How can this situation be characterized, described, classified, or analyzed?
After writing the questions, I would write my responses, deciding which particular questions and responses interest me the most. Perhaps, for instance, I would find myself most interested in the effects of development on the "natives" of small towns, particularly the inevitability of increased property taxes. This process of questioning thus provides me with a specific, narrow, well-defined focus within the vast issue of development of small towns in the Rocky Mountain region.
Related Information: Topic Cross
The topic cross helps you to narrow your topic by using a visual strategy. Just as you would focus a camera or a microscope, you arrange key words and phrases about your topic in such a way that they eventually point to your specific area of interest.
Example of a Topic Cross The first step in the process of using the topic cross is brainstorming. Spend a few minutes listing words and phrases that come to mind when you think about your topic. Then decide which words and phrases are most interesting and arrange them in a hierarchy, moving from general (at the top of the list) to specific (at the bottom of the list). This hierarchy will become the vertical axis of your cross. Demonstration: If my topic is "development of small towns in the Rocky Mountain region," I might generate the following useful ideas in brainstorming (arranged from general to specific).
I would write this list in an imagined middle column of a piece of blank paper or a computer screen, leaving plenty of space between each item. Then I would scan the list to determine where my real interest lies. Which topics in this list will be too broad to write about, given my writing assignment? Which will be too narrow? In this case, I might choose "economic effects on impoverished landowners" as a workable topic area. Once I had thus identified my area of interest, I would begin listing words and phrases about or relevant to that item, placing them on the horizontal axis of my topic cross. The list I would generate about "economic effects on impoverished landowners" might look like this:
Examining this list, I might decide that "rising property taxes" is a sufficiently narrow topic that is not too narrow to develop with my own ideas and research I might do. By using this strategy, I have arrived at a narrow, workable topic.
If your writing assignment requires research, you will probably find that the research process itself will dictate how broad or narrow your topic should be. We have all had the experience of doing a library search on a word like "environment" and coming up with thousands of sources. Almost as common is the experience of searching a term like "cultural animation" and coming up with only one source that seems useful. The topics we choose are often directly related to our research processes and their results.
It is important to remember that a narrow topic is not the same thing as a thesis statement. Unlike a topic, a thesis makes a claim of fact, provides a claim of value, or makes a recommendation about a topic under consideration. For example, your narrowed topic might be "the underemphasis on foreign language in U.S. secondary schools." A focused thesis statement making a claim about this topic might read, "U.S. secondary schools should require elementary students to take at least one course in a foreign language sometime during the 4th through 6th grades."
Transforming a workable topic into a possible thesis is really just a continuation of the narrowing process, with an emphasis on what you want to say about your topic. In this way, it is much like the "hypothesis" stage of the scientific method. You arrive at a thesis by attempting to make a statement about the topic you have chosen.
A working thesis is a tentative statement that you make about your topic early in the writing process, for the purpose of directing your thinking early. This thesis is likely to change somewhat or to be abandoned altogether as you move through the writing process, so it is best not to become too enamored of it.
There are two components of a working thesis. The first is, quite simply, your topic; and the second is your tentative statement about your topic. For example, if my narrowed topic is
"Rising property taxes in small towns in the Rocky Mountain region..."
I might add the following statement about that topic:
"...cause longtime residents and landowners in those towns not to be able to keep their property."
As I begin whatever research is necessary to support this thesis, I might find that I can't make this much of a claim. Or I might find that there are complexities that I hadn't considered. As I uncover new information about my topic, I will want to alter my working thesis accordingly, until it is workable and supportable.
A In The St. Martin's Handbook , Third Edition [italics], Andrea Lunsford and Robert Connors suggest a process for moving from a topic to a research "hypothesis," by way of examining the "issue" at hand and framing this issue as a "research question." The following is an example of how I might move from topic to hypothesis if my narrowed topic is "rising property taxes in small towns in the Rocky Mountain region."
This hypothesis, like a working thesis, is simply an early speculation on what I might find when I begin to research. As I read more and more about my topic, I will probably find that I need to make changes to the hypothesis in order to make it a supportable thesis. As I uncover new information about my topic, I will want to alter my working thesis accordingly, until it is workable and supportable.
One of the greatest challenges in written argument is determining what it is that you would like to (and are able to) say about your topic.
Before you begin drafting an argument paper, you need to decide (tentatively, at least) what it is that you will be arguing about the topic you have chosen. The following prompts should help you focus your argument from a topic to a position on that topic. What is your topic? (e.g.--Rising property taxes in small towns in the Rocky Mountain region) What are three controversies associated with this topic? (e.g.--Rising property taxes make the town affordable only to the wealthy. This changes the flavor the flavor of the town. It forces long-time land owners to sell their land.) What are three questions people might ask about these controversies? (e.g.--Are these rising property taxes, which are the results of development in small towns in the Rocky Mountain region, forcing long-time land owners out of their home towns? Are rising taxes and land values changing the whole cultural and economic foundation of the towns? Given the effects of rising property taxes on impoverished land owners in small towns, is development in this area a good idea?) Decide which of these questions you are most interesting in exploring. (e.g.--Given the effects of rising property taxes on impoverished land owners in small towns, is development in this area a good idea?) Now list several ways people might respond if you asked them your question. (e.g.--No, because impoverished land owners are unable to maintain the new standard of living. Yes, because development is always a good idea. Yes, because development is inevitable, and we can do nothing about it. Perhaps, but city planners and local government must find ways to protect the interests of impoverished land owners when they determine property taxes.) Finally, decide where you stand in this range of responses. Think of a thesis that expresses your view. Write out your thesis and revise it throughout your research process until it is specific and takes a single arguable position. (e.g.--Because impoverished land owners in small towns in the Rocky Mountain region are often badly hurt by the rising property taxes resulting from development, city planners and local government must find ways to protect the interests of these land owners when they determine property taxes.)
Don Zimmerman, Journalism and Technical Communication Professor Writers' understanding of topics and their fields of study allow them to focus on a specific topic. Following a good problem solving process or scientific method can help you select a topic. Whereas on the job, topics emerge from day to day activities. When working, you don't need to look for topics to write about. Your respective field/job responsibilities allow you to find the problems.
The ways that topics are approached and the types of topics that are discussed vary from discipline to discipline. It is important to investigate the types of topics that are discussed (and the ways that they are discussed) in your own discipline. As a writer, it is necessary to determine what topics are talked about and why in your own discipline (or in the discipline for which you are writing). This can be done by way of talking to professionals in the discipline, looking at relevant journals, and conducting Internet and database searches (to name a few possibilities).
Related Information: Browsing Journals Important to Your Discipline
Almost every discipline has journals that are associated with it, and scholars in the discipline depend on these journals in order to remain informed about what topics are being discussed. For example, scholars in the field of psychology rely on psychological journals; doctors rely on medical journals; and English professors rely on literary journals. Because journals are at the center of each discipline's current discussions, it is a good idea to browse them when looking for current topics. If you are unsure of how to go about doing this, talk to a professor in your discipline, a reference librarian in your library, or a librarian in your library's Current Periodicals room. These people can usually provide you with a few titles of important journals relevant to your field. Once you have these titles, you can locate a few issues of each journal in the Current Periodicals room, sit down for an hour or two, and look through the articles to see what is being talked about and what interests you.
Related Information: Online Searches and Databases
One way of getting to the sources which will discuss topics current to your discipline is by searching the various computer databases and search engines related to that discipline. A database is simply an arrangement of information by way of similar subject matter. For example, if you were researching a topic for a Sociology essay on group behavior of Deadheads, you might go to the Social Sciences Index to find sources related to your topic. For information on how to find relevant and useful databases, talk to the reference librarian in your library, or ask an expert in your field which databases he or she uses regularly.
Related Information: Talking to Professionals in Your Discipline
One of the most efficient ways to learn what topics are currently being discussed in your discipline is to talk to the experts: instructors and other professionals working within that discipline. We often forget that these people can be valuable resources to us, and can point us toward books, journals, databases, and other sources of information that scholars in our various fields use often.
Lauel Nesbitt and Dawn Kowalski. (1994-2024). Choosing and Refining Topics . The WAC Clearinghouse. Colorado State University. Available at https://wac.colostate.edu/repository/writing/guides/.
Copyright © 1994-2024 Colorado State University and/or this site's authors, developers, and contributors . Some material displayed on this site is used with permission.
Use your background information to think of appropriate search terms. Brainstorm every possible search term for your topic.Try to think of synonyms and related words for each keyword to help broaden or narrow your search.
Look at your topic. For example: ‘Are Canadian youth politically engaged?’ The keywords in this topic would be Canadian , youth , and political engagement .
These keywords can become:
My research question was ‘Can alternative energy sources help stop global warming?’
For this question, the keywords would be alternative energy sources, and global warming. So, some search terms could be:
My assignment:.
Write a research report on a topic of your choice
My broad topic for the assignment is ‘Global Warming’.
Narrowing your subject to a more specific topic takes a bit of research and thought.
Here are some ideas to help you narrow your topic:
Use these questions:
(Content reproduced from MIT.edu under a Creative Commons Attribution Non-Commercial License )
The subject we chose in the earlier step is ‘global warming.’ This subject is a very broad topic with many different aspects you could research. We will use the techniques above to narrow our subject to a research topic.
Sample research question: Can alternative energy sources help stop global warming?
by Evan Kramer
As master’s and PhD students, we all aspire to conduct quality research. The question many of us are faced with is: how do we formulate a research topic that is well poised for performing quality research? Research topics are meant to encompass the majority or entirety of our work during our graduate career and, when well-defined, can result in opportunities to publish several high-impact academic papers. The effort required to formulate a well-defined research topic is significant, but necessary to avoid running into unforeseen challenges during your PhD. This blog post discusses the concepts that should be considered for anyone looking to define their research topic. While students have varying degrees of autonomy in shaping their research due to funding constraints and advisor expectations, the concepts discussed in this blog post account for these facets and can serve as a framework for any situation.
Overview diagram of a framework for formulating a well-defined research topic.
Quality research is independent , important , and unique .
This definition identifies a set of requirements that a research topic must meet. These requirements will be discussed in more detail to orient the research topic formulation process.
Independent – Independent research can be conducted entirely by you without assistance from outside sources. While you should actively seek collaborations with others to boost the reach of your work, will you be able to complete your research objectives without relying on resources provided by others? Framing your research topic and objectives in this manner gives you protection to flakey collaborators and will keep you on track to graduate on time. For example, something you may want to avoid is crafting a research topic around the usage of one particular data set maintained by a private company. While initial collaboration talks may go smoothly, you don’t want your ability to pursue your research project in the hands of someone else!
Important – Important research makes a contribution towards answering a specific question, or a gap in knowledge, among a research community that has been posed by several scholars. You may ask yourself: if you carry out your research to completion, will your contributions answer outstanding questions posed by multiple scholars in your research community? Note that the question your work addresses may not be explicitly posed in the literature, but identifying common limitations can help formulate a gap in knowledge that you can work towards filling. Aligning your research objectives with specific and commonly posed questions can increase the chance of your work being cited by other scholars and integrated into practices in industry.
Unique – Unique research makes a first-of-its-kind contribution. There are several ways in which your research can be unique. For example, uniqueness may be assumed if you contribute the first work to a completely unanswered question in your field. Alternatively, you may make a unique contribution to a question that has already been addressed by approaching it in a new way. Knowledge of your chosen field’s state of the art and previous foundations is useful when checking the uniqueness of your work, which can only be verified by thorough literature review. Regardless of the way your research is unique, it is important to identify the uniqueness of your work within the context of existing work in related areas.
With these three research topic characteristics in mind, the following presents a high level path to formulating your well-defined research topic.
1. look inwards.
Based on previous experiences in coursework, internships, and extracurricular activities, create a two-column list. The first column lists research fields you found interesting. The second column lists ideas that align with your personal motivations for pursuing a career in STEM research. An example of this list may look like the following:
Space propulsion | Reducing aerospace industry contributions to climate change |
Aerospace controls | Increasing equitable access to space capabilities for low-resource nations |
Remote sensing | Improving accessibility of space data for non-experts |
High-speed aerodynamics | Bolstering safety of space travel |
LEO constellation astrodynamics | Enabling efficient natural disaster response for remote communities |
Given the two-column lists you created, start familiarizing yourself with the current state of the art. Starting with articles in popular science media outlets can be effective for initial cursory surveys. Any articles that pique your interest should be followed by deeper dives into related literature in Google Scholar. It is likely that several of the topics in the left column of your list get crossed off quickly when you realize they no longer interest you. Continue this process until a subset of around three areas remains. Your two-column list may then look like this:
Reducing aerospace industry contributions to climate change | |
Aerospace controls | Increasing equitable access to space capabilities for low-resource nations |
Remote sensing | Improving accessibility of space data for non-experts |
Bolstering safety of space travel | |
LEO constellation astrodynamics | Enabling efficient natural disaster response for remote communities |
Note that the right hand column remains unchanged. You very likely will not be able to address all of your personal motivations for pursuing STEM research in your eventual research topic, but now is when you can start connecting topics you find interesting to research applications that personally motivate you.
While the research topic definition process should be approached predominantly with your own interests in mind, at this stage, it is important to consider where your funding is coming from. Typically, there will be specific fields your research must overlap with based on your funding source. Schedule a discussion with your advisor to share your topic definition process so far and ask if there are topics you should add to your list based on research group and funding requirements. Based on this discussion, add a third column to the list you’ve created that describes the necessary areas of overlap for your research.
Reducing aerospace industry contributions to climate change | AI applied to satellite operations | |
Aerospace controls | Increasing equitable access to space capabilities for low-resource nations | Testbed development for satellite dynamics and control algorithm testing |
Remote sensing | Improving accessibility of space data for non-experts | Effects of the space environment on satellite operations |
Bolstering safety of space travel | ||
LEO constellation astrodynamics | Enabling efficient natural disaster response for remote communities |
At this point you are trying to iterate on combinations identified in your three-column list. You can begin to formulate an overarching research statement from these combinations. Research statements generally have the form “To…by…while…”. This sentence structure explicitly identifies what you are trying to accomplish, how you will accomplish it, and which constraints you will account for. A possible research statement could be defined with one entry from each column, or you may be able to create a topic with multiple entries from each column. In this blog’s example list, a research statement could be the following:
To enable efficient natural disaster response for remote communities by developing an AI-powered rapid response scheduling algorithm for a remote sensing satellite while accounting for limitations to satellite operations imposed by the space environment .
You may create a few iterations of overarching research statements like this. As you continue to read focused areas in the literature, formulate a focus area Venn Diagram. By allocating articles in your literature search to portions of the diagram, you can stay organized and keep track of the work you’re doing. For the example statement above, your Venn Diagram could look like this:
Venn diagram of research topic focus areas. The most relevant literature review items can be added to each region of the diagram to track and organize your efforts.
At this point, you are well on your way to formalizing your research topic. The formalization step involves writing research questions, drafting objective statements, and identifying your research contributions. AeroAstro Communications Lab fellows can help you with these next steps through one-on-one appointments !
Research topics verses research questions.
A “research topic” is the area of study that you are researching, while a “research question” is the more focused question that you aim to answer.
Depending on your starting point, you may arrive at a research question by taking different routes. Your research question might come from a topic you are interested in, or that you see being discussed in literature. If you are working in an applied sciences field or as a clinician, your research question might be informed by a problem, or a scenario encountered in the lab or in practice.
A good research question is:
A concept is an idea, theme, or aspect of a research topic being explored and analysed.
Identify the main concepts in your research topic or question to make it searchable.
Most research questions will have 2–4 concepts.
Searching for a single concept will return too many results on a topic, and these results will be too broad to answer your research question.
Too many concepts in your search will have the opposite effect and may not find any results at all.
A quick way to identify concepts in a research question is to find words or phrases that represent your main topic(s):
Here is an example of a research question and the main concepts:
The main concepts in this research question are:
Once you’ve identified your main concepts, the next step is to find synonyms or alternative terms for each concept.
Synonyms are alternative words or phrases that can be used to describe a concept.
Using synonyms is important in a search, as not everyone uses the same term for the same concept. It can help overcome limitations, such as:
For example, if searching for “film”, you could also include terms such as “movie”, “motion picture” and “cinema” to find more relevant results.
To find additional terms, search your original word or phrase using:
For more help understanding your research question and how to translate it into a search strategy, contact our library staff.
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Part of the book series: Research in Mathematics Education ((RME))
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Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.
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Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.
Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”
Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .
Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.
This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.
In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.
A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.
As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.
We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.
Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.
This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.
When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.
According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.
We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.
We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.
What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?
Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?
This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.
Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.
An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.
One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.
A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.
A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).
A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.
We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?
We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.
Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).
Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.
Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.
Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.
A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.
Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.
To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.
We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).
We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.
“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.
By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.
We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.
Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.
Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.
A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.
You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.
One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.
Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?
Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.
We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.
Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.
Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.
Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.
Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.
Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.
If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.
One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.
Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.
What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.
We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.
Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.
One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).
As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .
Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.
Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.
The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.
A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.
In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).
As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.
Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.
We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.
Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.
First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.
Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.
Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.
How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).
Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.
Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.
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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1
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Inhaltsverzeichnis
A research topic is the subject or issue that forms the basis of a research paper. It is a well-defined subject the researcher is interested in. While it can be phrased as a question, you are not required to do so. The research then addresses the question. It can also be phrased both as a research question and a hypothesis.
The purpose of this article is to help you understand what research topics are and how they are used to conduct good research. It covers the characteristics of good research topics and provides information on and techniques for coming up with good research topics. The importance of research topics in academic writing is explained and some examples of research topics are listed.
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Rational thinking and creative techniques are two key methods you can use to generate research ideas. You can use either of the techniques, or you can try both techniques and then decide which one you find more useful for your research. Both concepts are further discussed later in this article.
Tip: Keep in mind that you’ll need to create research questions based on your topic later on. It’s ok to begin with vague ideas, but later on you need to focus on a specific area of a topic.
The Delphi technique is an approach that many students have found useful for refining their research ideas. Usually, a number of people who are interested in the research are assembled to help generate and select more refined research topics. The next step will be to refine your ideas into a research question . This will require you to conduct more research on topics or issues that you found interesting during the research topic deciding phase.
A research proposal consists of an appropriate title that mirrors the content of the proposal; a background to justify the need for the research; a statement on what the research is meant to achieve. A section should be dedicated to the methods that will be adopted in order to achieve the research objectives within the expected timeframe. A section on resource considerations will help convince the reader about the feasibility of the research. This should be followed by a list of references.
Writing helps organize our ideas into coherent statements. For inspiration, check out some research proposal examples . The draft proposal should be discussed with your thesis supervisor or teaching assistant, who can advise you on how the proposal might be amended if necessary, so that the research can be completed within the proposed timeframe. This is of particular importance if the proposal has to be presented for funding or to an academic research committee for approval.
You’re the one who has to write the research paper or thesis, so it’s vital that YOU are interested in the topic that you’re researching. Your research topic shouldn’t be too vague. But in saying that, you also need to ensure that you’re able to write about your topic within the time frame provided. You need to be able to formulate your topic into a research question and a thesis statement later on.
If done using a systematic approach, finding research topics can be interesting. A range of techniques involving rational as well as creative thinking are used to find a research topic.
This is a problem-solving technique which generates best results when carried out as a group, but it can also be done by an individual. Find a quiet place to work and write down a problem related to your lectures or curriculum that interests you and of which you have some prior knowledge.
If you are working in a group, members can make suggestions regarding the problem. Make a note of all the suggestions and include all contributions, however wild they may be. Review each of the suggestions with your group and select the ones that most appeal to you. You may arrange discussing these suggestions with your thesis supervisor or the teaching assistant in charge of your project if needed.
Project leaders, teaching assistants, professional groups and practitioners in your field will often have project ideas they are happy to share. They might come up with good research topics; just be sure to document the ideas discussed so that you can remember to further explore them on your own.
Articles, reports in academic journals and books are all useful sources of research topics. Review articles in particular often indicate areas in which more research may be required. Most recently published reports usually contain recommendations which can form the basis of further research, and books contain an overview of research already undertaken, in addition to suggesting new areas to explore for further research.
This technique involves generating topics on the basis of a broad concept. Each of these topics constitutes an independent branch which can yield sub-branches. You can review these sub-branches and combine some of them to come up with new research topics. Your project supervisor or teaching assistant may be of help in selecting a final topic from the shortlisted ones if you cannot narrow your choice down to one topic.
Another way of finding a research topic is to review the assignments you have already completed and select the ones you received good grades in. These are the ones in which you are already knowledgeable. They will provide you with possibilities for further research.
A good research topic should have well defined objectives. Selecting a research topic which you will be interested in for the entire research duration is vital. If you have only a vague interest in the topic, it will be difficult to excel on such a topic. Therefore, you should have a genuine interest in the research topic you have chosen.
Make sure you possess the required skills and resources, or that you can develop the capability that is necessary to research the topic within the given timeframe. You should also be certain that you can access the data you will need to collect in the course of the research. Your research topic should be one you are familiar with and in which you have the capacity to produce a well-written final research report.
TIP: Always use transition words to properly connect the sentences and paragraphs in your thesis or essay.
Academic writing is a style of expression that defines the intellectual boundaries of a discipline. It focuses on a research problem and conveys an accepted interpretation of concepts or complex ideas. Research topics are germane to academic writing because they proffer rigorous arguments that can convince a reader to reconsider previously accepted position on a topic.
Previous research topics can serve as sources of inspiration for finding new research topics. Some examples of different research topics include: • Media and communications research paper topics • Environmental research paper topics • Business research paper topics
Depending on your field of study, looking at past projects can be very helpful in your search for new research topics.
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Thesis dialogue blueprint, writing wizard's template, research proposal compass.
Starting a research paper can seem overwhelming, but breaking it down into manageable steps can make the process much easier. This guide will walk you through each stage, from choosing a topic to finalizing your paper, ensuring you stay organized and focused. Whether you're new to research or looking to improve your skills, these steps will help you create a strong, well-structured paper.
Choosing a research topic is a crucial first step in writing a research paper. It sets the stage for your entire project, so it's important to choose wisely. Here are some steps to help you select a topic that is both interesting and feasible.
Start by thinking about what excites you. Pick a topic that you find fun and fulfilling. This will keep you motivated throughout your research. Make a list of subjects you enjoy and see how they can relate to your field of study. Your job will be more pleasant if you choose a topic that holds your interest.
Once you have a few ideas, check if they are too broad or too narrow. A good topic should be manageable within the time you have. Ask yourself if you can cover all aspects of the topic in your thesis. For example, exploring the link between technology and mental health could be narrowed down to how WhatsApp use impacts college students' well-being.
Before finalizing your topic, ensure that there are enough resources available. Conduct preliminary research to see if there is sufficient data and literature on your chosen topic. This step is vital as you may discover issues with your original idea or realize you have insufficient resources to explore the topic effectively. This key bit of groundwork allows you to redirect your research topic in a different, more feasible, or more relevant direction if necessary.
Understanding the importance of a research question.
A well-defined research question is the cornerstone of any successful research paper. It provides a clear focus and direction for your study, ensuring that your efforts are both relevant and meaningful. A strong research question helps you stay on track and avoid unnecessary detours. It also makes it easier to communicate the purpose and significance of your research to others.
To develop a compelling research question, start by identifying your interests and the gaps in the existing literature. Use the 5 W's: who, what, where, when, and why , to explore different aspects of your topic. This approach will help you narrow down your focus and create a question that is both specific and researchable. Additionally, consider the feasibility of your question by evaluating the availability of resources and the scope of your study.
Your research question should align with the objectives of your study. This means that it should be directly related to what you aim to achieve through your research. Clearly defined objectives will guide your research process and ensure that your question remains relevant throughout your study. By aligning your question with your objectives, you can produce a coherent and focused research paper that effectively addresses the problem at hand.
Start by collecting sources that are related to your research topic. Use libraries, online databases, and academic journals to find books, articles, and papers. Skimming sources initially can save you time; set aside those that seem useful for a more thorough read later.
Once you have gathered your sources, read through them carefully. Take notes on key points and different viewpoints. This will help you understand the current state of research in your field. Look for common themes and debates that can inform your own work.
As you analyze the existing research, look for areas that haven't been explored or questions that haven't been answered. These gaps can provide a direction for your own research and make your thesis more valuable. Identifying these gaps is crucial for crafting a strong research question and ensuring your work contributes new knowledge to the field.
Creating a solid research plan is crucial for the success of your thesis. It helps you stay organized and ensures that you cover all necessary aspects of your research.
Establishing context.
Starting your thesis introduction can be daunting, but it's crucial for setting the stage for your research. Establishing the context for your study helps readers understand the background and significance of your work. This section should provide a clear overview of what your thesis will cover, making it easier for readers to follow your arguments.
Your thesis statement is the heart of your introduction. Typically, it is placed at the end of the introductory paragraph. This statement should succinctly present the main argument or focus of your thesis, guiding the reader on what to expect.
Once you have your research question, you need to justify why it is important. Explain the significance of your research problem in the context of existing literature. Highlight the gaps your research aims to fill and how it will contribute to the field. This step is crucial for crafting a bachelor thesis that stands out.
Organizing sections.
A well-structured research paper is essential for clarity and coherence. Start by dividing your paper into key sections: Introduction, Literature Review, Methodology, Results, Discussion, and Conclusion. Each section should serve a specific purpose and contribute to the overall argument of your paper. Organize your research by identifying main topics and subtopics, gathering relevant sources, and summarizing key points. This will help you maintain a logical flow throughout your paper.
Ensuring a logical flow between sections and paragraphs is crucial. Use transitions to connect ideas and guide the reader through your arguments. Each paragraph should begin with a clear topic sentence that introduces the main idea, followed by supporting evidence and analysis. This approach not only enhances readability but also strengthens your argument.
Coherence is achieved when all parts of your paper work together to support your thesis statement. To maintain coherence, make sure each section and paragraph aligns with your research objectives. Regularly review your work to ensure that your ideas are presented logically and that your voice remains dominant. Cite sources carefully to avoid plagiarism and to give credit to the original authors.
Choosing data collection methods.
Selecting the right data collection methods is crucial for the success of your research. Data collection is the process of gathering, measuring, and analyzing accurate data. Consider methods such as surveys, interviews, or experiments based on your research needs. Each method has its strengths and weaknesses, so choose the one that best fits your study.
Once you have collected your data, the next step is to analyze it accurately. Use statistical tools and software to help you interpret the data. Create tables and graphs to illustrate your findings clearly. This will help you present your results in a structured and understandable way.
Interpreting your results is an essential part of your thesis. Discuss how your findings relate to your research questions and the existing literature. Highlight the significance of your analyses and the reliability of your findings. This will help you draw meaningful conclusions and provide valuable insights into your research topic.
Start by writing your first draft without worrying too much about perfection. Focus on getting your ideas down on paper. This initial draft is your chance to explore your thoughts and structure your argument. Remember, the goal is to create a foundation that you can build upon.
Once you have a draft, it's time to incorporate feedback. Share your work with your thesis supervisor and peers. Their insights can help you see your work from different perspectives and identify areas for improvement. Revising is a continuous process of re-seeing your writing. It involves considering larger issues like focus, organization, and audience.
Finally, polish your final draft. Pay attention to grammar, punctuation, and formatting. Ensure that your thesis is clear, concise, and free of errors. This step is crucial for making a strong impression and effectively communicating your research findings.
Adhering to style guides.
When formatting your research paper, it's crucial to follow the specific style guide recommended by your institution. Common styles include APA, MLA, and Chicago. Each style has its own set of rules for formatting headings, tables, and references. Adhering to these guidelines ensures your paper meets academic standards and is easy to read.
Citing your sources correctly is essential to avoid plagiarism and give credit to the original authors. Typically, a citation can include the author's name, date, location of the publishing company, journal title, or DOI (Digital Object Identifier) . Use the citation style specified by your university, such as APA or MLA . For example, in APA format, an in-text citation might look like this: (Smith, 2020).
Plagiarism is a serious academic offense. To avoid it, always cite the sources you use in your research. This not only gives credit to the original authors but also adds credibility to your work. Use tools like Grammarly’s Citation Generator to ensure your citations are flawless and your paper is free from plagiarism.
Understanding academic integrity.
Academic integrity is the foundation of any scholarly work. It involves being honest and responsible in your research and writing. Maintaining academic integrity ensures that your work is credible and respected. It also means giving proper credit to the original authors of the sources you use. This practice not only helps you avoid plagiarism but also strengthens your arguments by backing them up with credible sources.
To avoid plagiarism, always cite your sources correctly. Use a consistent citation style, such as APA or MLA, and make sure to include all necessary information. Here are some tips to help you:
Ensuring the originality of your work is crucial. This means that your ideas and findings should be your own, even if they are based on existing research. Here are some ways to ensure originality:
By following these steps, you can maintain academic integrity and produce a research paper that is both credible and original.
Proofreading and editing.
Before submitting your research paper, it's crucial to proofread and edit your work thoroughly. Start by reviewing the content for clarity and coherence. Ensure that each section flows logically and that your arguments are well-supported. Pay close attention to grammar, spelling, and punctuation errors, as these can detract from the professionalism of your paper. Consider reading your paper aloud or using a text-to-speech tool to catch mistakes you might have missed.
Once you have polished your paper, it's time to prepare it for submission. Make sure you adhere to the specific formatting guidelines provided by your institution or the journal you are submitting to. This includes checking the font style and size, margins, and page numbering. Ensure that all citations and references are correctly formatted according to the required style guide, such as APA or MLA. Double-check that your paper meets all the submission requirements, including word count and any additional documents that need to be included.
Before finalizing your research paper, seek feedback from peers or mentors. A fresh set of eyes can provide valuable insights and help identify areas for improvement that you might have overlooked. Share your paper with colleagues or use online platforms to get constructive criticism. Incorporating feedback from others can enhance the quality of your work and ensure that your arguments are clear and compelling.
Wrapping up your research paper can be a daunting task, but it doesn't have to be. Our step-by-step Thesis Action Plan is here to guide you through every stage, making the process smoother and less stressful. Ready to conquer your thesis challenges? Visit our website now and discover how we can help you achieve your academic goals.
Starting a research paper can seem overwhelming, but breaking it down into manageable steps makes the process much easier. By choosing a topic that interests you, conducting thorough research, and organizing your findings, you lay a strong foundation for your paper. Remember to create a clear thesis statement to guide your writing and keep your arguments focused. Drafting, revising, and seeking feedback are crucial steps to refine your work. Finally, ensure your paper is well-formatted and free of errors. With dedication and careful planning, you can successfully navigate the research paper writing process. Good luck!
How do i choose a research topic.
Start by thinking about what interests you. Pick a topic that you find fun and fulfilling. This will keep you motivated throughout your research. Also, make sure there are enough resources available on the topic.
A research question guides your study, helping you focus on a specific issue. It makes your research more organized and meaningful.
A literature review helps you understand what has already been studied about your topic. It shows gaps in the research that your study can fill.
Outline your methodology, create a timeline, and allocate resources. This helps you stay organized and ensures you cover all necessary aspects of your research.
Your thesis introduction should establish the context, present your thesis statement, and justify the research problem. This sets the stage for your study.
Organize your sections logically, ensure a smooth flow of ideas, and maintain coherence throughout the paper. Each part should connect well with the others.
Choose methods that best suit your research needs, such as surveys, interviews, or experiments. Use statistical tools to analyze data accurately and interpret your results.
Always cite your sources correctly and follow the citation style recommended by your institution. Use plagiarism checkers to ensure your work is original.
How to determine the perfect research proposal length.
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Tips for identifying scope.
Once you decide on a research topic, you need to determine the scope of your topic. The scope of a research topic is determined by how detailed you want your project to be. This process will tell you if your topic is already too narrow or too broad. Consider the following when determining the scope of your research topic (Leggett and Jackowski, 2012):
The following tips may help you identify the scope of your research topic (Center for Writing and Speaking, n.d.):
The following web page from Agnes Scott College, titled "Narrowing Scope" may assist you in determining the scope of your research topic.
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Methodology
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:
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.
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.
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 approach | Quantitative approach |
---|---|
and describe frequencies, averages, and correlations about relationships between variables |
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.
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 .
At each stage of the research design process, make sure that your choices are practically feasible.
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.
Quantitative designs can be split into four main types.
Type of design | Purpose and characteristics |
---|---|
Experimental | relationships effect on a |
Quasi-experimental | ) |
Correlational | |
Descriptive |
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.
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.
Type of design | Purpose and characteristics |
---|---|
Grounded theory | |
Phenomenology |
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.
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.
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 | Non-probability sampling |
---|---|
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.
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.
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 .
Questionnaires | Interviews |
---|---|
) |
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.
Quantitative observation | |
---|---|
There are many other ways you might collect data depending on your field and topic.
Field | Examples of data collection methods |
---|---|
Media & communication | Collecting a sample of texts (e.g., speeches, articles, or social media posts) for data on cultural norms and narratives |
Psychology | Using technologies like neuroimaging, eye-tracking, or computer-based tasks to collect data on things like attention, emotional response, or reaction time |
Education | Using tests or assignments to collect data on knowledge and skills |
Physical sciences | Using scientific instruments to collect data on things like weight, blood pressure, or chemical composition |
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.
If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.
With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.
Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.
However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.
As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.
Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.
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 means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.
Reliability | Validity |
---|---|
) ) |
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.
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:
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?
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.
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 specific calculations you can do depend on the level of measurement of your variables.
Using inferential statistics , you can:
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.
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 .
Approach | Characteristics |
---|---|
Thematic analysis | |
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.
Statistics
Research 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:
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:
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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Research Topic. Definition: Research topic is a specific subject or area of interest that a researcher wants to investigate or explore in-depth through research. It is the overarching theme or question that guides a research project and helps to focus the research activities towards a clear objective.
Selecting a topic to research is not a one-step task. Identifying and developing your topic is an ongoing process that does not end until you have finished your research project. Start with an idea you are interested in. Find and read some background information to get a better understanding of the topic, then use what you have learned to ...
Conceptualizing a research topic entails formulating a "defensible and researchable" research question. Conducting a literature search as one of the first steps in a graduate degree is often quite helpful as published peer-reviewed research articles are key to identify knowledge gaps in current literature. Thus, students can design and ...
A research topic is a subject or issue that a researcher is interested in when conducting research. A well-defined research topic is the starting point of every successful research project. Choosing a topic is an ongoing process by which researchers explore, define, and refine their ideas.
Microsoft Word - topic.doc. DEVELOPING A RESEARCH TOPIC. Every good research project has a well-defined topic. Selecting and developing a topic is an ongoing process by which you define and refine your ideas. You can then focus your research strategies to find relevant and appropriate information. Before you begin the research process, be sure ...
A good research topic will have a body of related research which is accessible and manageable. Identifying a topic with these characteristics at the beginning of the research process will ultimately save you time. Finding a research topic that is interesting, relevant, feasible, and worthy of your time may take substantial effort so you should ...
Philosophy of Research. Defining a Topic. Reviewing the Literature. Developing a Researchable Question. Research Design. Planning and Practicalities. Research Ethics. Data Collection. Data Analysis and Interpretation.
Whatever your field or discipline, the best advice to give on identifying a research topic is to choose something that you find really interesting. You will be spending an enormous amount of time with your topic, you need to be invested. Over the course of your research design, proposal and actually conducting your study, you may feel like you ...
A research topic is a subject that you are interested in investigating. For instance, Bees is a Topic. A research question drives your investigation. It is something that you want to know about your topic; something you will explore and try to answer. For example, "How do bees work together as a community?"
Select a topic. Choosing an interesting research topic is your first challenge. Here are some tips: Choose a topic that you are interested in! The research process is more relevant if you care about your topic. Narrow your topic to something manageable. If your topic is too broad, you will find too much information and not be able to focus.
Define a Topic. Effective research takes time. This page will help students: Understand assignment requirements. Select a topic for their research paper. Formulate a research question. Narrow or broaden a research question. Determine keywords and brainstorm search terms. If you are unsure about what is expected about your assignment, consult ...
A Definition of a Topic. A topic is the main organizing principle of a discussion, either verbal or written. Topics offer us an occasion for speaking or writing and a focus which governs what we say. They are the subject matter of our conversations, and the avenues by which we arrive at other subjects of conversations.
Research is defined as a meticulous and systematic inquiry process designed to explore and unravel specific subjects or issues with precision. This methodical approach encompasses the thorough collection, rigorous analysis, and insightful interpretation of information, aiming to delve deep into the nuances of a chosen field of study.
STEP 1: Define Your Topic. The first step when planning and writing a research paper is picking a good topic. A good topic is relevant to the assignment and has enough information available for you to use and is neither too broad nor too narrow. This section will help you pick a subject that interests you, and refine that subject to a specific ...
With these three research topic characteristics in mind, the following presents a high level path to formulating your well-defined research topic. A framework for formulating a well-defined research topic . 1. Look inwards. Based on previous experiences in coursework, internships, and extracurricular activities, create a two-column list.
A good research question is: a single question; researchable by collecting and analysing data; open to the possibility of different outcomes; clear and specific; narrow and focused. About searchable concepts. A concept is an idea, theme, or aspect of a research topic being explored and analysed. Identify the main concepts in your research topic ...
Step 1: Choose your topic. First you have to come up with some ideas. Your thesis or dissertation topic can start out very broad. Think about the general area or field you're interested in—maybe you already have specific research interests based on classes you've taken, or maybe you had to consider your topic when applying to graduate school and writing a statement of purpose.
According to the dictionary definition, you were doing research. Recall your high school assignments asking you to "research" a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some "original" sources. Often, the teacher referred to your product as a "research paper."
Answer: A research topic is a specific part of study in a broader area of study. For instance, for your research topic, the broader research area is malaria prevention in households. A research question aims to further narrow down the scope of the study. It is a possibility you explore through your study aiming to solve the problem of your ...
Definition: Research Topics. A research topic is the subject or issue that forms the basis of a research paper. It is a well-defined subject the researcher is interested in. While it can be phrased as a question, you are not required to do so. The research then addresses the question. It can also be phrased both as a research question and a ...
Choosing a Research Topic. Choosing a research topic is a crucial first step in writing a research paper. It sets the stage for your entire project, so it's important to choose wisely. Here are some steps to help you select a topic that is both interesting and feasible. Identifying Your Interests. Start by thinking about what excites you.
A research problem is a specific issue or gap in existing knowledge that you aim to address in your research. You may choose to look for practical problems aimed at contributing to change, or theoretical problems aimed at expanding knowledge. Some research will do both of these things, but usually the research problem focuses on one or the other.
Defining Scope. Once you decide on a research topic, you need to determine the scope of your topic. The scope of a research topic is determined by how detailed you want your project to be. This process will tell you if your topic is already too narrow or too broad. Consider the following when determining the scope of your research topic ...
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.
Concurrent validity example. Concurrent validity is often assessed in survey research. Concurrent validity example Let's say you've created a nutrition app with a simple quiz to rapidly assess users' healthy eating habits. To validate this quiz, you could administer it to a sample of people alongside a well-established but lengthy dietary questionnaire used by nutritionists.