research papers attributes

Research Paper

• Icon Calendar 11 June 2024
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A research paper is a product of seeking information, analysis, human thinking, and time. Basically, when scholars want to get answers to questions, they start to search for information to expand, use, approve, or deny findings. In simple words, research papers are results of processes by considering writing works and following specific requirements. Besides, scientists study and expand many theories, developing social or technological aspects of human science. However, in order to provide a quality product, they need to know the definition of such a work, its characteristics, type, structure, format, and how to write it in 7 steps.

What Is a Research Paper and Its Purpose

According to its definition, a research paper is a detailed and structured academic document that presents an individual’s analysis, interpretation, or argument based on existing knowledge and literature. The main purpose of writing a research paper is to contribute to existing literature, develop critical thinking and scientific skills, support academic and professional growth, share findings, demonstrate knowledge and competence, and encourage lifelong learning (Wankhade, 2018). Moreover, such a work is one of the types of papers where scholars analyze questions or topics, look for secondary sources, and write papers on defined themes. For example, if an assignment is to write about some causes of global warming or any other topic, a person must write a research proposal on it, analyzing important points and credible sources (Goodson, 2024). Although essays focus on personal knowledge, writing a scholarly document means analyzing sources by following academic standards. In turn, scientists must meet the strict structure of research papers (Busse & August, 2020). As such, writers need to analyze their topics, start to search for sources, cover key aspects, process credible articles, and organize final studies properly. However, a research paper’s length can vary significantly depending on its academic level and purpose.

• Length: Typically 2-10 pages.
• Word Count: Approximately 500-2,500 words.
• Length: Usually 10-30 pages.
• Word Count: Around 2,500-7,500 words.
• Length: Master’s theses are generally 40-80 pages, while doctoral dissertations can be 100-300 pages or more.
• Word Count: Master’s theses are typically 10,000-20,000 words, and doctoral dissertations can range from 20,000-100,000 words, depending on the discipline and complexity.
• Length: Generally 8-12 pages for short articles, but review articles and comprehensive studies can be longer.
• Word Count: Approximately 3,000-8,000 words.
• Length: Usually 5-10 pages.
• Word Count: Around 2,000-4,000 words.
• Length: Typically 6-12 pages.
• Word Count: Approximately 2,500-6,000 words.
• Length: Varies widely, often 20-100 pages.
• Word Count: Around 5,000-30,000 words.
• Length: Generally 5-15 pages.
• Word Count: Approximately 2,000-5,000 words.
• Length: Varies, usually 20-40 pages per chapter.
• Word Count: Around 5,000-10,000 words.
• Length: Typically 100-300 pages.
• Word Count: Approximately 30,000-100,000 words.

Research Characteristics

Any type of work must meet some standards. By considering a research paper, this work must be written accordingly. In this case, their main characteristics are the length, style, format, and sources (Graham & McCoy, 2014). Firstly, the study’s length defines the number of needed sources to be analyzed. Then, the style must be formal and cover impersonal and inclusive language (Graham & McCoy, 2014). Moreover, the format means academic standards of how to organize final works, including its structure and norms. Finally, sources and their number define works as research papers because of the volume of analyzed information (Graham & McCoy, 2014). Hence, these characteristics must be considered while writing scholarly documents. In turn, general formatting guidelines are:

• Use a standard font (e.g., Times New Roman, 12-point).
• Double-space the text.
• Include 1-inch margins on all sides.
• Indent the first line of each paragraph.
• Number all pages consecutively, usually in the upper right corner.

Types of Research Papers

In general, the length of assignments can be different because of instructions. For example, there are two main types of research papers, such as typical and serious works. Firstly, a typical research paper may include definitive, argumentative, interpretive, and other works (Goodson, 2024). In this case, typical papers are from 2 to 10 pages, where students analyze study questions or specific topics. Then, a serious research composition is the expanded version of typical works. In turn, the length of such a paper is more than 10 pages (Wankhade, 2018). Basically, such works cover a serious analysis with many sources. Therefore, typical and serious works are two types that scholars should consider when writing their documents.

Typical Research Works

Basically, typical research works depend on assignments, the number of sources, and the paper’s length. So, this composition is usually a long essay with the analyzed evidence. For example, students in high school and college get such assignments to learn how to research and analyze topics (Goodson, 2024). In this case, they do not need to conduct serious experiments with the analysis and calculation of data. Moreover, students must use the Internet or libraries in searching for credible secondary sources to find potential answers to specific questions. As a result, students gather information on topics and learn how to take defined sides, present unique positions, or explain new directions (Goodson, 2024). Hence, they require an analysis of primary and secondary sources without serious experiments or data.

Serious Research Studies

Although long papers require a lot of time for finding and analyzing credible sources, real experiments are an integral part of research work. Firstly, scholars at universities need to analyze the information from past studies to expand or disapprove of topics (Wankhade, 2018). Then, if scholars want to prove specific positions or ideas, they must get real evidence. In this case, experiments can be surveys, calculations, or other types of data that scholars do personally. Moreover, a dissertation is a serious research paper that young scientists write based on the analysis of topics, data from conducted experiments, and conclusions at the end of work (Wankhade, 2018). Thus, they are studies that take a lot of time, analysis of sources with gained data, and interpretation of results.

The structure and format of research papers depend on assignment requirements. In fact, when students get their assignments and instructions, they need to analyze specific research questions or topics, find reliable sources, and write final works. Basically, their structure and format consist of the abstract, outline, introduction, literature review, methodology, results, discussion, recommendations, limitations, conclusion, acknowledgments, and references (Graham & McCoy, 2014). However, students may not include some of these sections because of assigned instructions that they have and specific types they must follow. For instance, if instructions are not supposed to conduct real experiments, the methodology section can be skipped because of the data’s absence. In turn, the structure of the final work consists of:

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🔸 The First Part of a Research Study

Abstract or Executive Summary means the first section of a research paper that provides the study’s purpose, its questions or suggestions, and main findings with conclusions. Moreover, this paragraph of about 150 words should be written when the whole work is finished already (Graham & McCoy, 2014). Hence, abstract sections should describe key aspects of studies, including discussions about the relevance of findings.

Outline or Table of Contents serves as a clear map of the structure of a study.

Introduction provides the main information on problem statements, the indication of methodology, important findings, and principal conclusion. Basically, this section covers rationales behind the work or background research, explanation of the importance, defending its relevance, a brief description of experimental designs, defined study questions, hypotheses, or key aspects (Busse & August, 2020). Hence, scholars should provide a short overview of their studies.

🔸 Literature Review and Research or Experiment

Literature Review is needed for the analysis of past studies or scholarly articles to be familiar with research questions or topics. For example, this section summarizes and synthesizes arguments and ideas from scholarly sources without adding new contributions (Scholz, 2022). In turn, this part is organized around arguments or ideas, not sources.

Methodology or Materials and Methods covers explanations of research designs. Basically, techniques for gathering information and other aspects related to experiments must be described in a research paper. For instance, students and scholars document all specialized materials and general procedures (Turbek et al., 2016). In this case, individuals may use some or all of the methods in further studies or judge the scientific merit of the work. Moreover, scientists should explain how they are going to conduct their experiments.

Results mean the gained information or data after the study or experiment. Basically, scholars should present and illustrate their findings (Turbek et al., 2016). Moreover, this section may include tables or figures.

🔸 Analysis of Findings

Discussion is a section where scientists review the information in the introduction part, evaluate gained results, or compare it with past studies. In particular, students and scholars interpret gained data or findings in appropriate depth. For example, if results differ from expectations at the beginning, scientists should explain why that may have happened (Turbek et al., 2016). However, if results agree with rationales, scientists should describe theories that the evidence is supported.

Recommendations take their roots from a discussion section where scholars propose potential solutions or new ideas based on obtained results. In this case, if scientists have any recommendations on how to improve this research so that other scholars can use evidence in further studies, they must write what they think in this section (Graham & McCoy, 2014). Besides, authors can provide their suggestions for further investigation after their evaluations.

Limitations mean a consideration of research weaknesses and results to get new directions. For instance, if scholars find any limitations in their studies that may affect experiments, scholars must not use such knowledge because of the same mistakes (Busse & August, 2020). Moreover, scientists should avoid contradicting results, and, even more, they must write them in this section.

🔸 The Final Part of a Conducted Research

Conclusion includes final claims of a research paper based on findings. Basically, this section covers final thoughts and the summary of the whole work. Moreover, this section may be used instead of limitations and recommendations that would be too small by themselves (Wankhade, 2018). In this case, scientists do not need to use headings as recommendations and limitations.

Acknowledgments or Appendix may take different forms, from paragraphs to charts. In this section, scholars include additional information about what they did.

References mean a section where students, scholars, or scientists provide all used sources by following the format and academic rules.

How to Write a Research Paper in 7 Steps

Writing any research paper requires following a systematic process. Firstly, writers need to select a focused topic they want to analyze. To achieve this objective, comprehensive preliminary research must be conducted to gather credible and relevant sources (Scholz, 2022). After reviewing the existing literature, writers must develop a clear and concise thesis statement sentence to guide the direction of their studies. Then, organizing the main arguments and evidence into a detailed outline ensures a coherent structure. In turn, the initial draft should be started with a compelling introduction, proceeded with body paragraphs that substantiate the thesis through analysis, and ended with a conclusion that underscores the study’s importance (Turbek et al., 2016). Basically, concluding the work by summarizing the findings and emphasizing the significance of the study is crucial. Moreover, revising and editing for content, coherence, and clarity ensures quality (Busse & August, 2020). Finally, proofreading for grammatical accuracy and ensuring adherence to the required formatting guidelines is necessary before submitting the final paper. Hence, when starting a research paper, writers should do the next:

Step 1: Choose a Topic

• Select a Broad Subject: Begin by identifying a specific subject or theme of interest.
• Narrow Down Your Topic: Focus on a specific aspect of the subject or theme to make your examination more focused.
• Establish the Background: Do a preliminary analysis of sources to ensure there is enough information available and refine your topic further.
• Formulate a Research Question : Create a first draft of a clear, concise research question or thesis statement to guide your study.

Step 2: Conduct Preliminary Analysis

• Gather Credible Sources: Use books, academic journals, scholarly articles, reputable websites, and other primary and secondary sources.
• Choose Only Relevant Sources: Review chosen sources for their content and pick only relevant ones.
• Take Notes: Organize your notes, highlighting key points and evidence and how they relate to your initial thesis.
• Create an Annotated Bibliography: Summarize each source in one paragraph and note how it will contribute to your paper.

Step 3: Develop a Working Thesis Statement

• Be Specific: Revise your initial thesis, making it a working one, outlining the main argument or position of your paper.
• Make It Debatable: Ensure that your working thesis presents a viewpoint that others might challenge or debate.
• Be Concise: Write your working thesis statement in one or two sentences.
• Stay Focused: Your working thesis must be focused and specific.

Step 4: Create an Outline

• Beginning: Outline your opening paragraph, including your working thesis statement.
• Middle Sections : Separate your body into sections with headings for each main point or argument and include sub-points and supporting evidence.
• Ending: Plan your concluding section to summarize your findings and restate your thesis in the light of the evidence presented.
• The List of Sources: Finish your outline by providing citation entries of your sources.

Step 5: Write the First Draft

• Introduction: Start with an engaging opening, provide background information, and state your thesis.
• Body Section: Each body paragraph should focus on a single idea and start with a specific topic sentence, followed by evidence and analysis that supports your thesis.
• Conclusion: Summarize your arguments, restate the importance of your topic, and suggest further investigation, analysis, examination, or possible implications.
• Reference Page: Include the list of references used in your first draft.

Step 6: Revise and Edit

• Content Review: Check for clarity, coherence, and whether each part supports your thesis.
• Structure and Flow: Ensure logical flow of ideas between sections and paragraphs.
• Grammar and Style: Correct grammatical errors, improve sentence structure, and refine your writing style.
• Citations: Ensure all sources are correctly cited in your chosen citation style (APA, MLA, Chicago/Turabian, Harvard, etc.).

Step 7: Finalize Your Paper

• Proofread: Carefully proofread for any remaining errors or typos.
• Format: Ensure your paper adheres to the required format, including title page, headers, font, and margins.
• Reference List: Double-check your bibliography, reference, or works cited page for accuracy.
• Submit: Make sure to submit your paper by the deadline.

In conclusion, a research paper is a formal academic document designed to provide a detailed analysis, interpretation, or argument based on in-depth study. Its structured format includes providing opening components, such as the abstract, outline, and introduction; study aspects, such as literature review, methodology, and results; analysis of findings, such as discussion, recommendations, and limitations; and final parts, such as conclusion, acknowledgments, appendices, and references. Understanding the essential elements and adhering to academic standards ensures the creation of a well-organized and meaningful research paper.

Busse, C., & August, E. (2020). How to write and publish a research paper for a peer-reviewed journal. Journal of Cancer Education , 36 (5), 909–913. https://doi.org/10.1007/s13187-020-01751-z

Goodson, P. (2024). Becoming an academic writer: 50 exercises for paced, productive, and powerful writing . Sage.

Graham, L., & McCoy, I. (2014). How to write a great research paper: A step-by-step handbook. Incentive Publications by World Book.

Scholz, F. (2022). Writing and publishing a scientific paper. ChemTexts , 8 (1), 1–7. https://doi.org/10.1007/s40828-022-00160-7

Turbek, S. P., Chock, T. M., Donahue, K., Havrilla, C. A., Oliverio, A. M., Polutchko, S. K., Shoemaker, L. G., & Vimercati, L. (2016). Scientific writing made easy: A step‐by‐step guide to undergraduate writing in the Biological Sciences. The Bulletin of the Ecological Society of America , 97 (4), 417–426. https://doi.org/10.1002/bes2.1258

Wankhade, L. (2018). How to write and publish a research paper: A complete guide to writing and publishing a research paper . Independent Published.

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Writing a Research Paper

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The Research Paper

There will come a time in most students' careers when they are assigned a research paper. Such an assignment often creates a great deal of unneeded anxiety in the student, which may result in procrastination and a feeling of confusion and inadequacy. This anxiety frequently stems from the fact that many students are unfamiliar and inexperienced with this genre of writing. Never fear—inexperience and unfamiliarity are situations you can change through practice! Writing a research paper is an essential aspect of academics and should not be avoided on account of one's anxiety. In fact, the process of writing a research paper can be one of the more rewarding experiences one may encounter in academics. What is more, many students will continue to do research throughout their careers, which is one of the reasons this topic is so important.

Becoming an experienced researcher and writer in any field or discipline takes a great deal of practice. There are few individuals for whom this process comes naturally. Remember, even the most seasoned academic veterans have had to learn how to write a research paper at some point in their career. Therefore, with diligence, organization, practice, a willingness to learn (and to make mistakes!), and, perhaps most important of all, patience, students will find that they can achieve great things through their research and writing.

The pages in this section cover the following topic areas related to the process of writing a research paper:

• Genre - This section will provide an overview for understanding the difference between an analytical and argumentative research paper.
• Choosing a Topic - This section will guide the student through the process of choosing topics, whether the topic be one that is assigned or one that the student chooses themselves.
• Identifying an Audience - This section will help the student understand the often times confusing topic of audience by offering some basic guidelines for the process.
• Where Do I Begin - This section concludes the handout by offering several links to resources at Purdue, and also provides an overview of the final stages of writing a research paper.

How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

Need a helping hand?

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications . If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

Can you help me with a full paper template for this Abstract:

Background: Energy and sports drinks have gained popularity among diverse demographic groups, including adolescents, athletes, workers, and college students. While often used interchangeably, these beverages serve distinct purposes, with energy drinks aiming to boost energy and cognitive performance, and sports drinks designed to prevent dehydration and replenish electrolytes and carbohydrates lost during physical exertion.

Objective: To assess the nutritional quality of energy and sports drinks in Egypt.

Material and Methods: A cross-sectional study assessed the nutrient contents, including energy, sugar, electrolytes, vitamins, and caffeine, of sports and energy drinks available in major supermarkets in Cairo, Alexandria, and Giza, Egypt. Data collection involved photographing all relevant product labels and recording nutritional information. Descriptive statistics and appropriate statistical tests were employed to analyze and compare the nutritional values of energy and sports drinks.

Results: The study analyzed 38 sports drinks and 42 energy drinks. Sports drinks were significantly more expensive than energy drinks, with higher net content and elevated magnesium, potassium, and vitamin C. Energy drinks contained higher concentrations of caffeine, sugars, and vitamins B2, B3, and B6.

Conclusion: Significant nutritional differences exist between sports and energy drinks, reflecting their intended uses. However, these beverages’ high sugar content and calorie loads raise health concerns. Proper labeling, public awareness, and responsible marketing are essential to guide safe consumption practices in Egypt.

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Writing the title and abstract for a research paper: Being concise, precise, and meticulous is the key

Milind s. tullu.

Department of Pediatrics, Seth G.S. Medical College and KEM Hospital, Parel, Mumbai, Maharashtra, India

This article deals with formulating a suitable title and an appropriate abstract for an original research paper. The “title” and the “abstract” are the “initial impressions” of a research article, and hence they need to be drafted correctly, accurately, carefully, and meticulously. Often both of these are drafted after the full manuscript is ready. Most readers read only the title and the abstract of a research paper and very few will go on to read the full paper. The title and the abstract are the most important parts of a research paper and should be pleasant to read. The “title” should be descriptive, direct, accurate, appropriate, interesting, concise, precise, unique, and should not be misleading. The “abstract” needs to be simple, specific, clear, unbiased, honest, concise, precise, stand-alone, complete, scholarly, (preferably) structured, and should not be misrepresentative. The abstract should be consistent with the main text of the paper, especially after a revision is made to the paper and should include the key message prominently. It is very important to include the most important words and terms (the “keywords”) in the title and the abstract for appropriate indexing purpose and for retrieval from the search engines and scientific databases. Such keywords should be listed after the abstract. One must adhere to the instructions laid down by the target journal with regard to the style and number of words permitted for the title and the abstract.

Introduction

This article deals with drafting a suitable “title” and an appropriate “abstract” for an original research paper. Because the “title” and the “abstract” are the “initial impressions” or the “face” of a research article, they need to be drafted correctly, accurately, carefully, meticulously, and consume time and energy.[ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ] Often, these are drafted after the complete manuscript draft is ready.[ 2 , 3 , 4 , 5 , 9 , 10 , 11 ] Most readers will read only the title and the abstract of a published research paper, and very few “interested ones” (especially, if the paper is of use to them) will go on to read the full paper.[ 1 , 2 ] One must remember to adhere to the instructions laid down by the “target journal” (the journal for which the author is writing) regarding the style and number of words permitted for the title and the abstract.[ 2 , 4 , 5 , 7 , 8 , 9 , 12 ] Both the title and the abstract are the most important parts of a research paper – for editors (to decide whether to process the paper for further review), for reviewers (to get an initial impression of the paper), and for the readers (as these may be the only parts of the paper available freely and hence, read widely).[ 4 , 8 , 12 ] It may be worth for the novice author to browse through titles and abstracts of several prominent journals (and their target journal as well) to learn more about the wording and styles of the titles and abstracts, as well as the aims and scope of the particular journal.[ 5 , 7 , 9 , 13 ]

The details of the title are discussed under the subheadings of importance, types, drafting, and checklist.

Importance of the title

When a reader browses through the table of contents of a journal issue (hard copy or on website), the title is the “ first detail” or “face” of the paper that is read.[ 2 , 3 , 4 , 5 , 6 , 13 ] Hence, it needs to be simple, direct, accurate, appropriate, specific, functional, interesting, attractive/appealing, concise/brief, precise/focused, unambiguous, memorable, captivating, informative (enough to encourage the reader to read further), unique, catchy, and it should not be misleading.[ 1 , 2 , 3 , 4 , 5 , 6 , 9 , 12 ] It should have “just enough details” to arouse the interest and curiosity of the reader so that the reader then goes ahead with studying the abstract and then (if still interested) the full paper.[ 1 , 2 , 4 , 13 ] Journal websites, electronic databases, and search engines use the words in the title and abstract (the “keywords”) to retrieve a particular paper during a search; hence, the importance of these words in accessing the paper by the readers has been emphasized.[ 3 , 4 , 5 , 6 , 12 , 14 ] Such important words (or keywords) should be arranged in appropriate order of importance as per the context of the paper and should be placed at the beginning of the title (rather than the later part of the title, as some search engines like Google may just display only the first six to seven words of the title).[ 3 , 5 , 12 ] Whimsical, amusing, or clever titles, though initially appealing, may be missed or misread by the busy reader and very short titles may miss the essential scientific words (the “keywords”) used by the indexing agencies to catch and categorize the paper.[ 1 , 3 , 4 , 9 ] Also, amusing or hilarious titles may be taken less seriously by the readers and may be cited less often.[ 4 , 15 ] An excessively long or complicated title may put off the readers.[ 3 , 9 ] It may be a good idea to draft the title after the main body of the text and the abstract are drafted.[ 2 , 3 , 4 , 5 ]

Types of titles

Titles can be descriptive, declarative, or interrogative. They can also be classified as nominal, compound, or full-sentence titles.

Descriptive or neutral title

This has the essential elements of the research theme, that is, the patients/subjects, design, interventions, comparisons/control, and outcome, but does not reveal the main result or the conclusion.[ 3 , 4 , 12 , 16 ] Such a title allows the reader to interpret the findings of the research paper in an impartial manner and with an open mind.[ 3 ] These titles also give complete information about the contents of the article, have several keywords (thus increasing the visibility of the article in search engines), and have increased chances of being read and (then) being cited as well.[ 4 ] Hence, such descriptive titles giving a glimpse of the paper are generally preferred.[ 4 , 16 ]

Declarative title

This title states the main finding of the study in the title itself; it reduces the curiosity of the reader, may point toward a bias on the part of the author, and hence is best avoided.[ 3 , 4 , 12 , 16 ]

Interrogative title

This is the one which has a query or the research question in the title.[ 3 , 4 , 16 ] Though a query in the title has the ability to sensationalize the topic, and has more downloads (but less citations), it can be distracting to the reader and is again best avoided for a research article (but can, at times, be used for a review article).[ 3 , 6 , 16 , 17 ]

From a sentence construct point of view, titles may be nominal (capturing only the main theme of the study), compound (with subtitles to provide additional relevant information such as context, design, location/country, temporal aspect, sample size, importance, and a provocative or a literary; for example, see the title of this review), or full-sentence titles (which are longer and indicate an added degree of certainty of the results).[ 4 , 6 , 9 , 16 ] Any of these constructs may be used depending on the type of article, the key message, and the author's preference or judgement.[ 4 ]

Drafting a suitable title

A stepwise process can be followed to draft the appropriate title. The author should describe the paper in about three sentences, avoiding the results and ensuring that these sentences contain important scientific words/keywords that describe the main contents and subject of the paper.[ 1 , 4 , 6 , 12 ] Then the author should join the sentences to form a single sentence, shorten the length (by removing redundant words or adjectives or phrases), and finally edit the title (thus drafted) to make it more accurate, concise (about 10–15 words), and precise.[ 1 , 3 , 4 , 5 , 9 ] Some journals require that the study design be included in the title, and this may be placed (using a colon) after the primary title.[ 2 , 3 , 4 , 14 ] The title should try to incorporate the Patients, Interventions, Comparisons and Outcome (PICO).[ 3 ] The place of the study may be included in the title (if absolutely necessary), that is, if the patient characteristics (such as study population, socioeconomic conditions, or cultural practices) are expected to vary as per the country (or the place of the study) and have a bearing on the possible outcomes.[ 3 , 6 ] Lengthy titles can be boring and appear unfocused, whereas very short titles may not be representative of the contents of the article; hence, optimum length is required to ensure that the title explains the main theme and content of the manuscript.[ 4 , 5 , 9 ] Abbreviations (except the standard or commonly interpreted ones such as HIV, AIDS, DNA, RNA, CDC, FDA, ECG, and EEG) or acronyms should be avoided in the title, as a reader not familiar with them may skip such an article and nonstandard abbreviations may create problems in indexing the article.[ 3 , 4 , 5 , 6 , 9 , 12 ] Also, too much of technical jargon or chemical formulas in the title may confuse the readers and the article may be skipped by them.[ 4 , 9 ] Numerical values of various parameters (stating study period or sample size) should also be avoided in the titles (unless deemed extremely essential).[ 4 ] It may be worthwhile to take an opinion from a impartial colleague before finalizing the title.[ 4 , 5 , 6 ] Thus, multiple factors (which are, at times, a bit conflicting or contrasting) need to be considered while formulating a title, and hence this should not be done in a hurry.[ 4 , 6 ] Many journals ask the authors to draft a “short title” or “running head” or “running title” for printing in the header or footer of the printed paper.[ 3 , 12 ] This is an abridged version of the main title of up to 40–50 characters, may have standard abbreviations, and helps the reader to navigate through the paper.[ 3 , 12 , 14 ]

Checklist for a good title

Table 1 gives a checklist/useful tips for drafting a good title for a research paper.[ 1 , 2 , 3 , 4 , 5 , 6 , 12 ] Table 2 presents some of the titles used by the author of this article in his earlier research papers, and the appropriateness of the titles has been commented upon. As an individual exercise, the reader may try to improvise upon the titles (further) after reading the corresponding abstract and full paper.

Checklist/useful tips for drafting a good title for a research paper

Some titles used by author of this article in his earlier publications and remark/comment on their appropriateness

The Abstract

The details of the abstract are discussed under the subheadings of importance, types, drafting, and checklist.

Importance of the abstract

The abstract is a summary or synopsis of the full research paper and also needs to have similar characteristics like the title. It needs to be simple, direct, specific, functional, clear, unbiased, honest, concise, precise, self-sufficient, complete, comprehensive, scholarly, balanced, and should not be misleading.[ 1 , 2 , 3 , 7 , 8 , 9 , 10 , 11 , 13 , 17 ] Writing an abstract is to extract and summarize (AB – absolutely, STR – straightforward, ACT – actual data presentation and interpretation).[ 17 ] The title and abstracts are the only sections of the research paper that are often freely available to the readers on the journal websites, search engines, and in many abstracting agencies/databases, whereas the full paper may attract a payment per view or a fee for downloading the pdf copy.[ 1 , 2 , 3 , 7 , 8 , 10 , 11 , 13 , 14 ] The abstract is an independent and stand-alone (that is, well understood without reading the full paper) section of the manuscript and is used by the editor to decide the fate of the article and to choose appropriate reviewers.[ 2 , 7 , 10 , 12 , 13 ] Even the reviewers are initially supplied only with the title and the abstract before they agree to review the full manuscript.[ 7 , 13 ] This is the second most commonly read part of the manuscript, and therefore it should reflect the contents of the main text of the paper accurately and thus act as a “real trailer” of the full article.[ 2 , 7 , 11 ] The readers will go through the full paper only if they find the abstract interesting and relevant to their practice; else they may skip the paper if the abstract is unimpressive.[ 7 , 8 , 9 , 10 , 13 ] The abstract needs to highlight the selling point of the manuscript and succeed in luring the reader to read the complete paper.[ 3 , 7 ] The title and the abstract should be constructed using keywords (key terms/important words) from all the sections of the main text.[ 12 ] Abstracts are also used for submitting research papers to a conference for consideration for presentation (as oral paper or poster).[ 9 , 13 , 17 ] Grammatical and typographic errors reflect poorly on the quality of the abstract, may indicate carelessness/casual attitude on part of the author, and hence should be avoided at all times.[ 9 ]

Types of abstracts

The abstracts can be structured or unstructured. They can also be classified as descriptive or informative abstracts.

Structured and unstructured abstracts

Structured abstracts are followed by most journals, are more informative, and include specific subheadings/subsections under which the abstract needs to be composed.[ 1 , 7 , 8 , 9 , 10 , 11 , 13 , 17 , 18 ] These subheadings usually include context/background, objectives, design, setting, participants, interventions, main outcome measures, results, and conclusions.[ 1 ] Some journals stick to the standard IMRAD format for the structure of the abstracts, and the subheadings would include Introduction/Background, Methods, Results, And (instead of Discussion) the Conclusion/s.[ 1 , 2 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 17 , 18 ] Structured abstracts are more elaborate, informative, easy to read, recall, and peer-review, and hence are preferred; however, they consume more space and can have same limitations as an unstructured abstract.[ 7 , 9 , 18 ] The structured abstracts are (possibly) better understood by the reviewers and readers. Anyway, the choice of the type of the abstract and the subheadings of a structured abstract depend on the particular journal style and is not left to the author's wish.[ 7 , 10 , 12 ] Separate subheadings may be necessary for reporting meta-analysis, educational research, quality improvement work, review, or case study.[ 1 ] Clinical trial abstracts need to include the essential items mentioned in the CONSORT (Consolidated Standards Of Reporting Trials) guidelines.[ 7 , 9 , 14 , 19 ] Similar guidelines exist for various other types of studies, including observational studies and for studies of diagnostic accuracy.[ 20 , 21 ] A useful resource for the above guidelines is available at www.equator-network.org (Enhancing the QUAlity and Transparency Of health Research). Unstructured (or non-structured) abstracts are free-flowing, do not have predefined subheadings, and are commonly used for papers that (usually) do not describe original research.[ 1 , 7 , 9 , 10 ]

The four-point structured abstract: This has the following elements which need to be properly balanced with regard to the content/matter under each subheading:[ 9 ]

Background and/or Objectives: This states why the work was undertaken and is usually written in just a couple of sentences.[ 3 , 7 , 8 , 9 , 10 , 12 , 13 ] The hypothesis/study question and the major objectives are also stated under this subheading.[ 3 , 7 , 8 , 9 , 10 , 12 , 13 ]

Methods: This subsection is the longest, states what was done, and gives essential details of the study design, setting, participants, blinding, sample size, sampling method, intervention/s, duration and follow-up, research instruments, main outcome measures, parameters evaluated, and how the outcomes were assessed or analyzed.[ 3 , 7 , 8 , 9 , 10 , 12 , 13 , 14 , 17 ]

Results/Observations/Findings: This subheading states what was found, is longer, is difficult to draft, and needs to mention important details including the number of study participants, results of analysis (of primary and secondary objectives), and include actual data (numbers, mean, median, standard deviation, “P” values, 95% confidence intervals, effect sizes, relative risks, odds ratio, etc.).[ 3 , 7 , 8 , 9 , 10 , 12 , 13 , 14 , 17 ]

Conclusions: The take-home message (the “so what” of the paper) and other significant/important findings should be stated here, considering the interpretation of the research question/hypothesis and results put together (without overinterpreting the findings) and may also include the author's views on the implications of the study.[ 3 , 7 , 8 , 9 , 10 , 12 , 13 , 14 , 17 ]

The eight-point structured abstract: This has the following eight subheadings – Objectives, Study Design, Study Setting, Participants/Patients, Methods/Intervention, Outcome Measures, Results, and Conclusions.[ 3 , 9 , 18 ] The instructions to authors given by the particular journal state whether they use the four- or eight-point abstract or variants thereof.[ 3 , 14 ]

Descriptive and Informative abstracts

Descriptive abstracts are short (75–150 words), only portray what the paper contains without providing any more details; the reader has to read the full paper to know about its contents and are rarely used for original research papers.[ 7 , 10 ] These are used for case reports, reviews, opinions, and so on.[ 7 , 10 ] Informative abstracts (which may be structured or unstructured as described above) give a complete detailed summary of the article contents and truly reflect the actual research done.[ 7 , 10 ]

Drafting a suitable abstract

It is important to religiously stick to the instructions to authors (format, word limit, font size/style, and subheadings) provided by the journal for which the abstract and the paper are being written.[ 7 , 8 , 9 , 10 , 13 ] Most journals allow 200–300 words for formulating the abstract and it is wise to restrict oneself to this word limit.[ 1 , 2 , 3 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 22 ] Though some authors prefer to draft the abstract initially, followed by the main text of the paper, it is recommended to draft the abstract in the end to maintain accuracy and conformity with the main text of the paper (thus maintaining an easy linkage/alignment with title, on one hand, and the introduction section of the main text, on the other hand).[ 2 , 7 , 9 , 10 , 11 ] The authors should check the subheadings (of the structured abstract) permitted by the target journal, use phrases rather than sentences to draft the content of the abstract, and avoid passive voice.[ 1 , 7 , 9 , 12 ] Next, the authors need to get rid of redundant words and edit the abstract (extensively) to the correct word count permitted (every word in the abstract “counts”!).[ 7 , 8 , 9 , 10 , 13 ] It is important to ensure that the key message, focus, and novelty of the paper are not compromised; the rationale of the study and the basis of the conclusions are clear; and that the abstract is consistent with the main text of the paper.[ 1 , 2 , 3 , 7 , 9 , 11 , 12 , 13 , 14 , 17 , 22 ] This is especially important while submitting a revision of the paper (modified after addressing the reviewer's comments), as the changes made in the main (revised) text of the paper need to be reflected in the (revised) abstract as well.[ 2 , 10 , 12 , 14 , 22 ] Abbreviations should be avoided in an abstract, unless they are conventionally accepted or standard; references, tables, or figures should not be cited in the abstract.[ 7 , 9 , 10 , 11 , 13 ] It may be worthwhile not to rush with the abstract and to get an opinion by an impartial colleague on the content of the abstract; and if possible, the full paper (an “informal” peer-review).[ 1 , 7 , 8 , 9 , 11 , 17 ] Appropriate “Keywords” (three to ten words or phrases) should follow the abstract and should be preferably chosen from the Medical Subject Headings (MeSH) list of the U.S. National Library of Medicine ( https://meshb.nlm.nih.gov/search ) and are used for indexing purposes.[ 2 , 3 , 11 , 12 ] These keywords need to be different from the words in the main title (the title words are automatically used for indexing the article) and can be variants of the terms/phrases used in the title, or words from the abstract and the main text.[ 3 , 12 ] The ICMJE (International Committee of Medical Journal Editors; http://www.icmje.org/ ) also recommends publishing the clinical trial registration number at the end of the abstract.[ 7 , 14 ]

Checklist for a good abstract

Table 3 gives a checklist/useful tips for formulating a good abstract for a research paper.[ 1 , 2 , 3 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 17 , 22 ]

Checklist/useful tips for formulating a good abstract for a research paper

Concluding Remarks

This review article has given a detailed account of the importance and types of titles and abstracts. It has also attempted to give useful hints for drafting an appropriate title and a complete abstract for a research paper. It is hoped that this review will help the authors in their career in medical writing.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

Acknowledgement

The author thanks Dr. Hemant Deshmukh - Dean, Seth G.S. Medical College & KEM Hospital, for granting permission to publish this manuscript.

What Should Be the Characteristics of a Good Research Paper?

by team@blp

In miscellaneous.

When people want to get answers to various issues, they search for information on the problems. From their findings, they expand them, aiming to agree or refute them. Research papers are common assignments in colleges. 

They follow specific research and writing guidelines to answer particular questions or assigned topics . They look into the critical topic of credible research sources and argue their findings in an orderly manner. To be termed as good, the research paper must bear the following characteristics.

In this Article

Gives credit to previous research work on the topic

• It’s hooked on a relevant research question.

It must be based on appropriate, systematic research methods

• The information must be accurate and controlled.
• It must be verifiable and rigorous.

It must be clear and coherent.

It must be dealt with critical analysis., it must be original., it must possess ethical integrity., be careful with the topic you choose, decide the sources you want to use, create your thesis statement , plan your points, write your paper, characteristics of a good research paper.

Writing a research paper aims to discover new knowledge, but the knowledge must have a base. Its base is the research done previously by other scholars. The student must acknowledge the previous research and avoid duplicating it in their writing process.

A college student must engage in deep research work to create a credible research paper. This makes the process lengthy and complex when choosing your topic, selecting sources, and developing its design. In addition, it requires a great deal of knowledge to piece everything together. Fortunately, Studyclerk will give you professional help anytime you need it. If you do not have enough knowledge and time to write a paper on your own, you can ask for  research paper help  by StudyClerk, where experienced paper writers will write your paper in no time. You can trust their expert writers to handle your assignment well and get a well-written paper in a short time.

It’s hooked on a relevant research question .

All the time a student spends researching multiple sources is to answer a specific research question. The question must be relevant to the current needs. This question guides them into the information they use or the line of argument they take.

The methodology of research a student chooses will determine the value of the information they get or give. The methods must be valid and credible to provide reliable outcomes. Whether the student chooses a qualitative, quantitative, or mixed approach, they must all be valuable and relevant. 

The information must be accurate and controlled .

A good research paper cannot be generalized information but specific, scientific information. That is why they must include references and record tests or information accurately. Moreover, they must keep the information controlled by staying within the topic from the first step of research to the last. 

It must be verifiable and rigorous .

The student must use information or write arguments that can be verified. If it’s a test, it must be replicable by another researcher. The sources must be verifiable and accurate. Without rigorous deep  research strategies , the paper cannot be good. They must put a lot of labor into both the writing and research processes to ensure the information is credible, clear, concise, original, and precise. 

The paper should be written clearly, concisely with logical progression from one section to another. This includes having a well-structured introduction, body, and conclusion. Each section should be coherent and contribute directly to the reader’s understanding of the research question, findings, and implications.

A good research paper involves not just reporting facts and data, but also critically analyzing them. This means evaluating the strengths and limitations of the research, discussing the implications of findings, and situating the results within the broader field of study. The analysis should engage with different perspectives and theories, showing an awareness of the complexity of the topic.

While it builds on previous research, a good research paper offers new insights or approaches to the topic. This could be through presenting new findings, developing a novel theoretical approach, or offering a unique combination of existing knowledge. Originality, especially the research statement , is crucial for advancing knowledge and adding value to the field.

Ethical considerations are paramount in research. A good research paper adheres to ethical standards when it comes to data collection, reporting, and analysis. This includes obtaining necessary permissions for using data, respecting participant privacy in the case of human subjects, and being transparent about any conflicts of interest.

How to write a good research paper

To write a good research paper, you must first understand what kind of question you have been assigned. Then, you will choose the best topic that you will love to write about. The following points will help you write a good research paper.

You must select a topic you love. Go for a topic that will be easier to research, which will give you a broader area of study. 

Your instructor doesn’t restrict you on the sources you must use. Broaden your mind so that you don’t limit yourself to specific sources of information. Sometimes you will get helpful information from sources you slightest thought as good.

Write your central statement to base your position on the research. Make it coherent contentious, and let it be a summary of your arguments.

Create an outline that will guide you when arguing your points

• Start  with the most vital points and smooth the flow.
• Pay attention to  paragraph structure  and let your arguments be clear.
• Finish with a compelling conclusion, and don’t forget to cite your sources.

A research paper requires extensive research methods to get solid points for supporting your stand. First, the sources you use must be verifiable by any other researcher. You must ensure your research work is original for your paper to be credible. Third, each point should be coherent with each paragraph. Finally, your research findings must be tagged on the research question and provide answers that apply to the current society. 

Author’s Bio

Helen Birk is an online freelance writer who holds an outstanding record of helping numerous students do their academic assignments. She is an expert in essays and thesis writing, and students simply love her for her high-quality work. In addition, she enjoys cycling, doing pencil sketching, and listening to spiritual podcasts in her free time.

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• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
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• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
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• Secondary Sources
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• Qualitative Methods
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• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

This glossary is intended to assist you in understanding commonly used terms and concepts when reading, interpreting, and evaluating scholarly research. Also included are common words and phrases defined within the context of how they apply to research in the social and behavioral sciences.

• Acculturation -- refers to the process of adapting to another culture, particularly in reference to blending in with the majority population [e.g., an immigrant adopting American customs]. However, acculturation also implies that both cultures add something to one another, but still remain distinct groups unto themselves.
• Accuracy -- a term used in survey research to refer to the match between the target population and the sample.
• Affective Measures -- procedures or devices used to obtain quantified descriptions of an individual's feelings, emotional states, or dispositions.
• Aggregate -- a total created from smaller units. For instance, the population of a county is an aggregate of the populations of the cities, rural areas, etc. that comprise the county. As a verb, it refers to total data from smaller units into a large unit.
• Anonymity -- a research condition in which no one, including the researcher, knows the identities of research participants.
• Baseline -- a control measurement carried out before an experimental treatment.
• Behaviorism -- school of psychological thought concerned with the observable, tangible, objective facts of behavior, rather than with subjective phenomena such as thoughts, emotions, or impulses. Contemporary behaviorism also emphasizes the study of mental states such as feelings and fantasies to the extent that they can be directly observed and measured.
• Beliefs -- ideas, doctrines, tenets, etc. that are accepted as true on grounds which are not immediately susceptible to rigorous proof.
• Benchmarking -- systematically measuring and comparing the operations and outcomes of organizations, systems, processes, etc., against agreed upon "best-in-class" frames of reference.
• Bias -- a loss of balance and accuracy in the use of research methods. It can appear in research via the sampling frame, random sampling, or non-response. It can also occur at other stages in research, such as while interviewing, in the design of questions, or in the way data are analyzed and presented. Bias means that the research findings will not be representative of, or generalizable to, a wider population.
• Case Study -- the collection and presentation of detailed information about a particular participant or small group, frequently including data derived from the subjects themselves.
• Causal Hypothesis -- a statement hypothesizing that the independent variable affects the dependent variable in some way.
• Causal Relationship -- the relationship established that shows that an independent variable, and nothing else, causes a change in a dependent variable. It also establishes how much of a change is shown in the dependent variable.
• Causality -- the relation between cause and effect.
• Central Tendency -- any way of describing or characterizing typical, average, or common values in some distribution.
• Chi-square Analysis -- a common non-parametric statistical test which compares an expected proportion or ratio to an actual proportion or ratio.
• Claim -- a statement, similar to a hypothesis, which is made in response to the research question and that is affirmed with evidence based on research.
• Classification -- ordering of related phenomena into categories, groups, or systems according to characteristics or attributes.
• Cluster Analysis -- a method of statistical analysis where data that share a common trait are grouped together. The data is collected in a way that allows the data collector to group data according to certain characteristics.
• Cohort Analysis -- group by group analytic treatment of individuals having a statistical factor in common to each group. Group members share a particular characteristic [e.g., born in a given year] or a common experience [e.g., entering a college at a given time].
• Confidentiality -- a research condition in which no one except the researcher(s) knows the identities of the participants in a study. It refers to the treatment of information that a participant has disclosed to the researcher in a relationship of trust and with the expectation that it will not be revealed to others in ways that violate the original consent agreement, unless permission is granted by the participant.
• Confirmability Objectivity -- the findings of the study could be confirmed by another person conducting the same study.
• Construct -- refers to any of the following: something that exists theoretically but is not directly observable; a concept developed [constructed] for describing relations among phenomena or for other research purposes; or, a theoretical definition in which concepts are defined in terms of other concepts. For example, intelligence cannot be directly observed or measured; it is a construct.
• Construct Validity -- seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
• Constructivism -- the idea that reality is socially constructed. It is the view that reality cannot be understood outside of the way humans interact and that the idea that knowledge is constructed, not discovered. Constructivists believe that learning is more active and self-directed than either behaviorism or cognitive theory would postulate.
• Content Analysis -- the systematic, objective, and quantitative description of the manifest or latent content of print or nonprint communications.
• Context Sensitivity -- awareness by a qualitative researcher of factors such as values and beliefs that influence cultural behaviors.
• Control Group -- the group in an experimental design that receives either no treatment or a different treatment from the experimental group. This group can thus be compared to the experimental group.
• Controlled Experiment -- an experimental design with two or more randomly selected groups [an experimental group and control group] in which the researcher controls or introduces the independent variable and measures the dependent variable at least two times [pre- and post-test measurements].
• Correlation -- a common statistical analysis, usually abbreviated as r, that measures the degree of relationship between pairs of interval variables in a sample. The range of correlation is from -1.00 to zero to +1.00. Also, a non-cause and effect relationship between two variables.
• Covariate -- a product of the correlation of two related variables times their standard deviations. Used in true experiments to measure the difference of treatment between them.
• Credibility -- a researcher's ability to demonstrate that the object of a study is accurately identified and described based on the way in which the study was conducted.
• Critical Theory -- an evaluative approach to social science research, associated with Germany's neo-Marxist “Frankfurt School,” that aims to criticize as well as analyze society, opposing the political orthodoxy of modern communism. Its goal is to promote human emancipatory forces and to expose ideas and systems that impede them.
• Data -- factual information [as measurements or statistics] used as a basis for reasoning, discussion, or calculation.
• Data Mining -- the process of analyzing data from different perspectives and summarizing it into useful information, often to discover patterns and/or systematic relationships among variables.
• Data Quality -- this is the degree to which the collected data [results of measurement or observation] meet the standards of quality to be considered valid [trustworthy] and  reliable [dependable].
• Deductive -- a form of reasoning in which conclusions are formulated about particulars from general or universal premises.
• Dependability -- being able to account for changes in the design of the study and the changing conditions surrounding what was studied.
• Dependent Variable -- a variable that varies due, at least in part, to the impact of the independent variable. In other words, its value “depends” on the value of the independent variable. For example, in the variables “gender” and “academic major,” academic major is the dependent variable, meaning that your major cannot determine whether you are male or female, but your gender might indirectly lead you to favor one major over another.
• Deviation -- the distance between the mean and a particular data point in a given distribution.
• Discourse Community -- a community of scholars and researchers in a given field who respond to and communicate to each other through published articles in the community's journals and presentations at conventions. All members of the discourse community adhere to certain conventions for the presentation of their theories and research.
• Discrete Variable -- a variable that is measured solely in whole units, such as, gender and number of siblings.
• Distribution -- the range of values of a particular variable.
• Effect Size -- the amount of change in a dependent variable that can be attributed to manipulations of the independent variable. A large effect size exists when the value of the dependent variable is strongly influenced by the independent variable. It is the mean difference on a variable between experimental and control groups divided by the standard deviation on that variable of the pooled groups or of the control group alone.
• Emancipatory Research -- research is conducted on and with people from marginalized groups or communities. It is led by a researcher or research team who is either an indigenous or external insider; is interpreted within intellectual frameworks of that group; and, is conducted largely for the purpose of empowering members of that community and improving services for them. It also engages members of the community as co-constructors or validators of knowledge.
• Empirical Research -- the process of developing systematized knowledge gained from observations that are formulated to support insights and generalizations about the phenomena being researched.
• Epistemology -- concerns knowledge construction; asks what constitutes knowledge and how knowledge is validated.
• Ethnography -- method to study groups and/or cultures over a period of time. The goal of this type of research is to comprehend the particular group/culture through immersion into the culture or group. Research is completed through various methods but, since the researcher is immersed within the group for an extended period of time, more detailed information is usually collected during the research.
• Expectancy Effect -- any unconscious or conscious cues that convey to the participant in a study how the researcher wants them to respond. Expecting someone to behave in a particular way has been shown to promote the expected behavior. Expectancy effects can be minimized by using standardized interactions with subjects, automated data-gathering methods, and double blind protocols.
• External Validity -- the extent to which the results of a study are generalizable or transferable.
• Factor Analysis -- a statistical test that explores relationships among data. The test explores which variables in a data set are most related to each other. In a carefully constructed survey, for example, factor analysis can yield information on patterns of responses, not simply data on a single response. Larger tendencies may then be interpreted, indicating behavior trends rather than simply responses to specific questions.
• Field Studies -- academic or other investigative studies undertaken in a natural setting, rather than in laboratories, classrooms, or other structured environments.
• Focus Groups -- small, roundtable discussion groups charged with examining specific topics or problems, including possible options or solutions. Focus groups usually consist of 4-12 participants, guided by moderators to keep the discussion flowing and to collect and report the results.
• Framework -- the structure and support that may be used as both the launching point and the on-going guidelines for investigating a research problem.
• Generalizability -- the extent to which research findings and conclusions conducted on a specific study to groups or situations can be applied to the population at large.
• Grey Literature -- research produced by organizations outside of commercial and academic publishing that publish materials, such as, working papers, research reports, and briefing papers.
• Grounded Theory -- practice of developing other theories that emerge from observing a group. Theories are grounded in the group's observable experiences, but researchers add their own insight into why those experiences exist.
• Group Behavior -- behaviors of a group as a whole, as well as the behavior of an individual as influenced by his or her membership in a group.
• Hypothesis -- a tentative explanation based on theory to predict a causal relationship between variables.
• Independent Variable -- the conditions of an experiment that are systematically manipulated by the researcher. A variable that is not impacted by the dependent variable, and that itself impacts the dependent variable. In the earlier example of "gender" and "academic major," (see Dependent Variable) gender is the independent variable.
• Individualism -- a theory or policy having primary regard for the liberty, rights, or independent actions of individuals.
• Inductive -- a form of reasoning in which a generalized conclusion is formulated from particular instances.
• Inductive Analysis -- a form of analysis based on inductive reasoning; a researcher using inductive analysis starts with answers, but formulates questions throughout the research process.
• Insiderness -- a concept in qualitative research that refers to the degree to which a researcher has access to and an understanding of persons, places, or things within a group or community based on being a member of that group or community.
• Internal Consistency -- the extent to which all questions or items assess the same characteristic, skill, or quality.
• Internal Validity -- the rigor with which the study was conducted [e.g., the study's design, the care taken to conduct measurements, and decisions concerning what was and was not measured]. It is also the extent to which the designers of a study have taken into account alternative explanations for any causal relationships they explore. In studies that do not explore causal relationships, only the first of these definitions should be considered when assessing internal validity.
• Life History -- a record of an event/events in a respondent's life told [written down, but increasingly audio or video recorded] by the respondent from his/her own perspective in his/her own words. A life history is different from a "research story" in that it covers a longer time span, perhaps a complete life, or a significant period in a life.
• Margin of Error -- the permittable or acceptable deviation from the target or a specific value. The allowance for slight error or miscalculation or changing circumstances in a study.
• Measurement -- process of obtaining a numerical description of the extent to which persons, organizations, or things possess specified characteristics.
• Meta-Analysis -- an analysis combining the results of several studies that address a set of related hypotheses.
• Methodology -- a theory or analysis of how research does and should proceed.
• Methods -- systematic approaches to the conduct of an operation or process. It includes steps of procedure, application of techniques, systems of reasoning or analysis, and the modes of inquiry employed by a discipline.
• Mixed-Methods -- a research approach that uses two or more methods from both the quantitative and qualitative research categories. It is also referred to as blended methods, combined methods, or methodological triangulation.
• Modeling -- the creation of a physical or computer analogy to understand a particular phenomenon. Modeling helps in estimating the relative magnitude of various factors involved in a phenomenon. A successful model can be shown to account for unexpected behavior that has been observed, to predict certain behaviors, which can then be tested experimentally, and to demonstrate that a given theory cannot account for certain phenomenon.
• Models -- representations of objects, principles, processes, or ideas often used for imitation or emulation.
• Naturalistic Observation -- observation of behaviors and events in natural settings without experimental manipulation or other forms of interference.
• Norm -- the norm in statistics is the average or usual performance. For example, students usually complete their high school graduation requirements when they are 18 years old. Even though some students graduate when they are younger or older, the norm is that any given student will graduate when he or she is 18 years old.
• Null Hypothesis -- the proposition, to be tested statistically, that the experimental intervention has "no effect," meaning that the treatment and control groups will not differ as a result of the intervention. Investigators usually hope that the data will demonstrate some effect from the intervention, thus allowing the investigator to reject the null hypothesis.
• Ontology -- a discipline of philosophy that explores the science of what is, the kinds and structures of objects, properties, events, processes, and relations in every area of reality.
• Panel Study -- a longitudinal study in which a group of individuals is interviewed at intervals over a period of time.
• Participant -- individuals whose physiological and/or behavioral characteristics and responses are the object of study in a research project.
• Peer-Review -- the process in which the author of a book, article, or other type of publication submits his or her work to experts in the field for critical evaluation, usually prior to publication. This is standard procedure in publishing scholarly research.
• Phenomenology -- a qualitative research approach concerned with understanding certain group behaviors from that group's point of view.
• Philosophy -- critical examination of the grounds for fundamental beliefs and analysis of the basic concepts, doctrines, or practices that express such beliefs.
• Phonology -- the study of the ways in which speech sounds form systems and patterns in language.
• Policy -- governing principles that serve as guidelines or rules for decision making and action in a given area.
• Policy Analysis -- systematic study of the nature, rationale, cost, impact, effectiveness, implications, etc., of existing or alternative policies, using the theories and methodologies of relevant social science disciplines.
• Population -- the target group under investigation. The population is the entire set under consideration. Samples are drawn from populations.
• Position Papers -- statements of official or organizational viewpoints, often recommending a particular course of action or response to a situation.
• Positivism -- a doctrine in the philosophy of science, positivism argues that science can only deal with observable entities known directly to experience. The positivist aims to construct general laws, or theories, which express relationships between phenomena. Observation and experiment is used to show whether the phenomena fit the theory.
• Predictive Measurement -- use of tests, inventories, or other measures to determine or estimate future events, conditions, outcomes, or trends.
• Principal Investigator -- the scientist or scholar with primary responsibility for the design and conduct of a research project.
• Probability -- the chance that a phenomenon will occur randomly. As a statistical measure, it is shown as p [the "p" factor].
• Questionnaire -- structured sets of questions on specified subjects that are used to gather information, attitudes, or opinions.
• Random Sampling -- a process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance. Random sampling can be accomplished by first numbering the population, then selecting the sample according to a table of random numbers or using a random-number computer generator. The sample is said to be random because there is no regular or discernible pattern or order. Random sample selection is used under the assumption that sufficiently large samples assigned randomly will exhibit a distribution comparable to that of the population from which the sample is drawn. The random assignment of participants increases the probability that differences observed between participant groups are the result of the experimental intervention.
• Reliability -- the degree to which a measure yields consistent results. If the measuring instrument [e.g., survey] is reliable, then administering it to similar groups would yield similar results. Reliability is a prerequisite for validity. An unreliable indicator cannot produce trustworthy results.
• Representative Sample -- sample in which the participants closely match the characteristics of the population, and thus, all segments of the population are represented in the sample. A representative sample allows results to be generalized from the sample to the population.
• Rigor -- degree to which research methods are scrupulously and meticulously carried out in order to recognize important influences occurring in an experimental study.
• Sample -- the population researched in a particular study. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferred. In studies that use inferential statistics to analyze results or which are designed to be generalizable, sample size is critical, generally the larger the number in the sample, the higher the likelihood of a representative distribution of the population.
• Sampling Error -- the degree to which the results from the sample deviate from those that would be obtained from the entire population, because of random error in the selection of respondent and the corresponding reduction in reliability.
• Saturation -- a situation in which data analysis begins to reveal repetition and redundancy and when new data tend to confirm existing findings rather than expand upon them.
• Semantics -- the relationship between symbols and meaning in a linguistic system. Also, the cuing system that connects what is written in the text to what is stored in the reader's prior knowledge.
• Social Theories -- theories about the structure, organization, and functioning of human societies.
• Sociolinguistics -- the study of language in society and, more specifically, the study of language varieties, their functions, and their speakers.
• Standard Deviation -- a measure of variation that indicates the typical distance between the scores of a distribution and the mean; it is determined by taking the square root of the average of the squared deviations in a given distribution. It can be used to indicate the proportion of data within certain ranges of scale values when the distribution conforms closely to the normal curve.
• Statistical Analysis -- application of statistical processes and theory to the compilation, presentation, discussion, and interpretation of numerical data.
• Statistical Bias -- characteristics of an experimental or sampling design, or the mathematical treatment of data, that systematically affects the results of a study so as to produce incorrect, unjustified, or inappropriate inferences or conclusions.
• Statistical Significance -- the probability that the difference between the outcomes of the control and experimental group are great enough that it is unlikely due solely to chance. The probability that the null hypothesis can be rejected at a predetermined significance level [0.05 or 0.01].
• Statistical Tests -- researchers use statistical tests to make quantitative decisions about whether a study's data indicate a significant effect from the intervention and allow the researcher to reject the null hypothesis. That is, statistical tests show whether the differences between the outcomes of the control and experimental groups are great enough to be statistically significant. If differences are found to be statistically significant, it means that the probability [likelihood] that these differences occurred solely due to chance is relatively low. Most researchers agree that a significance value of .05 or less [i.e., there is a 95% probability that the differences are real] sufficiently determines significance.
• Subcultures -- ethnic, regional, economic, or social groups exhibiting characteristic patterns of behavior sufficient to distinguish them from the larger society to which they belong.
• Testing -- the act of gathering and processing information about individuals' ability, skill, understanding, or knowledge under controlled conditions.
• Theory -- a general explanation about a specific behavior or set of events that is based on known principles and serves to organize related events in a meaningful way. A theory is not as specific as a hypothesis.
• Treatment -- the stimulus given to a dependent variable.
• Trend Samples -- method of sampling different groups of people at different points in time from the same population.
• Triangulation -- a multi-method or pluralistic approach, using different methods in order to focus on the research topic from different viewpoints and to produce a multi-faceted set of data. Also used to check the validity of findings from any one method.
• Unit of Analysis -- the basic observable entity or phenomenon being analyzed by a study and for which data are collected in the form of variables.
• Validity -- the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. A method can be reliable, consistently measuring the same thing, but not valid.
• Variable -- any characteristic or trait that can vary from one person to another [race, gender, academic major] or for one person over time [age, political beliefs].
• Weighted Scores -- scores in which the components are modified by different multipliers to reflect their relative importance.
• White Paper -- an authoritative report that often states the position or philosophy about a social, political, or other subject, or a general explanation of an architecture, framework, or product technology written by a group of researchers. A white paper seeks to contain unbiased information and analysis regarding a business or policy problem that the researchers may be facing.

Elliot, Mark, Fairweather, Ian, Olsen, Wendy Kay, and Pampaka, Maria. A Dictionary of Social Research Methods. Oxford, UK: Oxford University Press, 2016; Free Social Science Dictionary. Socialsciencedictionary.com [2008]. Glossary. Institutional Review Board. Colorado College; Glossary of Key Terms. Writing@CSU. Colorado State University; Glossary A-Z. Education.com; Glossary of Research Terms. Research Mindedness Virtual Learning Resource. Centre for Human Servive Technology. University of Southampton; Miller, Robert L. and Brewer, John D. The A-Z of Social Research: A Dictionary of Key Social Science Research Concepts London: SAGE, 2003; Jupp, Victor. The SAGE Dictionary of Social and Cultural Research Methods . London: Sage, 2006.

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

What Is a Research Design | Types, Guide & Examples

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

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

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

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

Table of contents

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

• Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

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

Types of quantitative research designs

Quantitative designs can be split into four main types.

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

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

• Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

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

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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

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

Operationalization

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

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

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

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

Reliability and validity

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

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

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

Sampling procedures

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

That means making decisions about things like:

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

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

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

Data management

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

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

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

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

Quantitative data analysis

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

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

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

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

Using inferential statistics , you can:

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

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

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

Qualitative data analysis

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

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

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

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

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

 Statistics

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

Research bias

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

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

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

Quantitative research designs can be divided into two main categories:

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

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

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

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

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

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

Operationalization means turning abstract conceptual ideas into measurable observations.

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

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

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

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by Imed Bouchrika, Phd

Co-Founder and Chief Data Scientist

Today’s technology has vastly improved one’s access to knowledge. As such, this has contributed to the production of notable academic research. In fact, a report from the National Science Foundation shows that the global research output for science and engineering increased at an annual rate of around 4% in the last decade . It is made evident by the large volume of peer-reviewed journal articles and conference papers published each year.

Academic research writing involves more than just choosing a topic, collecting and analyzing data, and leveraging academic writing tools . To be considered good, research must meet certain criteria. This article aims to answer the question “What are the characteristics of a good research?" by listing the criteria for such research. Hopefully, this guide can help researchers ensure the quality of research output.

Qualities of Good Academic Research Table of Contents

What is academic research, qualities of good research, common pitfalls of doing research.

Research is a common activity in academic institutions all over the world. In the United States, for instance, research output is bolstered by educational institutions such as Harvard University, Stanford University, and the Massachusetts Institute of Technology (Nature Index, n.d.).

Also called scholarly research, academic research has been defined as research that has the sole purpose of creating or furthering knowledge (ARTiFACTS, 2020). Academic research also tends to be theoretically focused, and its findings are evaluated through a peer review process and made public through scholarly journals and academic conferences.

In many cases, academic research is defined in contrast to professional research. Also called applied research, professional research is carried out to find solutions to practical problems. This research is also commonly organizationally focused (Belmont University, 2021).

Below is a table illustrating the main differences between academic and professional research.

1. Good research is anchored on a sound research question.

A sound research question is one of the most important characteristics of good research. In fact, formulating one is embedded in the curricula of research-heavy programs like engineering and physics degrees and careers . In 2010, Farrugia et al. proposed that developing a research question is the most important step in doing a research project, and is at the core of what makes a good research.

A good research question details exactly what a researcher wants to learn and defines a study’s scope. By formulating a good research question, researchers can ensure that they stay on track during the course of their study. This research question sets the scope of the study to a specific age group and focuses on the relationship between aerobic exercise and mental health outcomes. With a clear research question, researchers can design a study and develop a scope of work sample that includes selecting appropriate participants, determining the measurement instruments, collecting and analyzing data, and drawing conclusions based on the results.

However, the formulation of a research question is often easier said than done. As such, numerous frameworkslike the FINER and PICO criteriahave been invented to help researchers formulate sound research questions.

For instance, Cummings et al. (2013) suggest using FINER criteria to create or evaluate a research question. According to this set of criteria, a good research question is:

• I interesting

2. Good research follows a systematic, appropriate research methodology.

The overall quality and success of a research study are largely determined by the research methodology it uses (Thattamparambil, 2020). Choosing an appropriate research methodology helps ensure that researchers can collect relevant data and use the right data analysis techniques.

A good research methodology is another quality of good research. It refers to the systematic procedures or techniques a researcher uses to ensure that his study achieves valid, reliable results (Jansen & Warren, 2020). Research methodologies are often classified into qualitative research, quantitative research, and mixed-methods research.

• Qualitative research methodology involves collecting and analyzing non-numerical data, such as language to interpret subjects’ beliefs, experiences, and behaviors (Pathak et al., 2013). Qualitative research techniques include interviews, focus groups, and case studies.
• Quantitative research methodologies  involve the collection and analysis of numerical data to discover patterns, test relationships, and make predictions (Bhandari, 2021a). In doing quantitative research, surveys, experiments, and systematic observation can be used to collect accurate data.
• Mixed-methods research methodologies combine quantitative and qualitative methods. According to Wisdom and Cresswell (2013), combining quantitative and qualitative research methodologies “permits a more complete and synergistic utilization of data than do separate quantitative and qualitative data collection and analysis."

Researchers must consider a variety of factors in choosing the best methodology for their study. In most cases, research questions and objectives play a significant role in defining the most appropriate research methodology to use.

Researchers should also take into account the methods currently used by other researchers in their specific field. For instance, studies have shown the increasing use of mixed-methods research in the health sciences. In their 2019 article “Mixed methods and survey research in family medicine and community health" published in the Family Medicine and Community Health journal, Cresswell and Hirose observed how surveys were used in combination with focus groups on resident physicians’ communication and collaboration competencies:

“Thus, the authors in the Sonnenberg et al. study used an explanatory sequential mixed methods design to examine the ability of the IP clinicians to provide feedback to pediatric residents during their rotation. Using survey research in the first phase, the researchers compared IP supervisors and physician supervisors in terms of communication and if collaborative training objectives were met. …Then, in the second phase, the researchers conducted follow-up qualitative focus groups to probe a contextual understanding of the factors that influenced the process of assessment."

3. Good research acknowledges previous research on the topic.

While good research leads to the discovery of new knowledge, it also means studying previous research on the topic. By studying scholarly articles and other works related to your subject of interest, you get an idea of what has already been studied and how your study fits into existing research. You can easily find related studies by going through your institution’s library management system or other publicly available ones.

As one of the criteria of a good research, exploring previous research can also ensure that you’re not duplicating existing work, which is commonly checked in physics and industrial engineering careers . Related literature can also shed light on potential obstacles and issues researchers may encounter during their studies.

Given the importance of studying research related to one’s topic, most academic research projects (like theses or dissertations) feature a literature review. A literature review describes and objectively evaluates scholarly articles, books, and other credible sources relevant to a particular field of study, helping readers gain a full understanding of the topic at hand (Bloomsburg University of Pennsylvania, n.d.).

According to the latest edition of The STM Report from the International Association of Scientific, Technical, and Medical Publishers, there were approximately 33,100 active scholarly peer-reviewed English-language journals in mid-2018. At an annual growth rate of 4%, these journals publish over three million articles a year (Johnson et al., 2018). With these numbers, it appears to be unlikely for researchers to face difficulties in finding literature related to their research topic.

4. Good research uses relevant, empirical data and proper data analysis methods.

One of the most important qualities of a good research study is that it deals with empirical data. Empirical data is data that has been collected by researchers themselves through observation, experience, or experimentation (Bradford, 2017). This is crucial in doing good research because empirical data is considered objective, unbiased evidence.

Good research doesn’t stop with the collection of empirical data, the data collected must be analyzed properly as well. The type of data collected largely determines the right data analysis method to use.

Quantitative data, for instance, is usually analyzed through descriptive statistics or inferential statistics (Humans of Data, 2018). These statistics can help researchers find figures to summarize variables, find patterns, and make predictions. On the other hand, the analysis of qualitative data involves identifying and interpreting patterns and themes in textual data. Common analysis methods for qualitative data include content analysis, narrative analysis, and thematic analysis (Warren, 2020).

Using these analysis methods, you can interpret quantitative or qualitative data to answer your research question.

5. Good research is representative and generalizable.

Criteria of good research include being representative. In research, representativeness refers to a sample’s ability to represent a larger group. This means the characteristics of the subjects (people) being studied closely match those of the study’s target population (Austin Research, 2014).

In most cases, representativeness can be achieved through population sampling (Economic Research and Social Council, n.d.). By using proper methods to create a representative sample, researchers can ensure that their findings can be generalized to the larger population represented.

The table below depicts the uses, advantages, and limitations of the most common sampling methods used by researchers today.

6. Good research is guided by logic.

One of the distinguishing characteristics of research is that the entire process is guided by logic. Using logic, for instance, can help researchers determine what kind of data they need for answering their research question. Being guided by logic throughout the research process also helps researchers spot fallacies and inconsistencies in their claims and findings.

The logical processes of induction and deduction can also prove to be valuable in the research process. Golesh et al. (2019) proposed that logic aids researchers by helping them arrive at valid conclusions . According to the study, inductive reasoning can be used to discover patterns and construct generalizations and theories. Meanwhile, deductive reasoning can help researchers collect empirical data to confirm or refute theories or hypotheses.

Aside from these applications of logic, logical reasoning can also make more research more meaningful, especially if the research is to be used in the context of decision-making (Mehran University of Engineering and Technology, n.d.).

7. Good research has external validity.

Good research has external validity and reliability if its results or findings can be applied to the real world (Glen, 2015). If your research findings can be generalized to other situations or applied to a broader context, your study has high external validity.

There are two types of external validity for researchers to consider: population validity and ecological validity (Bhandari, 2021b). Research with findings that can be generalized from the sample to the larger population has a high population validity. Meanwhile, you can achieve ecological validity if you can apply your study’s findings to real-world situations and settings.

Since generalizable knowledge is almost always the aim of scientific research, external validity is an important component of good research as well.

8. Good research is replicable, reproducible, and transparent.

Replicability, reproducibility, and transparency are some of the most important characteristics of research. The replicability of a research study is important because this allows other researchers to test the study’s findings. Replicability can also improve the trustworthiness of a research’s findings among readers (Understanding Health Research, 2020).

Good research is also reproducible. Though replicability and reproducibility are often used interchangeably, research is reproducible if researchers achieve consistent results using the same data and analysis methods (Miceli, 2019). The reproducibility and replicability of a research study and its findings can confirm the study’s overall validity and credibility.

For research to be replicable or reproducible, it must also be transparent or available to other researchers. Research must follow proper research paper formatting or be written or presented in such a way that it provides comprehensive details on how data was collected and analyzed and how conclusions were reached (Baskin, 2015). This is why most scholarly articles provide clear descriptions of their corresponding research process.

9. Good research acknowledges its limitations and provides suggestions for future research.

In addition to information on data collection and analysis methods, good research also opens doors for future research on the topic. For instance, researchers can provide details on unexpected study findings or suggest techniques for exploring unaddressed aspects of your research problem or research question (Business Research Methodology, n.d.).

In many cases, these suggestions for future research stem from the research’s limitations. Researchers must acknowledge their study’s limitations and potential flaws and present these along with the study’s findings and conclusion. Ross and Zaidi (2019) further explain that a meaningful presentation of a research study’s limitations includes implications of these limitations and potential alternative approaches.

10. Good research is ethical.

Understandably, good research is carried out according to research ethics. According to the World Health Organization, research ethics provide academic research standards for conducting studies. These standards help protect the rights and dignity of research participants while ensuring that researchers practice values, such as honesty, objectivity, integrity, and accountability in their work (Resnik, 2020).

Resnik also emphasizes the importance of learning how to interpret and apply various ethical standards in research, especially since existing ethical codes won’t cover every situation.

Some of the most common violations of research ethics include:

• Falsification This involves the manipulation or omission of data or findings.
• Fabrication This involves making up data or results and presenting these as accurate.
• Plagiarism This refers to the use of another person’s work without giving due credit.

While self-citation and self-referencing are common research methodology best practices among scientists, recent studies show rising trends in excessive self-citation. A 2017 study on citation metrics revealed that at least 250 scientists collected over 50% of their citations from themselves or their co-authors. This figure is significantly higher than the median self-citation rate of 12.7% (Ioannis et al., 2019).

According to the Committee on Publication Ethics, extreme self-citation is a form of citation manipulation. This manipulation may stem from authorities’ over-reliance on citation metrics to make decisions on career advancement and research funding (Van Noorden & Chawla, 2019). As well, academic institutions and private organizations rely on citations to bolster their h-index ranking and overall institution ranking, creating an overly competitive market that invites unscrupulous scientists and organizations to manipulate the system.

Knowing what are the qualities of a good research enables research writers to convey authority and credibility. In addition to the characteristics of good research, researchers must also be aware of the difficulties they may encounter during the course of their study. Shreffler and Huecker (2021) list some of the pitfalls common in the research process:

• Underestimating the commitment required by a research study The process of properly conducting a research study and getting it published takes a significant amount of time and effort. Researchers must be prepared not only for lengthy data collection and analysis methods but also for setbacks, such as subjects dropping out of the study and article revisions.
• Searching for up-to-date, high-quality references Researchers may also encounter challenges in finding related literature or references that are relevant and up-to-date. This is why it’s important to adopt literature review strategies early during the research process.
• Not limiting variables of data to be collected It’s easy to get carried away during the data collection phase and collect as much data as possible. To ensure that the data collection period is used as efficiently as possible, researchers should ignore irrelevant variables in data and focus on the variables that will be most beneficial to the study.

Is your research good enough?

Hopefully, this guide on the qualities of good research has helped you evaluate whether your study is on the right track. Good research starts with a sound research question, which influences the research methodology, including data collection and analysis methods.

The findings of a good research study are based on empirical data collected from a sample representative of the population. More importantly, good research is ethical and transparent. Transparency is crucial in ensuring that a research study is replicable and reproducible. Moreover, you would want your work to be visible, so improving your digital footprint also helps.

If you’re looking for more ways to improve your research study, you can also check out our guide on writing a research paper for publication .

Key Insights

• Sound Research Question: A good research study starts with a well-defined, clear research question that guides the study's scope and objectives.
• Appropriate Methodology: The choice of research methodology is crucial. It ensures that data collection and analysis are valid, reliable, and suitable for the research question.
• Literature Review: Good research acknowledges and builds upon existing studies, ensuring the researcher is informed about the current state of knowledge in the field.
• Empirical Data and Analysis: Effective research relies on empirical data and appropriate data analysis methods to produce unbiased and objective findings.
• Representativeness and Generalizability: Research should be based on a representative sample to ensure findings can be generalized to a larger population.
• Logical Framework: The research process should be guided by logic, using inductive and deductive reasoning to reach valid conclusions.
• External Validity: Research findings should be applicable to real-world contexts and generalizable to other situations.
• Replicability and Transparency: Good research is replicable and reproducible, with transparent methodologies and clear reporting to allow for verification by other researchers.
• Acknowledging Limitations: Researchers should openly acknowledge the limitations of their studies and suggest directions for future research.
• Ethical Conduct: Adhering to ethical standards is essential, including honesty, integrity, and accountability in conducting and reporting research.

1. What makes a research question sound?

A sound research question is specific, clear, and focused on a particular issue. It should be feasible, interesting, novel, ethical, and relevant (FINER criteria). A well-formulated question defines the scope of the study and guides the research process.

2. How do I choose the right research methodology?

The right research methodology depends on the research question and objectives. Researchers should consider whether qualitative, quantitative, or mixed methods best suit their study. They should also review methodologies commonly used in their field to ensure compatibility and relevance.

3. Why is reviewing previous research important?

Reviewing previous research helps to build on existing knowledge, avoid duplication, and understand the current state of the field. It provides context for the new study and highlights potential challenges and gaps in existing research that the new study can address.

4. What is empirical data and why is it important?

Empirical data is information collected through direct observation or experimentation. It is crucial because it provides objective, unbiased evidence that supports the research findings. Proper analysis of empirical data ensures the reliability and validity of the study.

5. How can I ensure my research sample is representative?

To ensure representativeness, researchers should use proper sampling methods that reflect the characteristics of the larger population. Techniques like random sampling, stratified sampling, and cluster sampling help achieve a representative sample.

6. What role does logic play in the research process?

Logic helps in structuring the research process, from formulating the research question to drawing conclusions. Inductive reasoning helps in developing theories based on observed patterns, while deductive reasoning tests hypotheses derived from existing theories.

7. What is the difference between replicability and reproducibility in research?

Replicability means that other researchers can achieve similar results by following the same methodology. Reproducibility means obtaining consistent results using the same data and analysis methods. Both are essential for verifying the validity and credibility of research findings.

8. Why is it important to acknowledge research limitations?

Acknowledging limitations provides a complete picture of the research's scope and context. It helps readers understand potential flaws or constraints in the study and offers a basis for future research to address these issues.

9. How can researchers ensure their studies are ethical?

Researchers can ensure ethical conduct by following established guidelines and standards, such as obtaining informed consent, ensuring participant confidentiality, and avoiding data manipulation or fabrication. Transparency and integrity are key to maintaining ethical standards.

10. What are some common pitfalls in the research process?

Common pitfalls include underestimating the time and effort required, difficulty in finding relevant literature, and collecting irrelevant data. Researchers can avoid these pitfalls by careful planning, thorough literature review, and focusing on relevant variables.

References:

• ARTiFACTS. (2020, April 20).  What is academic research and what does it look like in practice? ARTiFACTS
• Austin Research. (2014, July 30).  The importance of representative samples and how to get them . Austin Research
• Baskin, P. (2020, December 22).  Transparency in research and reporting: Expanding the effort through new tools for authors and editors . Editage Insights
• Belmont University. (2021, April 30).  Research guides: Public relations: Academic and applied research . Research Guides at Belmont University
• Bhandari, P. (2021a).  What is quantitative research? | Definition, uses and methods . Scribbr
• Bhandari, P. (2021b).  External validity | Types, threats & examples . Scribbr
• Bradford, A. (2017, July 28).  Empirical evidence: A definition . Live Science
• Business Research Methodology. (n.d.).  Suggestions for future research . Research-Methodology
• Creswell, J. W., & Hirose, M. (2019). Mixed methods and survey research in family medicine and community health.  Family Medicine and Community Health ,  7 (2). NCBI
• Cummings, S. R., Browner, W. S., & Hulley, S. B. (2013). Conceiving the research question and developing the study plan. Designing clinical research , 4 , 14-22. Wolters Kluwer Health
• Economic and Social Research Council. (n.d.).  Methodologies: What makes good research?   ESRC
• Editage Insights. (2019, July 19).  What does good research mean?   Editage Insights
• Farrugia, P., Petrisor, B. A., Farrokhyar, F., & Bhandari, M. (2010). Research questions, hypotheses and objectives. Canadian journal of surgery , 53 (4), 278. NCBI
• Glen, S. (2019, June 27).  External validity definition & examples . Statistics How To
• Golesh, D., Baba Girei, Z., & Ibrahim, F. (n.d.). The role of logic in research.  International Journal of Scientific & Engineering Research ,  10 (10), 894-904. IJSER
• Humans of Data. (2019, July 12).  Your guide to qualitative and quantitative data analysis methods . Humans of Data
• Ioannidis, J. P., Baas, J., Klavans, R., & Boyack, K. W. (2019). A standardized citation metrics author database annotated for scientific field.  PLoS biology ,  17 (8), e3000384. PLoS Biology
• Jansen, D. (2021, June 21).  What is research methodology? Simple definition (With examples) . Grad Coach
• Mehran University of Engineering and Technology. (n.d.).  Criteria of good research . MUET-CRP
• Miceli, S. (2019, September 3).  Reproducibility and replicability in research . The National Academies of Sciences, Engineering, and Medicine 
• Nature Index. (n.d.).  United States of America (USA) | Country outputs . Retrieved July 9, 2021, from Nature Index
• Pathak, V., Jena, B., & Kalra, S. (2013). Qualitative research.  Perspectives in clinical research ,  4 (3). ProQuest
• Resnik, D. (2020, December 23).  What is ethics in research & why is it important?   National Institute of Environmental Health Sciences
• Ross, P. T., & Zaidi, N. L. B. (2019). Limited by our limitations.  Perspectives on medical education ,  8 (4), 261-264. NCBI
• Shreffler, J., & Huecker, M. R. (2021). Common Pitfalls In The Research Process. NCBI
• Thattamparambil, N. (2020, November 22).  How to choose the research methodology best suited for your study . Editage Insights
• Understanding Health Research. (n.d.).  Replicability . Understanding Health Research
• Van Noorden, R., & Chawla, D. (2019, August 19).  Hundreds of extreme self-citing scientists revealed in new database . Nature
• Ware, M., & Mabe, M. (2015). The STM report: An overview of scientific and scholarly journal publishing. STM
• Warren, K. (2021, June 21).  Qualitative data analysis methods 101: Top 5 + examples . Grad Coach
• Wisdom, J., & Creswell, J. W. (2013). Mixed methods: integrating quantitative and qualitative data collection and analysis while studying patient-centered medical home models.  Rockville: Agency for Healthcare Research and Quality . AHRQ

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Effects of Very Low Nicotine Content Cigarettes and Nicotine Vaping Device Characteristics on Choices to Smoke, Vape, or Abstain in Early Young Adults

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Rachel N Cassidy, Jennifer W Tidey, Mariel S Bello, Rachel Denlinger-Apte, Christine Goodwin, Julissa Godin, Patricia A Cioe, Robert Swift, Connor Demorest, Joseph S Koopmeiners, Eric Donny, Dorothy Hatsukami, Suzanne M Colby, Effects of Very Low Nicotine Content Cigarettes and Nicotine Vaping Device Characteristics on Choices to Smoke, Vape, or Abstain in Early Young Adults, Nicotine & Tobacco Research , 2024;, ntae194, https://doi.org/10.1093/ntr/ntae194

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A national nicotine reduction policy could reduce the public health toll of smoking. However, reducing nicotine in cigarettes may lead to changes in the use of other tobacco products such as nicotine vaping devices, particularly among young people. Product use outcomes may depend on characteristics of available nicotine vaping devices. We aimed to determine the impact of cigarette nicotine content, vaping device nicotine concentration, and vaping device flavors on choices to smoke, vape, or abstain.

Early young adults (ages 18-20 inclusive, N =80) who reported smoking daily and vaping nicotine at least twice in their lifetime participated in a laboratory study. Participants received either Very Low Nicotine Content (VLNC; 0.4 mg nicotine/g of tobacco) or Normal Nicotine Content (NNC; 15.8 mg/g) cigarettes. First, participants chose between their assigned cigarette or abstaining. Subsequently, participants chose between 2 cigarette puffs, 2 vape puffs, or abstaining. Vaping device nicotine concentration (3mg vs. 18mg/ml) and flavor (tobacco vs. non-tobacco) were manipulated within-subjects.

When only cigarettes were available, there were no differences between the VLNC and NNC groups on cigarette choices. When the nicotine vaping device was concurrently available, the VLNC group made fewer choices to smoke than the NNC group. Non-tobacco flavors and lower vaping device nicotine concentration were associated with fewer choices to smoke.

Nicotine vaping device availability reduced choices to smoke VLNC cigarettes, and vaping devices with lower nicotine and non-tobacco flavors led to the fewest choices to smoke. Regulators should consider that the availability and characteristics of alternative tobacco products can moderate the product standard’s impact.

The U.S. Food and Drug Administration may enact a reduced nicotine product standard that would affect all commercially-available cigarettes. One important population affected by this policy would be early young adults who smoke. We aimed to determine the impact of cigarette nicotine content, vaping device nicotine concentration, and vaping device flavors on choices to smoke, vape, or abstain. Lower nicotine in cigarettes, along with non-tobacco flavors and lower nicotine concentration in the vaping device, were associated with the fewest choices to smoke. Regulators should consider that the availability and characteristics of alternative tobacco products can moderate the product standard’s impact.

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How to cite ChatGPT

Use discount code STYLEBLOG15 for 15% off APA Style print products with free shipping in the United States.

We, the APA Style team, are not robots. We can all pass a CAPTCHA test , and we know our roles in a Turing test . And, like so many nonrobot human beings this year, we’ve spent a fair amount of time reading, learning, and thinking about issues related to large language models, artificial intelligence (AI), AI-generated text, and specifically ChatGPT . We’ve also been gathering opinions and feedback about the use and citation of ChatGPT. Thank you to everyone who has contributed and shared ideas, opinions, research, and feedback.

In this post, I discuss situations where students and researchers use ChatGPT to create text and to facilitate their research, not to write the full text of their paper or manuscript. We know instructors have differing opinions about how or even whether students should use ChatGPT, and we’ll be continuing to collect feedback about instructor and student questions. As always, defer to instructor guidelines when writing student papers. For more about guidelines and policies about student and author use of ChatGPT, see the last section of this post.

Quoting or reproducing the text created by ChatGPT in your paper

If you’ve used ChatGPT or other AI tools in your research, describe how you used the tool in your Method section or in a comparable section of your paper. For literature reviews or other types of essays or response or reaction papers, you might describe how you used the tool in your introduction. In your text, provide the prompt you used and then any portion of the relevant text that was generated in response.

Unfortunately, the results of a ChatGPT “chat” are not retrievable by other readers, and although nonretrievable data or quotations in APA Style papers are usually cited as personal communications , with ChatGPT-generated text there is no person communicating. Quoting ChatGPT’s text from a chat session is therefore more like sharing an algorithm’s output; thus, credit the author of the algorithm with a reference list entry and the corresponding in-text citation.

When prompted with “Is the left brain right brain divide real or a metaphor?” the ChatGPT-generated text indicated that although the two brain hemispheres are somewhat specialized, “the notation that people can be characterized as ‘left-brained’ or ‘right-brained’ is considered to be an oversimplification and a popular myth” (OpenAI, 2023).

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

You may also put the full text of long responses from ChatGPT in an appendix of your paper or in online supplemental materials, so readers have access to the exact text that was generated. It is particularly important to document the exact text created because ChatGPT will generate a unique response in each chat session, even if given the same prompt. If you create appendices or supplemental materials, remember that each should be called out at least once in the body of your APA Style paper.

When given a follow-up prompt of “What is a more accurate representation?” the ChatGPT-generated text indicated that “different brain regions work together to support various cognitive processes” and “the functional specialization of different regions can change in response to experience and environmental factors” (OpenAI, 2023; see Appendix A for the full transcript).

Creating a reference to ChatGPT or other AI models and software

The in-text citations and references above are adapted from the reference template for software in Section 10.10 of the Publication Manual (American Psychological Association, 2020, Chapter 10). Although here we focus on ChatGPT, because these guidelines are based on the software template, they can be adapted to note the use of other large language models (e.g., Bard), algorithms, and similar software.

The reference and in-text citations for ChatGPT are formatted as follows:

• Parenthetical citation: (OpenAI, 2023)
• Narrative citation: OpenAI (2023)

Let’s break that reference down and look at the four elements (author, date, title, and source):

Author: The author of the model is OpenAI.

Date: The date is the year of the version you used. Following the template in Section 10.10, you need to include only the year, not the exact date. The version number provides the specific date information a reader might need.

Title: The name of the model is “ChatGPT,” so that serves as the title and is italicized in your reference, as shown in the template. Although OpenAI labels unique iterations (i.e., ChatGPT-3, ChatGPT-4), they are using “ChatGPT” as the general name of the model, with updates identified with version numbers.

The version number is included after the title in parentheses. The format for the version number in ChatGPT references includes the date because that is how OpenAI is labeling the versions. Different large language models or software might use different version numbering; use the version number in the format the author or publisher provides, which may be a numbering system (e.g., Version 2.0) or other methods.

Bracketed text is used in references for additional descriptions when they are needed to help a reader understand what’s being cited. References for a number of common sources, such as journal articles and books, do not include bracketed descriptions, but things outside of the typical peer-reviewed system often do. In the case of a reference for ChatGPT, provide the descriptor “Large language model” in square brackets. OpenAI describes ChatGPT-4 as a “large multimodal model,” so that description may be provided instead if you are using ChatGPT-4. Later versions and software or models from other companies may need different descriptions, based on how the publishers describe the model. The goal of the bracketed text is to briefly describe the kind of model to your reader.

Source: When the publisher name and the author name are the same, do not repeat the publisher name in the source element of the reference, and move directly to the URL. This is the case for ChatGPT. The URL for ChatGPT is https://chat.openai.com/chat . For other models or products for which you may create a reference, use the URL that links as directly as possible to the source (i.e., the page where you can access the model, not the publisher’s homepage).

Other questions about citing ChatGPT

You may have noticed the confidence with which ChatGPT described the ideas of brain lateralization and how the brain operates, without citing any sources. I asked for a list of sources to support those claims and ChatGPT provided five references—four of which I was able to find online. The fifth does not seem to be a real article; the digital object identifier given for that reference belongs to a different article, and I was not able to find any article with the authors, date, title, and source details that ChatGPT provided. Authors using ChatGPT or similar AI tools for research should consider making this scrutiny of the primary sources a standard process. If the sources are real, accurate, and relevant, it may be better to read those original sources to learn from that research and paraphrase or quote from those articles, as applicable, than to use the model’s interpretation of them.

We’ve also received a number of other questions about ChatGPT. Should students be allowed to use it? What guidelines should instructors create for students using AI? Does using AI-generated text constitute plagiarism? Should authors who use ChatGPT credit ChatGPT or OpenAI in their byline? What are the copyright implications ?

On these questions, researchers, editors, instructors, and others are actively debating and creating parameters and guidelines. Many of you have sent us feedback, and we encourage you to continue to do so in the comments below. We will also study the policies and procedures being established by instructors, publishers, and academic institutions, with a goal of creating guidelines that reflect the many real-world applications of AI-generated text.

For questions about manuscript byline credit, plagiarism, and related ChatGPT and AI topics, the APA Style team is seeking the recommendations of APA Journals editors. APA Style guidelines based on those recommendations will be posted on this blog and on the APA Style site later this year.

Update: APA Journals has published policies on the use of generative AI in scholarly materials .

We, the APA Style team humans, appreciate your patience as we navigate these unique challenges and new ways of thinking about how authors, researchers, and students learn, write, and work with new technologies.

American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000

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Home » Research Report – Example, Writing Guide and Types

Research Report – Example, Writing Guide and Types

Table of Contents

Research Report

Definition:

Research Report is a written document that presents the results of a research project or study, including the research question, methodology, results, and conclusions, in a clear and objective manner.

The purpose of a research report is to communicate the findings of the research to the intended audience, which could be other researchers, stakeholders, or the general public.

Components of Research Report

Components of Research Report are as follows:

Introduction

The introduction sets the stage for the research report and provides a brief overview of the research question or problem being investigated. It should include a clear statement of the purpose of the study and its significance or relevance to the field of research. It may also provide background information or a literature review to help contextualize the research.

Literature Review

The literature review provides a critical analysis and synthesis of the existing research and scholarship relevant to the research question or problem. It should identify the gaps, inconsistencies, and contradictions in the literature and show how the current study addresses these issues. The literature review also establishes the theoretical framework or conceptual model that guides the research.

Methodology

The methodology section describes the research design, methods, and procedures used to collect and analyze data. It should include information on the sample or participants, data collection instruments, data collection procedures, and data analysis techniques. The methodology should be clear and detailed enough to allow other researchers to replicate the study.

The results section presents the findings of the study in a clear and objective manner. It should provide a detailed description of the data and statistics used to answer the research question or test the hypothesis. Tables, graphs, and figures may be included to help visualize the data and illustrate the key findings.

The discussion section interprets the results of the study and explains their significance or relevance to the research question or problem. It should also compare the current findings with those of previous studies and identify the implications for future research or practice. The discussion should be based on the results presented in the previous section and should avoid speculation or unfounded conclusions.

The conclusion summarizes the key findings of the study and restates the main argument or thesis presented in the introduction. It should also provide a brief overview of the contributions of the study to the field of research and the implications for practice or policy.

The references section lists all the sources cited in the research report, following a specific citation style, such as APA or MLA.

The appendices section includes any additional material, such as data tables, figures, or instruments used in the study, that could not be included in the main text due to space limitations.

Types of Research Report

Types of Research Report are as follows:

Thesis is a type of research report. A thesis is a long-form research document that presents the findings and conclusions of an original research study conducted by a student as part of a graduate or postgraduate program. It is typically written by a student pursuing a higher degree, such as a Master’s or Doctoral degree, although it can also be written by researchers or scholars in other fields.

Research Paper

Research paper is a type of research report. A research paper is a document that presents the results of a research study or investigation. Research papers can be written in a variety of fields, including science, social science, humanities, and business. They typically follow a standard format that includes an introduction, literature review, methodology, results, discussion, and conclusion sections.

Technical Report

A technical report is a detailed report that provides information about a specific technical or scientific problem or project. Technical reports are often used in engineering, science, and other technical fields to document research and development work.

Progress Report

A progress report provides an update on the progress of a research project or program over a specific period of time. Progress reports are typically used to communicate the status of a project to stakeholders, funders, or project managers.

Feasibility Report

A feasibility report assesses the feasibility of a proposed project or plan, providing an analysis of the potential risks, benefits, and costs associated with the project. Feasibility reports are often used in business, engineering, and other fields to determine the viability of a project before it is undertaken.

Field Report

A field report documents observations and findings from fieldwork, which is research conducted in the natural environment or setting. Field reports are often used in anthropology, ecology, and other social and natural sciences.

Experimental Report

An experimental report documents the results of a scientific experiment, including the hypothesis, methods, results, and conclusions. Experimental reports are often used in biology, chemistry, and other sciences to communicate the results of laboratory experiments.

Case Study Report

A case study report provides an in-depth analysis of a specific case or situation, often used in psychology, social work, and other fields to document and understand complex cases or phenomena.

Literature Review Report

A literature review report synthesizes and summarizes existing research on a specific topic, providing an overview of the current state of knowledge on the subject. Literature review reports are often used in social sciences, education, and other fields to identify gaps in the literature and guide future research.

Research Report Example

Following is a Research Report Example sample for Students:

Title: The Impact of Social Media on Academic Performance among High School Students

This study aims to investigate the relationship between social media use and academic performance among high school students. The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The findings indicate that there is a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students. The results of this study have important implications for educators, parents, and policymakers, as they highlight the need for strategies that can help students balance their social media use and academic responsibilities.

Introduction:

Social media has become an integral part of the lives of high school students. With the widespread use of social media platforms such as Facebook, Twitter, Instagram, and Snapchat, students can connect with friends, share photos and videos, and engage in discussions on a range of topics. While social media offers many benefits, concerns have been raised about its impact on academic performance. Many studies have found a negative correlation between social media use and academic performance among high school students (Kirschner & Karpinski, 2010; Paul, Baker, & Cochran, 2012).

Given the growing importance of social media in the lives of high school students, it is important to investigate its impact on academic performance. This study aims to address this gap by examining the relationship between social media use and academic performance among high school students.

Methodology:

The study utilized a quantitative research design, which involved a survey questionnaire administered to a sample of 200 high school students. The questionnaire was developed based on previous studies and was designed to measure the frequency and duration of social media use, as well as academic performance.

The participants were selected using a convenience sampling technique, and the survey questionnaire was distributed in the classroom during regular school hours. The data collected were analyzed using descriptive statistics and correlation analysis.

The findings indicate that the majority of high school students use social media platforms on a daily basis, with Facebook being the most popular platform. The results also show a negative correlation between social media use and academic performance, suggesting that excessive social media use can lead to poor academic performance among high school students.

Discussion:

The results of this study have important implications for educators, parents, and policymakers. The negative correlation between social media use and academic performance suggests that strategies should be put in place to help students balance their social media use and academic responsibilities. For example, educators could incorporate social media into their teaching strategies to engage students and enhance learning. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. Policymakers could develop guidelines and policies to regulate social media use among high school students.

Conclusion:

In conclusion, this study provides evidence of the negative impact of social media on academic performance among high school students. The findings highlight the need for strategies that can help students balance their social media use and academic responsibilities. Further research is needed to explore the specific mechanisms by which social media use affects academic performance and to develop effective strategies for addressing this issue.

Limitations:

One limitation of this study is the use of convenience sampling, which limits the generalizability of the findings to other populations. Future studies should use random sampling techniques to increase the representativeness of the sample. Another limitation is the use of self-reported measures, which may be subject to social desirability bias. Future studies could use objective measures of social media use and academic performance, such as tracking software and school records.

Implications:

The findings of this study have important implications for educators, parents, and policymakers. Educators could incorporate social media into their teaching strategies to engage students and enhance learning. For example, teachers could use social media platforms to share relevant educational resources and facilitate online discussions. Parents could limit their children’s social media use and encourage them to prioritize their academic responsibilities. They could also engage in open communication with their children to understand their social media use and its impact on their academic performance. Policymakers could develop guidelines and policies to regulate social media use among high school students. For example, schools could implement social media policies that restrict access during class time and encourage responsible use.

References:

• Kirschner, P. A., & Karpinski, A. C. (2010). Facebook® and academic performance. Computers in Human Behavior, 26(6), 1237-1245.
• Paul, J. A., Baker, H. M., & Cochran, J. D. (2012). Effect of online social networking on student academic performance. Journal of the Research Center for Educational Technology, 8(1), 1-19.
• Pantic, I. (2014). Online social networking and mental health. Cyberpsychology, Behavior, and Social Networking, 17(10), 652-657.
• Rosen, L. D., Carrier, L. M., & Cheever, N. A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29(3), 948-958.

Note*: Above mention, Example is just a sample for the students’ guide. Do not directly copy and paste as your College or University assignment. Kindly do some research and Write your own.

Applications of Research Report

Research reports have many applications, including:

• Communicating research findings: The primary application of a research report is to communicate the results of a study to other researchers, stakeholders, or the general public. The report serves as a way to share new knowledge, insights, and discoveries with others in the field.
• Informing policy and practice : Research reports can inform policy and practice by providing evidence-based recommendations for decision-makers. For example, a research report on the effectiveness of a new drug could inform regulatory agencies in their decision-making process.
• Supporting further research: Research reports can provide a foundation for further research in a particular area. Other researchers may use the findings and methodology of a report to develop new research questions or to build on existing research.
• Evaluating programs and interventions : Research reports can be used to evaluate the effectiveness of programs and interventions in achieving their intended outcomes. For example, a research report on a new educational program could provide evidence of its impact on student performance.
• Demonstrating impact : Research reports can be used to demonstrate the impact of research funding or to evaluate the success of research projects. By presenting the findings and outcomes of a study, research reports can show the value of research to funders and stakeholders.
• Enhancing professional development : Research reports can be used to enhance professional development by providing a source of information and learning for researchers and practitioners in a particular field. For example, a research report on a new teaching methodology could provide insights and ideas for educators to incorporate into their own practice.

How to write Research Report

Here are some steps you can follow to write a research report:

• Identify the research question: The first step in writing a research report is to identify your research question. This will help you focus your research and organize your findings.
• Conduct research : Once you have identified your research question, you will need to conduct research to gather relevant data and information. This can involve conducting experiments, reviewing literature, or analyzing data.
• Organize your findings: Once you have gathered all of your data, you will need to organize your findings in a way that is clear and understandable. This can involve creating tables, graphs, or charts to illustrate your results.
• Write the report: Once you have organized your findings, you can begin writing the report. Start with an introduction that provides background information and explains the purpose of your research. Next, provide a detailed description of your research methods and findings. Finally, summarize your results and draw conclusions based on your findings.
• Proofread and edit: After you have written your report, be sure to proofread and edit it carefully. Check for grammar and spelling errors, and make sure that your report is well-organized and easy to read.
• Include a reference list: Be sure to include a list of references that you used in your research. This will give credit to your sources and allow readers to further explore the topic if they choose.
• Format your report: Finally, format your report according to the guidelines provided by your instructor or organization. This may include formatting requirements for headings, margins, fonts, and spacing.

Purpose of Research Report

The purpose of a research report is to communicate the results of a research study to a specific audience, such as peers in the same field, stakeholders, or the general public. The report provides a detailed description of the research methods, findings, and conclusions.

Some common purposes of a research report include:

• Sharing knowledge: A research report allows researchers to share their findings and knowledge with others in their field. This helps to advance the field and improve the understanding of a particular topic.
• Identifying trends: A research report can identify trends and patterns in data, which can help guide future research and inform decision-making.
• Addressing problems: A research report can provide insights into problems or issues and suggest solutions or recommendations for addressing them.
• Evaluating programs or interventions : A research report can evaluate the effectiveness of programs or interventions, which can inform decision-making about whether to continue, modify, or discontinue them.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies.

When to Write Research Report

A research report should be written after completing the research study. This includes collecting data, analyzing the results, and drawing conclusions based on the findings. Once the research is complete, the report should be written in a timely manner while the information is still fresh in the researcher’s mind.

In academic settings, research reports are often required as part of coursework or as part of a thesis or dissertation. In this case, the report should be written according to the guidelines provided by the instructor or institution.

In other settings, such as in industry or government, research reports may be required to inform decision-making or to comply with regulatory requirements. In these cases, the report should be written as soon as possible after the research is completed in order to inform decision-making in a timely manner.

Overall, the timing of when to write a research report depends on the purpose of the research, the expectations of the audience, and any regulatory requirements that need to be met. However, it is important to complete the report in a timely manner while the information is still fresh in the researcher’s mind.

Characteristics of Research Report

There are several characteristics of a research report that distinguish it from other types of writing. These characteristics include:

• Objective: A research report should be written in an objective and unbiased manner. It should present the facts and findings of the research study without any personal opinions or biases.
• Systematic: A research report should be written in a systematic manner. It should follow a clear and logical structure, and the information should be presented in a way that is easy to understand and follow.
• Detailed: A research report should be detailed and comprehensive. It should provide a thorough description of the research methods, results, and conclusions.
• Accurate : A research report should be accurate and based on sound research methods. The findings and conclusions should be supported by data and evidence.
• Organized: A research report should be well-organized. It should include headings and subheadings to help the reader navigate the report and understand the main points.
• Clear and concise: A research report should be written in clear and concise language. The information should be presented in a way that is easy to understand, and unnecessary jargon should be avoided.
• Citations and references: A research report should include citations and references to support the findings and conclusions. This helps to give credit to other researchers and to provide readers with the opportunity to further explore the topic.

Advantages of Research Report

Research reports have several advantages, including:

• Communicating research findings: Research reports allow researchers to communicate their findings to a wider audience, including other researchers, stakeholders, and the general public. This helps to disseminate knowledge and advance the understanding of a particular topic.
• Providing evidence for decision-making : Research reports can provide evidence to inform decision-making, such as in the case of policy-making, program planning, or product development. The findings and conclusions can help guide decisions and improve outcomes.
• Supporting further research: Research reports can provide a foundation for further research on a particular topic. Other researchers can build on the findings and conclusions of the report, which can lead to further discoveries and advancements in the field.
• Demonstrating expertise: Research reports can demonstrate the expertise of the researchers and their ability to conduct rigorous and high-quality research. This can be important for securing funding, promotions, and other professional opportunities.
• Meeting regulatory requirements: In some fields, research reports are required to meet regulatory requirements, such as in the case of drug trials or environmental impact studies. Producing a high-quality research report can help ensure compliance with these requirements.

Limitations of Research Report

Despite their advantages, research reports also have some limitations, including:

• Time-consuming: Conducting research and writing a report can be a time-consuming process, particularly for large-scale studies. This can limit the frequency and speed of producing research reports.
• Expensive: Conducting research and producing a report can be expensive, particularly for studies that require specialized equipment, personnel, or data. This can limit the scope and feasibility of some research studies.
• Limited generalizability: Research studies often focus on a specific population or context, which can limit the generalizability of the findings to other populations or contexts.
• Potential bias : Researchers may have biases or conflicts of interest that can influence the findings and conclusions of the research study. Additionally, participants may also have biases or may not be representative of the larger population, which can limit the validity and reliability of the findings.
• Accessibility: Research reports may be written in technical or academic language, which can limit their accessibility to a wider audience. Additionally, some research may be behind paywalls or require specialized access, which can limit the ability of others to read and use the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Key attribute generation from review texts based on in-context learning for recommender systems

• Published: 08 August 2024

Cite this article

• Jungmin Park 1 &
• Younghoon Lee 2  

40 Accesses

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User review texts provide valuable information for recommender systems, as they express various dimensions and perspectives regarding the experience of a user with a specific item. Consequently, many studies have proposed recommender systems based on review texts. However, because review texts typically contain a high proportion of noise that is not related to user preferences or item characteristics, existing studies that input the entire review text into the model are vulnerable to noise issues. Therefore, this study proposes a methodology for extracting key attributes based on in-context learning(ICL) to fundamentally address the noise problem in review texts. We used zero-shot, one-shot, and few-shot large language model (LLM) ICL to generate key attributes that define user preferences and item characteristics from integrated review texts, and we trained a recommender system to predict user ratings on items using the generated key attributes as new input. Our proposed research is the first to create and utilize new user and item characteristics through LLM ICL for a recommender system. Experiments demonstrate that our methodology effectively generates key attributes related to user preferences and item characteristics from review texts and achieves superior predictive performance compared to existing review-based recommender systems.

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Park, J., Lee, Y. Key attribute generation from review texts based on in-context learning for recommender systems. Appl Intell (2024). https://doi.org/10.1007/s10489-024-05698-2

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Research on quantitative analysis methods for the spatial characteristics of traditional villages based on three-dimensional point cloud data: a case study of liukeng village, jiangxi, china.

1. Introduction

2. literature review, 2.1. research on spatial characteristics of traditional villages, 2.2. new developments in the study of spatial characteristics in traditional villages brought by 3d point cloud data, 3. materials and methods, 3.1. study area, 3.2. methods, 3.2.1. step i: field data collection: obtaining 3d point cloud data through low-altitude uav aerial photography and handheld laser scanners, 3.2.2. step ii: data processing: point cloud preprocessing and object classification, 3.2.3. step iii: data analysis and application: extraction of quantitative indicators of village spatial characteristics and interpretation of construction wisdom, 4.1. topographic environment: visualization and interpretation of feng shui concepts and site selection wisdom, 4.1.1. interpretation of the connotation and wisdom in feng shui forest, 4.1.2. micro-topography-based quantification of water management, 4.2. street spaces: spatial scale and hierarchical division, 4.2.1. quantification of street space scale, 4.2.2. hierarchy of street spaces, 4.3. building elements: characteristics and morphology of residential courtyards, 4.3.1. quantitative analysis of residential courtyard scale, 4.3.2. summary of the form of residential courtyards, 5. discussion, 5.1. strategy for utilizing 3d point cloud data, 5.2. innovations, 5.3. limitations, 5.4. future application scenarios, 5.4.1. village spatial basic information data layer, 5.4.2. village historical and cultural knowledge application layer, 5.4.3. village public display and tour service layer, 6. conclusions, author contributions, data availability statement, conflicts of interest.

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Li, Z.; Wang, T.; Sun, S. Research on Quantitative Analysis Methods for the Spatial Characteristics of Traditional Villages Based on Three-Dimensional Point Cloud Data: A Case Study of Liukeng Village, Jiangxi, China. Land 2024 , 13 , 1261. https://doi.org/10.3390/land13081261

Li Z, Wang T, Sun S. Research on Quantitative Analysis Methods for the Spatial Characteristics of Traditional Villages Based on Three-Dimensional Point Cloud Data: A Case Study of Liukeng Village, Jiangxi, China. Land . 2024; 13(8):1261. https://doi.org/10.3390/land13081261

Li, Zhe, Tianlian Wang, and Su Sun. 2024. "Research on Quantitative Analysis Methods for the Spatial Characteristics of Traditional Villages Based on Three-Dimensional Point Cloud Data: A Case Study of Liukeng Village, Jiangxi, China" Land 13, no. 8: 1261. https://doi.org/10.3390/land13081261

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