Is Concept Paper

A concept paper can be defined as a concise document which outlines the fundamental aspects of a grant proposal. It outlines the initial ideas, objectives, and theoretical framework of a proposed research project. It is usually two to three-page long overview of the proposal. However, they differ from both research proposal and original research paper in lacking a detailed plan and methodology for a specific study as in research proposal provides and exclusion of the findings and analysis of a completed research project as in an original research paper. A concept paper primarily focuses on introducing the basic idea, intended research question, and the framework that will guide the research.

Purpose of a Concept Paper

A concept paper serves as an initial document, commonly required by private organizations before a formal proposal submission. It offers a preliminary overview of a project or research’s purpose, method, and implementation. It acts as a roadmap, providing clarity and coherence in research direction. Additionally, it also acts as a tool for receiving informal input. The paper is used for internal decision-making, seeking approval from the board, and securing commitment from partners. It promotes cohesive communication and serves as a professional and respectful tool in collaboration.

These papers aid in focusing on the core objectives, theoretical underpinnings, and potential methodology of the research, enabling researchers to gain initial feedback and refine their ideas before delving into detailed research.

Key Elements of a Concept Paper

Key elements of a concept paper include the title page , background , literature review , problem statement , methodology, timeline, and references. It’s crucial for researchers seeking grants as it helps evaluators assess the relevance and feasibility of the proposed research.

Writing an effective concept paper in academic research involves understanding and incorporating essential elements:

How to Write a Concept Paper?

To ensure an effective concept paper, it’s recommended to select a compelling research topic, pose numerous research questions and incorporate data and numbers to support the project’s rationale. The document must be concise (around five pages) after tailoring the content and following the formatting requirements. Additionally, infographics and scientific illustrations can enhance the document’s impact and engagement with the audience. The steps to write a concept paper are as follows:

1. Write a Crisp Title:

Choose a clear, descriptive title that encapsulates the main idea. The title should express the paper’s content. It should serve as a preview for the reader.

2. Provide a Background Information:

Give a background information about the issue or topic. Define the key terminologies or concepts. Review existing literature to identify the gaps your concept paper aims to fill.

3. Outline Contents in the Introduction:

Introduce the concept paper with a brief overview of the problem or idea you’re addressing. Explain its significance. Identify the specific knowledge gaps your research aims to address and mention any contradictory theories related to your research question.

4. Define a Mission Statement:

The mission statement follows a clear problem statement that defines the problem or concept that need to be addressed. Write a concise mission statement that engages your research purpose and explains why gaining the reader’s approval will benefit your field.

5. Explain the Research Aim and Objectives:

Explain why your research is important and the specific questions you aim to answer through your research. State the specific goals and objectives your concept intends to achieve. Provide a detailed explanation of your concept. What is it, how does it work, and what makes it unique?

6. Detail the Methodology:

Discuss the research methods you plan to use, such as surveys, experiments, case studies, interviews, and observations. Mention any ethical concerns related to your research.

7. Outline Proposed Methods and Potential Impact:

Provide detailed information on how you will conduct your research, including any specialized equipment or collaborations. Discuss the expected results or impacts of implementing the concept. Highlight the potential benefits, whether social, economic, or otherwise.

8. Mention the Feasibility

Discuss the resources necessary for the concept’s execution. Mention the expected duration of the research and specific milestones. Outline a proposed timeline for implementing the concept.

9. Include a Support Section:

Include a section that breaks down the project’s budget, explaining the overall cost and individual expenses to demonstrate how the allocated funds will be used.

10. Provide a Conclusion:

Summarize the key points and restate the importance of the concept. If necessary, include a call to action or next steps.

Although the structure and elements of a concept paper may vary depending on the specific requirements, you can tailor your document based on the guidelines or instructions you’ve been given.

Here are some tips to write a concept paper:

Example of a Concept Paper

Here is an example of a concept paper. Please note, this is a generalized example. Your concept paper should align with the specific requirements, guidelines, and objectives you aim to achieve in your proposal. Tailor it accordingly to the needs and context of the initiative you are proposing.

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Importance of a Concept Paper

Concept papers serve various fields, influencing the direction and potential of research in science, social sciences, technology, and more. They contribute to the formulation of groundbreaking studies and novel ideas that can impact societal, economic, and academic spheres.

A concept paper serves several crucial purposes in various fields:

In summary, a well-crafted concept paper is essential in outlining a clear, concise, and structured framework for new ideas or proposals. It helps in assessing the feasibility, viability, and potential impact of the concept before investing significant resources into its implementation.

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Role of AI in Writing Concept Papers

The increasing use of AI, particularly generative models, has facilitated the writing process for concept papers. Responsible use involves leveraging AI to assist in ideation, organization, and language refinement while ensuring that the originality and ethical standards of research are maintained.

AI plays a significant role in aiding the creation and development of concept papers in several ways:

1. Idea Generation and Organization

AI tools can assist in brainstorming initial ideas for concept papers based on key concepts. They can help in organizing information, creating outlines, and structuring the content effectively.

2. Summarizing Research and Data Analysis

AI-powered tools can assist in conducting comprehensive literature reviews, helping writers to gather and synthesize relevant information. AI algorithms can process and analyze vast amounts of data, providing insights and statistics to support the concept presented in the paper.

3. Language and Style Enhancement

AI grammar checker tools can help writers by offering grammar, style, and tone suggestions, ensuring professionalism. It can also facilitate translation, in case a global collaboration.

4. Collaboration and Feedback

AI platforms offer collaborative features that enable multiple authors to work simultaneously on a concept paper, allowing for real-time contributions and edits.

5. Customization and Personalization

AI algorithms can provide personalized recommendations based on the specific requirements or context of the concept paper. They can assist in tailoring the concept paper according to the target audience or specific guidelines.

6. Automation and Efficiency

AI can automate certain tasks, such as citation formatting, bibliography creation, or reference checking, saving time for the writer.

7. Analytics and Prediction

AI models can predict potential outcomes or impacts based on the information provided, helping writers anticipate the possible consequences of the proposed concept.

8. Real-Time Assistance

AI-driven chat-bots can provide real-time support and answers to specific questions related to the concept paper writing process.

AI’s role in writing concept papers significantly streamlines the writing process, enhances the quality of the content, and provides valuable assistance in various stages of development, contributing to the overall effectiveness of the final document.

Concept papers serve as the stepping stone in the research journey, aiding in the crystallization of ideas and the formulation of robust research proposals. It the cornerstone for translating ideas into impactful realities. Their significance spans diverse domains, from academia to business, enabling stakeholders to evaluate, invest, and realize the potential of groundbreaking concepts.

Frequently Asked Questions

A concept paper can be defined as a concise document outlining the fundamental aspects of a grant proposal such as the initial ideas, objectives, and theoretical framework of a proposed research project.

A good concept paper should offer a clear and comprehensive overview of the proposed research. It should demonstrate a strong understanding of the subject matter and outline a structured plan for its execution.

Concept paper is important to develop and clarify ideas, develop and evaluate proposal, inviting collaboration and collecting feedback, presenting proposals for academic and research initiatives and allocating resources.

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How to Write a Concept Paper Easily with Our Guide

Did you know that some of the most revolutionary ideas in history started with a simple concept paper? From scientific breakthroughs to groundbreaking inventions, the power of well-crafted concept papers cannot be underestimated.

In this article, experts at our academic essay writing service will demystify the process of writing a concept paper, offering straightforward tips and guidance to help you articulate your ideas effectively. Whether you're a researcher, entrepreneur, or student, you'll lay the foundation for your next big endeavor effortlessly.

Defining What is a Concept Paper

A concept paper is a starting point for any major project or research endeavor. When you're asked to write one, what your teachers or professors are really asking for is a clear, concise summary of what you plan to explore or investigate. It's your chance to explain your idea, why it matters, and how you're going to tackle it.

Imagine you're pitching your idea to someone who doesn't know anything about it. You want to grab their attention and get them excited about what you're planning to do. That's what a concept paper is all about – setting the stage for your project or research in a way that makes people want to learn more.

Don't Delay Your Scholarly Pursuits!

Our team is here to nurture your concepts! Seize this opportunity to lay the groundwork for your academic exploration.

Why Does a Concept Paper Matter

So, why does knowing how to write a concept paper for academic research matter? First off, it helps you clarify your thoughts and organize your ideas. Writing down your concept forces you to think through the details of your project, which can be super helpful, especially when things start to get overwhelming.

Secondly, it's a way to get feedback early on. By sharing your concept paper with your teachers, advisors, or classmates, you can get valuable input that can help you refine your idea and make it even better.

Plus, it shows that you're serious about your project. Taking the time to write a concept paper demonstrates to your instructors that you've put thought and effort into your work, which can earn you some serious brownie points.

Understanding How Long is a Concept Paper

When it comes to the length of a concept paper, think quality over quantity. It's not about hitting a specific word count; it's about conveying your ideas clearly and concisely. In general, a concept paper is meant to be short and to the point. You want to give enough detail to explain your idea thoroughly, but you don't want to overwhelm your reader with unnecessary information.

As a rule of thumb, most concept papers range from 1 to 3 pages. However, this can vary depending on your specific assignment or the requirements of the project you're proposing.

The key is to focus on the essentials. Include a brief introduction to your topic, a clear statement of your purpose or objective, an overview of your methodology or approach, and a summary of the potential impact or significance of your project. And if you ever need further help, simply ask us - write my research paper for the professionally crafted project.

Concept Paper Vs. Research Paper

While both concept papers and research papers are common in academia, they serve different purposes and have distinct formats.

A concept paper, as we've discussed, is a concise document that outlines the basic idea or proposal for a project. It's like the blueprint or roadmap for your research endeavor. The focus here is on articulating the central concept, defining the objectives, and outlining the methodology. Think of writing a concept paper as laying the groundwork before diving into the detailed work of a research project.

On the other hand, a research paper is a more comprehensive and in-depth exploration of a topic or question. It involves conducting original research, analyzing data, and presenting findings in a formal written format. Research papers typically follow a structured format, including an introduction, literature review, methodology, results, discussion, and conclusion.

How to Write a Concept Paper in 8 Steps

Alright, getting into the nitty-gritty of writing your concept paper format might seem a bit overwhelming at first, but don't worry! We've got your back. By breaking down the process into eight manageable steps, we'll guide you through each stage with clarity and confidence.

Define the Study Title and Its Objectives

The first crucial step in crafting your concept paper is to clearly define the study title and its objectives. This sets the foundation for your entire paper and helps guide your research direction.

Begin by crafting a clear and concise title that effectively communicates the essence of your study. Your title should be descriptive yet succinct, giving readers a glimpse into the focus of your research.

Next, outline the objectives of your study. What specific goals do you aim to achieve through your research? Be precise and realistic in outlining these objectives, ensuring they are achievable within the scope of your study.

Explain the Study's Context and Extent

After defining the title and objectives, it's essential to provide context and define the extent of your study. This step of how to write a concept paper for college helps readers understand the background and scope of your research.

Start by providing background information on the topic of your study. Discuss relevant theories, concepts, or existing research that contextualizes your work and highlights its importance.

Next, define the extent of your study by outlining its boundaries and limitations. What specific aspects of the topic will you focus on, and what areas will you exclude? Clarifying these boundaries helps ensure that your research remains focused and manageable.

Additionally, consider discussing the significance of your study within the broader field. How does your research contribute to existing knowledge, and what potential impact does it have?

Identify the Issue

This is where you clearly articulate the core challenge or question that your research seeks to explore. Start by providing a concise overview of the issue at hand. What is the specific problem or question that motivates your research? Why is it important or relevant within your field of study?

Next, consider providing context or background information that helps readers understand the significance of the issue. This could include discussing relevant trends, statistics, or real-world examples that highlight the importance of addressing the problem.

Finally, be sure to articulate the significance of the issue within the broader context of your field. Why is it important to study this particular issue, and what potential impact could your research have on addressing it?

List Goals and Objectives

In this step, you'll make a concept paper outline of the specific goals and objectives of your study. Goals represent the broader aims of your research, while objectives provide clear, measurable steps toward achieving those goals.

Start by defining your overarching goals. What do you hope to accomplish through your research? Think about the broader outcomes or changes you aim to bring about in your field or community.

Next, break down these goals into smaller, achievable objectives. Objectives should be specific, measurable, achievable, relevant, and time-bound (SMART). They should outline the concrete steps you will take to accomplish your goals.

Consider organizing your goals and objectives into a hierarchical structure, with broader goals at the top and more specific objectives underneath. Even if you'd rather buy essay from our pros, this step will help you provide clarity and coherence to your research plan.

Approach and Methodology

In this step, you'll detail the approach and methodology you'll use to conduct your research. According to our expert thesis writing service , this section is crucial as it outlines the methods you'll employ to address your research question and achieve your objectives.

Start by explaining your overall approach to research. Will you be conducting qualitative or quantitative research, or perhaps a combination of both? Describe the rationale behind your chosen approach and how it aligns with your research goals.

Next, outline the specific methodologies you'll use to collect and analyze data. This may include methods such as surveys, interviews, experiments, or literature reviews. Provide justification for why each method is appropriate for addressing your research question and objectives.

Be sure to consider any ethical considerations or limitations associated with your chosen methodologies and outline how you plan to address them.

Finally, discuss your data analysis plan. How will you analyze the data you collect to draw meaningful conclusions? Will you use statistical analysis, thematic coding, or another method?

Overview of Planned Methods and Expected Outcomes

In this step of how to write a concept paper for research, you'll provide an overview of the specific methods you plan to use and outline the expected outcomes or results.

Start by summarizing the methods you'll employ to collect data. This may include qualitative methods such as interviews or focus groups, quantitative methods such as surveys or experiments, or a combination of both. Briefly explain why you've chosen these methods and how they align with your research goals.

Next, outline the planned steps for implementing each method. Describe the procedures you'll follow to collect and analyze data, including any tools or instruments you'll use.

After detailing your methods, discuss the expected outcomes or results of your research. What do you hope to learn or discover through your study? How will your findings contribute to existing knowledge in your field?

Be realistic in your expectations and consider potential challenges or limitations that may affect your results. By acknowledging these factors upfront, you demonstrate a thoughtful and nuanced understanding of your research process.

Include Supporting Details

Here, you'll enrich your concept paper by incorporating supporting details that bolster your argument and provide additional context for your research.

Start by providing relevant background information or literature reviews that support your research topic. This could include citing key studies, theories, or concepts that inform your understanding of the issue.

Next, consider including any relevant data, statistics, or examples that illustrate the significance of your research topic. This could involve presenting findings from previous studies, real-world examples, or case studies that highlight the need for further investigation.

Additionally, discuss any theoretical frameworks or conceptual models that underpin your research approach. How do these frameworks help guide your study and shape your research questions?

Finally, be sure to cite your sources properly using the appropriate citation style (e.g., APA, MLA). This demonstrates academic integrity and allows readers to verify the information you've presented.

Wrap Up with a Summary

In this final step, you'll bring your concept paper to a close by summarizing the key points and reinforcing the significance of your research.

If you're uncertain how to write a conclusion for an essay , start by briefly recapping the main elements of your concept paper, including the research topic, objectives, methodology, and expected outcomes. This helps reinforce the central message of your paper and reminds readers of the key insights you've presented.

Next, reiterate the importance of your research topic and its potential impact within your field. Emphasize how your study fills a gap in existing knowledge or addresses a pressing issue, highlighting the relevance and significance of your research.

Finally, conclude with a call to action or a thought-provoking statement that encourages further reflection or discussion. This could involve suggesting avenues for future research, proposing practical implications for policymakers or practitioners, or inviting readers to consider the broader implications of your findings.

Tips for Writing a Concept Paper

Now that you've got a solid understanding of how to write a concept paper, let's explore some invaluable tips to help you navigate the writing process with finesse.

• Be Specific in Your Objectives : Clearly define your objectives with measurable outcomes. Avoid vague language and ensure each objective is actionable and achievable within the scope of your study. Specific objectives provide clarity and help guide your research effectively.
• Provide Contextual Background : Offer sufficient background information to contextualize your research topic. This includes explaining relevant theories, historical context, or existing literature related to your study. Providing context in your concept paper helps readers understand the significance of your research and its relevance within the broader field.
• Justify Your Methodological Choices : Explain why you've chosen specific research methods and justify their appropriateness for your study. Consider factors such as feasibility, ethical considerations, and alignment with your research objectives. Providing a rationale for your methodological choices adds credibility to your research approach.
• Anticipate and Address Limitations : Acknowledge potential limitations or challenges associated with your study and discuss how you plan to mitigate them. This demonstrates a thoughtful approach to your research and shows that you've considered the broader implications of your study. Being transparent about limitations also helps manage expectations and build trust with your audience.

Concept Paper Example

Now that we've explored the steps and tips for writing a concept paper let's put theory into practice. In this section, we'll provide you with a concept paper example to illustrate how these principles can be applied in a real-world scenario.

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Concept Paper Topics

In this section, we'll provide you with a range of thought-provoking concept paper ideas spanning various disciplines and interests. Whether you're passionate about social issues, scientific advancements, or want to learn how to research a topic on cultural phenomena, you're sure to find inspiration here.

• The Influence of Instagram Fitness Influencers on Body Image Perception Among Adolescent Girls
• Implementing Bicycle-Sharing Programs to Reduce Carbon Emissions in Downtown Metropolitan Areas
• Analyzing the Effectiveness of Food Pantry Programs in Alleviating Food Insecurity Among Undergraduate Students at Urban Universities
• Assessing the Accuracy and Efficiency of Machine Learning Algorithms in Early Detection of Breast Cancer Using Medical Imaging Data
• Strategies for Increasing Female Representation in Computer Science and Engineering Programs at Universities
• Investigating the Impact of Workplace Mindfulness Programs on Employee Burnout Rates in High-stress Industries
• Barriers to Accessing Mental Health Services in Rural Appalachia: A Case Study
• The Ecological Impact of Microplastic Contamination on Coral Reef Ecosystems in the Caribbean
• Addressing Online Harassment and Cyberbullying Among Middle School Students Through Digital Literacy Education Programs
• The Relationship Between Proximity to Parks and Greenspaces and Mental Health Outcomes in Urban Dwellers: A Cross-sectional Study
• Virtual Reality Rehabilitation for Upper Limb Motor Recovery After Stroke: A Comparative Analysis of Traditional Therapy Methods
• Evaluating the Economic Viability and Environmental Sustainability of Indoor Vertical Farming Systems in Urban Settings
• Psychological Profiles of Adolescent Online Gamers: A Longitudinal Study on Risk Factors for Gaming Addiction
• Peer Mentoring Interventions for Improving Academic Performance and Retention Rates Among First-generation College Students in STEM Majors
• Universal Basic Income Pilot Programs: Assessing Socioeconomic Impacts and Policy Implications in Scandinavian Countries.

And there you have it - you've journeyed through the ins and outs of concept paper writing! You've learned the ropes, discovered valuable tips, explored an example, and got a bunch of topic ideas to fuel your creativity.

Now armed with the know-how, it's time to dive in and start crafting your concept paper. Remember to keep it focused, stay organized, and don't forget to let your passion shine through. With your enthusiasm and newfound skills, there's no doubt you'll create a paper that grabs attention and makes a real impact in your field.

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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Need Help Locating Statistics?

Resources for locating data and statistics can be found here:

Statistics & Data Research Guide

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

• The data is usually gathered using structured research instruments.
• The results are based on larger sample sizes that are representative of the population.
• The research study can usually be replicated or repeated, given its high reliability.
• Researcher has a clearly defined research question to which objective answers are sought.
• All aspects of the study are carefully designed before data is collected.
• Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
• Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
• Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

  Things to keep in mind when reporting the results of a study using quantitative methods :

• Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
• Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
• Explain the techniques you used to "clean" your data set.
• Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
• Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
• When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
• Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
• Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
• Always tell the reader what to look for in tables and figures .

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

• Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
• Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
• Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

• Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
• Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
• Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

• Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

• Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
• Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
• Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
• Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

• Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
• Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
• Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

• Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
• Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
• Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
• You can summarize vast sources of information and make comparisons across categories and over time; and,
• Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

• Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
• Uses a static and rigid approach and so employs an inflexible process of discovery;
• The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
• Results provide less detail on behavior, attitudes, and motivation;
• Researcher may collect a much narrower and sometimes superficial dataset;
• Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
• The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
• Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

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What is a Concept Paper and How do You Write One?

• By DiscoverPhDs
• August 26, 2020

What is a Concept Paper?

A concept paper is a short document written by a researcher before starting their research project, with the purpose of explaining what the study is about, why it is important and the methods that will be used.

The concept paper will include your proposed research title, a brief introduction to the subject, the aim of the study, the research questions you intend to answer, the type of data you will collect and how you will collect it. A concept paper can also be referred to as a research proposal.

What is the Purpose of a Concept Paper?

The primary aim of a research concept paper is to convince the reader that the proposed research project is worth doing. This means that the reader should first agree that the research study is novel and interesting. They should be convinced that there is a need for this research and that the research aims and questions are appropriate.

Finally, they should be satisfied that the methods for data collection proposed are feasible, are likely to work and can be performed within the specific time period allocated for this project.

The three main scenarios in which you may need to write a concept paper are if you are:

• A final year undergraduate or master’s student preparing to start a research project with a supervisor.
• A student submitting a research proposal to pursue a PhD project under the supervision of a professor.
• A principal investigator submitting a proposal to a funding body to secure financial support for a research project.

How Long is a Concept Paper?

The concept paper format is usually between 2 and 3 pages in length for students writing proposals for undergraduate, master’s or PhD projects. Concept papers written as part of funding applications may be over 20 pages in length.

How do you Write a Concept Paper?

There are 6 important aspects to consider when writing a concept paper or research proposal:

• 1. The wording of the title page, which is best presented as a question for this type of document. At this study concept stage, you can write the title a bit catchier, for example “Are 3D Printed Engine Parts Safe for Use in Aircraft?”.
• A brief introduction and review of relevant existing literature published within the subject area and identification of where the gaps in knowledge are. This last bit is particularly important as it guides you in defining the statement of the problem. The concept paper should provide a succinct summary of ‘the problem’, which is usually related to what is unknown or poorly understood about your research topic . By the end of the concept paper, the reader should be clear on how your research idea will provide a ‘solution’ to this problem.
• The overarching research aim of your proposed study and the objectives and/or questions you will address to achieve this aim. Align all of these with the problem statement; i.e. write each research question as a clear response to addressing the limitations and gaps identified from previous literature. Also give a clear description of your primary hypothesis.
• The specific data outputs that you plan to capture. For example, will this be qualitative or quantitative data? Do you plan to capture data at specific time points or at other defined intervals? Do you need to repeat data capture to asses any repeatability and reproducibility questions?
• The research methodology you will use to capture this data, including any specific measurement or analysis equipment and software you will use, and a consideration of statistical tests to help interpret the data. If your research requires the use of questionnaires, how will these be prepared and validated? In what sort of time frame would you plan to collect this data?
• Finally, include a statement of the significance of the study , explaining why your research is important and impactful. This can be in the form of a concluding paragraph that reiterate the statement of the problem, clarifies how your research will address this and explains who will benefit from your research and how.

You may need to include a short summary of the timeline for completing the research project. Defining milestones of the time points at which you intend to complete certain tasks can help to show that you’ve considered the practicalities of running this study. It also shows that what you have proposed is feasible in order to achieve your research goal.

If you’re pitching your proposed project to a funder, they may allocate a proportion of the money based on the satisfactory outcome of each milestone. These stakeholders may also be motivated by knowing that you intend to convert your dissertation into an article for journal publication; this level of dissemination is of high importance to them.

Additionally, you may be asked to provide a brief summary of the projected costs of running the study. For a PhD project this could be the bench fees associated with consumables and the cost of any travel if required.

Make sure to include references and cite all other literature and previous research that you discuss in your concept paper.

This guide gave you an overview of the key elements you need to know about when writing concept papers. The purpose of these are first to convey to the reader what your project’s purpose is and why your research topic is important; this is based on the development of a problem statement using evidence from your literature review.

Explain how it may positively impact your research field and if your proposed research design is appropriate and your planned research method achievable.

Do you need to have published papers to do a PhD? The simple answer is no but it could benefit your application if you can.

In this post you’ll learn what the significance of the study means, why it’s important, where and how to write one in your paper or thesis with an example.

A science investigatory project is a science-based research project or study that is performed by school children in a classroom, exhibition or science fair.

Join thousands of other students and stay up to date with the latest PhD programmes, funding opportunities and advice.

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The purpose of research is to enhance society by advancing knowledge through developing scientific theories, concepts and ideas – find out more on what this involves.

Dr Pattison gained his PhD in Cosmology from the University of Portsmouth. He is now finishing a short term post-doc within the same research group and developing a career in science communication and science education.

Dr Smethurst gained her DPhil in astrophysics from the University of Oxford in 2017. She is now an independent researcher at Oxford, runs a YouTube channel with over 100k subscribers and has published her own book.

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Quantitative Research

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Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data. Descartes, the seventeenth-century philosopher, suggested that how the results are achieved is often more important than the results themselves, as the journey taken along the research path is a journey of discovery. High-quality quantitative research is characterized by the attention given to the methods and the reliability of the tools used to collect the data. The ability to critique research in a systematic way is an essential component of a health professional’s role in order to deliver high quality, evidence-based healthcare. This chapter is intended to provide a simple overview of the way new researchers and health practitioners can understand and employ quantitative methods. The chapter offers practical, realistic guidance in a learner-friendly way and uses a logical sequence to understand the process of hypothesis development, study design, data collection and handling, and finally data analysis and interpretation.

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Babbie ER. The practice of social research. 14th ed. Belmont: Wadsworth Cengage; 2016.

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Wilson LA, Black DA. Health, science research and research methods. Sydney: McGraw Hill; 2013.

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Wilson, L.A. (2019). Quantitative Research. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_54

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Key Concepts in Quantitative Research

In this module, we are going to explore the nuances of quantitative research, including the main types of quantitative research, more exploration into variables (including confounding and extraneous variables), and causation.

Content includes:

• Flaws, “Proof”, and Rigor
• The Steps of Quantitative Methodology
• Major Classes of Quantitative Research
• Experimental versus Non-Experimental Research
• Types of Experimental Research
• Types of Non-Experimental Research
• Research Variables
• Confounding/Extraneous Variables
• Causation versus correlation/association

Objectives:

• Discuss the flaws, proof, and rigor in research.
• Describe the differences between independent variables and dependent variables.
• Describe the steps in quantitative research methodology.
• Describe experimental, quasi-experimental, and non-experimental research studies
• Describe confounding and extraneous variables.
• Differentiate cause-and-effect (causality) versus association/correlation

Flaws, Proof, and Rigor in Research

One of the biggest hurdles that students and seasoned researchers alike struggle to grasp, is that research cannot “ prove ” nor “ disprove ”. Research can only support a hypothesis with reasonable, statistically significant evidence.

Indeed. You’ve heard it incorrectly your entire life. You will hear professors, scientists, radio ads, podcasts, and even researchers comment something to the effect of, “It has been proven that…” or “Research proves that…” or “Finally! There is proof that…”

We have been duped. Consider the “ prove ” word a very bad word in this course. The forbidden “P” word. Do not say it, write it, allude to it, or repeat it. And, for the love of avocados and all things fluffy, do not include the “P” word on your EBP poster. You will be deducted some major points.

We can only conclude with reasonable certainty through statistical analyses that there is a high probability that something did not happen by chance but instead happened due to the intervention that the researcher tested. Got that? We will come back to that concept but for now know that it is called “statistical significance”.

All research has flaws. We might not know what those flaws are, but we will be learning about confounding and extraneous variables later on in this module to help explain how flaws can happen.

Remember this: Sometimes, the researcher might not even know that there was a flaw that occurred. No research project is perfect. There is no 100% awesome. This is a major reason why it is so important to be able to duplicate a research project and obtain similar results. The more we can duplicate research with the same exact methodology and protocols, the more certainty we have in the results and we can start accounting for flaws that may have sneaked in.

Finally, not all research is equal. Some research is done very sloppily, and other research has a very high standard of rigor. How do we know which is which when reading an article? Well, within this module, we will start learning about some things to look for in a published research article to help determine rigor. We do not want lazy research to determine our actions as nurses, right? We want the strongest, most reliable, most valid, most rigorous research evidence possible so that we can take those results and embed them into patient care. Who wants shoddy evidence determining the actions we take with your grandmother’s heart surgery?

Independent Variables and Dependent Variables

As we were already introduced to, there are measures called “variables” in research. This will be a bit of a review but it is important to bring up again, as it is a hallmark of quantitative research. In quantitative studies, the concepts being measured are called variables (AKA: something that varies). Variables are something that can change – either by manipulation or from something causing a change. In the article snapshots that we have looked at, researchers are trying to find causes for phenomena. Does a nursing intervention cause an improvement in patient outcomes? Does the cholesterol medication cause a decrease in cholesterol level? Does smoking cause  cancer?

The presumed cause is called the independent variable. The presumed effect is called the dependent variable. The dependent variable is “dependent” on something causing it to change. The dependent variable is the outcome that a researcher is trying to understand, explain, or predict.

Think back to our PICO questions. You can think of the intervention (I) as the independent variable and the outcome (O) as the dependent variable.

The independent variable is manipulated by the researcher or can be variants of influence. Whereas the dependent variable is never manipulated.

Variables do not always measure cause-and-effect. They can also measure a direction of influence.

Here is an example of that: If we compared levels of depression among men and women diagnosed with pancreatic cancer and found men to be more depressed, we cannot conclude that depression was caused by gender. However, we can note that the direction of influence   clearly runs from gender to depression. It makes no sense to suggest the depression influenced their gender.

In the above example, what is the independent variable (IV) and what is the dependent variable (DV)? If you guessed gender as the IV and depression as the DV, you are correct! Important to note in this case that the researcher did not manipulate the IV, but the IV is manipulated on its own (male or female).

Researchers do not always have just one IV. In some cases, more than one IV may be measured. Take, for instance, a study that wants to measure the factors that influence one’s study habits. Independent variables of gender, sleep habits, and hours of work may be considered. Likewise, multiple DVs can be measured. For example, perhaps we want to measure weight and abdominal girth on a plant-based diet (IV).

Now, some studies do not have an intervention. We will come back to that when we talk about non-experimental research.

The point of variables is so that researchers have a very specific measurement that they seek to study.

Let’s look at a couple of examples:

Now you try! Identify the IVs and DVs:

IV and DV Case Studies (Leibold, 2020)

Case Three:   Independent variable: Healthy Lifestyle education with a focus on physical activity; Dependent variable: Physical activity rate before and after education intervention, Heart rate before and after education intervention, Blood pressures before and after education intervention.

Case Four:   Independent variable: Playing classical music; Dependent variable:  Grade point averages post classical music, compared to pre-classical music.

Case Five: Independent variable: No independent variable as there is no intervention.  Dependent variable: The themes that emerge from the qualitative data.

The Steps in Quantitative Research Methodology

Now, as we learned in the last module, quantitative research is completely objective. There is no subjectivity to it. Why is this? Well, as we have learned, the purpose of quantitative research is to make an inference about the results in order to generalize these results to the population.

In quantitative studies, there is a very systematic approach that moves from the beginning point of the study (writing a research question) to the end point (obtaining an answer). This is a very linear and purposeful flow across the study, and all quantitative research should follow the same sequence.

• Identifying a problem and formulating a research question . Quantitative research begins with a theory . As in, “something is wrong and we want to fix it or improve it”.  Think back to when we discussed research problems and formulating a research question. Here we are! That is the first step in formulating a quantitative research plan.
• Formulate a hypothesis . This step is key. Researchers need to know exactly what they are testing so that testing the hypothesis can be achieved through specific statistical analyses.
• A thorough literature review .  At this step, researchers strive to understand what is already known about a topic and what evidence already exists.
• Identifying a framework .  When an appropriate framework is identified, the findings of a study may have broader significance and utility (Polit & Beck, 2021).
• Choosing a study design . The research design will determine exactly how the researcher will obtain the answers to the research question(s). The entire design needs to be structured and controlled, with the overarching goal of minimizing bias and errors. The design determines what data will be collected and how, how often data will be collected, what types of comparisons will be made. You can think of the study design as the architectural backbone of the entire study.
• Sampling . The researcher needs to determine a subset of the population that is to be studied. We will come back to the sampling concept in the next module. However, the goal of sampling is to choose a subset of the population that adequate reflects the population of interest.
• I nstruments to be used to collect data (with reliability and validity as a priority). Researchers must find a way to measure the research variables (intervention and outcome) accurately. The task of measuring is complex and challenging, as data needs to be collected reliably (measuring consistently each time) and valid. Reliability and validity are both about how well a method measures something. The next module will cover this in detail.
• Obtaining approval for ethical/legal human rights procedures . As we will learn in an upcoming module, there needs to be methods in place to safeguard human rights.
• Data collection . The fun part! Finally, after everything has been organized and planned, the researcher(s) begin to collect data. The pre-established plan (methodology) determines when data collection begins, how to accomplish it, how data collection staff will be trained, and how data will be recorded.
• Data analysis . Here comes the statistical analyses. The next module will dive into this.
• Discussion . After all the analyses have been complete, the researcher then needs to interpret the results and examine the implications. Researchers attempt to explain the findings in light of the theoretical framework, prior evidence, theory, clinical experience, and any limitations in the study now that it has been completed. Often, the researcher discusses not just the statistical significance, but also the clinical significance, as it is common to have one without the other.
• Summary/references . Part of the final steps of any research project is to disseminate (AKA: share) the findings. This may be in a published article, conference, poster session, etc. The point of this step is to communicate to others the information found through the study.  All references are collected so that the researchers can give credit to others.
• Budget and funding . As a last mention in the overall steps, budget and funding for research is a consideration. Research can be expensive. Often, researchers can obtain a grant or other funding to help offset the costs.

Edit: Steps in Quantitative Research video. Step 12 should say “Dissemination” (sharing the results).

Experimental, Quasi-Experimental, and Non-Experimental Studies

To start this section, please watch this wonderful video by Jenny Barrow, MSN, RN, CNE, that explains experimental versus nonexperimental research.

(Jenny Barrow, 2019)

Now that you have that overview, continue reading this module.

Experimental Research : In experimental research, the researcher is seeking to draw a conclusion between an independent variable and a dependent variable. This design attempts to establish cause-effect relationships among the variables. You could think of experimental research as experimenting with “something” to see if it caused “something else”.

A true experiment is called a Randomized Controlled Trial (or RCT). An RCT is at the top of the echelon as far as quantitative experimental research. It’s the gold standard of scientific research. An RCT, a true experimental design, must have 3 features:

• An intervention : The experiment does something to the participants by the option of manipulating the independent variable.
• Control : Some participants in the study receive either the standard care, or no intervention at all. This is also called the counterfactual – meaning, it shows what would happen if no intervention was introduced.
• Randomization : Randomization happens when the researcher makes sure that it is completely random who receives the intervention and who receives the control. The purpose is to make the groups equal regarding all other factors except receipt of the intervention.

Note: There is a lot of confusion with students (and even some researchers!) when they refer to “ random assignment ” versus “ random sampling ”. Random assignment  is a signature of a true experiment. This means that if participants are not truly randomly assigned to intervention groups, then it is not a true experiment. We will talk more about random sampling in the next module.

One very common method for RCT’s is called a pretest-posttest design .  This is when the researcher measures the outcome before and after the intervention. For example, if the researcher had an IV (intervention/treatment) of a pain medication, the DV (pain) would be measured before the intervention is given and after it is given. The control group may just receive a placebo. This design permits the researcher to see if the change in pain was caused by the pain medication because only some people received it (Polit & Beck, 2021).

Another experimental design is called a crossover design . This type of design involves exposing participants to more than one treatment. For example, subject 1 first receives treatment A, then treatment B, then treatment C. Subject 2 might first receive treatment B, then treatment A, and then treatment C. In this type of study, the three conditions for an experiment are met: Intervention, randomization, and control – with the subjects serving as their own control group.

Control group conditions can be done in 4 ways:

• No intervention is used; control group gets no treatment at all
• “Usual care” or standard of care or normal procedures used
• An alternative intervention is uses (e.g. auditory versus visual stimulation)
• A placebo or pseudo-intervention, presumed to have no therapeutic value, is used

Quasi-Experimental Research : Quasi-experiments involve an experiment just like true experimental research. However, they lack randomization and some even lack a control group.  Therefore, there is implementation and testing of an intervention, but there is an absence of randomization.

For example, perhaps we wanted to measure the effect of yoga for nursing students. The IV (intervention of yoga) is being offered to all nursing students and therefore randomization is not possible. For comparison, we could measure quality of life data on nursing students at a different university. Data is collected from both groups at baseline and then again after the yoga classes. Note, that in quasi-experiments, the phrase “comparison group” is sometimes used instead of “control group” against which outcome measures are collected.

Sometimes there is no comparison group either. This would be called a one-group pretest-posttest design .

Non-Experimental Research : Sometimes, cause-problem research questions cannot be answered with an experimental or quasi-experimental design because the IV cannot be manipulated. For example, if we want to measure what impact prerequisite grades have on student success in nursing programs, we obviously cannot manipulate the prerequisite grades. In another example, if we wanted to investigate how low birth weight impacts developmental progression in children, we cannot manipulate the birth weight. Often, you will see the word “observational” in lieu of non-experimental researcher. This does not mean the researcher is just standing and watching people, but instead it refers to the method of observing data that has already been established without manipulation.

There are various types of non-experimental research:

Correlational research : A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. In the example of prerequisites and nursing program success, that is a correlational design. Consider hypothetically, a researcher is studying a correlation between cancer and marriage. In this study, there are two variables: disease and marriage. Let us say marriage has a negative association with cancer. This means that married people are less likely to develop cancer.

Cohort design (also called a prospective design) : In a cohort study, the participants do not have the outcome of interest to begin with. They are selected based on the exposure status of the individual. They are then followed over time to evaluate for the occurrence of the outcome of interest. Cohorts may be divided into exposure categories once baseline measurements of a defined population are made. For example, the Framingham Cardiovascular Disease Study (CVD) used baseline measurements to divide the population into categories of CVD risk factors. Another example:  An example of a cohort study is comparing the test scores of one group of people who underwent extensive tutoring and a special curriculum and those who did not receive any extra help. The group could be studied for years to assess whether their scores improve over time and at what rate.

Retrospective design : In retrospective studies, the outcome of interest has already occurred (or not occurred – e.g., in controls) in each individual by the time s/he is enrolled, and the data are collected either from records or by asking participants to recall exposures. There is no follow-up of participants. For example, a researcher might examine the medical histories of 1000 elderly women to identify the causes of health problems.

Case-control design : A study that compares two groups of people: those with the disease or condition under study (cases) and a very similar group of people who do not have the condition. For example, investigators conducted a case-control study to determine if there is an association between colon cancer and a high fat diet. Cases were all confirmed colon cancer cases in North Carolina in 2010. Controls were a sample of North Carolina residents without colon cancer.

Descriptive research : Descriptive research design is a type of research design that aims to obtain information to systematically describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem, rather than the why. For example, the researcher might wish to discover the percentage of motorists who tailgate – the prevalence  of a certain behavior.

There are two other designs to mention, which are both on a time continuum basis.

Cross-sectional design : All data are collected at a single point in time. Retrospective studies are usually cross-sectional. The IV usually concerns events or behaviors occurring in the past. One cross-sectional study example in medicine is a data collection of smoking habits and lung cancer incidence in a given population. A cross-sectional study like this cannot solely determine that smoking habits cause lung cancer, but it can suggest a relationship that merits further investigation. Cross-sectional studies serve many purposes, and the cross-sectional design is the most relevant design when assessing the prevalence of disease, attitudes and knowledge among patients and health personnel, in validation studies comparing, for example, different measurement instruments, and in reliability studies.

Longitudinal design : Data are collected two or more times over an extended period. Longitudinal designs are better at showing patterns of change and at clarifying whether a cause occurred before an effect (outcome). A challenge in longitudinal studies is attrition or the loss of participants over time. In a longitudinal study subjects are followed over time with continuous or repeated monitoring of risk factors or health outcomes, or both. Such investigations vary enormously in their size and complexity. At one extreme a large population may be studied over decades. An example of a longitudinal design is a multiyear comparative study of the same children in an urban and a suburban school to record their cognitive development in depth.

Confounding and Extraneous Variables

Confounding variables  are a type of extraneous variable that occur which interfere with or influence the relationship between the independent and dependent variables. In research that investigates a potential cause-and-effect relationship, a confounding variable is an unmeasured third variable that influences both the supposed cause and the supposed effect.

It’s important to consider potential confounding variables and account for them in research designs to ensure results are valid. You can imagine that if something sneaks in to influence the measured variables, it can really muck up the study!

Here is an example:

You collect data on sunburns and ice cream consumption. You find that higher ice cream consumption is associated with a higher probability of sunburn. Does that mean ice cream consumption causes sunburn?

Here, the confounding variable is temperature: hot temperatures cause people to both eat more ice cream and spend more time outdoors under the sun, resulting in more sunburns.

To ensure the internal validity of research, the researcher must account for confounding variables. If he/she fails to do so, the results may not reflect the actual relationship between the variables that they are interested in.

For instance, they may find a cause-and-effect relationship that does not actually exist, because the effect they measure is caused by the confounding variable (and not by the independent variable).

Here is another example:

The researcher finds that babies born to mothers who smoked during their pregnancies weigh significantly less than those born to non-smoking mothers. However, if the researcher does not account for the fact that smokers are more likely to engage in other unhealthy behaviors, such as drinking or eating less healthy foods, then he/she might overestimate the relationship between smoking and low birth weight.

Extraneous variables are any variables that the researcher is not investigating that can potentially affect the outcomes of the research study. If left uncontrolled, extraneous variables can lead to inaccurate conclusions about the relationship between IVs and DVs.

Extraneous variables can threaten the internal validity of a study by providing alternative explanations for the results. In an experiment, the researcher manipulates an independent variable to study its effects on a dependent variable.

In a study on mental performance, the researcher tests whether wearing a white lab coat, the independent variable (IV), improves scientific reasoning, the dependent variable (DV).

Students from a university are recruited to participate in the study. The researcher manipulates the independent variable by splitting participants into two groups:

• Participants in the experimental   group are asked to wear a lab coat during the study.
• Participants in the control group are asked to wear a casual coat during the study.

All participants are given a scientific knowledge quiz, and their scores are compared between groups.

When extraneous variables are uncontrolled, it’s hard to determine the exact effects of the independent variable on the dependent variable, because the effects of extraneous variables may mask them.

Uncontrolled extraneous variables can also make it seem as though there is a true effect of the independent variable in an experiment when there’s actually none.

In the above experiment example, these extraneous variables can affect the science knowledge scores:

• Participant’s major (e.g., STEM or humanities)
• Participant’s interest in science
• Demographic variables such as gender or educational background
• Time of day of testing
• Experiment environment or setting

If these variables systematically differ between the groups, you can’t be sure whether your results come from your independent variable manipulation or from the extraneous variables.

In summary, an extraneous variable is anything that could influence the dependent variable. A confounding variable influences the dependent variable, and also correlates with or causally affects the independent variable.

Cause-and-Effect (Causality) Versus Association/Correlation  

A very important concept to understand is cause-and-effect, also known as causality, versus correlation. Let’s look at these two concepts in very simplified statements. Causation means that one thing caused  another thing to happen. Correlation means there is some association between the two thing we are measuring.

It would be nice if it were as simple as that. These two concepts can indeed by confused by many. Let’s dive deeper.

Two or more variables are considered to be related or associated, in a statistical context, if their values change so that as the value of one variable increases or decreases so does the value of the other variable (or the opposite direction).

For example, for the two variables of “hours worked” and “income earned”, there is a relationship between the two if the increase in hours is associated with an increase in income earned.

However, correlation is a statistical measure that describes the size and direction of a relationship between two or more variables. A correlation does not automatically mean that the change in one variable caused the change in value in the other variable.

Theoretically, the difference between the two types of relationships is easy to identify — an action or occurrence can cause another (e.g. smoking causes an increase in the risk of developing lung cancer), or it can correlate with another (e.g. smoking is correlated with alcoholism, but it does not cause alcoholism). In practice, however, it remains difficult to clearly establish cause and effect, compared with establishing correlation.

Simplified in this image, we can say that hot and sunny weather causes an increase in ice cream consumption. Similarly, we can demise that hot and sunny weather increases the incidence of sunburns. However, we cannot say that ice cream caused a sunburn (or that a sunburn increases consumption of ice cream). It is purely coincidental. In this example, it is pretty easy to anecdotally surmise correlation versus causation. However, in research, we have statistical tests that help researchers differentiate via specialized analyses.

Here is a great Khan Academy video of about 5 minutes that shows a worked example of correlation versus causation with regard to sledding accidents and frostbite cases:

https://www.khanacademy.org/test-prep/praxis-math/praxis-math-lessons/gtp–praxis-math–lessons–statistics-and-probability/v/gtp–praxis-math–video–correlation-and-causation

References & Attribution

“ Light bulb doodle ” by rawpixel licensed CC0 .

“ Magnifying glass ” by rawpixel licensed CC0

“ Orange flame ” by rawpixel licensed CC0 .

Jenny Barrow. (2019). Experimental versus nonexperimental research. https://www.youtube.com/watch?v=FJo8xyXHAlE

Leibold, N. (2020). Research variables. Measures and Concepts Commonly Encountered in EBP. Creative Commons License: BY NC

Polit, D. & Beck, C. (2021).  Lippincott CoursePoint Enhanced for Polit’s Essentials of Nursing Research  (10th ed.). Wolters Kluwer Health.

Evidence-Based Practice & Research Methodologies Copyright © by Tracy Fawns is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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How To Write a Concept Paper for Academic Research: An Ultimate Guide

A concept paper is one of the first steps in helping you fully realize your research project. Because of this, some schools opt to teach students how to write concept papers as early as high school. In college, professors sometimes require their students to submit concept papers before suggesting their research projects to serve as the foundations for their theses.

If you’re reading this right now, you’ve probably been assigned by your teacher or professor to write a concept paper. To help you get started, we’ve prepared a comprehensive guide on how to write a proper concept paper.

Related: How to Write Significance of the Study (with Examples)

Table of Contents

What is the concept paper, 1. academic research concept papers, 2. advertising concept papers, 3. research grant concept papers, concept paper vs. research proposal, tips for finding your research topic, 2. think of research questions that you want to answer in your project, 3. formulate your research hypothesis, 4. plan out how you will achieve, analyze, and present your data, 2. introduction, 3. purpose of the study, 4. preliminary literature review, 5. objectives of the study, 6. research questions and hypotheses, 7. proposed methodology, 8. proposed research timeline, 9. references, sample concept paper for research proposal (pdf), tips for writing your concept paper.

Generally, a concept paper is a summary of everything related to your proposed project or topic. A concept paper indicates what the project is all about, why it’s important, and how and when you plan to conduct your project.

Different Types of the Concept Paper and Their Uses

This type of concept paper is the most common type and the one most people are familiar with. Concept papers for academic research are used by students to provide an outline for their prospective research topics.

These concept papers are used to help students flesh out all the information and ideas related to their topic so that they may arrive at a more specific research hypothesis.

Since this is the most common type of concept paper, it will be the main focus of this article.

Advertising concept papers are usually written by the creative and concept teams in advertising and marketing agencies.

Through a concept paper, the foundation or theme for an advertising campaign or strategy is formed. The concept paper can also serve as a bulletin board for ideas that the creative and concept teams can add to or develop. 

This type of concept paper usually discusses who the target audience of the campaign is, what approach of the campaign will be, how the campaign will be implemented, and the projected benefits and impact of the campaign to the company’s sales, consumer base, and other aspects of the company.

This type of concept paper is most common in the academe and business world. Alongside proving why your research project should be conducted, a research grant concept paper must also appeal to the company or funding agency on why they should be granted funds.

The paper should indicate a proposed timeline and budget for the entire project. It should also be able to persuade the company or funding agency on the benefits of your research project– whether it be an increase in sales or productivity or for the benefit of the general public.

It’s important to discuss the differences between the two because a lot of people often use these terms interchangeably.

A concept paper is one of the first steps in conducting a research project. It is during this process that ideas and relevant information to the research topic are gathered to produce the research hypothesis. Thus, a concept paper should always precede the research proposal. 

A research proposal is a more in-depth outline of a more fleshed-out research project. This is the final step before a researcher can conduct their research project. Although both have similar elements and structures, a research proposal is more specific when it comes to how the entire research project will be conducted.

Getting Started on Your Concept Paper

1. find a research topic you are interested in.

When choosing a research topic, make sure that it is something you are passionate about or want to learn more about. If you are writing one for school, make sure it is still relevant to the subject of your class. Choosing a topic you aren’t invested in may cause you to lose interest in your project later on, which may lower the quality of the research you’ll produce.

A research project may last for months and even years, so it’s important that you will never lose interest in your topic.

• Look for inspiration everywhere. Take a walk outside, read books, or go on your computer. Look around you and try to brainstorm ideas about everything you see. Try to remember any questions you might have asked yourself before like why something is the way it is or why can’t this be done instead of that . 
• Think big. If you’re having trouble thinking up a specific topic to base your research project on, choosing a broad topic and then working your way down should help.
• Is it achievable? A lot of students make the mistake of choosing a topic that is hard to achieve in terms of materials, data, and/or funding available. Before you decide on a research topic, make sure you consider these aspects. Doing so will save you time, money, and effort later on.
• Be as specific as can be. Another common mistake that students make is that they sometimes choose a research topic that is too broad. This results in extra effort and wasted time while conducting their research project. For example: Instead of “The Effects of Bananas on Hungry Monkeys” , you could specify it to “The Effects of Cavendish Bananas on Potassium-deficiency in Hungry Philippine Long-tailed Macaques in Palawan, Philippines”.

Now that you have a general idea of the topic of your research project, you now need to formulate research questions based on your project. These questions will serve as the basis for what your project aims to answer. Like your research topic, make sure these are specific and answerable.

Following the earlier example, possible research questions could be:

• Do Cavendish bananas produce more visible effects on K-deficiency than other bananas?
• How susceptible are Philippine long-tailed macaques to K-deficiency?
• What are the effects of K-deficiency in Philippine long-tailed macaques?

After formulating the research questions, you should also provide your hypothesis for each question. A research hypothesis is a tentative answer to the research problem. You must provide educated answers to the questions based on your existing knowledge of the topic before you conduct your research project.

After conducting research and collecting all of the data into the final research paper, you will then have to approve or disprove these hypotheses based on the outcome of the project.

Prepare a plan on how to acquire the data you will need for your research project. Take note of the different types of analysis you will need to perform on your data to get the desired results. Determine the nature of the relationship between different variables in your research.

Also, make sure that you are able to present your data in a clear and readable manner for those who will read your concept paper. You can achieve this by using tables, charts, graphs, and other visual aids.

Related: How to Make Conceptual Framework (with Examples and Templates)

Generalized Structure of a Concept Paper

Since concept papers are just summaries of your research project, they are usually short and  no longer than 5 pages. However, for big research projects, concept papers can reach up to more than 20 pages.

Your teacher or professor may give you a certain format for your concept papers. Generally, most concept papers are double-spaced and are less than 500 words in length. 

Even though there are different types of concept papers, we’ve provided you with a generalized structure that contains elements that can be found in any type of concept paper.

The title for your paper must be able to effectively summarize what your research is all about. Use simple words so that people who read the title of your research will know what it’s all about even without reading the entire paper. 

The introduction should give the reader a brief background of the research topic and state the main objective that your project aims to achieve. This section should also include a short overview of the benefits of the research project to persuade the reader to acknowledge the need for the project.

The Purpose of the Study should be written in a way that convinces the reader of the need to address the existing problem or gap in knowledge that the research project aims to resolve. In this section, you have to go into more detail about the benefits and value of your project for the target audience/s. 

This section features related studies and papers that will support your research topic. Use this section to analyze the results and methodologies of previous studies and address any gaps in knowledge or questions that your research project aims to answer. You may also use the data to assert the importance of conducting your research.

When choosing which papers and studies you should include in the Preliminary Literature Review, make sure to choose relevant and reliable sources. Reliable sources include academic journals, credible news outlets, government websites, and others. Also, take note of the authors for the papers as you will need to cite them in the References section.

Simply state the main objectives that your research is trying to achieve. The objectives should be able to indicate the direction of the study for both the reader and the researcher. As with other elements in the paper, the objectives should be specific and clearly defined.

Gather the research questions and equivalent research hypotheses you formulated in the earlier step and list them down in this section.

In this section, you should be able to guide the reader through the process of how you will conduct the research project. Make sure to state the purpose for each step of the process, as well as the type of data to be collected and the target population.

Depending on the nature of your research project, the length of the entire process can vary significantly. What’s important is that you are able to provide a reasonable and achievable timeline for your project.

Make sure the time you will allot for each component of your research won’t be too excessive or too insufficient so that the quality of your research won’t suffer.

Ensure that you will give credit to all the authors of the sources you used in your paper. Depending on your area of study or the instructions of your professor, you may need to use a certain style of citation.

There are three main citation styles: the American Psychological Association (APA), Modern Language Association (MLA), and the Chicago style.

The APA style is mostly used for papers related to education, psychology, and the sciences. The APA citation style usually follows this format:

The MLA citation style is the format used by papers and manuscripts in disciplines related to the arts and humanities. The MLA citation style follows this format:

The Chicago citation style is usually used for papers related to business, history, and the fine arts. It follows this citation format:

This is a concept paper sample provided by Dr. Bernard Lango from the Jomo Kenyatta University of Agriculture and Technology (modified for use in this article). Simply click the link above the download the PDF file.

• Use simple, concise language. Minimize the use of flowery language and always try to use simple and easy-to-understand language. Too many technical or difficult words in your paper may alienate your readers and make your paper hard to read. 
• Choose your sources wisely. When scouring the Internet for sources to use, you should always be wary and double-check the authenticity of your source. Doing this will increase the authenticity of your research project’s claims and ensure better data gathered during the process.
• Follow the specified format, if any. Make sure to follow any specified format when writing your concept paper. This is very important, especially if you’re writing your concept paper for class. Failure to follow the format will usually result in point deductions and delays because of multiple revisions needed.
• Proofread often. Make it a point to reread different sections of your concept paper after you write them. Another way you can do this is by taking a break for a few days and then coming back to proofread your writing. You may notice certain areas you’d like to revise or mistakes you’d like to fix. Make proofreading a habit to increase the quality of your paper.

Written by Ruth Raganit

in Career and Education , Juander How

Last Updated May 30, 2022 04:34 PM

Ruth Raganit

Ruth Raganit obtained her Bachelor of Science degree in Geology from the University of the Philippines – Diliman. Her love affair with Earth sciences began when she saw a pretty rock and wondered how it came to be. She also likes playing video games, doing digital art, and reading manga.

Browse all articles written by Ruth Raganit

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• Published: 30 April 2024

Developing more useful equity measurements for flood-risk management

• Adam B. Pollack   ORCID: orcid.org/0000-0001-6642-0591 1 ,
• Casey Helgeson   ORCID: orcid.org/0000-0001-5333-9954 2 , 3 ,
• Carolyn Kousky 4 &
• Klaus Keller   ORCID: orcid.org/0000-0002-5451-8687 1  

Nature Sustainability ( 2024 ) Cite this article

Metrics details

• Climate-change policy
• Natural hazards

Decision-makers increasingly invoke equity to motivate, design, implement and evaluate strategies for managing flood risks. Unfortunately, there is little guidance on how analysts can develop measurements that support these tasks. Here we analyse how equity can be defined and measured by surveying 167 peer-reviewed publications that explicitly state an interest in equity in the context of flood-risk management. Our main result is a taxonomy that systematizes how equity has been, and can be, defined and measured in flood-risk research. The taxonomy embodies how equity is a pluralistic and unavoidably ethical concept. Despite this, we find that most quantitative studies fail to motivate or defend critical value judgements on which their findings depend. We also find that studies often include only a single equity measurement. This practice can overlook important trade-offs between competing perspectives on equity. For example, the few studies that employ distinct principles show that conclusions about equity depend on which principle underlies a specific measurement and how that principle is operationalized. We draw on our analysis to suggest practices for developing more useful equity indicators and performing more comprehensive quantitative equity assessments in the broader context of environmental risks.

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Data availability

All data and materials used in the analysis are freely and permanently available via Zenodo 115 . This analysis was tested and confirmed for reproducibility by S. Baboolal on 11 July 2023. If you have any issues reproducing the results, please contact the corresponding author on the GitHub repository.

Code availability

All code used in the analysis are freely and permanently available via Zenodo 115 . This analysis was tested and confirmed for reproducibility by S. Baboolal on 11 July 2023. If you have any issues reproducing the results, please contact the corresponding author on the GitHub repository.

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Acknowledgements

We thank D. Spiegelman for an annotated bibliography of several key references; C. Bacon, M. Budolfson, C. Cooper, J. Doss-Gollin, A. Giang, B. Kopp, J. Kwakkel, C. Little, R. Nicholas, C. Nolte, Y. Romitti, V. Srikrishnan and N. Tuana for reading an earlier version of the manuscript and offering helpful feedback; A. Alipour, S. Baboolal, P. Hegde, X. Huang, M. May, S. Roth, S. Sreenivasan, N. Tebyanian and H. Ye for conversations and support. We also thank S. Baboolal for confirming code reproducibility and S. Wishbone for invaluable inputs. All authors acknowledge funding from the Megalopolitan Coastal Transformation Hub (MACH) under NSF award ICER-2103754. A.B.P. and K.K. acknowledge funding from Dartmouth College.

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A.B.P., C.H., C.K. and K.K. conceptualized the project, developed the methodology, and reviewed and edited the manuscript. A.B.P. conducted investigations, performed formal analysis and administered the project. A.B.P. and C.H. performed visualization. C.K. and K.K. acquired funding and supervised the project. A.B.P. wrote the original draft of the manuscript.

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Pollack, A.B., Helgeson, C., Kousky, C. et al. Developing more useful equity measurements for flood-risk management. Nat Sustain (2024). https://doi.org/10.1038/s41893-024-01345-3

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DOI : https://doi.org/10.1038/s41893-024-01345-3

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