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From ideas to studies: how to get ideas and sharpen them into research questions

Jan p vandenbroucke.

1 Leiden University Medical Center, Leiden, the Netherlands

2 Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark

3 Department of Medical Statistics and Centre for Global NCDs, London School of Hygiene and Tropical Medicine, London, UK

Neil Pearce

Where do new research questions come from? This is at best only partially taught in courses or textbooks about clinical or epidemiological research. Methods are taught under the assumption that a researcher already knows the research question and knows which methods will fit that question. Similarly, the real complexity of the thought processes that lead to a scientific undertaking is almost never described in published papers. In this paper, we first discuss how to get an idea that is worth researching. We describe sources of new ideas and how to foster a creative attitude by “cultivating your thoughts”. Only a few of these ideas will make it into a study. Next, we describe how to sharpen and focus a research question so that a study becomes feasible and a valid test of the underlying idea. To do this, the idea needs to be “pruned”. Pruning a research question means cutting away anything that is unnecessary, so that only the essence remains. This includes determining both the latent and the stated objectives, specific pruning questions, and the use of specific schemes to structure reasoning. After this, the following steps include preparation of a brief protocol, conduct of a pilot study, and writing a draft of the paper including draft tables. Then you are ready to carry out your research.

Introduction

How do you get an idea for a study? How do you turn your idea into a testable hypothesis, and turn this into an appropriate and feasible study design? This is usually at best only partially taught in epidemiology courses. Most courses and textbooks assume that you know your research question and the general methods that you will need to answer it. Somehow it is assumed that you can readily translate your idea into a specific framework, such as the PICO framework (Patient, Intervention, Control or Comparison, Outcome) 1 or the FINER framework (Feasible, Interesting, Novel, Ethical, and Relevant) 2 or that you can fit it into counterfactual reasoning. 3 However, before describing your project in one of these frameworks, you first need to have an idea for your study and think about it in general terms: why you might do a study and how you might do a study.

This paper considers the complex process of having ideas, keeping track of them, turning them into studies, trying them out in pilot studies, and writing a draft paper before you finally embark on your study.

The paper is intended for novice researchers in clinical or public health epidemiology. It is not intended to be a comprehensive literature review about creativity, nor a sociology or philosophical treatise about why scientists get particular ideas (and not other ideas). It is based on our personal experience of (a combined) 70+ epidemiologic research-years. We have worked on very different topics, mostly on opposite sides of the globe, yet found that our experiences are quite similar. The fact that these issues are rarely covered in epidemiology courses has provided motivation to reflect on our experience.

Getting new ideas

So how do you get an idea? How some juxtaposition of neural patterns in our brain suddenly creates a new idea is a process that we are far from understanding. According to Karl Popper, the origin of new ideas does not matter; the only thing of interest is to devise how to test them. 4 Over the past decades, the literature has been enriched with new ideas about “being creative” in science – as witnessed in the book Innovation Generation by Ness. 5

In the present paper, we will not cover the literature about creativity and discovery in depth, but we will discuss the issues that we consider relevant to epidemiologic research. We will first consider the more general principles.

The real complexity of the thought processes that lead to a scientific undertaking is almost never described in published papers. Immunologist Medawar claimed that in this respect almost all scientific papers may be a fraud – not in the sense that scientists deliberately produce misleading data, but in the sense that the real thought processes that lead to the data and conclusions are not mentioned. 6 Scientists tell us about their real thought processes in memoirs, inaugural, or valedictory lectures – which is why these are so much more interesting than “standard” papers or presentations.

What strikes our minds: regularities or anomalies?

All sciences study a particular “object of knowledge” (eg, “matter”, “life”). Ideas come from experience and previous knowledge or facts about this object of knowledge, although this knowledge is always filtered through the perspective of one or more theories. 7 Epidemiology studies the distribution and determinants of disease in human populations, 8 and epidemiological ideas arise from observing and thinking about populations. 9 These could be clinical populations (ie, clinical experience, sometimes involving just a few patients), exposure-based populations (eg, workers exposed to a particular chemical), or general populations (geographically defined or sociologically defined). Whatever the population we are interested in, ideas come from observing either regularities or anomalies.

The observation of regularities (“induction”) is a common origin of new ideas. 4 , 10 – 13 Philosopher David Hume described “Induction” as: regularly seeing two things happening in succession (like pushing a switch and a light going on) leads to suspicions of causality. As he pointed out, causality can never be proven by the mere observation of “constant conjunctions”, but observing regularities can start our train of thought. 12

An anomaly (or irregularity) strikes our mind, because it defies our expectations. The regularity that we expected was our “hypothesis” (even if it was not really explicitly formulated); the anomaly is a “refutation”. 4 , 13 It forces us to think about other explanations, and these lead to new hypotheses that we then try to test. Thus, scientists do not usually start from hypotheses that are nicely formulated “out of the blue”, but instead start from previous knowledge and experience; when they are challenged by anomalies, scientists seek new explanations. 14

An interesting way to discover anomalies is to enter a new field of research; since you have other background experience than the people already in the field, you see things that they take for granted but that strike you as odd – at the same time, you may also see new explanations for these anomalies. One of the pioneers of clinical epidemiology, Sackett, once wrote that scientists should “retire” from a field as soon as they become “experts”. 15 When you are too long in a field, you will no longer see the anomalies, and you may even obstruct newcomers with new explanations. Of course, there are differences between scientists: some roam across various fields and others stick to a problem area that they explore with increasing depth – then the increasing depth and the new techniques that one needs for advancing one’s thoughts will be like a “new field”.

Taxonomies of discovery

Few researchers have listed the different ways in which one can arrive at new ideas, that is, lists of ways of discovery. We will present two of them – which have very different origins but remarkable similarities. Several examples of studies corresponding to items on these two lists are given in Appendix Examples A1–A10 .

Sources for new ideas about health care evaluation were described by Crombie and Davies in the chapter “Developing the research question” of their book on Research in Health Care that reflects a UK public health experience. 16

• “Review existing practice […] the current organisation and delivery of health care is not as good as it could be […]”
• “Challenge accepted ideas […] much of health care is based on accepted practice rather than research evidence […]” ( Appendix Example A3 )
• “Look for conflicting views […] which indicate either that there is not enough evidence, or that some practitioners are misinformed”
• “Investigate geographical variation […] reflecting on the reasons [for geographical variation] can be a fruitful source of research questions […]” ( Appendix Example A6 )
• “Identify Cinderella topics […] important areas of health care are often overlooked […]”
• “Let loose the imagination […] look for wild or impossible ideas […] free the mind from the constraints of conventional wisdom […].”

A taxonomy for sources of clinical research questions about medical care and clinical problems was proposed by Hulley and Cummings, in the context of clinical research in the US: 2

• “Build on experience;” your own experience, that of close colleagues with whom you can freely discuss your research ideas, and that of a good mentor, because young researchers might not yet have much experience, “An essential strategy for a young investigator is to apprentice himself to an experienced senior scientist who has the time and interest to work with him regularly.”
• ○ By harvesting “the medical literature and attending journal clubs, national and international meetings, seeking informal conversations with other scientists and colleagues”
• ○ “A sceptical attitude about prevailing beliefs can stimulate good research questions”
• ○ Be alert to “careful observation of patients, which has historically been one of the major sources of descriptive studies” ( Appendix Examples A1 and A2 )
• ○ Your experiences in teaching; having to explain something may make you aware of gaps in your knowledge; questions by patients and colleagues may similarly identify things that we do not fully understand or ignore
• “Keep the imagination roaming […]” by a mixture of creativity and tenacity; “put an unresolved question clearly in view and turn on the mental switch that lets the mind run freely toward it”.

A special mention needs to be made about the last categories of both the lists: “Let loose the imagination” and “Keep the imagination roaming”. These are especially important to find innovative solutions. In many situations wherein you cannot do a perfect study and you run a grave danger of potential confounding or bias, it helps to “get deeply immersed”: to understand the problem biologically, clinically, socially, organizationally, and environmentally will help you to think about what is happening, why it is happening, and whether you can find situations in which the potential confounders or biases do not exist or exists in reverse. You should forget formal designs and think out of the box: you will find instances of studies that mutually reinforce each other and may even arrive at formulating new designs or analytic solutions (see Appendix Examples A7–A10 ).

Keeping track of your ideas

It is not only important to have good ideas but also important to develop them. Researchers who work in laboratories have the habit of keeping “lab logs”. They write down briefly the results of an experiment, note why they think it went wrong, and how they will perform the next experiment. This permits them to trace how they changed the experiments or even the content and the direction of their research. We should do the same in epidemiologic and clinical research, particularly in the stage of creating new ideas. Such notes about ideas can include not only hypotheses and views or results by others but also drawing directed acyclic graphs (DAGs) (see “Intermezzo: specific schemes to structure reasoning” section) to make the causal structures of ideas clear.

The greatest minds kept track of their thoughts. Charles Darwin’s notebooks document his ideas, his observations, his readings, and new theories and facts that struck him. 17 For example, Darwin noted a story that he heard from his father, a medical practitioner. His father recounted that he had been struck by one of his patients’ ways of expressing himself, because he had attended a parent of the patient who had had the same mannerisms – even though the parent had died when the patient was still an infant. Remarks like these still have relevance today when we think about the heredity and evolution of behavior.

The sociologist C Wright Mills carried the description of the process one step further in the appendix of his book on The Sociological Imagination . 18 He encourages young sociologists to set up a file of stacked cards to keep track of “[…] personal experience and professional activities, studies underway and studies planned […]” which “[…] encourages you to capture ‘fringe thoughts’: various ideas which may be by-products of everyday life, stretches of conversations […]”. These notes are continuously reshuffled, regrouped under new headings, and pondered. Mills denounced the habit of most (social) scientists who feel the need to write about their plans only when they are going to apply for a grant. He thought that scientists should continually work with their file of ideas and regularly take stock of how these have evolved.

Such strategies are still relevant today, even if our “logs” are kept in electronic form, particularly because grant writing has become more demanding, hectic, and time-consuming. From such files, new research projects are born: while your ideas gradually develop, you keep wondering what data you might need to prove a certain proposition, and how you might get those data in the easiest way possible. Often, ideas are reshuffled and regrouped under new headings. A new observation, a new piece of literature may make old ones fall into place, or there may suddenly be a new opportunity to work out an old idea.

A complementary advice recently came in a blog from a contemporary sociologist, Aldrich: his advice is to “Write as if you don’t have the data”, that is, to write “[…] the literature review and planning phase of a project, preferably before it has been locked into a specific research design”. 19

The role of emotions

Underlying the discovery process, there are often two emotions: “surprise” and “indignation”. Surprise is the intellectual emotion when we see something happening against expectation: a patient with an unusual exposure, unusual disease manifestation, sudden cure, or sudden ill-understood deterioration; a laboratory result that is an anomaly; and a sudden epidemic of disease in a population. Indignation is the moral emotion: a group of patients is not being treated well because we lack sufficient knowledge, or because we are blundering in organizing health care or in transmitting and applying public health knowledge. Some passion is useful to bring any undertaking to a good end, be it that the passion should be restrained and channeled into polite undertakings, like in a research protocol. While doing the research project, maintaining some of the original passion will help you to find ways to overcome the daily hassles of research, the misadventures, the difficulties of getting others to collaborate, and the difficulties of getting published ( Appendix Example A11 ).

Sharpening the research question: the pruning

Pruning a research question means cutting away anything that is unnecessary, so that only the essence remains.

The initial spark of an idea will usually lead to some rather general research question. Invariably, this is too ambitious, or so all-encompassing that it cannot be researched (at least not within the time frame of a single grant or PhD project). You have to refine your research question into something that is interesting, yet feasible. To do so, you have to know clearly where you are heading. The emphasis on a clear preconceived idea about what you want to attain by your research often comes as a surprise; some people object: “[…] isn’t research about discovery? How can you know in advance what you want to find?”

The social scientist Verschuren proposed the “wristwatch metaphor”. 20 A researcher is not like a beachcomber, who strolls along the beach to see whether anything valuable washed ashore. Rather, a researcher is like someone who has lost her wristwatch on the beach and returns to search for it. She knows what part of the beach to look, she can describe her wristwatch in detail, and once she has found it, she knows that this is the watch she was looking for. Some further background to these ideas can be found in Appendix B .

Charles Medawar wrote in his Advice to a Young Scientist (page 18) 21 that as much as politics is the ‘art of the possible’, research is the ‘art of the soluble’. A research question should be limited to a question that can be solved with the resources at hand. This does not mean that you should preferentially study “trivial” questions with easy solutions. It does mean that you should seek out your particular niche: something specific, something that was overlooked by others, or some new twist to a general question, so that you can make your own contribution.

The concept of “serendipity” is often invoked when thinking of “seeking novelty”: it means finding something that you were not looking for. For a full discussion of the more complex reality that shows how, in reality, “chance favors a prepared mind”, see Appendix C .

Proceed in the inverse order of the paper that you will write

From the aforementioned, we know that we need a precise aim and a soluble research question.

How can we achieve this? The best approach is to “begin at the end”, that is, the conclusion that you hope to support when you eventually publish your research findings, perhaps many years from now. 22 Most medical research papers have a fixed format: introduction, methods, results, discussion. Usually, the discussion has three parts: summary of the results, discussion of the strengths and limitations, and the importance and interpretation of the findings. There you start: you try to imagine what such last lines of the eventual paper might be – in particular what their intent, their message to the reader might be. Another useful strategy would be to imagine what might be written in the separate box “What this paper adds” that many journals nowadays ask to convey the message from the authors clearly and succinctly to the readers.

The “latent” versus the “stated” objective

The pioneer clinical epidemiologist Feinstein wrote that a good research consultant should be like a good clinician, who first wants to learn from the patient: “What is the chief complaint?”, that is, which is the problem that you want to study. Next, “What will you do with the answer?” 22 The latter question is not just about the potential conclusions of the research paper, but more importantly, their meaning. What is the intended effect (or impact) of the findings? He called this the “latent objective”: what do you want to achieve or change by your project; the “stated objective” is different, it is the type of result that the study will deliver. For example, the stated objective can be that you want to do a randomized trial to compare one intervention versus another and that you will look at recurrence of disease. The latent objective might be that you are concerned that one intervention may be harmful to patients, driven by special interests, and that if this is the case it should be abolished.

Rather analogously, the long-time editor of the Annals of Internal Medicine , Edward Huth, proposed in his book about medical publishing the “So-What” and the “Who-Cares” tests: “What may happen if the paper’s message is correct?”; may it change concepts and treatment or stimulate further exciting research? 23 In fact, many funders now require such an “impact statement” as part of the grant application process.

Experienced research consultants know that when trying to discover the latent objective, it is useful to brush aside the detailed protocol and to ask directly what the meaning of the research is. The meaning of the research is often not clearly stated in a formal study protocol that limits itself more or less to “stated aims”. 24 Like a patient who cannot articulate her/his complaints very well, would-be researchers lose themselves in trivial “side issues” or operational details of the protocol. Appendix Examples A2 and A11 explain the importance of elucidating the underlying frustration of the clinician-researcher to clearly guide a research effort.

After initial questions have set the scene and clarified the “latent objective” of a project, the next questions are more operational, translating the latent objective back into a “stated objective”. 22 The stated objective should be a feasible research project. According to Feinstein, one should ask: what maneuver is to be executed (what intervention, deliberate or not, and how is it administered), what groups are to be compared (and why those groups), and what is the outcome that we will study?

In these phases of discussion, one needs to immerse oneself into the problem: one has to understand it biologically and clinically, and how it is dealt with in the daily practice of health care in the setting in which you will do research. Getting deeply immersed in the problem is the only way of arriving at shrewd or new solutions for studies on vexing medical or public health problems ( Appendix Example A9 ). Mere discussion of technical or procedural aspects of a proposed design, data collection, or analysis will usually not lead to new insights.

Specific pruning questions, to ask yourself or others

In initial discussions, one goes back and forth between the general aim (the latent objective), the scientific questions that follow from it, and the possible research designs (with stated objectives). After feeling secure about the “latent” aim, proceed with more specific questions.

• Try to describe exactly the knowledge gap that you want to fill (ie, the watch that you lost at the beach). Is it about etiology, about pathogenesis, about prognosis? What should change for the benefit of a particular group of patients? Try to be as specific as possible. Do your colleagues see these problems and their solutions as you do? – and if not, why don’t they?
• Once you know the point you want to make, describe what table or figure you need to fill the gap in knowledge, that is, what would your results look like? This means drawing a simple table or graph. Are these the data you want? Will these tables convince your colleagues? What objections might they have? Keep in mind that if the research results go against ingrained beliefs, they will be scrutinized mercilessly, so the important aspects of your research should be able to withstand likely objections.
• Thereafter, the questions become more practical: what study design is needed to produce this table, this figure? Can we do this? Do we have the resources or can we find them?

Be self-critical

You should always remain self-critical about the aspects that threaten the validity of your study ( Appendix Example A12 ). 25 If the practical problems are too large, or the research question too unfeasibly grandiose, it might be wise to settle for a less ambitious aim ( Appendix Example A13 ).

Paraphrasing Miettinen, 26 the first decision is whether you should do the study at all. There might be several reasons to decide not to pursue a study. One might be that arriving at a satisfactory design will be impossible, because of biases that you are unable to solve. It serves no purpose to add another study that suffers from the same unsolved problems as previous studies. For example, it does not serve any purpose to do yet another study that shows lower mortality in vegetarians, if you cannot solve the problems of confounding that vegetarians are persons who have different lifestyles in comparison with others. 27 (If, however, you have found a solution – pursue it at all means!) Nevertheless, thinking about the potential problems and ultimate aims of a seemingly impossible question can foster the development of a new study design or a new method of analysis, ( Appendix Examples A2, A9, and A10 ). In the same vein, deciding that you cannot do a study yourself might make you look for collaboration with persons who have the type of data that you do not, for example, in a different population where it is believed that confounding is not so severe or may even be in the opposite direction.

All studies have imperfections, but you need to be aware which ones you can tolerate. 28 In the early stages of an enquiry, an “imperfect” study might still be worthwhile to see whether “there might be something in it”. For example, time trends or ecological comparisons are often seen as poor study designs to assess causality by themselves, but they can be very valuable in helping to develop ideas, as well as providing a “reality check” about the potential credibility of some hypothesis. 29

Conversely, it is pointless to add yet another study, however perfect, showing what is already known very well – unless you have to do it for “political” purposes, say, for convincing decision makers in your own country.

Finally, it is not a good use of your time to chase something completely improbable or futile. For example, at the present state of the debate, it serves no purpose to add another study about the presence or absence of clinical benefits or harms of homeopathy: no one will change his or her mind about the issue. 30 , 31 An exception might be something that is highly improbable, but that if true might lead to completely revolutionary insights – such an idea might be worth pursuing, even if the initial reaction of outsiders might remain incredulousness. Still, you should pursue unlikely hypotheses knowingly, that is, with the right amount of self-criticism – in particular, to make yourself aware when you are in a blind alley.

To keep yourself on the “straight and narrow”, it helps to form a group of people who cover different aspects of the problem you want to study: clinical, biochemical and physiological, and methodological – to discuss the project as equals. Such discussions can not only be tremendous fun but also will invariably lead to more profound and diverse research questions and will help to find solutions for practical as well as theoretical problems. In the right circumstances of a “machtsfreie Dialog” 32 (a communication in which all are equal and that is only based on rational arguments and not on power – which all scientific debates should be), such a circle of colleagues and friends will help you to be self-critical.

Finally, when pursuing one’s research interests, one should be prepared to learn new skills from other fields or collaborate with others from these fields. If one stays only with the techniques and skills that one knows, it might not lead to the desired answers. 33

What if the data already exist? And you are employed to do a particular analysis with an existing protocol?

Even in the circumstance that the data already exist, it greatly helps to not jump into an analysis, but to think for yourself what you would ideally like to do – if there were no constraints. As Aldrich mentioned, 19 also in that circumstance researchers should still

[…] begin their literature review and conceptual modeling as if they had the luxury of a blank slate […]. Writing without data constraints will, I believe, free their imaginations to range widely over the realm of possibilities, before they are brought to earth by practical necessities.

Moreover, this will make clear what compromises one will make by accepting the available data and the existing analysis protocol. Otherwise, one starts an analysis without being sufficiently aware of the limitations of a particular analysis on particular data.

The difference between explanatory and pragmatic research

A useful distinction is between explanatory and pragmatic research: the former is research that aims at discovery and explanation, whereas the latter is intended to evaluate interventions or diagnostic procedures. The first type of research consists of chasing explanations by pursuing different and evolving hypotheses; the second type of research aims at making decisions about actions in future patients. 27 The two opposites differ strongly in their thinking about the types of studies to pursue (eg, observational vs randomized), about the role of prior specification of a research hypothesis, about the need for “sticking to a prespecified protocol”, and about subgroup analyses and multiplicity of analyses. Some of these will be explained in the following subheadings.

The difference between explanatory and pragmatic trials is sometimes thought to mirror the difference between doing randomized trials versus observational research. However, even for randomized trials, a difference exists between “ pragmatic” and “explanatory” trials (coined first by Schwartz and Lellouch). 34 Because it is not always easy to delineate what aspects of a randomized trial are “pragmatic” or “explanatory”, instruments have been crafted to help researchers and evaluators. 35 , 36 Conversely, not all observational studies are explanatory: some are needed for pragmatic decisions (think about adverse effects of drugs and also about diagnostic evaluations where studies should influence practice guidelines) – while other studies aim at explaining how nature works.

Which iterations should you allow yourself? Anticipating the next project

Thinking about a research problem is a strongly iterative process. 2 , 33 , 37 One starts with a broad aim and then tries out several possible ideas about studies that might lead to better understanding or to better solutions.

Likewise, project proposals characteristically go through many iterations. In the early phases of the research, it is commonplace that the study design or even the research question is changed. Specific suggestions about common research problems and their potential solutions were given by Hulley and Cummings, 2 which we reproduce in Appendix D .

The revision of the aims of a project may be profound, in particular in explanatory research (see “The difference between explanatory and pragmatic research” section), in contrast to pragmatic research (see “Shouldn’t you stick to a predefined protocol?” section). The chemist Whitesides wrote: “Often the objectives of a paper when it is finished are different from those used to justify starting the work. Much of good science is opportunistic and revisionist”. 38 Along a similar line, Medawar proposed that to do justice to the real thought processes of a research undertaking, the discussion section of a paper should come at the beginning, since the thought processes of a scientist start with an expectation about particular results. The expectation determines which findings are of interest and why they will be interpreted in a particular way. 6 He added that in real scientific life, scientists get new ideas (ie, new expectations) while doing their research, but “[…] many of them apparently are ashamed to admit, that hypotheses appear in their mind along uncharted byways of thought”. 6

“Seeing something in the data” can be an important part of scientific discovery. This is often decried as “data dredging”, which it is not: one sees something because of one’s background knowledge and thereby there always is some “prior” that exists – even if that was not specified beforehand in the study protocol. 27 , 39 The word “exploratory” is often misused when it is used to characterize a study. True “exploratory” data analysis would only exists if it is mindlessly done, such as a Genome Wide Association Study (GWAS) analysis – but even GWAS analyses have specific aims, which becomes clear when results are interpreted and some findings are designated as “important” and others not. As stated by Rothman:

Hypotheses are not generated by data; they are proposed by scientists. The process by which scientists use their imagination to create hypotheses has no formal methodology […]. Any study, whether considered exploratory or not, can serve to refute a hypothesis. 40

Appendix Examples A5 and A7 show how projects changed mid-course because of a new discovery in the data or in the background knowledge about a research topic.

Generally, it is a good habit to think through what the next project might be, once you will have the result of the project you are currently thinking about, so as to know what direction your research might take. 33

Shouldn’t you stick to a predefined protocol?

Different research aims, in particular along the “explanatory” versus “pragmatic” continuum, may lead to different attitudes on the amount of change that protocols may endure while doing research. 27 , 39 For randomized trials, and also for pragmatic observational research, the research question is usually fixed: does a new therapy lead to better outcomes for a particular group of patients in a particular setting? Because findings from randomized trials or pragmatic observational research may lead to millions of patients to adopt or avoid a particular therapy (which means that their well-being or even life depends on the research) researchers are generally not at liberty to change their hypotheses at the last moment – for example, by suddenly declaring an interest in a particular subgroup. They should stick to the predefined protocol. If a change is needed for practical reasons, it should be clearly stated in the resulting publications. This makes thinking about research questions and doing pilot studies beforehand all the more important (see “Pilot Study” section).

In contrast, much epidemiologic and clinical research tries to explain how nature works. This gives greater leeway: exploration of data can lead to new insights. Thus, “sticking to the protocol” is a good rule for randomized trials and pragmatic observational research, but may be counterproductive for explanatory research. 39 , 41 Nevertheless, it is good to keep track of the changes in your thoughts and in the protocol, even if only for yourself. In practice, many situations are intermediate; in particular when using large available data sets, it often happens that one envisages in a protocol what one would do with the data, only to discover upon opening the data files that the data fall short or are more complex than imagined; this is another reason for doing pilot studies, even with large available data sets (see “Pilot Study” section).

How much literature should you read?

If you are setting up a new research project in a new area, do not start by reading too much. You will quickly drown in the ideas of others. Rather, read a few general reviews that identify unanswered problems. Only return to the literature after you have defined your research question and provisionally your study design. Now, the literature suddenly becomes extremely interesting, since you know what types of papers you need. You also know what the potential objections and shortcomings are of the different design options, because you thought about them yourself. The number of relevant papers usually greatly shrinks, see Appendix Example A4 .

Shouldn’t you do a systematic review first?

It is argued that before embarking on a new piece of research, one should first do a systematic review and/or meta-analysis, because this may help to define the gaps in knowledge more precisely, and guide new research – or may show that the question has been solved. This argument is somewhat circular. A systematic review is a piece of research in itself, intended for publication, and requires much time and effort. Like any piece of research, it requires a clear research question. As such it does not “identify gaps”: a systematic review is about a research question which is already specified, but for which more information is needed. Thus, the main function of the advice to first do a systematic review is to know whether the research question that one has in mind has not yet been solved by others. Perusing the literature in depth is absolutely needed, for example, before embarking on a randomized trial or on a major observational study. However, this is not the same as doing a formal systematic review. In-depth scoping of the literature will suffice. If it is found that potentially valuable studies already exist on the research question that one has in mind, then the new study that one is thinking about may be discarded, and a systematic review should be done instead.

Intermezzo: specific schemes to structure reasoning

Specific schemes have been proposed to guide our reasoning between the stage of delineation of the “gap in knowledge” and the stage of proposing the research design.

The acronym FINER (feasible, interesting, novel, ethical, and relevant) was coined by Hulley and Cummings 2 and denotes the different aspects that one should consider to judge a budding research proposal. These words are a good checklist for an in-depth self-scrutiny of your research. The central aspects are the feasibility and whether the possible answers are exciting (and/or much needed).

The PICO format (Patient, Intervention, Control or Comparison, Outcome) is advocated by the evidence-based medicine and Cochrane movements and is very useful for clinical therapeutic research, particularly randomized controlled trials (RCTs). 1 , 42 Questions about therapeutic interventions are highly specific, for example, a particular chemotherapeutic scheme (the intervention) is proposed to study survival (the outcome) among young women with a particular form of stage III breast cancer (the patients). This framework is less useful, and becomes a bit pointless, for etiologic research about generalizable questions such as: “Does smoking cause lung cancer?” which applies to all humans and to different types of smoking. Of course, all research will be done in particular population, with particular smoking habits, but this does not necessarily define the research question. Some of the first investigations about smoking and lung cancer were done in male doctors aged ≥35 years in the UK 43 – this was a very convenient group to research, but being a male doctor in the UK is not part of the research question.

The PICO format is thus most applicable for pragmatic research. A much more detailed and elaborate scheme for pragmatic research was proposed by the US Patient-Centered Outcomes Research Institute (PCORI) which has published Methodology Standards, including “Standards for Formulating Research Questions”. While we would not agree with all six standards, junior investigators may find the structure useful as they think through their options – especially for pragmatic research questions. 44

Counterfactual reasoning 3 emphasizes those aspects of the “ideal randomized trial” that should be mimicked by an observational study. A key question is whether your study is addressing a hypothesis that could in theory be studied in a randomized trial. For example, if the research question is “does smoking cause lung cancer?”, then this is a question that could in theory (but not in practice) be addressed by randomizing study participants to be smokers or nonsmokers. In this situation, it may be useful to design your observational study with the intention of obtaining the same answer that would have been obtained if you had been able to do a randomized trial.

However, the aims of explanatory observational research are different from those of randomized trials. 27 Explanatory research about disease etiology may involve “states” like being female, being old, being obese, having hypertension, having a high serum cholesterol, carrying the BrCa1 gene, and so on, as causes of disease. None of these causes are interventions. In contrast, RCTs focus on what to do to change particular causes: which interventions are feasible and work? For example, being female might expose a person to job discrimination; the intervention might be to have women on the appointment committee or to use some kind of positive discrimination. Likewise, the gene for phenylketonuria leads to disease, but the intervention is to change the diet. For carriers of BRCa1 genes, different strategies can be evaluated in RCTs to evaluate their effectiveness in preventing premature death due to breast cancer: frequent screening, prophylactic mastectomy, hormone treatment, and so on – which may have different effects. For obesity or hypertension or hypercholesterolemia, different types of interventions are possible – with potentially different effects and different adverse effects.

The interventionist outlook, that is, trying to mimic an RCT, can be very useful, for some type of observational studies, for example, about the adverse effects of drugs. It helps to make certain that one can mimic an “intervention” (ie, patients starting to use particular drugs) that is specific and consistent in groups of patients that are comparable (more technically, exchangeable – meaning that the results of the investigation would not change if the persons exposed and nonexposed were swapped). These conditions can be met in a credible way, if there are competing drugs for a similar indication, so that there is an active drug comparator: the interventions (use of different drugs in different patients) will be well defined, and the patients on the different drugs will tend to be comparable. This works particularly well if you are focusing on adverse drug effects that were unknown or unpredictable at the time of prescription. 45 , 46 For example, you may obtain more valid findings in a study that compares the adverse effects of two different beta agonists for asthma care (ie, two different drugs within the same class), than to design a study which compares patients who are prescribed beta agonists with patients who are prescribed other asthma medication, or no medication at all – because the latter might be a highly different group of patients. 47

As mentioned, there are some important studies about causes of diseases where a randomized trial is not feasible, even in theory. In particular, there are various “states” which are major causes of disease (obesity, cholesterol, hypertension, diabetes, etc). These states strongly affect the risks of disease and death, but cannot be randomized. For example, it is difficult to conceive of randomizing study participants to be obese or not obese; however, we could randomize them for the reduction of obesity, for example, through exercise, but such a study would assess the effects of a particular intervention, not of obesity itself. Still, it remains important to estimate the overall effects of obesity, that is, to answer the question “would this group of people have had different health status, on the average, if they had not been obese”. In this situation, the concept of “interventions” is not relevant to designing your study (at least in the way that the term “intervention” is commonly used). What is more relevant is simply to focus on the counterfactual contrast which is being assessed (eg, a body mass index [BMI] of 35 versus a BMI of 25), without specifying how this contrast came about.

A technique that has gone hand in hand with counterfactual reasoning in epidemiology is drawing DAGs; several introductions to DAG theory can be found in epidemiologic textbooks. 3 , 48 DAGs can be useful in the brainstorming phase of a study, after the general research question has been defined. At this stage, a general structure for the study is envisaged and the complexity of the causal processes needs clarification. A DAG can be extremely useful for illustrating the context in which a causal question is being asked, the assumptions that will be involved in the analyses (eg, whether a particular risk factor is a confounder, a mediator, or a col-lider), and help us question the validity of our reasoning. 49 Using DAGs helps us also decide which variables we need to collect information on and how they should be measured and defined. Given that DAGs root in causal thinking, their construction is, of necessity, subjective.

Preparation: pilot study, protocol, and advance writing

Doing a pilot study and collecting ancillary information about feasibility.

May I now start? is a question heard after lengthy deliberations about the research question and the potential studies that follow from it. Such deliberations almost invariably produce a lot of enthusiasm and exhilaration – because they are fun. The researcher wants to begin collecting data or start the analysis. However, Crombie and Davies, in their chapter about “Developing the research question” state emphatically: “Don’t rush into a study”. 16 Separate from doing a pilot study, which is about the procedures of your study, you may also need to collect ancillary information before actually starting your study.

Pilot study

Even if you think you are totally certain of what you want, you should first do a pilot study, based on a brief protocol. 2 , 22 That initial protocol should be easy to write. You have already discussed the aim and design of your study. Write them down. You expect a particular type of information that is essential and that will tell the essence of your message (a particular 2-by-2 or X-by-Y table, a particular graph), which you can describe.

Pilot studies are not done to know the likely direction of the results; instead, the aim is to see whether you will be able to perform the procedures of your study – and ultimately whether that really is the study you want to do. 50 The aim is to save yourself from embarrassment: data that very surprisingly do not turn out to be what you expected, questionnaires that are misunderstood or do not deliver the answers that you need or that are not returned, laboratories that do not produce, patients who do not show up, heads of other departments who block access to their patients or materials, or yourself who needs more time to manage the complexity of the undertaking.

We have never heard of someone who was sorry for having done a pilot. Conversely, we know many persons who found out at much personal embarrassment and institutional cost that their project was unfeasible. In intermediate cases, the pilot may show the need to change questionnaires or procedures before the study goes ahead.

In principle, a pilot study should be exactly like your final study and test out all your procedures on a small number of persons. Often, it is better to approach the task piecemeal and pilot different aspects of the research one by one.

A tough question is how to do pilot studies and pilot analyses when ethical or institutional review board approval is necessary for some of the actions in a pilot study. One solution might be to avoid piloting some procedures; for example, try parts of the procedure – for example, you may not be able to randomize in a pilot, but you may be able to try out data collection procedures and forms. There is a degree of circularity about piloting, also in obtaining funding, as one may need funding for the pilot. In practice, the best step might be to ask the ethics committee or review board of your institute which aspects of the research can be piloted and under what conditions.

In Appendix E , several questions that you might ask in pilot studies are listed. They may lead to profound reassessments of your research – particularly if you are piloting the collection of new data, but also if the research involves analyses of existing data.

Ancillary information

It may be necessary to collect additional information about event rates or standard deviations of measurements to calculate the statistical precision that might be obtained. Also, sometimes you need other ways of “testing the water” like procedures to streamlining data collection from different centers in order to know whether the study is feasible. Depending on the study size and importance, such activities may become studies in themselves and actually take a lot of time and money.

Advance writing of paper: before full data collection and/or analysis

Whitesides’ advice is:

The key to efficient use of your and my time is that we start exchanging outlines and proposals as early in a project as possible. Do not, under any circumstances, wait until the collection of data is ‘complete’ before starting to write an outline. 38

After the pilot study, you have a firm grasp of all elements that are necessary for a scientific paper: introduction, materials and methods, results, and discussion. In the introduction, you explain why you have done this research. Almost always, an introduction comprises three ideas: what is the general problem? what is the particular research question? what study will you perform to answer that question? This is followed by the materials and methods section. They have been extensively discussed and have been fine-tuned in the study protocol and the pilot study. Thereafter come the results sections. By now, you know what tables or figures you want and how you can obtain them, but not what the final numbers will look like. You will also have an idea about the auxiliary tables that you might need to explain your data to others (such as a table with the baseline characteristics or an additional table with a subgroup analysis). You can now draft the layouts of all these tables. Visualizing the presentation of your results in advance is the “bare minimum” of writing in advance.

Finally, the discussion section. Can you write a discussion before you know the final data? Of course you can; you even must think ahead. In principle, there are only three possible outcomes: the study can give the results that you hoped for; it can show the inverse; or something indeterminate in between. In all instances, you can imagine how you will react. One possibility is that you are disappointed by the results of your study, and you will tend to find excuses for why it did not produce the results you hoped for. What excuses might your produce? The other possibility is that it does show what you wanted; then you may have to imagine how others will react and what their objections might be. If the results are indeterminate, everybody might be disappointed, and you will need to explain the failure of your research to give clear-cut results. When you detect a specific weakness by imagining this situation, you may wish to change aspects of your study.

As we explain in Appendix F , there is no need to write a very extensive paper as a first draft – on the contrary, it might be more useful to write a short paper, which has the advantage that others will more readily read it and comment on it.

Never be afraid to discuss your study at all stages extensively with others, not only your immediate research colleagues but also semi-outsiders and also in this advance-writing stage. If you know, or are told by others, that a particular direction of your results might not be believed and therefore draw criticism because of some potential deficiency in your study, why not remedy it at this stage? Looking at what you have written, or by discussing potential results with others, you will be able to imagine more clearly what your readers and critical colleagues might object to.

Writing a paper beforehand is the ultimate test of whether the research project is what you wanted, whether your reasoning flows logically, or whether you forgot something. The initial draft will be a yardstick for yourself and for others – whatever happens during the course of your research. This will help you to surmount surprise happenings: you have written down where you started and why, and therefore you will also know very securely when and why you have to take a detour – or even a U-turn.

Writing is difficult and time-consuming. Writing a paper can easily take 5–10 revisions, which might span a full year (inclusive of the time it takes your supervisor or your colleagues to produce comments). During the writing, you will often be obliged to go back to the data and do additional or different analyses. Since your paper will need many revisions, and this will take such a long time, why not take a head-start at the beginning of your data collection? It will save frustration and lost time at the end of your project.

Many guidelines and advices exist about writing, both about the substance (how to use words and phrases) and about the process. All beginning researchers should have a look at some books and papers about writing, and seasoned researchers can still profit from rereading them. Several reporting guidelines exist for several types of studies (RCTs, observational, diagnostic research, etc). They are often very detailed, in describing what should be in title, abstract, and so on. Although they should not be mechanically adhered to, 28 they help writing. In Appendix F , we have collected some wisdom that we particularly liked; several books on writing are listed, as well as reporting guidelines that help researchers to craft papers that are readable and contain all the information that is necessary and useful to others.

Now you can start “your research”

After the piloting and after having written your paper, you are ready to start your data collection, your analysis, or whatever is needed to “do your research”.

The work that is needed before you can start to “do your research” will take a great deal of time and effort. What will you have achieved after setting up a piece of research following the lengthy and involved precepts of this paper? You will have specified a limited research question that you will solve. You will add one little shining stone to the large mosaic of science. At the time that you do the study, you may still be too close to see its effect on the overall picture. That will come over the years.

Further reading

Some texts that we mention in the paper might be especially worthwhile for further reading; see Appendix G .

Acknowledgments

We thank Miguel Hernán, Stuart Pocock, and Bianca De Stavola for their informative comments on an earlier draft manuscript, as well as two anonymous reviewers of Clinical Epidemiology . The Centre for Global NCDs is supported by the Wellcome Trust Institutional Strategic Support Fund (097834/Z/11/B). This work was also supported by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013 / ERC grant agreement number 668954).

The authors report no conflicts of interest in this work.

WashU Libraries

Conducting research.

• The Process

How to choose a topic

Testing your topic, formulate your research strategy, types of sources.

• Step 2: Finding background info.
• Step 3: Gathering more info.
• Get it This link opens in a new window
• Step 5: Evaluating your sources
• Step 6: Citing your sources
• FAQs This link opens in a new window
• Library Vocabulary
• Research in the Humanities
• Research in the Social Sciences
• Research in the Sciences

Information Overload: Narrowing your Research

Overwhelmed with too many or irrelevant results? Consider the following questions for refining your topic:

• Is there a specific time period you want to cover?
• Is there a geographic region or country on which you would like to focus?
• Is there a particular aspect of this subject that interests you? For example, historical influence, sociological aspects, ethical issues, cultural significance.
• Is there a specific group or individual you could research?

You can also combine multiple questions to further narrow your subject.

Information Desert: Broadening your Research

When exploring your research focus, consider the following questions for broadening your topic:

• What elements could you add to your paper? For example, expanding the time period or changing the geographic location. 
• What other issues are involved in this research?
• What is the bigger concept of your subject?

The very first step in the research process is choosing a topic that is not too broad or too narrow in scope.

To help you define a good topic you are advised to do one or all of the following:

• use reference sources (such as encyclopedias );
• consult other sources as suggested on the page find and read background information ;
• state your topic as a question (e.g., Can sleep disorders effect academic success in college students?);
• identify the main concepts or keywords in your question (e.g., college students, grade point average, sleep disorders);
• consult with your instructor or TA;
• or consult with a subject librarian who specializes in the field of study you are researching.

If you think you have a good topic or are getting close, try applying your topic ideas to the questions listed below.

Test the main concepts or keywords in your topic by looking them up in the appropriate background sources or by using them as search terms in the WUSTL Discovery Catalog and in library databases .

• If you are finding too much information and too many sources, narrow your topic by using the and operator: college students and grade point average and sleep disorders.
• Finding too little information may indicate that you need to broaden your topic. For example, look for information on students, rather than college students.
• Link synonymous search terms with or : academic achievement or grade point average or school failure.
• When you use a truncation symbol, most often the asterisk (*), the system will search for all terms and phrases starting with the word stem that appears before the symbol.  For example, searching "sleep disorder*" will yield results including disorder, disorders, disordered, etc. This will broaden your search and increase the number of items you find.

Once you have identified and tested your topic, you're ready to take the next step, finding background information .

The steps to your research strategy will depend on how much time you have and the type of project on which you are working. In order to conduct effective research, you need to gather appropriate information for your topic. Consider the following questions to help you determine the best research strategy:

How much time do you have?

If you have limited time, it is advisable to focus your information gathering on articles from journals, magazines, newspapers and on books which are in the library or on the web.

If you have more time to plan your research, you will be able to incorporate a variety of materials on your topic and to obtain resources from other libraries .

On what type of project are you working?

The depth of research will depend on the nature of your project. You may need to consider the guidelines specified by your professor on the length of paper or presentation.

What type of information do you need?

Your approach to the topic will determine the type of resources you will use. For example, some research may involve collecting facts, while other research may include gathering various opinions on an issue or argument. You may also want to consider whether your topic will be enhanced by including primary resources. The following types of resources may serve as a guide:

• Internet resources
• Book reviews
• Dissertations
• Statistical information
• Music scores
• Sound recordings
• Internet reference sources
• Government documents
• Manuscripts

Do you need primary sources? Secondary sources? Both?

"You need to consider whether your project requires primary or secondary sources and, if you will use both, whether a particular work is a primary or a secondary source in the context of your work. Primary sources are basic materials with little or no annotation or editorial alteration, such as manuscripts, diaries, letters, interviews, and laboratory reports. Secondary sources derive from primary materials and include analysis, interpretation, and commentary on primary materials."

"Depending on the point of view of your research paper, a given source may be either primary or secondary. A research paper on William James, the nineteenth-century philosopher, would treat R.W.B. Lewis's The Jameses: A Family Narrative as a secondary source, whereas a paper on Lewis, a well-known critic and biographer, would treat the same book as a primary source. Your assignment may require you to emphasize either primary or secondary sources or to use a combination of the two." -- (Slade, Carole. Form and style. Boston : Houghton Mifflin Co., c1997.)

Primary sources  can be tricky.  Whether a source is  primary  depends on how you use it. A primary source is a written text, artifact, or other original creation upon which you focus your analysis and interpretation. For example, an article that analyzes a book, song, or society would be considered a secondary source. However, that article could function as a primary source--if you are analyzing the ideas of the author of that article, then it functions as a primary source. So anything could function as a primary source--just consider how you are using it: if it's the object of your analysis, then it's a primary source.

A  secondary source  is a work that interprets or analyzes an historical event or phenomenon. It is generally at least one step removed from the event is often based on primary sources. Examples include: scholarly or popular books and articles, reference books, and textbooks.

Tertiary sources are encyclopedias, dictionaries, textbooks and other reference materials that provide broad overviews of particular topics. Where secondary sources summarize and interpret an event or phenomenon, tertiary sources summarize and interpret other resources. They can be a great place to begin studying unfamiliar topics.

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Research Process: An Overview: Refining Your Topic

• Choosing a Topic
• Refining Your Topic
• Finding Information
• Evaluating Your Sources
• Database Searching
• APA Citation This link opens in a new window

TIP: Be Flexible

It is common to modify your topic during the research process. You can never be sure of what you may find. You may find too much and need to narrow your focus, or too little and need to broaden your focus. This is a normal part of the research process. When researching, you may not wish to change your topic, but you may decide that some other aspect of the topic is more interesting or manageable.

Steps to Refining Your Topic

Once you have chosen a general topic idea the next step is to refine your topic and ulitmately to formulate a research question.

Consider the points below to keep your research focused and on track.  If you continue to have difficulties defining a topic talk to your instructor or a librarian.

The Research Question

Once you have the topic you would like to research, the next step is forming your research question. Your research question should be focused and specifc.  The result should also be a question for which there are two or more possible answers.  See some examples below:

Assignment Guidelines

Before selecting your topic, make sure you know what your final project should look like. Each instructor will probably have different assignment requirements so be sure to read your assignment thoroughly and check for specific guidelines concerning:

• The number of sources you are required to use
• The kinds of sources are you able to use - books vs. web sites vs. journal articles or a variety?
• The type of research you are you being asked to conduct. - original research or review what research has been done?
• The length of your final project - two-pages, ten pages, etc. or an informal, five minute presentation?
• The depth of your project - Is your project an overview of the subject or in-depth and focused coverage of a specific aspect?
• The scope you are required to cover - Is this an historical summary or a report of current developments?

You instructor will probably provide specific requirements for your assignment, if not the table below may provide a rough guide:

Assigning Limits to Your Topic

A topic will be very difficult to research if it is too broad or narrow. One way to narrow a broad topic is to assign limits to what you will cover. Some common ways to limit a topic are listed below using the broad topic, "the environment" as an example.

Remember that a topic may be too difficult to research if it is too:

• locally confined - Topics this specific may only be covered in these (local) newspapers, if at all.

Example: What sources of pollution affect the Genesee County water supply?

• recent - If a topic is quite recent, books or journal articles may not be available, but newspaper or magazine articles may. Also, Web sites related to the topic may or may not be available.
• broadly interdisciplinary - You could be overwhelmed with superficial information.

Example: How can the environment contribute to the culture, politics and society of the Western states?

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11.1 The Purpose of Research Writing

Learning objectives.

• Identify reasons to research writing projects.
• Outline the steps of the research writing process.

Why was the Great Wall of China built? What have scientists learned about the possibility of life on Mars? What roles did women play in the American Revolution? How does the human brain create, store, and retrieve memories? Who invented the game of football, and how has it changed over the years?

You may know the answers to these questions off the top of your head. If you are like most people, however, you find answers to tough questions like these by searching the Internet, visiting the library, or asking others for information. To put it simply, you perform research.

Whether you are a scientist, an artist, a paralegal, or a parent, you probably perform research in your everyday life. When your boss, your instructor, or a family member asks you a question that you do not know the answer to, you locate relevant information, analyze your findings, and share your results. Locating, analyzing, and sharing information are key steps in the research process, and in this chapter, you will learn more about each step. By developing your research writing skills, you will prepare yourself to answer any question no matter how challenging.

Reasons for Research

When you perform research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you (and other people) have about the world. This is one of the most basic reasons for performing research.

But the research process does not end when you have solved your mystery. Imagine what would happen if a detective collected enough evidence to solve a criminal case, but she never shared her solution with the authorities. Presenting what you have learned from research can be just as important as performing the research. Research results can be presented in a variety of ways, but one of the most popular—and effective—presentation forms is the research paper . A research paper presents an original thesis, or purpose statement, about a topic and develops that thesis with information gathered from a variety of sources.

If you are curious about the possibility of life on Mars, for example, you might choose to research the topic. What will you do, though, when your research is complete? You will need a way to put your thoughts together in a logical, coherent manner. You may want to use the facts you have learned to create a narrative or to support an argument. And you may want to show the results of your research to your friends, your teachers, or even the editors of magazines and journals. Writing a research paper is an ideal way to organize thoughts, craft narratives or make arguments based on research, and share your newfound knowledge with the world.

Write a paragraph about a time when you used research in your everyday life. Did you look for the cheapest way to travel from Houston to Denver? Did you search for a way to remove gum from the bottom of your shoe? In your paragraph, explain what you wanted to research, how you performed the research, and what you learned as a result.

Research Writing and the Academic Paper

No matter what field of study you are interested in, you will most likely be asked to write a research paper during your academic career. For example, a student in an art history course might write a research paper about an artist’s work. Similarly, a student in a psychology course might write a research paper about current findings in childhood development.

Having to write a research paper may feel intimidating at first. After all, researching and writing a long paper requires a lot of time, effort, and organization. However, writing a research paper can also be a great opportunity to explore a topic that is particularly interesting to you. The research process allows you to gain expertise on a topic of your choice, and the writing process helps you remember what you have learned and understand it on a deeper level.

Research Writing at Work

Knowing how to write a good research paper is a valuable skill that will serve you well throughout your career. Whether you are developing a new product, studying the best way to perform a procedure, or learning about challenges and opportunities in your field of employment, you will use research techniques to guide your exploration. You may even need to create a written report of your findings. And because effective communication is essential to any company, employers seek to hire people who can write clearly and professionally.

Writing at Work

Take a few minutes to think about each of the following careers. How might each of these professionals use researching and research writing skills on the job?

• Medical laboratory technician
• Small business owner
• Information technology professional
• Freelance magazine writer

A medical laboratory technician or information technology professional might do research to learn about the latest technological developments in either of these fields. A small business owner might conduct research to learn about the latest trends in his or her industry. A freelance magazine writer may need to research a given topic to write an informed, up-to-date article.

Think about the job of your dreams. How might you use research writing skills to perform that job? Create a list of ways in which strong researching, organizing, writing, and critical thinking skills could help you succeed at your dream job. How might these skills help you obtain that job?

Steps of the Research Writing Process

How does a research paper grow from a folder of brainstormed notes to a polished final draft? No two projects are identical, but most projects follow a series of six basic steps.

These are the steps in the research writing process:

• Choose a topic.
• Plan and schedule time to research and write.
• Conduct research.
• Organize research and ideas.
• Draft your paper.
• Revise and edit your paper.

Each of these steps will be discussed in more detail later in this chapter. For now, though, we will take a brief look at what each step involves.

Step 1: Choosing a Topic

As you may recall from Chapter 8 “The Writing Process: How Do I Begin?” , to narrow the focus of your topic, you may try freewriting exercises, such as brainstorming. You may also need to ask a specific research question —a broad, open-ended question that will guide your research—as well as propose a possible answer, or a working thesis . You may use your research question and your working thesis to create a research proposal . In a research proposal, you present your main research question, any related subquestions you plan to explore, and your working thesis.

Step 2: Planning and Scheduling

Before you start researching your topic, take time to plan your researching and writing schedule. Research projects can take days, weeks, or even months to complete. Creating a schedule is a good way to ensure that you do not end up being overwhelmed by all the work you have to do as the deadline approaches.

During this step of the process, it is also a good idea to plan the resources and organizational tools you will use to keep yourself on track throughout the project. Flowcharts, calendars, and checklists can all help you stick to your schedule. See Chapter 11 “Writing from Research: What Will I Learn?” , Section 11.2 “Steps in Developing a Research Proposal” for an example of a research schedule.

Step 3: Conducting Research

When going about your research, you will likely use a variety of sources—anything from books and periodicals to video presentations and in-person interviews.

Your sources will include both primary sources and secondary sources . Primary sources provide firsthand information or raw data. For example, surveys, in-person interviews, and historical documents are primary sources. Secondary sources, such as biographies, literary reviews, or magazine articles, include some analysis or interpretation of the information presented. As you conduct research, you will take detailed, careful notes about your discoveries. You will also evaluate the reliability of each source you find.

Step 4: Organizing Research and the Writer’s Ideas

When your research is complete, you will organize your findings and decide which sources to cite in your paper. You will also have an opportunity to evaluate the evidence you have collected and determine whether it supports your thesis, or the focus of your paper. You may decide to adjust your thesis or conduct additional research to ensure that your thesis is well supported.

Remember, your working thesis is not set in stone. You can and should change your working thesis throughout the research writing process if the evidence you find does not support your original thesis. Never try to force evidence to fit your argument. For example, your working thesis is “Mars cannot support life-forms.” Yet, a week into researching your topic, you find an article in the New York Times detailing new findings of bacteria under the Martian surface. Instead of trying to argue that bacteria are not life forms, you might instead alter your thesis to “Mars cannot support complex life-forms.”

Step 5: Drafting Your Paper

Now you are ready to combine your research findings with your critical analysis of the results in a rough draft. You will incorporate source materials into your paper and discuss each source thoughtfully in relation to your thesis or purpose statement.

When you cite your reference sources, it is important to pay close attention to standard conventions for citing sources in order to avoid plagiarism , or the practice of using someone else’s words without acknowledging the source. Later in this chapter, you will learn how to incorporate sources in your paper and avoid some of the most common pitfalls of attributing information.

Step 6: Revising and Editing Your Paper

In the final step of the research writing process, you will revise and polish your paper. You might reorganize your paper’s structure or revise for unity and cohesion, ensuring that each element in your paper flows into the next logically and naturally. You will also make sure that your paper uses an appropriate and consistent tone.

Once you feel confident in the strength of your writing, you will edit your paper for proper spelling, grammar, punctuation, mechanics, and formatting. When you complete this final step, you will have transformed a simple idea or question into a thoroughly researched and well-written paper you can be proud of!

Review the steps of the research writing process. Then answer the questions on your own sheet of paper.

• In which steps of the research writing process are you allowed to change your thesis?
• In step 2, which types of information should you include in your project schedule?
• What might happen if you eliminated step 4 from the research writing process?

Key Takeaways

• People undertake research projects throughout their academic and professional careers in order to answer specific questions, share their findings with others, increase their understanding of challenging topics, and strengthen their researching, writing, and analytical skills.
• The research writing process generally comprises six steps: choosing a topic, scheduling and planning time for research and writing, conducting research, organizing research and ideas, drafting a paper, and revising and editing the paper.

Writing for Success Copyright © 2015 by University of Minnesota is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Research Topics – Ideas and Examples

Table of Contents

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.

How to Choose Research Topic

You can Choose a Research Topic by following the below guide:

Identify your Interests

One of the most important factors to consider when choosing a research topic is your personal interest. This is because you will be spending a considerable amount of time researching and writing about the topic, so it’s essential that you are genuinely interested and passionate about it. Start by brainstorming a list of potential research topics based on your interests, hobbies, or areas of expertise. You can also consider the courses that you’ve enjoyed the most or the topics that have stood out to you in your readings.

Review the Literature

Before deciding on a research topic, you need to understand what has already been written about it. Conducting a preliminary review of the existing literature in your field can help you identify gaps in knowledge, inconsistencies in findings, or unanswered questions that you can explore further. You can do this by reading academic articles, books, and other relevant sources in your field. Make notes of the themes or topics that emerge and use this information to guide your research question.

Consult with your Advisor

Your academic advisor or a mentor in your field can provide you with valuable insights and guidance on choosing a research topic. They can help you identify areas of interest, suggest potential research questions, and provide feedback on the feasibility of your research proposal. They can also direct you towards relevant literature and resources that can help you develop your research further.

Consider the Scope and Feasibility

The research topic you choose should be manageable within the time and resource constraints of your project. Be mindful of the scope of your research and ensure that you are not trying to tackle a topic that is too broad or too narrow. If your topic is too broad, you may find it challenging to conduct a comprehensive analysis, while if it’s too narrow, you may struggle to find enough material to support your research.

Brainstorm with Peers

Discussing potential research topics with your peers or colleagues can help you generate new ideas and perspectives. They may have insights or expertise that you haven’t considered, and their feedback can help you refine your research question. You can also join academic groups or attend conferences in your field to network with other researchers and get inspiration for your research.

Consider the Relevance

Choose a research topic that is relevant to your field of study and has the potential to contribute to the existing knowledge. You can consider the latest trends and emerging issues in your field to identify topics that are both relevant and interesting. Conducting research on a topic that is timely and relevant can also increase the likelihood of getting published or presenting your research at conferences.

Keep an Open Mind

While it’s essential to choose a research topic that aligns with your interests and expertise, you should also be open to exploring new ideas or topics that may be outside of your comfort zone. Consider researching a topic that challenges your assumptions or introduces new perspectives that you haven’t considered before. You may discover new insights or perspectives that can enrich your research and contribute to your growth as a researcher.

Components of Research Topic

A research topic typically consists of several components that help to define and clarify the subject matter of the research project. These components include:

• Research problem or question: This is the central issue or inquiry that the research seeks to address. It should be well-defined and focused, with clear boundaries that limit the scope of the research.
• Background and context: This component provides the necessary background information and context for the research topic. It explains why the research problem or question is important, relevant, and timely. It may also include a literature review that summarizes the existing research on the topic.
• Objectives or goals : This component outlines the specific objectives or goals that the research seeks to achieve. It should be clear and concise, and should align with the research problem or question.
• Methodology : This component describes the research methods and techniques that will be used to collect and analyze data. It should be detailed enough to provide a clear understanding of how the research will be conducted, including the sampling method, data collection tools, and statistical analyses.
• Significance or contribution : This component explains the significance or contribution of the research topic. It should demonstrate how the research will add to the existing knowledge in the field, and how it will benefit practitioners, policymakers, or society at large.
• Limitations: This component outlines the limitations of the research, including any potential biases, assumptions, or constraints. It should be transparent and honest about the potential shortcomings of the research, and how these limitations will be addressed.
• Expected outcomes or findings : This component provides an overview of the expected outcomes or findings of the research project. It should be realistic and based on the research objectives and methodology.

Purpose of Research Topic

The purpose of a research topic is to identify a specific area of inquiry that the researcher wants to explore and investigate. A research topic is typically a broad area of interest that requires further exploration and refinement through the research process. It provides a clear focus and direction for the research project, and helps to define the research questions and objectives. A well-defined research topic also helps to ensure that the research is relevant and useful, and can contribute to the existing body of knowledge in the field. Ultimately, the purpose of a research topic is to generate new insights, knowledge, and understanding about a particular phenomenon, issue, or problem.

Characteristics of Research Topic

some common characteristics of a well-defined research topic include:

• Relevance : A research topic should be relevant and significant to the field of study and address a current issue, problem, or gap in knowledge.
• Specificity : A research topic should be specific enough to allow for a focused investigation and clear understanding of the research question.
• Feasibility : A research topic should be feasible, meaning it should be possible to carry out the research within the given constraints of time, resources, and expertise.
• Novelty : A research topic should add to the existing body of knowledge by introducing new ideas, concepts, or theories.
• Clarity : A research topic should be clearly articulated and easy to understand, both for the researcher and for potential readers of the research.
• Importance : A research topic should be important and have practical implications for the field or society as a whole.
• Significance : A research topic should be significant and have the potential to generate new insights and understanding in the field.

Examples of Research Topics

Here are some examples of research topics that are currently relevant and in-demand in various fields:

• The impact of social media on mental health: With the rise of social media use, this topic has gained significant attention in recent years. Researchers could investigate how social media affects self-esteem, body image, and other mental health concerns.
• The use of artificial intelligence in healthcare: As healthcare becomes increasingly digitalized, researchers could explore the use of AI algorithms to predict and prevent disease, optimize treatment plans, and improve patient outcomes.
• Renewable energy and sustainable development: As the world seeks to reduce its carbon footprint, researchers could investigate the potential of renewable energy sources such as wind and solar power, and how these technologies can be integrated into existing infrastructure.
• The impact of workplace diversity and inclusion on employee productivity: With an increasing focus on diversity and inclusion in the workplace, researchers could investigate how these factors affect employee morale, productivity, and retention.
• Cybersecurity and data privacy: As data breaches and cyber attacks become more common, researchers could explore new methods of protecting sensitive information and preventing malicious attacks.
• T he impact of mindfulness and meditation on stress reduction: As stress-related health issues become more prevalent, researchers could investigate the effectiveness of mindfulness and meditation practices on reducing stress and improving overall well-being.

Research Topics Ideas

Here are some Research Topics Ideas from different fields:

• The impact of social media on mental health and well-being.
• The effectiveness of various teaching methods in improving academic performance in high schools.
• The role of AI and machine learning in healthcare: current applications and future potentials.
• The impact of climate change on wildlife habitats and conservation efforts.
• The effects of video game violence on aggressive behavior in young adults.
• The effectiveness of mindfulness-based stress reduction techniques in reducing anxiety and depression.
• The impact of technology on human relationships and social interactions.
• The role of exercise in promoting physical and mental health in older adults.
• The causes and consequences of income inequality in developed and developing countries.
• The effects of cultural diversity in the workplace on job satisfaction and productivity.
• The impact of remote work on employee productivity and work-life balance.
• The relationship between sleep patterns and cognitive functioning.
• The effectiveness of online learning versus traditional classroom learning.
• The role of government policies in promoting renewable energy adoption.
• The effects of childhood trauma on mental health in adulthood.
• The impact of social media on political participation and civic engagement.
• The effectiveness of cognitive-behavioral therapy in treating anxiety disorders.
• The relationship between nutrition and cognitive functioning.
• The impact of gentrification on urban communities.
• The effects of music on mood and emotional regulation.
• The impact of microplastics on marine ecosystems and food webs.
• The role of artificial intelligence in detecting and preventing cyberattacks.
• The effectiveness of mindfulness-based interventions in managing chronic pain.
• The relationship between personality traits and job satisfaction.
• The effects of social isolation on mental and physical health in older adults.
• The impact of cultural and linguistic diversity on healthcare access and outcomes.
• The effectiveness of psychotherapy in treating depression and anxiety in adolescents.
• The relationship between exercise and cognitive aging.
• The effects of social media on body image and self-esteem.
• The role of corporate social responsibility in promoting sustainable business practices.
• The impact of mindfulness meditation on attention and focus in children.
• The relationship between political polarization and media consumption habits.
• The effects of urbanization on mental health and well-being.
• The role of social support in managing chronic illness.
• The impact of social media on romantic relationships and dating behaviors.
• The effectiveness of behavioral interventions in promoting physical activity in sedentary adults.
• The relationship between sleep quality and immune function.
• The effects of workplace diversity and inclusion programs on employee retention.
• The impact of climate change on global food security.
• The role of music therapy in improving communication and social skills in individuals with autism spectrum disorder.
• The impact of cultural values on the development of mental health stigma.
• The effectiveness of mindfulness-based stress reduction techniques in reducing burnout in healthcare professionals.
• The relationship between social media use and body dissatisfaction among adolescents.
• The effects of nature exposure on cognitive functioning and well-being.
• The role of peer mentoring in promoting academic success in underrepresented student populations.
• The impact of neighborhood characteristics on physical activity and obesity.
• The effectiveness of cognitive rehabilitation interventions in improving cognitive functioning in individuals with traumatic brain injury.
• The relationship between organizational culture and employee job satisfaction.
• The effects of cultural immersion experiences on intercultural competence development.
• The role of assistive technology in promoting independence and quality of life for individuals with disabilities.
• The impact of workplace design on employee productivity and well-being.
• The impact of digital technologies on the music industry and artist revenues.
• The effectiveness of cognitive behavioral therapy in treating insomnia.
• The relationship between social media use and body weight perception among young adults.
• The effects of green spaces on mental health and well-being in urban areas.
• The role of mindfulness-based interventions in reducing substance use disorders.
• The impact of workplace bullying on employee turnover and job satisfaction.
• The effectiveness of animal-assisted therapy in treating mental health disorders.
• The relationship between teacher-student relationships and academic achievement.
• The effects of social support on resilience in individuals experiencing adversity.
• The role of cognitive aging in driving safety and mobility.
• The effectiveness of psychotherapy in treating post-traumatic stress disorder (PTSD).
• The relationship between social media use and sleep quality.
• The effects of cultural competency training on healthcare providers’ attitudes and behaviors towards diverse patient populations.
• The role of exercise in preventing chronic diseases such as type 2 diabetes and cardiovascular disease.
• The impact of the gig economy on job security and worker rights.
• The effectiveness of art therapy in promoting emotional regulation and coping skills in children and adolescents.
• The relationship between parenting styles and child academic achievement.
• The effects of social comparison on well-being and self-esteem.
• The role of nutrition in promoting healthy aging and longevity.
• The impact of gender diversity in leadership on organizational performance.
• The effectiveness of family-based interventions in treating eating disorders.
• The relationship between social media use and perceived loneliness among older adults.
• The effects of mindfulness-based interventions on pain management in chronic pain patients.
• The role of physical activity in preventing and treating depression.
• The impact of cultural differences on communication and conflict resolution in international business.
• The effectiveness of eye movement desensitization and reprocessing (EMDR) in treating anxiety disorders.
• The relationship between student engagement and academic success in higher education.
• The effects of discrimination on mental health outcomes in minority populations.
• The role of virtual reality in enhancing learning experiences.
• The impact of social media influencers on consumer behavior and brand loyalty.
• The effectiveness of acceptance and commitment therapy (ACT) in treating chronic pain.
• The relationship between social media use and body image dissatisfaction among men.
• The effects of exposure to nature on cognitive functioning and creativity.
• The role of spirituality in coping with illness and disability.
• The impact of automation on employment and job displacement.
• The effectiveness of dialectical behavior therapy (DBT) in treating borderline personality disorder.
• The relationship between teacher-student relationships and school attendance.
• The effects of mindfulness-based interventions on workplace stress and burnout.
• The role of exercise in promoting cognitive functioning and brain health in older adults.
• The impact of diversity and inclusion initiatives on organizational innovation and creativity.
• The effectiveness of cognitive remediation therapy in treating schizophrenia.
• The relationship between social media use and body dissatisfaction among women.
• The effects of exposure to natural light on mood and sleep quality.
• The role of spirituality in enhancing well-being and resilience in military personnel.
• The impact of artificial intelligence on job training and skill development.
• The effectiveness of interpersonal therapy (IPT) in treating depression.
• The relationship between parental involvement and academic achievement among low-income students.
• The effects of mindfulness-based interventions on emotional regulation and coping skills in trauma survivors.
• The role of nutrition in preventing and treating mental health disorders.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research Question Examples 🧑🏻‍🏫

25+ Practical Examples & Ideas To Help You Get Started 

By: Derek Jansen (MBA) | October 2023

A well-crafted research question (or set of questions) sets the stage for a robust study and meaningful insights.  But, if you’re new to research, it’s not always clear what exactly constitutes a good research question. In this post, we’ll provide you with clear examples of quality research questions across various disciplines, so that you can approach your research project with confidence!

Research Question Examples

• Psychology research questions
• Business research questions
• Education research questions
• Healthcare research questions
• Computer science research questions

Examples: Psychology

Let’s start by looking at some examples of research questions that you might encounter within the discipline of psychology.

How does sleep quality affect academic performance in university students?

This question is specific to a population (university students) and looks at a direct relationship between sleep and academic performance, both of which are quantifiable and measurable variables.

What factors contribute to the onset of anxiety disorders in adolescents?

The question narrows down the age group and focuses on identifying multiple contributing factors. There are various ways in which it could be approached from a methodological standpoint, including both qualitatively and quantitatively.

Do mindfulness techniques improve emotional well-being?

This is a focused research question aiming to evaluate the effectiveness of a specific intervention.

How does early childhood trauma impact adult relationships?

This research question targets a clear cause-and-effect relationship over a long timescale, making it focused but comprehensive.

Is there a correlation between screen time and depression in teenagers?

This research question focuses on an in-demand current issue and a specific demographic, allowing for a focused investigation. The key variables are clearly stated within the question and can be measured and analysed (i.e., high feasibility).

Examples: Business/Management

Next, let’s look at some examples of well-articulated research questions within the business and management realm.

How do leadership styles impact employee retention?

This is an example of a strong research question because it directly looks at the effect of one variable (leadership styles) on another (employee retention), allowing from a strongly aligned methodological approach.

What role does corporate social responsibility play in consumer choice?

Current and precise, this research question can reveal how social concerns are influencing buying behaviour by way of a qualitative exploration.

Does remote work increase or decrease productivity in tech companies?

Focused on a particular industry and a hot topic, this research question could yield timely, actionable insights that would have high practical value in the real world.

How do economic downturns affect small businesses in the homebuilding industry?

Vital for policy-making, this highly specific research question aims to uncover the challenges faced by small businesses within a certain industry.

Which employee benefits have the greatest impact on job satisfaction?

By being straightforward and specific, answering this research question could provide tangible insights to employers.

Examples: Education

Next, let’s look at some potential research questions within the education, training and development domain.

How does class size affect students’ academic performance in primary schools?

This example research question targets two clearly defined variables, which can be measured and analysed relatively easily.

Do online courses result in better retention of material than traditional courses?

Timely, specific and focused, answering this research question can help inform educational policy and personal choices about learning formats.

What impact do US public school lunches have on student health?

Targeting a specific, well-defined context, the research could lead to direct changes in public health policies.

To what degree does parental involvement improve academic outcomes in secondary education in the Midwest?

This research question focuses on a specific context (secondary education in the Midwest) and has clearly defined constructs.

What are the negative effects of standardised tests on student learning within Oklahoma primary schools?

This research question has a clear focus (negative outcomes) and is narrowed into a very specific context.

Need a helping hand?

Examples: Healthcare

Shifting to a different field, let’s look at some examples of research questions within the healthcare space.

What are the most effective treatments for chronic back pain amongst UK senior males?

Specific and solution-oriented, this research question focuses on clear variables and a well-defined context (senior males within the UK).

How do different healthcare policies affect patient satisfaction in public hospitals in South Africa?

This question is has clearly defined variables and is narrowly focused in terms of context.

Which factors contribute to obesity rates in urban areas within California?

This question is focused yet broad, aiming to reveal several contributing factors for targeted interventions.

Does telemedicine provide the same perceived quality of care as in-person visits for diabetes patients?

Ideal for a qualitative study, this research question explores a single construct (perceived quality of care) within a well-defined sample (diabetes patients).

Which lifestyle factors have the greatest affect on the risk of heart disease?

This research question aims to uncover modifiable factors, offering preventive health recommendations.

Examples: Computer Science

Last but certainly not least, let’s look at a few examples of research questions within the computer science world.

What are the perceived risks of cloud-based storage systems?

Highly relevant in our digital age, this research question would align well with a qualitative interview approach to better understand what users feel the key risks of cloud storage are.

Which factors affect the energy efficiency of data centres in Ohio?

With a clear focus, this research question lays a firm foundation for a quantitative study.

How do TikTok algorithms impact user behaviour amongst new graduates?

While this research question is more open-ended, it could form the basis for a qualitative investigation.

What are the perceived risk and benefits of open-source software software within the web design industry?

Practical and straightforward, the results could guide both developers and end-users in their choices.

Remember, these are just examples…

In this post, we’ve tried to provide a wide range of research question examples to help you get a feel for what research questions look like in practice. That said, it’s important to remember that these are just examples and don’t necessarily equate to good research topics . If you’re still trying to find a topic, check out our topic megalist for inspiration.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

18k Accesses

Abstractspiepr Abs1

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.

You have full access to this open access chapter,  Download chapter PDF

Part I. What Is Research?

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 .

Exercise 1.1

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.

Exercise 1.2

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.

Creating an Image 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.

Descriptor 1. Experience Carefully Planned in Advance

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.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

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.

Exercise 1.3

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?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

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.

Doing Scientific Inquiry

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.

Exercise 1.4

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.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

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.

Exercise 1.5

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?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing 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.

Part II. Why Do Educators Do Research?

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 .

Exercise 1.7

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.

Part III. Conducting Research as a Practice of Failing Productively

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.

Exercise 1.8

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).

Exercise 1.9

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.

Part IV. Preview of Chap. 2

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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Choose Your Test

Sat / act prep online guides and tips, 113 great research paper topics.

General Education

One of the hardest parts of writing a research paper can be just finding a good topic to write about. Fortunately we've done the hard work for you and have compiled a list of 113 interesting research paper topics. They've been organized into ten categories and cover a wide range of subjects so you can easily find the best topic for you.

In addition to the list of good research topics, we've included advice on what makes a good research paper topic and how you can use your topic to start writing a great paper.

What Makes a Good Research Paper Topic?

Not all research paper topics are created equal, and you want to make sure you choose a great topic before you start writing. Below are the three most important factors to consider to make sure you choose the best research paper topics.

#1: It's Something You're Interested In

A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject. Even if a certain research paper topic is getting a lot of buzz right now or other people seem interested in writing about it, don't feel tempted to make it your topic unless you genuinely have some sort of interest in it as well.

#2: There's Enough Information to Write a Paper

Even if you come up with the absolute best research paper topic and you're so excited to write about it, you won't be able to produce a good paper if there isn't enough research about the topic. This can happen for very specific or specialized topics, as well as topics that are too new to have enough research done on them at the moment. Easy research paper topics will always be topics with enough information to write a full-length paper.

Trying to write a research paper on a topic that doesn't have much research on it is incredibly hard, so before you decide on a topic, do a bit of preliminary searching and make sure you'll have all the information you need to write your paper.

#3: It Fits Your Teacher's Guidelines

Don't get so carried away looking at lists of research paper topics that you forget any requirements or restrictions your teacher may have put on research topic ideas. If you're writing a research paper on a health-related topic, deciding to write about the impact of rap on the music scene probably won't be allowed, but there may be some sort of leeway. For example, if you're really interested in current events but your teacher wants you to write a research paper on a history topic, you may be able to choose a topic that fits both categories, like exploring the relationship between the US and North Korea. No matter what, always get your research paper topic approved by your teacher first before you begin writing.

113 Good Research Paper Topics

Below are 113 good research topics to help you get you started on your paper. We've organized them into ten categories to make it easier to find the type of research paper topics you're looking for.

Arts/Culture

• Discuss the main differences in art from the Italian Renaissance and the Northern Renaissance .
• Analyze the impact a famous artist had on the world.
• How is sexism portrayed in different types of media (music, film, video games, etc.)? Has the amount/type of sexism changed over the years?
• How has the music of slaves brought over from Africa shaped modern American music?
• How has rap music evolved in the past decade?
• How has the portrayal of minorities in the media changed?

Current Events

• What have been the impacts of China's one child policy?
• How have the goals of feminists changed over the decades?
• How has the Trump presidency changed international relations?
• Analyze the history of the relationship between the United States and North Korea.
• What factors contributed to the current decline in the rate of unemployment?
• What have been the impacts of states which have increased their minimum wage?
• How do US immigration laws compare to immigration laws of other countries?
• How have the US's immigration laws changed in the past few years/decades?
• How has the Black Lives Matter movement affected discussions and view about racism in the US?
• What impact has the Affordable Care Act had on healthcare in the US?
• What factors contributed to the UK deciding to leave the EU (Brexit)?
• What factors contributed to China becoming an economic power?
• Discuss the history of Bitcoin or other cryptocurrencies  (some of which tokenize the S&P 500 Index on the blockchain) .
• Do students in schools that eliminate grades do better in college and their careers?
• Do students from wealthier backgrounds score higher on standardized tests?
• Do students who receive free meals at school get higher grades compared to when they weren't receiving a free meal?
• Do students who attend charter schools score higher on standardized tests than students in public schools?
• Do students learn better in same-sex classrooms?
• How does giving each student access to an iPad or laptop affect their studies?
• What are the benefits and drawbacks of the Montessori Method ?
• Do children who attend preschool do better in school later on?
• What was the impact of the No Child Left Behind act?
• How does the US education system compare to education systems in other countries?
• What impact does mandatory physical education classes have on students' health?
• Which methods are most effective at reducing bullying in schools?
• Do homeschoolers who attend college do as well as students who attended traditional schools?
• Does offering tenure increase or decrease quality of teaching?
• How does college debt affect future life choices of students?
• Should graduate students be able to form unions?

• What are different ways to lower gun-related deaths in the US?
• How and why have divorce rates changed over time?
• Is affirmative action still necessary in education and/or the workplace?
• Should physician-assisted suicide be legal?
• How has stem cell research impacted the medical field?
• How can human trafficking be reduced in the United States/world?
• Should people be able to donate organs in exchange for money?
• Which types of juvenile punishment have proven most effective at preventing future crimes?
• Has the increase in US airport security made passengers safer?
• Analyze the immigration policies of certain countries and how they are similar and different from one another.
• Several states have legalized recreational marijuana. What positive and negative impacts have they experienced as a result?
• Do tariffs increase the number of domestic jobs?
• Which prison reforms have proven most effective?
• Should governments be able to censor certain information on the internet?
• Which methods/programs have been most effective at reducing teen pregnancy?
• What are the benefits and drawbacks of the Keto diet?
• How effective are different exercise regimes for losing weight and maintaining weight loss?
• How do the healthcare plans of various countries differ from each other?
• What are the most effective ways to treat depression ?
• What are the pros and cons of genetically modified foods?
• Which methods are most effective for improving memory?
• What can be done to lower healthcare costs in the US?
• What factors contributed to the current opioid crisis?
• Analyze the history and impact of the HIV/AIDS epidemic .
• Are low-carbohydrate or low-fat diets more effective for weight loss?
• How much exercise should the average adult be getting each week?
• Which methods are most effective to get parents to vaccinate their children?
• What are the pros and cons of clean needle programs?
• How does stress affect the body?
• Discuss the history of the conflict between Israel and the Palestinians.
• What were the causes and effects of the Salem Witch Trials?
• Who was responsible for the Iran-Contra situation?
• How has New Orleans and the government's response to natural disasters changed since Hurricane Katrina?
• What events led to the fall of the Roman Empire?
• What were the impacts of British rule in India ?
• Was the atomic bombing of Hiroshima and Nagasaki necessary?
• What were the successes and failures of the women's suffrage movement in the United States?
• What were the causes of the Civil War?
• How did Abraham Lincoln's assassination impact the country and reconstruction after the Civil War?
• Which factors contributed to the colonies winning the American Revolution?
• What caused Hitler's rise to power?
• Discuss how a specific invention impacted history.
• What led to Cleopatra's fall as ruler of Egypt?
• How has Japan changed and evolved over the centuries?
• What were the causes of the Rwandan genocide ?

• Why did Martin Luther decide to split with the Catholic Church?
• Analyze the history and impact of a well-known cult (Jonestown, Manson family, etc.)
• How did the sexual abuse scandal impact how people view the Catholic Church?
• How has the Catholic church's power changed over the past decades/centuries?
• What are the causes behind the rise in atheism/ agnosticism in the United States?
• What were the influences in Siddhartha's life resulted in him becoming the Buddha?
• How has media portrayal of Islam/Muslims changed since September 11th?

Science/Environment

• How has the earth's climate changed in the past few decades?
• How has the use and elimination of DDT affected bird populations in the US?
• Analyze how the number and severity of natural disasters have increased in the past few decades.
• Analyze deforestation rates in a certain area or globally over a period of time.
• How have past oil spills changed regulations and cleanup methods?
• How has the Flint water crisis changed water regulation safety?
• What are the pros and cons of fracking?
• What impact has the Paris Climate Agreement had so far?
• What have NASA's biggest successes and failures been?
• How can we improve access to clean water around the world?
• Does ecotourism actually have a positive impact on the environment?
• Should the US rely on nuclear energy more?
• What can be done to save amphibian species currently at risk of extinction?
• What impact has climate change had on coral reefs?
• How are black holes created?
• Are teens who spend more time on social media more likely to suffer anxiety and/or depression?
• How will the loss of net neutrality affect internet users?
• Analyze the history and progress of self-driving vehicles.
• How has the use of drones changed surveillance and warfare methods?
• Has social media made people more or less connected?
• What progress has currently been made with artificial intelligence ?
• Do smartphones increase or decrease workplace productivity?
• What are the most effective ways to use technology in the classroom?
• How is Google search affecting our intelligence?
• When is the best age for a child to begin owning a smartphone?
• Has frequent texting reduced teen literacy rates?

How to Write a Great Research Paper

Even great research paper topics won't give you a great research paper if you don't hone your topic before and during the writing process. Follow these three tips to turn good research paper topics into great papers.

#1: Figure Out Your Thesis Early

Before you start writing a single word of your paper, you first need to know what your thesis will be. Your thesis is a statement that explains what you intend to prove/show in your paper. Every sentence in your research paper will relate back to your thesis, so you don't want to start writing without it!

As some examples, if you're writing a research paper on if students learn better in same-sex classrooms, your thesis might be "Research has shown that elementary-age students in same-sex classrooms score higher on standardized tests and report feeling more comfortable in the classroom."

If you're writing a paper on the causes of the Civil War, your thesis might be "While the dispute between the North and South over slavery is the most well-known cause of the Civil War, other key causes include differences in the economies of the North and South, states' rights, and territorial expansion."

#2: Back Every Statement Up With Research

Remember, this is a research paper you're writing, so you'll need to use lots of research to make your points. Every statement you give must be backed up with research, properly cited the way your teacher requested. You're allowed to include opinions of your own, but they must also be supported by the research you give.

#3: Do Your Research Before You Begin Writing

You don't want to start writing your research paper and then learn that there isn't enough research to back up the points you're making, or, even worse, that the research contradicts the points you're trying to make!

Get most of your research on your good research topics done before you begin writing. Then use the research you've collected to create a rough outline of what your paper will cover and the key points you're going to make. This will help keep your paper clear and organized, and it'll ensure you have enough research to produce a strong paper.

What's Next?

Are you also learning about dynamic equilibrium in your science class? We break this sometimes tricky concept down so it's easy to understand in our complete guide to dynamic equilibrium .

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Want to know the fastest and easiest ways to convert between Fahrenheit and Celsius? We've got you covered! Check out our guide to the best ways to convert Celsius to Fahrenheit (or vice versa).

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Christine graduated from Michigan State University with degrees in Environmental Biology and Geography and received her Master's from Duke University. In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist. She has taught English and biology in several countries.

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Research idea: How to write your own

The world of European programmes is based on ideas, facts and research on pretty much anything that has...

The world of European programmes is based on ideas, facts and research on pretty much anything that has to do with improving the labor market, the scientific world, current technologies, and society as we know it. If your organization or you as a researcher want to become a part of the programmes then you are going to need to work on a specific idea.

In most cases, the project starts based on the call to action provided by the European Union. And yes, this might be considered one of the easiest ways to do so. The Commission requires specific actions to be taken on a specific matter. If your organisation can form a proposal suggesting solutions to those actions then you just write your proposal, you submit it to your national agency and if approved you start implementing the project.

And yes, this might be a great way for you to start entering the world of European programmes. However, it is not the kind of way that will make you a well-known experienced partner or someone who is making a great impact through European programme implementation.

The solution, in this case, is a research idea. Instead of creating a proposal and by default the project based on a call, you could create a research idea that serves a particular purpose. After you do so, you can match that idea to a specific European commission call and build the entire proposal around it. But why is this such a good way to start?

This is a valid question. In most cases, people will claim that this is quite a complicated process. Why create a research idea when you can just create the proposal based on what the court requires? The answer is quite simple. A research idea and a very specific matter that offers a very specific solution will attract a much better consortium. The entire proposal that will be built around that idea will have a purpose. You will notice that writing that proposal is going to be a lot easier if you have a research idea. Last but not least, you are going to build a reputation. If you do have the ability to create your research ideas, the kind of ideas that people will like them by default more and more partners will want to become a part of your consortium.

Writing the idea

Coming up with a research idea can be quite complicated. There are a lot of different things that will need to be taken into account. First and foremost, you will need to focus on the expertise of your organization to build the idea. For example, if you are an expert in entrepreneurship you cannot hope to build a research idea specified in the health department. Coming up with a product or a machine that will help solve a worldwide health crisis is not something the businessman can do.

However, as a researcher, you can focus on your expertise which could be pretty much any scientific field and start building a specific research idea. You will want to narrow down your options to the one subject matter that you can support the best with valid arguments and provable solutions.

Do your research

Let's assume that you are a researcher on the health field and you are interested in creating a research idea that will help solve a very specific problem. Before you start writing the idea you need to do your research to know exactly what kinds of actions have already been taken regarding the problem you are attempting to solve.

That alone is going to help you create the research idea. You can draw from those actions are perhaps even use them as arguments to suggest your solutions. Moreover, you could use the results of those actions as a way to boost your very own research idea thus giving it a lot more prestige.

Now your limits

As a researcher, whether you are working alone or are employed in a research facility, you will need to know your limits. There are only so many things you can do as an individual or as part of the consortium. Creating a research idea that will require top-quality partners, expertise and technology that is difficult to find is not going to make things easy for you.

On the contrary, if you keep your idea just a tad lower you could find a consortium capable of supporting that idea that's creating an effective proposal. If that proposal gets approved and that research idea is implemented then you can simply take things to the next level. Use the results of the first project to create a new research idea, maybe an improvement of the old one. In other words, built on your ideas one step at a time. A process like that could take years to be completed and as a researcher, you already know that.

Take your time to create the idea

This is a common mistake that a lot of researchers out there might make. They get excited about a project or a concept and they start creating a research idea aiming at completing it very fast. As a result, they will have an inconclusive idea in their hands. More importantly, they will not be able to find a call to match the idea. They are most likely going to apply to a call that does not have complete relevancy resulting in the idea of getting rejected.

By taking the time to create your research idea you will have the opportunity to gather as much information as possible. At the same time, you will study all of the European Commission's calls around your sector and the sector of the research idea, aiming at finding the one call that will suit you the best.

Create drafts

Rome was not built in a day. No research idea can be born and completed in one night. You will need to create drafts upon drafts, built on the idea in multiple different ways and try to combine as many of them as possible until you have a final product in your hands. Those drafts will help you create the final idea which will be the center of your proposal.

Simultaneously, the drafts you will create could provide you with more ideas for the future. Keeping notes and creating drafts is certainly going to give you enough material to build your research idea focusing on the important aspects of it and of course, utilizing all information and possible outcomes the right way.

Create your database

Who's to say that the idea you are currently working on has not already been developed by someone on the other end of the world? By taking your time as suggested above, you will have the opportunity to do a lot of research and find all the valuable information concerning your research idea.

By doing so, you will start creating a massive database of information surrounding a particular subject matter. You need to try and think about this as your library. A library that will contain all the valuable information regarding your research idea and any kind of research you might want to conduct in the future.

Editing is important.

This is a much more technical process but it is most certainly a very important one. A research idea can be quite complicated and by not processing it correctly you could end up with a bad result. You are going to be presenting that idea to your potential partners.

Proper wording will make it easier for you to process and explain your idea as well as others to understand it!

As a researcher, you already know how to conduct proper research to form an idea. As a business owner, our most valuable tip is the following. Do not appoint the task of creating a research idea to someone inexperienced or irrelevant to the field of the idea. Always make sure that your researchers will be up to the task and ready to create the best research idea for project proposal!

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Proposal Essay Examples: Convincing Ideas for Your Research Paper or Essay

Struggling to craft a captivating and well-built proposal essay? Many students find it challenging to compose a proposal-based essay and struggle to generate convincing ideas. If this sounds familiar, read on. In this comprehensive guide, we streamline the process of brainstorming and composing work, offering resources like suggestions on how to write a proposal essay, suggested steps when writing, useful examples, and efficient essay-crafting tips.

Developed through several years of expertise in scholarly writing, our article is meticulously tailored to help you excel in your academic assignments. Join us as we explore crafting an exceptional proposal paper. With the right tools and assistance, you'll move from ambiguity to self-assurance, ready to write an impressive work. Let's master the art of creating an attention-grabbing essay.

What is a Proposal Essay?

A proposal essay succinctly outlines the key content and aim of your intended study, summarizing its primary points and overall intent. Unlike a thesis, which presents the main idea of your academic study, a proposal-focused assignment acts as a detailed plan addressing a specific problem. As a proposal writer, you identify an issue, suggest a possible solution, and then provide persuasive evidence for the audience to have them support your viewpoint. Your goal is to convince them that this view is exceptional and deserves implementation. When writing such an essay, consider it as a chance to immerse in practical issues and showcase analytical and creative thinking skills. These papers serve as strategic tools, allowing an author to present their ideas or beliefs compellingly. Beyond business or economics, they encourage solution-seeking and reasoning skills across a variety of disciplines.

In a nutshell, a proposal-driven assignment allows you to demonstrate your ability to think innovatively and critically, addressing real-life issues with practical solutions. Now that you understand what is a proposal essay, join us in exploring its specifics and revealing your writer’s potential.

How to Write a Proposal Essay

Creating a successful proposal-related paper necessitates thorough preparation and an understanding of your audience's needs. To write such an essay, observe these stages:

• Extensively investigate your assignment’s topic to identify a chosen problem.
• Develop a compelling thesis statement summarizing your suggested solution.
• Make a solid proposal essay outline to logically organize all your ideas and ensure unity and cohesion.
• Present solid proof to support your viewpoints and anticipate any objections.
• Refine your writing carefully to enhance content clarity and logic.

When you are occupied with thoughts on how to write a paper proposal, handy tools like the AI essay generator Aithor have become indispensable helpers. Aithor, our intuitive assistant, empowers writers by utilizing advanced technology to generate ideas, check accuracy, and offer alternative words, improving the piece of writing. Explore the innovative capabilities of our AI tool by visiting https://aithor.com/ai-essay-generator and let it assist you with your assignment.

Check out some additional tips to enhance your overall essay quality:

• Get to know your audience and tailor your planned proposal to its interests.
• Use convincing language to involve your audience to advocate for your notion.
• Incorporate relevant data, instances, and statistics to reinforce your position.
• Address possible counterarguments to demonstrate thorough consideration.
• Use a powerful summary to conclude and inspire to act, urging support for your concepts.

To wrap up, writing a decent proposal-based essay requires in-depth investigation, persuasive argumentation, and attention to detail. By following the mentioned guidelines and additional tips, you can smoothly write a solid solution-focused writing that inspires action.

Prewriting Stage

Setting for a journey of composing a proposal-related assignment can be overwhelming. How to start a proposal essay? To ease this process, academic writers advocate for a systematic approach to craft a captivating piece of writing.

Here's a full guide to guarantee your assignment paper stands out. Know Your Reader

Being sympathetic to your prospective listeners is paramount when writing a persuasive paper. Who will you write for? Identify their key roles, preferences, and concerns to efficiently customize your message. This ensures mutual resonance in your views and addresses their specific needs and expectations.

Research Academic investigation forms the foundation of a robust convincing paper. Even with a prior understanding of the material, delving deeper yields new insights and perspectives. Revising scholarly literature enhances arguments, lending authority and credibility to your message.

Set an Issue

State the topic and challenges precisely and clearly. Use evidence to accentuate its significance and establish your grasp of the matter. That step is pivotal in gaining the audience's sympathy and support.

Define a Solution

Offer a straightforward and practical way out to the identified problem. Ensure its clarity and usefulness, aligning with indicated requirements. Frame your resolution in terms of objectives, delineating primary goals and additional benefits your project will provide.

Write an Essay Proposal Outline

Crafting an outline for your persuasive paper is essential. This helps put your ideas in order and create a logical flow. When structuring your paper, begin with a catchy introduction that describes the problem. Outline your suggested resolution with strong evidence, facts, and illustrations. Finally, summarize the noteworthy aspects and emphasize the relevance of your proposal. This structured approach enhances coherence and persuasiveness.

Ø  For executive proposals, add organizational data and budget analysis, maintaining clear and direct language, devoid of unnecessary jargon.

Structure of a Proposal Essay

Generating a credible proposal-focused essay involves several main components, each serving a definite purpose to efficiently convey your key idea. Here's a full breakdown of how to write an essay proposal:

Introduction

• Captivating Intro

Capture the readers' attention with an eye-catching hook. Precisely state your essay’s thesis statement, conveying your message succinctly and convincingly.

•   Context and Background

Provide a solid background for your proposed idea, thus setting a stage for the topic matter and its validity.

• Research Relevance

State why your investigation is essential, drawing upon the background info provided.

• Problem Statement

Dive deeper into the presented issue, delineating its relevance and impact to deliver a captivating context for your written work.

• Proposal Statement

State your projected way out to the mentioned challenges. Emphasize its paybacks and mention potential shortcomings to showcase its viability.

•   Implementation Plan

Clarify in detail how you wish to put your words into effect, addressing practical considerations and potential obstacles.

• Expected Outcome

Talk about the positive effects that you expect from executing your solution proposal, conveying distinctly its probable impact.

• Evaluation of Feasibility

Consider the proposal’s practicability considering the essential resources and would-be objections.

• Resource Management and Timeline

Indicate the demanded resources and generate a timeline for implementation if applicable.

• Research Queries and Objectives

List the goals of your inquiry and say how will addressing the challenges impact your audience. Utilize credible sources and data to reinforce your arguments.

•   Study Design and Methodology

Explain your methodology for addressing the challenge, illustrating the rationale behind your selected approach, and predicting the anticipated outcomes.

• Key Points Summary 

Recap the main points from the intro, background, and topic relevance, along with the hypotheses/research questions sections.

• Importance and Potential Impact

Accentuate how your investigation can hypothetically contribute to addressing the mentioned issue and consider potential consequences if the proposal is not implemented.

• Call to Action and Close

Restate the proposal’s relevance, leaving the audience with a convincing call to action. Express gratitude for the committee's consideration and leave readers with a sense of anticipation for the proposed research.

•   Bibliography (Optional)

Include a literature list that references the materials used and displays the work’s contents to demonstrate the depth of the investigation. It is usually placed at the end of the whole text as a separate section.

Remember to refine your final draft for clarity and conciseness, testing if the paper proposal format is well-constructed. Consider seeking some feedback from others to enhance the presentation and proposal actuality. Additionally, ensure each paragraph flows smoothly and plausibly and supports your general argument. This ensures content clarity and cohesion throughout your text.

Academic Research Study Proposal Sample 2024

Here is a sample idea for an interesting proposal paper:

• The proposed research study will investigate the risks of sending messages while driving and explore measures to mitigate this hazardous behavior.
•  Texting when driving continues to be a widespread issue despite various awareness campaigns and legal restrictions.
• The study will focus on examining the mental and physical distractions caused by this activity. Also, the proposal will delve into the increased likelihood of mishaps and fatalities associated with such behavior.
• Utilizing a mixed-methods approach, the investigation will gather data through surveys, interviews, and driving simulations from a diverse sample of drivers across different age groups and regions.
•  Data analysis will include statistical analysis of accident rates, qualitative coding of interview responses, and thematic analysis of driving simulation outcomes.
•  The essay's findings aim to raise awareness among policymakers, law enforcement agencies, and the public about the grave dangers of texting when driving.
• Additionally, the investigation will propose recommendations for interventions such as stricter enforcement of existing regulations, educational programs targeting drivers of all ages, and the creation of technological solutions to prevent distraction-related cases.
• Ultimately, this study seeks to add to the lessening of crashes and fatalities caused by texting in a car and encourage safer driving habits in society.

Final Remarks

In composing a robust proposal essay, the journey from beginning to culmination is marked by strategic planning and scrupulous work. If you embrace a methodical approach, a captivating paper will emerge. Such vital details as understanding the audience, conducting in-depth research, describing the challenges, proposing possible way-outs, and structuring your arguments are vital elements of a successfully written work. Each phase of this process contributes to the clarity and persuasiveness of the text, ensuring resonance with readers. Using illustrative examples adds depth and relatability to the proposal.

Ultimately, the proposal paper showcases not only analytical prowess and solution-seeking acumen but also adept communication of intricate concepts. With unwavering dedication and meticulous focus on details, the proposal essay becomes a testament to effective persuasion and insightful discourse.

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Is your research plan inclusive 3 ways to check.

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Fake Dictionary, definition of the word research.

Despite the best of intentions, researchers tend to design plans that reflect their own identities and biases and can inadvertently center themselves in research design. Oftentimes, that might mean leaving out historically marginalized groups in research design. To serve all people inclusively, it's important to research all people’s needs inclusively.

In my interview with Dr. Varina Michaels, founder and director of Paisley Group and executive director of Women of Colour Australia , a leading not-for-profit that advocates for, supports and strengthens the lives and experiences of women of color, she recommended starting with these questions when talking with people who want to be more inclusive with their research:

• Who are the communities you are trying to serve?
• What are their needs?
• How do you know?

The last question is especially powerful. We tend to make assumptions about groups, especially ones that we are not part of, based on shortcut stereotypes or assumptions that have been passed down over time. Because most white people still live in highly segregated areas where they don't interact with as many people of color, they might default to false stereotypes and outdated assumptions due to their lack of direct lived experiences.

Google Chrome Deadline 72 Hours To Update Or Delete Your Browser

The fed quietly ‘admits’ gold is replacing the dollar as collapse ‘fear’ predicted to trigger a $15.7 trillion etf bitcoin price gold flip, apple loop iphone 16 pro details ios 18 s ai plans iphone 14 pro special offer, establish an inclusive research plan from the start.

Research planning starts before the research starts. Michaels recommends that before conducting research, you get feedback from participants on the initial research plan:

• Is this area important or should we spend our time somewhere else?
• Are the questions culturally appropriate and what could we be asking to be most accessible?
• Did we maximize the impact of your time and accurately represent you?

Settings also matter for inclusive research design. Michaels emphasizes, “If the same person takes the survey in different settings, you get different outcomes.” Different settings may signal different levels of safety or have different distractions, especially for historically marginalized people. It is critical to ensure anonymity in the research design and space for candid responses. There's no point to doing the research if people aren't going to be honest about their perceptions.

Center Women of Color in Inclusive Research Design

As the saying goes, “rising tides lift all boats.” When research focuses on the most marginalized people first, we create more opportunities for inclusion for the general population. People with intersectional identities, such as women of color, often bring a diverse lens, fresh perspectives and innovative thinking to the research because their experiences are unique.

As Michaels shares, “The most common response from women of color is to let the work speak and not my race, color, or gender.” When their voices are centered, others are uplifted.

“People cannot just take one cultural lens in a survey—that does not fully reflect their full human identity. That is why it is important to take their full human complexity into the research design,” Michaels comments. When we consider the dominant group's perspective in research design, we leave out a vast array of other innovative solutions and ideas that everyone can benefit from.

By addressing the needs of those who face the greatest barriers, researchers can create interventions and policies that lift everyone up. It's a reminder that true inclusivity requires a commitment to justice and equity for all.

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[Arxiv-2024] MotionLLM: Understanding Human Behaviors from Human Motions and Videos

IDEA-Research/MotionLLM

Folders and files, repository files navigation, motionllm: understanding human behaviors from human motions and videos.

Ling-Hao Chen 😎 1, 3 , Shunlin Lu 😎 2, 3 , Ailing Zeng 3 , Hao Zhang 3, 4 , Benyou Wang 2 , Ruimao Zhang 2 , Lei Zhang 🤗 3

😎 Co-first author. Listing order is random. 🤗 Corresponding author.

1 Tsinghua University, 2 School of Data Science, The Chinese University of Hong Kong, Shenzhen (CUHK-SZ), 3 International Digital Economy Academy (IDEA), 4 The Hong Kong University of Science and Technology

• [2024-05-31]: Paper, demo, and codes are released.

This study delves into the realm of multi-modality (i.e., video and motion modalities) human behavior understanding by leveraging the powerful capabilities of Large Language Models (LLMs). Diverging from recent LLMs designed for video-only or motion-only understanding, we argue that understanding human behavior necessitates joint modeling from both videos and motion sequences (e.g., SMPL sequences) to capture nuanced body part dynamics and semantics effectively. In light of this, we present MotionLLM, a straightforward yet effective framework for human motion understanding, captioning, and reasoning. Specifically, MotionLLM adopts a unified video-motion training strategy that leverages the complementary advantages of existing coarse video-text data and fine-grained motion-text data to glean rich spatial-temporal insights. Furthermore, we collect a substantial dataset, MoVid, comprising diverse videos, motions, captions, and instructions. Additionally, we propose the MoVid-Bench, with carefully manual annotations, for better evaluation of human behavior understanding on video and motion. Extensive experiments show the superiority of MotionLLM in the caption, spatial-temporal comprehension, and reasoning ability.

🤩 Highlight Applications

🔧 Technical Solution

We provide a simple online demo for you to try MotionLLM. Below is the guidance to deploy the demo on your local machine.

Step 1: Set up the environment

Step 2: download the pre-trained model.

Please follow the instruction of Lit-GPT to prepare the LLM model (vicuna 1.5-7B). These files will be:

If you have any confusion, we will update a more detailed instruction in couple of days.

We now release one versions of the MotionLLM checkpoints, namely v1.0 (download here ). Opening for the suggestions to Ling-Hao Chen and Shunlin Lu.

Keep them in a folder named and remember the path ( LINEAR_V and LORA ).

2.3 Run the demo

If you have some error in downloading the huggingface model, you can try the following command with the mirror of huggingface.

The GRADIO_TEMP_DIR=temp defines a temporary directory as ./temp for the Gradio to store the data. You can change it to your own path.

After thiess, you can open the browser and visit the local host via the command line output reminder. If it is not loaded, please change the IP address as your local IP address (via command ifconfig ).

• Release the video demo of MotionLLM.
• Release the motion demo of MotionLLM.
• Release the MoVid dataset and MoVid-Bench.
• Release the tuning instruction of MotionLLM.

💋 Acknowledgement

The author team would like to deliver many thanks to many people. Qing Jiang helps a lot with some parts of manual annotation on MoVid Bench and resolves some ethics issues of MotionLLM. Jingcheng Hu provided some technical suggestions for efficient training. Shilong Liu and Bojia Zi provided some significant technical suggestions on LLM tuning. Jiale Liu, Wenhao Yang, and Chenlai Qian provided some significant suggestions for us to polish the paper. Hongyang Li helped us a lot with the figure design. Yiren Pang provided GPT API keys when our keys were temporarily out of quota. The code is on the basis of Video-LLaVA , HumanTOMATO , MotionGPT . lit-gpt , and HumanML3D . Thanks to all contributors!

This code is distributed under an IDEA LICENSE . Note that our code depends on other libraries and datasets which each have their own respective licenses that must also be followed.

If you have any question, please contact at: thu [DOT] lhchen [AT] gmail [DOT] com AND shunlinlu0803 [AT] gmail [DOT] com.

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• Copy URL https://www.pbs.org/newshour/world/who-is-claudia-sheinbaum-heres-what-to-know-about-mexicos-next-president

Who is Claudia Sheinbaum? Here’s what to know about Mexico’s next president

MEXICO CITY (AP) — Claudia Sheinbaum, who will be Mexico’s first woman leader in the nation’s more than 200 years of independence, captured the presidency by promising continuity.

The 61-year-old former Mexico City mayor and lifelong leftist ran a disciplined campaign capitalizing on her predecessor’s popularity before emerging victorious in Sunday’s vote, according to an official quick count. But with her victory now in hand, Mexicans will look to see how Sheinbaum, a very different personality from mentor and current President Andrés Manuel López Obrador, will assert herself.

READ MORE: Mexico picks Claudia Sheinbaum for president, first woman to hold the job

While she hewed close to López Obrador politically and shares many of his ideas about the government’s role in addressing inequality, she is viewed as less combative and more data-driven.

Sheinbaum’s background is in science. She has a Ph.D. in energy engineering. Her brother is a physicist. In a 2023 interview with The Associated Press, Sheinbaum said, “I believe in science.”

Observers say that grounding showed itself in Sheinbaum’s actions as mayor during the COVID-19 pandemic, when her city of some 9 million people took a different approach from what López Obrador espoused at the national level.

READ MORE: These are the pressing gender-related issues facing Mexico’s next president

While the federal government was downplaying the importance of coronavirus testing, Mexico City expanded its testing regimen. Sheinbaum set limits on businesses’ hours and capacity when the virus was rapidly spreading, even though López Obrador wanted to avoid any measures that would hurt the economy. And she publicly wore protective masks and urged social distancing while the president was still lunging into crowds.

Mexico’s persistently high levels of violence will be one of her most immediate challenges after she takes office Oct. 1. On the campaign trail she said little more than that she would expand the quasi-military National Guard created by López Obrador and continue his strategy of targeting social ills that make so many young Mexicans easy targets for cartel recruitment.

“Let it be clear, it doesn’t mean an iron fist, wars or authoritarianism,” Sheinbaum said of her approach to tackling criminal gangs, during her final campaign event. “We will promote a strategy of addressing the causes and continue moving toward zero impunity.”

Sheinbaum has praised López Obrador profusely and said little that the president hasn’t said himself. She blamed neoliberal economic policies for condemning millions to poverty, promised a strong welfare state and praised Mexico’s large state-owned oil company, Pemex, while also promising to emphasize clean energy.

READ MORE: What to know about Mexico’s historic elections on Sunday that will likely put a woman in power

“For me, being from the left has to do with that, with guaranteeing the minimum rights to all residents,” Sheinbaum told the AP last year.

In contrast to López Obrador, who seemed to relish his highly public battles with other branches of the government and also the news media, Sheinbaum is expected by many observers to be less combative or at least more selective in picking her fights.

“It appears she’s going to go in a different direction,” said Ivonne Acuña Murillo, a political scientist at Iberoamerican University. “I don’t know how much.”

Sheinbaum will also be the first person from a Jewish background to lead the overwhelmingly Catholic country.

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[Subscription Required]  If your local campus anti-Israel protester is feeling dejected after the end of an encampment, tell her to buck up. Graduation gifts have arrived in the mail from two very grateful Uncle Als—al Qaeda and Ayatollah Ali Khamenei.

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Credit report errors are more common than you think. Here's how to dispute one

Nearly half of all credit reports may contain errors, some of them costly to your credit score, according to a new watchdog report.

Two consumer groups, Consumer Reports and WorkMoney, invited more than 4,300 volunteers to check their credit reports for accuracy, as a sort of performance review of the three major credit agencies: Equifax , Experian and TransUnion .

Here’s what the y found :

◾ One-quarter of the consumers were unable to access their credit reports, which are supposed to be available to all.

◾ Among those who read their reports, 44% found errors.

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◾ Of the errors, 27% were potentially damaging to the consumer’s credit.

The findings, released in late April, suggest that American consumers would be wise to read their reports. The credit agencies allow free access to them on a site called AnnualCreditReport.com .

“People don’t volunteer to be a part of this system, and a lot of decisions are made about you based on what’s in your account,” said Lisa Gill , an investigative reporter at Consumer Reports.

Related story: What information is on your credit report? Here's what I found when I read my own.

Credit scores are part of 'being able to afford life'

Credit reports factor into a dizzying array of consumer transactions. If you want to rent an apartment, buy a house, take a new job, or negotiate a better rate on a car loan, insurance premium, or cellphone contract, your credit score may determine your success. People with weak credit may get turned down, or penalized with higher rates and more stringent terms.

“It’s such an important part of people being able to afford life,” said Carrie Joy Grimes , CEO of WorkMoney, a nonprofit that helps consumers with their finances. “This is not a partisan issue. This is everyone in America.”

Consumer advocates acknowledge that it has probably never been easier to access your credit score, a metric of creditworthiness that ranges from 300 to 850, and the report upon which the score is based.

Long ago, consumers weren’t permitted to read their credit reports. Americans eventually gained the right to see their credit dossier, typically for a $15 fee. A 2003 law guaranteed access to free credit reports once a year . Today, consumers may see their reports once a week.

Industry leaders say they want consumers to read their reports, and to help credit agencies spot and fix potential errors.

“The consumer reporting industry shares the same goal as consumers, advocates, and regulators when it comes to credit reports: they should be accurate and complete,” the Consumer Data Industry Association, a group that represents the credit bureaus, said about the new report in a statement to USA TODAY.

“The nationwide credit reporting agencies are working diligently across the financial ecosystem to achieve that goal,” the statement said. “The entire business model of these companies is predicated on accuracy: when the information is accurate, everyone wins.”

Credit agency complaints nearly doubled in a year

Consumer watchdogs say the credit bureaus should do a better job.

Credit agencies are the most common subject of complaints filed to the federal Consumer Financial Protection Bureau, according to research by the U.S. Public Interest Research Group (PIRG). Complaints about credit reporting nearly doubled between 2021 and 2022, the nonprofit found.

Most complaints concerned allegations of improper use of credit reports, errors, or problems with getting an agency to correct mistakes, said Teresa Murray , consumer watchdog director at PIRG.

The credit bureaus “have not served consumers well for decades,” Murray said. “It’s gotten better, but it’s still a huge problem.”

Complaints are increasing, in part, because consumers have better access to their credit reports and are more keenly aware of them, she said. The massive Equifax data breach in 2017 raised public awareness of credit reports and their vulnerability.

In the Consumer Reports investigation, 872 consumers said they found errors in their credit reports about financial information: accounts they didn’t recognize, payments wrongly reported as late or missed, and debt-collection efforts of which they were not aware, among other issues.

'I had no idea this could happen'

One consumer volunteer in the watchdog study was Tammy Chambers, 55, of Tacoma, Washington.

When Chambers reviewed her Experian credit report, earlier this year, she found four delinquent loans totaling more than $2,000. None of them were hers.

Chambers said an identity thief took out the consumer installment loans in her name more than a year ago. When the loans went delinquent, her credit score sank from nearly 800 to “maybe 520,” she said. She spent months working with the loan company and the credit agency, trying to get the debts removed, to no avail.

“I did my due diligence,” she said. “I had no idea this could happen.”

Chambers finally got the debts expunged this spring. According to Consumer Reports, most of the fault lay not with Experian but with the company that issued the loans, which kept reporting them on Chambers’ account long after she had filed disputes.

Hundreds of other consumers in the watchdog study found mistaken personal information, including incorrect addresses and wrong or misspelled names.

Errors on credit reports can unfairly damage your credit score

Financial errors involving delinquent accounts are worrisome, consumer advocates say, because they can unfairly damage your credit score.

“Anything that’s reporting debt and collections that’s not yours, that is going to pull that score down 30, 40, 50 points, sometimes more,” Gill said.

An unfamiliar name or address or account on a credit report, meanwhile, “can be a signal of identity theft,” Gill said.

Roughly one-quarter of consumers in the watchdog study were unable to access their credit reports in the first place.

Many couldn’t get past the screening questions, which asked them to identify a familiar car loan or home mortgage on a multiple-choice list. Others got past those questions only to hit an error message, saying their credit reports were unavailable.

If you're concerned about your credit report, consumer advocates offer these tips:

Freeze your credit

Freezing your credit means no one can open a new account in your name. It’s free, and a great way to combat identity theft, Murray said.

PIRG offers a step-by-step guide .

One downside: If you want to open a new account, you will have to temporarily unfreeze your credit.

Read your credit reports

Consumers should review their credit reports at least once a year, looking for errors and anything unfamiliar, Murray said.

“If you want to overachieve, stagger them,” she said: Read a report from a different agency every four months.

Report any errors

If you find an error on a credit report, especially something that could affect your credit score or signal possible identity theft, you should report it.

“The bureaus are responsible for providing accurate information on the report,” Gill said.

You can report errors at any of the three credit bureau websites. If the error is on a specific account, consider contacting that company directly.

If necessary, file a complaint

If you find an error in a credit report, give the credit bureau time to fix it. If that doesn’t work, Murray said, file a complaint with the CFPB.

Complaints matter, Murray said: The more of them the agency receives, the more likely policymakers will step in to make it easier for future consumers to review and correct their credit reports.

Daniel de Visé covers personal finance for USA TODAY.

Microsoft Research Blog

Introducing aurora: the first large-scale foundation model of the atmosphere.

Published June 3, 2024

By Wessel Bruinsma , Senior Researcher Megan Stanley , Senior Researcher Ana Lucic , Researcher Richard Turner , Visiting Researcher Paris Perdikaris , Principal Research Manager

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When Storm Ciarán battered northwestern Europe in November 2023, it left a trail of destruction. The low-pressure system associated with Storm Ciarán set new records for England, marking it as an exceptionally rare meteorological event. The storm’s intensity caught many off guard, exposing the limitations of current weather-prediction models and highlighting the need for more accurate forecasting in the face of climate change. As communities grappled with the aftermath, the urgent question arose: How can we better anticipate and prepare for such extreme weather events? 

A recent study by Charlton-Perez et al. (2024) underscored the challenges faced by even the most advanced AI weather-prediction models in capturing the rapid intensification and peak wind speeds of Storm Ciarán. To help address those challenges, a team of Microsoft researchers developed Aurora, a cutting-edge AI foundation model that can extract valuable insights from vast amounts of atmospheric data . Aurora presents a new approach to weather forecasting that could transform our ability to predict and mitigate the impacts of extreme events—including being able to anticipate the dramatic escalation of an event like Storm Ciarán.  

A flexible 3D foundation model of the atmosphere

Aurora’s effectiveness lies in its training on more than a million hours of diverse weather and climate simulations, which enables it to develop a comprehensive understanding of atmospheric dynamics. This allows the model to excel at a wide range of prediction tasks, even in data-sparse regions or extreme weather scenarios. By operating at a high spatial resolution of 0.1° (roughly 11 km at the equator), Aurora captures intricate details of atmospheric processes, providing more accurate operational forecasts than ever before—and at a fraction of the computational cost of traditional numerical weather-prediction systems. We estimate that the computational speed-up that Aurora can bring over the state-of-the-art numerical forecasting system Integrated Forecasting System (IFS) is ~5,000x. 

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Beyond its impressive accuracy and efficiency, Aurora stands out for its versatility. The model can forecast a broad range of atmospheric variables, from temperature and wind speed to air-pollution levels and concentrations of greenhouse gases. Aurora’s architecture is designed to handle heterogeneous gold standard inputs and generate predictions at different resolutions and levels of fidelity. The model consists of a flexible 3D Swin Transformer with Perceiver-based encoders and decoders, enabling it to process and predict a range of atmospheric variables across space and pressure levels. By pretraining on a vast corpus of diverse data and fine-tuning on specific tasks, Aurora learns to capture intricate patterns and structures in the atmosphere, allowing it to excel even with limited training data when it is being fine-tuned for a specific task. 

Fast prediction of atmospheric chemistry and air pollution

A prime example of Aurora’s versatility is its ability to forecast air-pollution levels using data from the Copernicus Atmosphere Monitoring Service (CAMS), a notoriously difficult task due to the complex interplay of atmospheric chemistry, weather patterns, and human activities, as well as the highly heterogeneous nature of CAMS data. By leveraging its flexible encoder-decoder architecture and attention mechanisms, Aurora effectively processes and learns from this challenging data, capturing the unique characteristics of air pollutants and their relationships with meteorological variables. This enables Aurora to produce accurate five-day global air-pollution forecasts at 0.4° spatial resolution, outperforming state-of-the-art atmospheric chemistry simulations on 74% of all targets, demonstrating its remarkable adaptability and potential to tackle a wide range of environmental prediction problems, even in data-sparse or highly complex scenarios. 

Data diversity and model scaling improve atmospheric forecasting

One of the key findings of this study is that pretraining on diverse datasets significantly improves Aurora’s performance compared to training on a single dataset. By incorporating data from climate simulations, reanalysis products, and operational forecasts, Aurora learns a more robust and generalizable representation of atmospheric dynamics. It is thanks to its scale and diverse pretraining data corpus that Aurora is able outperform state-of-the-art numerical weather-prediction models and specialized deep-learning approaches across a wide range of tasks and resolutions. 

A direct consequence of Aurora’s scale, both in terms of architecture design and training data corpus, as well as its pretraining and fine-tuning protocols, is its superior performance over the best specialized deep learning models. As an additional validation of the benefits of fine-tuning a large model pretrained on many datasets, we compare Aurora against GraphCast — pretrained only on ERA5 and currently considered the most skillful AI model at 0.25-degree resolution and lead times up to five days. Additionally, we include IFS HRES in this comparison, the gold standard in numerical weather prediction. We show that Aurora outperforms both when measured against analysis, weather station observations, and extreme values. 

A paradigm shift in Earth system modeling 

The implications of Aurora extend far beyond atmospheric forecasting. By demonstrating the power of foundation models in the Earth sciences, this research paves the way for the development of comprehensive models that encompass the entire Earth system. The ability of foundation models to excel at downstream tasks with scarce data could democratize access to accurate weather and climate information in data-sparse regions, such as the developing world and polar regions. This could have far-reaching impacts on sectors like agriculture, transportation, energy harvesting, and disaster preparedness, enabling communities to better adapt to the challenges posed by climate change. 

As the field of AI-based environmental prediction evolves, we hope Aurora will serve as a blueprint for future research and development. The study highlights the importance of diverse pretraining data, model scaling, and flexible architectures in building powerful foundation models for the Earth sciences. With continued advancements in computational resources and data availability, we can envision a future where foundation models like Aurora become the backbone of operational weather and climate prediction systems, providing timely, accurate, and actionable insights to decision-makers and the public worldwide. 

Acknowledgements

We are grateful for the contributions of Cristian Bodnar, a core contributor to this project.

Related publications

Aurora: a foundation model of the atmosphere, meet the authors.

Wessel Bruinsma

Senior Researcher

Megan Stanley

Richard Turner

Visiting Researcher

Paris Perdikaris

Principal Research Manager

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