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Whether you are writing a research paper on a short story for a high school or college level class, the process of researching the story is essentially the same, though an instructor in a college course will likely expect more. Read the short story thoroughly, making notes when necessary, before you begin researching it. Creating your research paper allows you to explore more about the short story and present that information to your reader.
Read any handout or notes that you have taken on the specific requirements for the research paper you will be writing. Take special note of the word/page count required as well as the type of works cited page required, both in terms of format as well as how many sources you must have. You should also note if your instructor asks for a particular number of primary sources in addition to secondary sources. Determine how many, if any, of your sources can be from websites.
Find a quiet place to read, and reread, the short story you have been assigned. Take detailed notes as you read.
Look for reviews of the story you will be writing about. You should be able to locate several different reviews on the story in your campus or local public library. While you can find reviews of many short stories online, make certain that any online resource you use to assist you in writing your research paper is a credible source. Generally, academic sources are credible. Reference libraries that provide access to sources like Proquest and MUSE are useful when conducting research, but you may need a university ID number to access these types of online resources.
Study the reviews carefully. Often times you will find annotations below the actual text where an authority will offer definitions as well as insight on what a particular line or passage means. Generally, a scholar on the author and work itself will also explain the text in a broader context, drawing conclusions as to where the author drew inspiration from others' works, or in developing a particular character or the overall theme of the story itself.
Write your paper using the references you selected to support the statements you want to make in your research paper. Also use your own notes to remind you of observations you made when reading the story.
Daniel Ketchum holds a Bachelor of Arts from East Carolina University where he also attended graduate school. Later, he taught history and humanities. Ketchum is experienced in 2D and 3D graphic programs, including Photoshop, Poser and Hexagon and primarily writes on these topics. He is a contributor to sites like Renderosity and Animotions.
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Skillful storytelling helps listeners understand the essence of complex concepts and ideas in meaningful and often personal ways. For this reason, storytelling is being embraced by scientists who not only want to connect more authentically with their audiences, but also want to understand how the brain processes this powerful form of communication. Here we present part of a conversation between a group of scientists actively engaged with the practice and/or the science of storytelling. We highlight the brain networks involved in the telling and hearing of stories and show how storytelling is being used well beyond the realm of public communication to add a deeper dimension to communication with our students and colleagues, as well as helping to make our profession more inclusive.
It is now more urgent than ever that scientists take an active role in engaging with and educating the public about what they do as scientists, why they do it, and why it matters. It is in this context that many scientists hear about the craft of storytelling. The personal narrative detail that is often at the heart of a good story is one of the most powerful forms of communication that exists. Indeed, the craft of storytelling has enjoyed a renaissance of sorts with storytelling-based approaches being used in everything from promoting new startups, to inspiring creativity in the workplace, to business leadership strategy. This is because stories, and in particular personal stories, have the ability to illuminate fault lines, highlight oddities, and paint a picture of the past, present, and future that is both compelling and easily understandable.
The science community has also started to embrace the power of storytelling, as illustrated by the popularity of science storytelling organizations, such as The Story Collider, science storytelling socials at the Annual Society for Neuroscience (SFN) meeting, and SFN minisymposia devoted to the topic of storytelling. What follows here is part of a larger conversation among some of the members of the 2018 SFN minisymposium entitled “Telling stories of science.” In anticipation of that minisymposium event, we present part of an interview-style conversation led by the chair of that session, Wendy Suzuki, and several of the symposium participants. The theme of the conversation is the science and power of storytelling. We start with what we know about the pattern of brain activation seen when we hear, view, or tell stories, based on the work of Prof. Uri Hasson. We then address the variety of ways that bench scientists (Prof. Rachel Yehuda) and science professionals (Dr. Mónica I. Feliú-Mójer and Dr. Jean Mary Zarate) have used storytelling in their professional lives. It is clear that storytelling is not only the focus of a growing body of cognitive neuroscientific exploration, but is already being used in a myriad of ways not only to educate the general public about the value of science, but to effectively convey essential information to our colleagues and students and, more broadly, to help improve the way science is done.
WS: Prof. Uri Hasson, why did you start looking at the brain activation associated with stories?
UH: I am interested in the neural mechanism underlying human communication. On a daily basis, I am able to communicate my thoughts, feeling, and intentions, using words, to other brains while at the same time being able to comprehend other brains' own spoken words. It occurred to us that stories are one of the most effective ways to communicate, so we started to look at what is going on in the listeners' brains as they listen to real-life spoken stories, and how their brains' responses relate to the responses observed in the storyteller's brain as she tells the story.
WS: What did you find?
UH: To my great surprise, we found that the neural activity in many cortical and subcortical areas was similar across all listeners, ranging from early auditory areas, to linguistic areas, to high-order areas in the parietal and frontal cortices. As expected, the intersubject neural similarity in early auditory areas was coupled to the acoustic properties of the spoken words. In contrast, the intersubject neural similarity in high-order areas, which mainly overlap with the default mode network (DMN), was decoupled from the acoustic features and was coupled to the story's narrative.
Further studies showed, for example, that the neural responses in the DMN were similar across Russian listeners who listened to a Russian story and English listeners who listened to a translated version of the same story, demonstrating that the same narrative can evoke similar responses, regardless of the linguistic system used to convey it ( Honey et al., 2012 ).
WS: Given that the same story can be understood in many different ways, how can all listeners exhibit similar brain responses when listening to a story?
UH: Excellent point! We hypothesized that the level of similarity in high-order areas across subjects is mediated by the level of shared understanding. To test this idea, we manipulated the level of shared understanding to the exact same narrative. Here we presented an ambiguous story to subjects. Then we ruined the ambiguity of the story, by telling half of the subjects one version of the story and the other half a different version ( Yeshurun et al., 2017 ). We then measured the similarity in brain responses in the same high-order brain areas across subjects and found that the responses were more similar between subjects who had similar interpretation of the narrative relative to subjects with the opposing interpretation. Indeed, we could classify, with about 85% confidence, the subjects' interpretation based on the similarity of their brain responses to other subjects who were given the same version.
WS: So far, you've only told us about the listeners' brains. What is happening with the speaker's brain?
UH: When we compared the responses in the speaker's brain as she told a story to the responses in the listeners' brain as they listened to it, we found that the responses in the listeners' brain are coupled (correlated with a lag) to the responses in the speaker's brain ( Stephens et al., 2010 ). Furthermore, the stronger the correlation (neural alignment) between the speaker's brain and listener's brain, the better the communication, as assessed with postscan comprehension tests.
WS: Fascinating! What do you think are the implications of these findings?
UH: We gather our ideas and belief from other brains we are connected to—show me your friends and I will tell you who you are—and from the social media we consume. Sadly, in this current time, there are forces that try to set us apart. We are living in a polarized world, in which people in our society are losing its common ground and drifting apart. Our task, as scientists and as storytellers, is to see how we can re-create and rebuild our common uniting story, while at the same time, preserving our personal stories and allowing each and every one of our unique voices to be heard.
We now turn to insights from some of our seasoned science storytellers. It seems that learning and sharing your science stories have affected and inspired all of them in both similar and unique ways. We often think about storytelling in the context of public speaking, but Prof. Rachel Yehuda explicitly uses it when giving regular science talks.
WS: How has storytelling helped you communicate with fellow scientists?
RY: I have always used storytelling to communicate science to my science colleagues because the backstory behind how a scientific question gets asked and answered is as interesting as the data generated. Engaging listeners in the scientific journey creates a stronger, more meaningful transfer of knowledge because it elicits participation and creates an intellectual investment and emotional bond between the speaker and the audience.
Details about the scientists' personal life can also be relevant to the scientific journey and questions being asked. Autobiographical and personal reflections may seem like the opposite of objective scientific data, but since I have started including more of these in presentations, I have been surprised by the synergy between anecdote and fact. Their combination appears to increase the salience of information to the public who are the ultimate consumers, and also funders through their tax dollars, of scientific information.
WS: Dr. Jean Zarate, how has science storytelling helped in your role as an editor?
JZ: I found that science storytelling changed the way I interact with my science colleagues in my role as editor at Nature Neuroscience . For my editorial duties, I tend to focus only on the science and determine whether the overarching messages in the paper are impactful and properly supported by the data and the interpretations. But by actually preparing and presenting at a science storytelling event myself, I was reminded about the human side to the science I read every day: that there are at least one or two personal stories motivating scientists' research interests and their career trajectories. And in sharing a story about my own scientific path, I slowly realized that revealing some details about my personal science trajectory, including sharing with the scientists my science passions, allowed the investigators and trainees to see a more human side to someone who was often regarded simply as “the editor.” I think remembering that these more personal stories exist, on both sides, has influenced the way I interact with researchers when discussing their work and when helping them to communicate their findings and their implications more clearly to our readers.
WS: Dr. Zarate, has storytelling also affected the way you help your authors shape their introductions? If so, how?
JZ: Absolutely. As I prepared my story, I learned how to engage the audience quickly and tweak the text to avoid alienating people with statements that I thought were harmless. For scientific papers, the introduction is a perfect opener to engage the audience and get them excited to read your research or your review paper. If it takes nearly two pages to reach the research question or thesis statement or if the introduction is filled with technical jargon or casts certain work in an unfavorable light, then you will lose your audience quickly. So, I work with authors to present their ideas in a clear, succinct manner that communicates their ideas in a balanced and appropriate tone, so that the readers will keep reading.
WS: Dr. Mónica Feliú-Mójer, can you share your unique perspective on the power of storytelling and how you have used it in your career?
MF-M: As a kid, I devoured storybooks. When I wasn't reading, or making up my own stories, I was out and about in my rural home, catching lizards and finding rocks. Although I have always loved science and storytelling, I didn't connect the two until I was about to start my PhD.
After completing my undergraduate degree, I moved from Puerto Rico to Boston. Far from home, I longed for an opportunity to stay connected and give back to my community. I stumbled upon that opportunity in science storytelling, when I volunteered to write and edit popular science stories for Puerto Rico's main newspaper. During graduate school, telling the stories of Puerto Rican science and scientists empowered me to bring my whole self into research, and unapologetically connect my culture and science. Now, as a professional science communicator, I use storytelling as a tool for inclusion and social justice.
Originally, I thought that by leaving lab research to be a communicator, I would miss out on one of my favorite things about science: using my creativity to help me solve problems. But surprisingly, science storytelling has unleashed my creativity in unexpected ways. As a storyteller, I get to apply the process of discovery to find ways to make science compelling, or work with an animator to translate a concept into visuals.
Today, I combine storytelling with my scientific and cultural backgrounds to make science more accessible and inclusive to communities that are underrepresented in, and excluded from, science. For example, I coproduce a series called “Background to Breakthrough” that is flipping the narrative about the value of diversity in science. Instead of telling the typical underdog story, the series looks at how the identities, culture, and background of underrepresented scientists fuel their ingenuity and approaches to problem solving. I also get to share my expertise by training young underrepresented scientists in science communication. Science storytelling has allowed me to meaningfully connect with myself and my communities. Telling science stories changed the course of my career, and I am a better scientist for it.
WS: Why do you think that personal element is so powerful especially when we as scientists speak to the public?
RY: Personal stories are not only humanizing, but if the scientist takes the time to convey potentially technical information in a more accessible manner, it is easier for the public to understand how the information is directly relevant to them. For example, my work is on the long-lasting impact of trauma exposure on oneself and possibly even one's descendants and involves neurobiological and molecular mechanisms. I have found that telling the story of how this work developed and presenting the work simply provides a greater reach and resonance than if the observations were presented as they are in scientific journals.
Storytelling is both a useful and fascinating topic to scientists from a multitude of perspectives. From a cognitive neuroscience perspective, it is of great interest to understand how this ancient form of communication engages and even entrains our brains in reproducible ways. From a practical perspective, it is of great interest to understand how storytelling can be used to help us improve both how we engage in science and expand who engages in science. There is much more we have to learn about how we as scientists can incorporate storytelling into our professional lives as we strive to make science more understandable, more inclusive, and ultimately, more beneficial to the world.
The authors declare no competing financial interests.
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Many authors start with the figures when writing a scientific paper, but it is easier to tell a good story if you start with the Introduction and the Results, and leave the figures to later.
Think back to when you were a little girl or boy, going on a long drive or getting ready for bed. From time to time, you probably asked a parent to tell you a story or read you a storybook. I know I did and so did my children. Well, we’re big boys and girls now, but we still love stories. Scientists can take advantage of this basic human desire by incorporating elements of storytelling when they prepare articles for submission to scientific journals: articles that tell a story will be better understood by and have a greater impact on readers.
Of course, scientific story telling is not easy. Aside from the fact that few scientists are trained in writing, there are two major problems. First, we have to tell the truth, a restriction story-tellers do not face. Second, we have to deal with restrictive formats, such as length limits, figure limits, and mandated order of sections. Nonetheless, it can be done and done well.
I think that the key is to prepare your paper in the sequence that a storyteller would. The three most important parts of a paper are the figures, the Results and the Introduction, probably in that order. It is therefore no surprise that authors often begin by preparing the figures, then move on to Results, and save the Introduction for near the end. In this article I will explain why I think it is better to reverse this sequence.
Starting with the text is not as strange as it might seem. Take operas for example: even though they are all about the music, the libretto is usually written before the score. That said, I do understand why it has become common practice to prepare figures before writing the text. It is easier and more fun to make figures than to think or write. After a day of cropping micrographs, adjusting font sizes, and arranging the panels in perfect rectangles, you feel like you’ve gotten something done. But all this is a displacement activity (definition: an unnecessary activity that you do because you are trying to delay doing a more difficult or unpleasant activity).
This is not to say that you should ignore your data at this stage: you absolutely need to know what you have and don’t have before you write. A simple expedient is to collect rough versions of panels with minimal editing on a digital bulletin board – PowerPoint slides work well. Then write the text and revise it a few times before arranging and polishing the figures. In my lab, and despite my pleas, people often bring me excellent figures along with fragments of text or no text at all. As we go through draft after draft, panels are often added, removed or altered – and always rearranged. It makes me feel bad to think about the wasted time and effort.
Don’t think I’m trying to overturn long-held dogma. The 'figure first' strategy is a product of Photoshop and Illustrator. Back in the day, when micrographs were generated with an enlarger and graphs with Letraset, it was necessary to have a definitive plan before starting to print and draw. I have no nostalgia for those cumbersome methods – but they did help make sure that thought preceded action.
So if not with the figures, where should you start? With the plot. You likely began your study with a question in mind. What does gene w do? How does cell x develop? Can method y help us understand disease z? At some point, you feel that you have gained enough insight to begin writing a paper – but more often than not, the data don’t provide an answer to the precise question you began with. If you try to fit the answer to the question, you risk ending up with a compendium of results that is less cohesive than it could be. Instead, start with the answer, figure out what the question should have been, and build on that. This seems counterintuitive, but it works. It is the first step in crafting a story.
The key is to prepare your paper in the sequence that a storyteller would
Once you have the question and answer in mind, write a rough draft of the Introduction, treating it as what is now called an elevator-pitch – a succinct statement meant to convince the listener/reader of your product’s value. What was the gap in knowledge you wanted to fill? What is the question to which you will provide an answer? Why is it important? What was your strategy? What did you find out? What conclusions did you draw? Why did they matter?
Using the introduction as a guide, move on to the results. Think hard about the best order in which to present them, feeling free to take advantage of what is, to my knowledge, the only fiction that is fully allowable in a scientific paper: you don’t need to present experiments in the sequence in which they were done or explain why they were actually done. Put another way, a scientific paper is not an autobiography; the story you tell should be about the science, not about you. The order of presentation can be, and often should be, quite different from the order of execution.
To organize the results, begin with a detailed outline in which you take account of the data you have. Your PowerPoint repository will be valuable here. As the outline takes shape, you will likely find some holes that you need to fill. If you’re lucky, you’ll also find some datasets that seemed worrisomely incomplete but don’t matter now, because they are not essential to the story you are going to tell. Revise the outline to take account of these realizations.
Next, write a draft of the Results section. Then read it over and reconsider whether you’ve made it easy for the reader to understand how the results lead to the conclusions you want to draw. If they don’t, you can rearrange sections, consider changing the plot, or even come to grips with the possibility that you’re not as close to finished as you had hoped to be.
In presenting your results, you have to tell the truth and nothing but the truth. What you don’t have to do is tell the whole truth. In other words, you can select the results you present, as well as the order in which you present them, to shape your narrative. There is one crucial caveat: if you have results that call your conclusions into question, you need to present them, and explain why your (possibly modified) conclusions are still justified. My point is that you don’t need to describe everything you did. Think about whether each group of results makes the story more compelling or serves as a distraction. If it is the latter, be ruthless in omitting it. On occasion, you may have spent so much time on a set of experiments that you just can’t bear to cut it out completely. Try to resist temptation, but if you can’t, make it short.
Even when describing the most relevant results, work on being concise. This is difficult, as noted long ago by Blaise Pascal in an aphorism generally credited to Mark Twain: “I would have written a shorter letter but I didn’t have the time.” Just as it takes effort to omit distracting results, it takes effort to edit out needless detail. A few weeks ago, I tried to read an article in my field that seemed like a lightly edited lab notebook. I bet it was full of useful information, but I’ll never know. There was no story there so I quickly put it aside.
Next comes the Discussion, which provides an opportunity for you to highlight what you want the reader to remember – the key results and principal conclusions. This is conventionally done by summarizing the results in a paragraph, following with sections devoted to major points, and finishing with a brief concluding paragraph. This format works well if you keep the story in mind as you write.
Think about whether each group of results makes the story more compelling or serves as a distraction. If it is the latter, be ruthless in omitting it.
To that end, remember that just as you don’t have to include marginally relevant data in the Results section, you don’t have to rehash all of the results in the Discussion. Instead, plan a small number of subsections (between two and five) within the Discussion, in each of which you state a conclusion, summarize the results that support it, and relate it to previous work in the field. By citing key papers, you acknowledge your debt to your predecessors and avoid being accused of claiming more novelty than is justifiable. This is not the place, though, for a literature review. For example, if you have implicated a gene in a process, you need to be clear on whether this has been done before – but you don’t have to talk about unrelated roles of the gene or its mechanisms of action in other contexts.
These sections can also serve other purposes. You should consider uncertainties and note critical questions that remain unanswered. Acknowledging weaknesses in your argument is not only honest but can be helpful: it is harder for a reviewer to be harshly critical if you have already been self-critical. You can also point out the broader implications of your work and speculate on what the future might hold. Be sparing, though, in claiming that experiments to test your speculations are in progress, as the reviewer or editor might be temped to ask you to resubmit once you’ve done these experiments. And as elsewhere, keep it concise and make sure it furthers the plot.
At this point you have a full draft of the main sections. Once you are fairly satisfied, you’re ready to turn it into a complete manuscript by polishing the figures, writing Figure Legends, Methods and Abstract, and completing the reference list.
Finally, it is time to get feedback from your colleagues. In my lab, we have a practice called 'paper bashing' in which we devote a long lab meeting to going over a paper line by line. Here’s the main lesson I have learned from this painful but invaluable process: almost every time a lab member or other reader points out a problem with a word, sentence, section or conclusion, they are right, and something needs to be done. On the other hand, the particular improvements they suggest are often not the best ones. You have thought about the work more deeply than they have, and are more familiar with the results and the literature, so you are probably better than they are at coming up with useful solutions. In short, use the criticism to highlight points that need attention, but don’t be afraid to use your own judgment in deciding what to do.
It is, after all, your story to tell.
Joshua R Sanes is in the Center for Brain Science and the Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, United States
Competing interests.
© 2019, Sanes
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Identifying a research problem to investigate requires a preliminary search for and critical review of the literature in order to gain an understanding about how scholars have examined a topic. Scholars rarely structure research studies in a way that can be followed like a story; they are complex and detail-intensive and often written in a descriptive and conclusive narrative form. However, in the social and behavioral sciences, journal articles and stand-alone research reports are generally organized in a consistent format that makes it easier to compare and contrast studies and interpret their findings.
General Reading Strategies
W hen you first read an article or research paper, focus on asking specific questions about each section. This strategy can help with overall comprehension and with understanding how the content relates [or does not relate] to the problem you want to investigate. As you review more and more studies, the process of understanding and critically evaluating the research will become easier because the content of what you review will begin to coalescence around common themes and patterns of analysis. Below are recommendations on how to read each section of a research paper effectively. Note that the sections to read are out of order from how you will find them organized in a journal article or research paper.
1. Abstract
The abstract summarizes the background, methods, results, discussion, and conclusions of a scholarly article or research paper. Use the abstract to filter out sources that may have appeared useful when you began searching for information but, in reality, are not relevant. Questions to consider when reading the abstract are:
2. Introduction
If, after reading the abstract, you believe the paper may be useful, focus on examining the research problem and identifying the questions the author is trying to address. This information is usually located within the first few paragraphs of the introduction or in the concluding paragraph. Look for information about how and in what way this relates to what you are investigating. In addition to the research problem, the introduction should provide the main argument and theoretical framework of the study and, in the last paragraphs of the introduction, describe what the author(s) intend to accomplish. Questions to consider when reading the introduction include:
3. Literature Review
The literature review describes and critically evaluates what is already known about a topic. Read the literature review to obtain a big picture perspective about how the topic has been studied and to begin the process of seeing where your potential study fits within the domain of prior research. Questions to consider when reading the literature review include:
4. Discussion/Conclusion
The discussion and conclusion are usually the last two sections of text in a scholarly article or research report. They reveal how the author(s) interpreted the findings of their research and presented recommendations or courses of action based on those findings. Often in the conclusion, the author(s) highlight recommendations for further research that can be used to develop your own study. Questions to consider when reading the discussion and conclusion sections include:
5. Methods/Methodology
The methods section describes the materials, techniques, and procedures for gathering information used to examine the research problem. If what you have read so far closely supports your understanding of the topic, then move on to examining how the author(s) gathered information during the research process. Questions to consider when reading the methods section include:
6. Results
After reading the above sections, you should have a clear understanding of the general findings of the study. Therefore, read the results section to identify how key findings were discussed in relation to the research problem. If any non-textual elements [e.g., graphs, charts, tables, etc.] are confusing, focus on the explanations about them in the text. Questions to consider when reading the results section include:
7. References
The references list the sources used by the author(s) to document what prior research and information was used when conducting the study. After reviewing the article or research paper, use the references to identify additional sources of information on the topic and to examine critically how these sources supported the overall research agenda. Questions to consider when reading the references include:
NOTE: A final strategy in reviewing research is to copy and paste the title of the source [journal article, book, research report] into Google Scholar . If it appears, look for a "cited by" reference followed by a hyperlinked number under the record [e.g., Cited by 45]. This number indicates how many times the study has been subsequently cited in other, more recently published works. This strategy, known as citation tracking, can be an effective means of expanding your review of pertinent literature based on a study you have found useful and how scholars have cited it. The same strategies described above can be applied to reading articles you find in the list of cited by references.
Specific Reading Strategies
Effectively reading scholarly research is an acquired skill that involves attention to detail and an ability to comprehend complex ideas, data, and theoretical concepts in a way that applies logically to the research problem you are investigating. Here are some specific reading strategies to consider.
As You are Reading
Taking notes as you read will save time when you go back to examine your sources. Here are some suggestions:
Write down thoughts that come to mind that may help clarify your understanding of the research problem. Here are some examples of questions to ask yourself:
Adapted from text originally created by Holly Burt, Behavioral Sciences Librarian, USC Libraries, April 2018.
When is it Important to Read the Entire Article or Research Paper
Laubepin argues, "Very few articles in a field are so important that every word needs to be read carefully." * However, this implies that some studies are worth reading carefully if they directly relate to understanding the research problem. As arduous as it may seem, there are valid reasons for reading a study from beginning to end. Here are some examples:
* Laubepin, Frederique. How to Read (and Understand) a Social Science Journal Article . Inter-University Consortium for Political and Social Research (ISPSR), 2013
Shon, Phillip Chong Ho. How to Read Journal Articles in the Social Sciences: A Very Practical Guide for Students . 2nd edition. Thousand Oaks, CA: Sage, 2015; Lockhart, Tara, and Mary Soliday. "The Critical Place of Reading in Writing Transfer (and Beyond): A Report of Student Experiences." Pedagogy 16 (2016): 23-37; Maguire, Moira, Ann Everitt Reynolds, and Brid Delahunt. "Reading to Be: The Role of Academic Reading in Emergent Academic and Professional Student Identities." Journal of University Teaching and Learning Practice 17 (2020): 5-12.
Thesis dialogue blueprint, writing wizard's template, research proposal compass.
Starting a research paper can seem overwhelming, but breaking it down into manageable steps can make the process much easier. This guide will walk you through each stage, from choosing a topic to finalizing your paper, ensuring you stay organized and focused. Whether you're new to research or looking to improve your skills, these steps will help you create a strong, well-structured paper.
Choosing a research topic is a crucial first step in writing a research paper. It sets the stage for your entire project, so it's important to choose wisely. Here are some steps to help you select a topic that is both interesting and feasible.
Start by thinking about what excites you. Pick a topic that you find fun and fulfilling. This will keep you motivated throughout your research. Make a list of subjects you enjoy and see how they can relate to your field of study. Your job will be more pleasant if you choose a topic that holds your interest.
Once you have a few ideas, check if they are too broad or too narrow. A good topic should be manageable within the time you have. Ask yourself if you can cover all aspects of the topic in your thesis. For example, exploring the link between technology and mental health could be narrowed down to how WhatsApp use impacts college students' well-being.
Before finalizing your topic, ensure that there are enough resources available. Conduct preliminary research to see if there is sufficient data and literature on your chosen topic. This step is vital as you may discover issues with your original idea or realize you have insufficient resources to explore the topic effectively. This key bit of groundwork allows you to redirect your research topic in a different, more feasible, or more relevant direction if necessary.
Understanding the importance of a research question.
A well-defined research question is the cornerstone of any successful research paper. It provides a clear focus and direction for your study, ensuring that your efforts are both relevant and meaningful. A strong research question helps you stay on track and avoid unnecessary detours. It also makes it easier to communicate the purpose and significance of your research to others.
To develop a compelling research question, start by identifying your interests and the gaps in the existing literature. Use the 5 W's: who, what, where, when, and why , to explore different aspects of your topic. This approach will help you narrow down your focus and create a question that is both specific and researchable. Additionally, consider the feasibility of your question by evaluating the availability of resources and the scope of your study.
Your research question should align with the objectives of your study. This means that it should be directly related to what you aim to achieve through your research. Clearly defined objectives will guide your research process and ensure that your question remains relevant throughout your study. By aligning your question with your objectives, you can produce a coherent and focused research paper that effectively addresses the problem at hand.
Start by collecting sources that are related to your research topic. Use libraries, online databases, and academic journals to find books, articles, and papers. Skimming sources initially can save you time; set aside those that seem useful for a more thorough read later.
Once you have gathered your sources, read through them carefully. Take notes on key points and different viewpoints. This will help you understand the current state of research in your field. Look for common themes and debates that can inform your own work.
As you analyze the existing research, look for areas that haven't been explored or questions that haven't been answered. These gaps can provide a direction for your own research and make your thesis more valuable. Identifying these gaps is crucial for crafting a strong research question and ensuring your work contributes new knowledge to the field.
Creating a solid research plan is crucial for the success of your thesis. It helps you stay organized and ensures that you cover all necessary aspects of your research.
Establishing context.
Starting your thesis introduction can be daunting, but it's crucial for setting the stage for your research. Establishing the context for your study helps readers understand the background and significance of your work. This section should provide a clear overview of what your thesis will cover, making it easier for readers to follow your arguments.
Your thesis statement is the heart of your introduction. Typically, it is placed at the end of the introductory paragraph. This statement should succinctly present the main argument or focus of your thesis, guiding the reader on what to expect.
Once you have your research question, you need to justify why it is important. Explain the significance of your research problem in the context of existing literature. Highlight the gaps your research aims to fill and how it will contribute to the field. This step is crucial for crafting a bachelor thesis that stands out.
Organizing sections.
A well-structured research paper is essential for clarity and coherence. Start by dividing your paper into key sections: Introduction, Literature Review, Methodology, Results, Discussion, and Conclusion. Each section should serve a specific purpose and contribute to the overall argument of your paper. Organize your research by identifying main topics and subtopics, gathering relevant sources, and summarizing key points. This will help you maintain a logical flow throughout your paper.
Ensuring a logical flow between sections and paragraphs is crucial. Use transitions to connect ideas and guide the reader through your arguments. Each paragraph should begin with a clear topic sentence that introduces the main idea, followed by supporting evidence and analysis. This approach not only enhances readability but also strengthens your argument.
Coherence is achieved when all parts of your paper work together to support your thesis statement. To maintain coherence, make sure each section and paragraph aligns with your research objectives. Regularly review your work to ensure that your ideas are presented logically and that your voice remains dominant. Cite sources carefully to avoid plagiarism and to give credit to the original authors.
Choosing data collection methods.
Selecting the right data collection methods is crucial for the success of your research. Data collection is the process of gathering, measuring, and analyzing accurate data. Consider methods such as surveys, interviews, or experiments based on your research needs. Each method has its strengths and weaknesses, so choose the one that best fits your study.
Once you have collected your data, the next step is to analyze it accurately. Use statistical tools and software to help you interpret the data. Create tables and graphs to illustrate your findings clearly. This will help you present your results in a structured and understandable way.
Interpreting your results is an essential part of your thesis. Discuss how your findings relate to your research questions and the existing literature. Highlight the significance of your analyses and the reliability of your findings. This will help you draw meaningful conclusions and provide valuable insights into your research topic.
Start by writing your first draft without worrying too much about perfection. Focus on getting your ideas down on paper. This initial draft is your chance to explore your thoughts and structure your argument. Remember, the goal is to create a foundation that you can build upon.
Once you have a draft, it's time to incorporate feedback. Share your work with your thesis supervisor and peers. Their insights can help you see your work from different perspectives and identify areas for improvement. Revising is a continuous process of re-seeing your writing. It involves considering larger issues like focus, organization, and audience.
Finally, polish your final draft. Pay attention to grammar, punctuation, and formatting. Ensure that your thesis is clear, concise, and free of errors. This step is crucial for making a strong impression and effectively communicating your research findings.
Adhering to style guides.
When formatting your research paper, it's crucial to follow the specific style guide recommended by your institution. Common styles include APA, MLA, and Chicago. Each style has its own set of rules for formatting headings, tables, and references. Adhering to these guidelines ensures your paper meets academic standards and is easy to read.
Citing your sources correctly is essential to avoid plagiarism and give credit to the original authors. Typically, a citation can include the author's name, date, location of the publishing company, journal title, or DOI (Digital Object Identifier) . Use the citation style specified by your university, such as APA or MLA . For example, in APA format, an in-text citation might look like this: (Smith, 2020).
Plagiarism is a serious academic offense. To avoid it, always cite the sources you use in your research. This not only gives credit to the original authors but also adds credibility to your work. Use tools like Grammarly’s Citation Generator to ensure your citations are flawless and your paper is free from plagiarism.
Understanding academic integrity.
Academic integrity is the foundation of any scholarly work. It involves being honest and responsible in your research and writing. Maintaining academic integrity ensures that your work is credible and respected. It also means giving proper credit to the original authors of the sources you use. This practice not only helps you avoid plagiarism but also strengthens your arguments by backing them up with credible sources.
To avoid plagiarism, always cite your sources correctly. Use a consistent citation style, such as APA or MLA, and make sure to include all necessary information. Here are some tips to help you:
Ensuring the originality of your work is crucial. This means that your ideas and findings should be your own, even if they are based on existing research. Here are some ways to ensure originality:
By following these steps, you can maintain academic integrity and produce a research paper that is both credible and original.
Proofreading and editing.
Before submitting your research paper, it's crucial to proofread and edit your work thoroughly. Start by reviewing the content for clarity and coherence. Ensure that each section flows logically and that your arguments are well-supported. Pay close attention to grammar, spelling, and punctuation errors, as these can detract from the professionalism of your paper. Consider reading your paper aloud or using a text-to-speech tool to catch mistakes you might have missed.
Once you have polished your paper, it's time to prepare it for submission. Make sure you adhere to the specific formatting guidelines provided by your institution or the journal you are submitting to. This includes checking the font style and size, margins, and page numbering. Ensure that all citations and references are correctly formatted according to the required style guide, such as APA or MLA. Double-check that your paper meets all the submission requirements, including word count and any additional documents that need to be included.
Before finalizing your research paper, seek feedback from peers or mentors. A fresh set of eyes can provide valuable insights and help identify areas for improvement that you might have overlooked. Share your paper with colleagues or use online platforms to get constructive criticism. Incorporating feedback from others can enhance the quality of your work and ensure that your arguments are clear and compelling.
Wrapping up your research paper can be a daunting task, but it doesn't have to be. Our step-by-step Thesis Action Plan is here to guide you through every stage, making the process smoother and less stressful. Ready to conquer your thesis challenges? Visit our website now and discover how we can help you achieve your academic goals.
Starting a research paper can seem overwhelming, but breaking it down into manageable steps makes the process much easier. By choosing a topic that interests you, conducting thorough research, and organizing your findings, you lay a strong foundation for your paper. Remember to create a clear thesis statement to guide your writing and keep your arguments focused. Drafting, revising, and seeking feedback are crucial steps to refine your work. Finally, ensure your paper is well-formatted and free of errors. With dedication and careful planning, you can successfully navigate the research paper writing process. Good luck!
How do i choose a research topic.
Start by thinking about what interests you. Pick a topic that you find fun and fulfilling. This will keep you motivated throughout your research. Also, make sure there are enough resources available on the topic.
A research question guides your study, helping you focus on a specific issue. It makes your research more organized and meaningful.
A literature review helps you understand what has already been studied about your topic. It shows gaps in the research that your study can fill.
Outline your methodology, create a timeline, and allocate resources. This helps you stay organized and ensures you cover all necessary aspects of your research.
Your thesis introduction should establish the context, present your thesis statement, and justify the research problem. This sets the stage for your study.
Organize your sections logically, ensure a smooth flow of ideas, and maintain coherence throughout the paper. Each part should connect well with the others.
Choose methods that best suit your research needs, such as surveys, interviews, or experiments. Use statistical tools to analyze data accurately and interpret your results.
Always cite your sources correctly and follow the citation style recommended by your institution. Use plagiarism checkers to ensure your work is original.
How to determine the perfect research proposal length.
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Three faculty-led teams, including two from the SPHHS, are featured on the UMass Amherst website in a story on the innovative ways UMass Amherst researchers are working to promote health equity. The teams, each of which received a 2024 Large-Scale Integrative Research Award (LIRA) from the Office of the Vice Chancellor for Research and Engagement, are seeking to close societal health disparities by studying social determinants, engaging communities, and harnessing the power of the arts.
Professor of Community Health Education Susan Shaw 's work in community-based, participatory research as Director of the Center for Community Health Equity Research (CCHER) is highlighted. “Community-based participatory research requires that research partnerships be based on community needs, grounded in understanding the community, and aligned with the mission and goals of the community partner organization,” Shaw explains. “This approach helps rebuild trust in communities that have often experienced extensive research but little investment and can help generate community-led solutions to achieve health equity.”
With funding from the LIRA grant, Shaw and collaborators plan to expand on CCHER’s work by developing a proposal for a National Institutes of Health-supported Center of Excellence in Investigator Development and Community Engagement. Shaw’s collaborators include Kathryn Derose , professor of community health education; Airín Martínez , associate professor of health policy and management; Daniel López-Cevallos , associate professor of community health education; and Linnea Evans , assistant professor of community health education.
The Center of Excellence would provide funding for pilot awards for new investigators—especially those from underrepresented groups—whose research focuses on health equity. The center would also offer hands-on training in participatory approaches; opportunities for individual and peer mentoring; a monthly seminar series and workshops featuring experts on health equity research topics; and opportunities for collaborative research on questions of interest to community members. Participants would learn about proposal development, participatory research approaches, broad dissemination of findings, and how to turn results into community-led action.
The story also examines the work by another group of UMass Amherst researchers to catalyze existing energy and expertise on campus around using Arts-Based Research (ABR) to address inequities in health and the environment. The story notes that ABR is a fast-growing research methodology that uses the systematic process of artmaking as a primary way of understanding and examining experiences—both of researchers and the people they involve in their studies, who are sometimes one and the same.
“Arts-based research is a powerful methodology because of its visceral nature, which aligns nicely with the goals of creating on-the-ground research, intervention, and action in health and environmental research,” explains Professor of Community Health Education Aline Gubrium , who is leading the project. “Art also communicates sensibilities in ways that can’t always be conveyed through text or numbers. Art is also socially connecting. It channels joy and care.”
The team includes Marla Miller , distinguished professor of history; Sally Pirie , professor of child and family studies and director of the CBR Lab ; Elizabeth Krause , professor of anthropology; Sarah Goff , professor of health promotion and policy; and Sandy Litchfield , associate professor of architecture. They have individually conducted arts-based work on health and environmental topics ranging from reproductive justice, population politics, and LGBTQ+ youth mental health to aging and environmental humanities. Now they aim to nurture a network of faculty from around campus—including those in fields like engineering, chemistry, or veterinary sciences that may not, on their face, appear to lend themselves to ABR—to build community and generate ideas around arts-based approaches to research.
Read the full feature here.
Focus on racial and ethnic health disparities, structural racism and health, gender and sexuality, community-based and participatory research.
Focus on sexual and reproductive health, rights, and justice; participatory digital, visual, and narrative research methodologies; health promotion
The physics behind the most annoying thing that could ever happen to you: a paper cut, the physics behind a very annoying thing that could ever happen to you: a paper cut.
Scientists have figured out what type of paper is the most prone to cut skin. Kaare Jensen, associate professor of physics at the Technical University of Denmark, explains.
Copyright © 2024 NPR. All rights reserved. Visit our website terms of use and permissions pages at www.npr.org for further information.
NPR transcripts are created on a rush deadline by an NPR contractor. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR’s programming is the audio record.
Article by Tracey Bryant Photo by Evan Krape August 29, 2024
Biotechnology has proven to be a real problem-solver for some big challenges in our lives — from producing the insulin that people with diabetes need to regulate their blood sugar to manufacturing sustainable chemicals.
And now the University of Delaware is poised to take the tools of biotechnology to the next level for researchers in the Northeast and Mid-Atlantic regions.
UD is one of five institutions that the U.S. National Science Foundation is funding to advance a network of biofoundries, where researchers will be able to rapidly design, create, test and streamline tools and products that will accelerate research and workforce training for the emerging “bioeconomy” based on sustainable, renewable resources.
Mark Blenner, Thomas and Kipp Gutshall Career Development Associate Professor in UD’s Department of Chemical and Biomolecular Engineering and affiliated faculty member with the Microbiology Graduate Program, is the principal investigator on the project, which involves researchers at UD, Penn State and Worcester Polytechnic Institute.
The recipients of a $2 million grant from NSF, the UD-led team is creating the NSF Center for Robust, Equitable and Accessible Technology (CREATE) for Next-Generation BioFoundries to democratize access to the tools of modern biotechnology. The project team aims to provide users from academia and industry with automation and design tools to rapidly produce proteins, biosensors and bacteriophage products commonly used in biotechnology research.
“Our team is excited about training the next generation of scientists and engineers who will address our society’s most important problems — from sustainability to energy to therapeutics,” Blenner said. “This work will put Delaware squarely at the forefront of enabling the bioeconomy.”
Key audiences for the project include academic institutions such as primarily undergraduate institutions, Historically Black Colleges and Universities and other minority-serving institutions, and women’s colleges in the Northeast and Mid-Atlantic.
“Bioscience is a significant driver of our regional economy, and this project will further accelerate the research and workforce training capabilities of our UD faculty and students in this expanding area,” said Miguel Garcia-Diaz, UD’s vice president for research, scholarship and innovation.
“This project also will have great synergy with other major initiatives underway at UD and in partnership with our collaborators, from NIIMBL and the Delaware Biotechnology Institute to the new CURB NSF Engineering Research Center in St. Louis.”
Each biofoundry will focus on a different area of biology or biotechnology, but all will advance both in-house and user-initiated projects, train the next generation of the scientific workforce, engage with consumers and users of the products developed and continually enhance workflows and processes to accelerate the translation of ideas.
“Across all fields of science and engineering, including biology, answering grand challenges requires sustained development of technologies, sophisticated instrumentation, and workflows, but not every researcher at every institution can access those critical capabilities,” said NSF Director Sethuraman Panchanathan.
“The new BioFoundries will help democratize access, helping to spur opportunities everywhere so innovation can come from anywhere. Not only will these BioFoundries advance biology, but they will spur developments in artificial intelligence, data storage, health, climate resilience and more.”
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Professor Samuel Gershman and postdoc Momchil Tomov had volunteers play Atari-style video games while hooked up to fMRI scanners. Based on the results, they learned the directional flow of information was top-down during game play, the opposite of their original hypothesis.
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How does the human brain navigate complex circumstances — say, driving through Harvard Square traffic at 5 p.m.?
One theory gaining support with psychologists and neuroscientists is that the brain creates causal models of the world that help with planning and execution. It’s akin to running mental simulations to see which outcomes are good or bad. “You learn this internal model of the environment, which you can use to predict what will happen if you take different courses of action,” explained Momchil Tomov, an associate in psychology Professor Samuel Gershman ’s Computational Cognitive Neuroscience Lab .
In recent decades, computer scientists have developed these ideas into a system dubbed Reinforcement Learning (or RL for short). Researchers such as Tomov who work at the intersection of psychology and technology have even introduced computational models that attempt to capture how RL plays out in the brain. In a new paper published in Neuron , Tomov and his co-authors used functional magnetic resonance (fMRI) to compare their algorithmic theory against real-world imaging .
Why craft algorithms that attempt to formalize human thinking and decision-making? “It’s difficult to study cognitive processes without having a precise computational model that maps inputs to outputs,” said Tomov, who earned his Ph.D. in neurobiology at Harvard in 2019 and worked with Gershman as a postdoc until 2021.
Researchers also hope their work leads to advances in RL, which can navigate complex environments and is considered one of the biggest success stories in artificial intelligence. It has, in fact, bested humans in realms including board and video games, but until recently has proven a somewhat slow learner. “ Algorithms that are more human-like can perform better in certain domains than traditional machine-learning,” Tomov said.
The group’s experiment leans on the prior work of two of the study co-authors. Thomas Pouncy , another doctoral researcher in Gershman’s lab , outlined in 2021 a more complex, theory-based RL system. A computational theory-based RL model was introduced in a subsequent paper by MIT postdoctoral researcher Pedro Tsividis . It proved much faster than previous iterations in learning new video games. In terms of speed, Tomov said, it’s far closer to the human ability to pick up on such a task.
The whole process led the researchers to hypothesize on the neural architecture of human decision-making and learning. In the new study, the researchers tested their algorithm on 32 volunteers who played and eventually mastered Atari-style video games while hooked up to fMRI scanners , which measure the small changes in blood flow that come with brain activity.
As the researchers expected, this yielded evidence of activity theory-based models in the prefrontal cortex at the front of the brain with theory updates occurring in the posterior cortex, or back of the brain. Where their hypotheses — and their algorithm — diverged was in the details. The researchers specifically expected to find evidence of theory-based models in the orbitofrontal cortex. Instead they found them in the inferior frontal gyrus. This makes sense in hindsight, Tomov said, as previous research out of Gershman’s lab found the inferior frontal gyrus involved with learning “causal rules that govern the world.”
More surprises were found at the back of the brain, where the occipital cortex and the ventral pathway — both central to visual processing — appear to be involved when those models require updating. “Whenever you get surprising information that is inconsistent with your current theory, that’s when we see not just an update signal in the ventral pathway, but also, that’s when the theory becomes activated in the inferior frontal gyrus,” Tomov summarized.
Finally, fMRI scans revealed the directional flow of information in the brain. Tomov and his co-authors had hypothesized that information flows bottom-up. Instead, it seems to flow top-down during game play.
“It’s almost as if it’s coming from the model, stored somewhere in the prefrontal cortex, flowing down to the posterior visual regions,” he said. “But then when there’s a discrepancy — when an update happens — the pattern of information flow flips. Now information flows bottom-up, from posterior regions to frontal regions.”
Tomov has been studying theory-based RL with Gershman for four years. Two years ago, he started applying these ideas to self-driving cars as a full-time employee with a Boston venture. “How do you get from here to the next intersection and make a left turn without hitting anyone?” he asked. “Basically, there’s this internal model of the world with other drivers and predictions about what they’re going to do.”
The research described in this report was funded in part by the National Science Foundation.
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Health Sciences researchers encourage its use, but caution that it takes quality data and human supervision to keep “hallucinations” at bay.
Using artificial intelligence in research can help make some tedious tasks easier but ensuring the data is free of biases and misinformation can aid in accuracy.
Photo by Getty Images
Researchers in the field of health sciences are harnessing the power of artificial intelligence to revolutionize their approach to understanding and combating diseases. Across laboratories and institutions worldwide, AI algorithms are now not only assisting but often leading the charge in analyzing vast datasets, predicting patient outcomes and even uncovering novel therapeutic targets. This transformative partnership between human ingenuity and machine learning promises to reshape the landscape of health care, offering unprecedented insights and potential solutions to some of the most challenging medical mysteries of our time.
Brian Ahn, PhD, dean of the U of A College of Nursing
Photo by Kris Hanning, U of A Health Sciences Office of Communications
I did not write that paragraph. The artificial intelligence application in ChatGPT did. And while allowing a large language model like ChatGPT to sort through my interviews and synthesize the key points of everyone I interviewed would make my job much easier, is it the ideal or ethical way to present research to an audience?
“AI has the potential to revolutionize teaching, research and problem-solving by enhancing education, advancing research capabilities and improving patient care outcomes,” said Brian Ahn, PhD, dean of the University of Arizona College of Nursing . “Embracing AI responsibly and ethically can lead to significant advancements in nursing practice and health care as a whole.”
Ahn is uniquely positioned to understand this impact. In addition to his extensive nursing research, he has a Bachelor of Engineering degree in electrical engineering from the University of Seoul College of Engineering and a Master of Science degree in Electrical and Computer Engineering from the University of Florida College of Engineering. Ahn currently leads an NIH R01 study that integrates brain AI digital technology into pain and symptom management in older adults.
“The rapid advancement of health care technology, such as machine learning and artificial intelligence, requires the integration of these new technologies into our education and research programs,” Ahn said. “Our college is in the process of establishing a new nursing engineering program and ‘Center for Health and Technology’ to incorporate computer technology into nursing education and research.”
It all starts with good data
AI is a part of computer science that uses computers to do tasks that have historically required a human to complete, like problem-solving or simulating human capabilities, such as analyzing data or translating language. For researchers, sorting large data sets can be onerous work. But utilizing AI can cut that effort drastically.
Janine Hinton, PhD, an associate clinical professor and director of the Steele Innovative Learning Center in the College of Nursing
While images of Skynet might come to mind for some people when the words “AI” and “simulating human capabilities” are combined in one sentence, the ability to sort through large amounts of information, seeking patterns or even holes in the data, can free up researchers to focus on other parts of problems.
“Most of our research has been focused on assessing the current capabilities of AI or large language models,” said Christopher Edwards , PharmD, an associate clinical professor at the R. Ken Coit College of Pharmacy .
Edwards and his colleagues Bernadette Cornelison, PharmD, and Brian Erstad, PharmD , recently worked on a project that examined the accuracy of Chat GPT in providing patient-facing information, particularly on common questions patients should ask their pharmacist when they fill a new prescription. The research assessed the output of the model for accuracy and completeness to see if it was generating quality information. It was looking to see if the AI was “hallucinating,” which is when an AI provides inaccurate or misleading information. The AI may have incomplete or incorrect data; there may be biases in the data or the old “garbage in, garbage out” with false information in the data set.
“It can be very helpful writing learning objectives, test questions and editing,” said Janine Hinton, PhD, an associate clinical professor and director of the Steele Innovative Learning Center in the College of Nursing. “But you have to be very careful. It’ll give you a reference that doesn’t make sense. It’s just hallucinating.
Christopher Edwards, PharmD, an associate clinical professor at the R. Ken Coit College of Pharmacy
“But it will also present ideas that maybe I hadn’t originally thought of and just help me get my work done faster. I know that there are people who really want to get it moving in health care, but there are challenges with confidentiality, with clinical decision-making. But I do think there are a lot of ways to blend it with other tools and our expertise to get our work done.”
Hinton, who is also a member of the BIO5 Institute, explained that the College of Nursing uses AI to model a patient in simulation training at the Gilbert campus . The AI monitors and provides cues and clues to students to help them recognize interventions faster.
AI is much like gold mining
Travis Wheeler, PhD, an associate professor at the Coit College of Pharmacy whose doctoral degree is in computer science from the U of A, compared AI to mining.
“The power of AI comes from combining lots of training data with advanced techniques for learning to extract patterns from the data,” he said. “It’s a bit like mining. You might have a process that sifts through the dirt to extract big pieces of gold or minerals, but if there’s nothing valuable in the dirt, you won’t get anything out of it. That’s like feeding bad data to an AI model, and is what we mean by ‘garbage in.’ But if the dirt has a ton of really useful stuff and your method only extracts the gold, there are still some useful rare earth materials that you tossed away because you were using bad technology. You would be missing other things that are in there.
“With better methods, you can extract more material out of that dirt. As AI methods advance, it’s like building better mining methods, where you can extract more information out of the data you are given. It’s not only the quality of the data but also the tools used to extract the information out of that data.”
Wheeler is a lynchpin at the Health Sciences for AI work. He designs AI architectures able to ingest data while accounting for biases or missing data, to allow the artificial intelligence models to learn to tell the difference between that hypothetical gold-painted rock and a real gold nugget. He has spent more than 25 years in research in designing algorithms, statistical models, and software for problems motivated by biological data.
“The key idea behind AI and machine learning is that these models learn to perform classification or prediction tasks based on patterns extracted from the training data,” he said. “The challenge of the whole thing is both developing these large data sets that will provide the necessary information and then developing the kind of neat computational architectures that are capable of learning from those data.”
Beyond Chat GPT and crunching numbers
Travis Wheeler, PhD, an associate professor at the R. Ken Coit College of Pharmacy
But much like mining, recognizing when you have a gold nugget versus a gold-painted rock is important for researchers using AI.
“You’re taking data that is not completely vetted, not completely curated, so we have to learn how to mitigate bad-quality data,” said Nirav Merchant , director of the Data Science Institute and a member of the university’s AI Access & Integrity Working Group.
Any chef can tell you that your dinner is only as good as the ingredients you use. It’s the same with using AI in research. But AI can move beyond crunching large data sets.
Allan Hamilton , MD, the executive director of the Arizona Simulation Technology and Education Center , is researching how AI can be used as a coaching tool .
“AI should move the educational experience up almost to real time. It’s coaching each individual exactly how they need to be coached,” he said.
One way Hamilton uses AI is through a bot that can respond in real time, using a variety of emotions, to help coach new physicians. The second part of his research is finding ways AI can free up physicians.
Nirav Merchant, director of the Data Science Institute
Photo by Noelle Haro-Gomez, U of A Health Sciences Office of Communications
“Thirty percent of a doctor’s time is paperwork,” Hamilton said. “We know AI can do a lot of paperwork for us. How do we reapply that time? Hopefully the answer would be, You put it to good human use!”
For instance, he described a scenario in an intensive care unit where AI is monitoring a patient.
“AI could make predictions about which patients were more likely to need rapid response, but it might also say the whole ICU team doesn’t need to respond; you can send just two people,” Hamilton said. “It ended up being 245% better at identifying who was likely to need rapid response than the hospital teams determined.
“It’s like, is it safer for me to be on the road with GPS and not looking around trying to figure out where I am going? Yeah, it is.”
Hamilton, though, cautions against health-care providers relying too much on AI.
“I always say to students, ‘Bots don’t go to jail. Doctors do.’ So, if a patient dies because a physician did precisely what a bot told them to do rather than what their training guided them toward, the human will be held responsible,” he said.
A good tool when used properly
The researchers agreed that being transparent when AI or chatbots have been used in research is necessary for research integrity. As useful as it is to have AI write a draft of an abstract or study results, researchers need to be up front that it was utilized.
Allan Hamilton, MD, the executive director of the Arizona Simulation Technology and Education Center
Justin Starren, MD, PhD , the director of the Center for Biomedical Informatics and Biostatistics at the University of Arizona Health Sciences , compared relying on AI to his time in New York, where he lived on a wooded lot.
“That meant I had a chain saw,” he said. “A chain saw is a great tool, but if you don’t really understand how it works, you’re probably going to get the nickname ‘Stubby.’ The current AI tools are like chain saws – they can cut through a huge amount of data really fast. And they can figuratively take an arm off equally as fast. They can be profoundly powerful, but profoundly stupid. The risk is that we know very well that people tend to believe computers, even when they are wrong. It’s an extremely powerful tool.”
The issues of ensuring that good-quality data is being used, what the AI has been trained on and what tweaks were put into the system after it was trained are critical to minimizing racial bias or made-up answers.
“These tools can be great proofreaders, great hypothesis generators and do universe matrix analysis to find the hole in the data, but we need to be transparent about their use,” Starren added.
“I prefer to look at it as augmented intelligence rather than artificial intelligence,” said Merchant. “If you know how to use it, you’re going to be productive with it, but if you don’t know how to engage with it, you’re going to always try and find a nail for that hammer. So, stop thinking of AI as the hammer and just look where you can use it. Where can you use the automation that comes with some AI components?”
“The power of AI comes from combining lots of training data with advanced techniques for learning to extract patterns from the data.” Travis Wheeler, PhD, an associate professor at the R. Ken Coit College of Pharmacy
So much more to come with AI
Merchant cautioned researchers that chat tools and large language models are only the tip of the iceberg when it comes to using AI in research.
“People are building really purposeful analysis methods and tools that are constantly coming out,” he said. “Pay attention to those and see how we can use them because they will readily improve your science.”
Justin Starren, MD, PhD, the director of the Center for Biomedical Informatics and Biostatistics at the University of Arizona Health Sciences
For most of the Health Sciences researchers, however, AI, or more specifically, Chat GPT, can’t replace the human touch when “swimming in the sea of language,” as Starren put it. Often, AI-written content just doesn’t read “human.”
“I tried to use it to help write my wedding vows,” Edwards said. “And then I read it, and thought, ‘This is mechanical garbage.’ I don’t want to sound like this, because this is terrible. It gave me a starting point, though, and spurred my creative juices.”
Much like the start of this story, I asked ChatGPT to wrap it up as if it were writing it:
As AI continues to evolve and integrate into health sciences, its role as both a tool and a collaborator will only expand. The potential benefits are immense, from streamlining data analysis to enhancing patient care and education. However, the conversation around its ethical use and integration is equally crucial. As researchers and practitioners navigate this new frontier, they must balance the efficiency AI offers with the nuanced human touch that remains indispensable in healthcare. The ongoing challenge will be to harness AI’s capabilities responsibly, ensuring that it complements rather than compromises the human elements of empathy, creativity and critical thinking.
To learn more about the University of Arizona’s artificial intelligence resources and tools, a website outlining standards, usage and AI-related courses is available. The AI working group holds regular meetings on AI-related topics.
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2.    Choose the Subjects You Will Emphasize In Your Paper. Ensure that your research piece concentrates on certain subjects. For instance, you may opt to emphasize the book's characters or the plot's content. This will make outlining your thoughts and writing your research report much simpler.
This page addresses the research process -- the things that should be done before the actual writing of the paper -- and strategies for engaging in the process. Although this LibGuide focuses on researching short stories, this particular page is more general in scope and is applicable to most lower-division college research assignments.
That's it. If you want to tell a story in your paper, think of the six plot elements (character, setting, tension, action, climax, resolution) and the other three story essentials (main theme, chronology, purpose). In no time you'll have outlined the backbone of your narrative and be ready to create a paper that is concise, compelling, and ...
The story can be changed later on, to match the strongest results in the paper, or if the context for the research changes (for example, sometimes when working on a research problem, people can ...
ENG 102 - Short Story Research Guide; 7. Write Your Paper; Search this Guide Search. ENG 102 - Short Story Research Guide. This step-by-step guide will help you complete your Eng 102 short story assignment. Write Your Paper/Project Getting Started. Writing Fundamentals from Writer's Reference Center.
Telling a story in your paper: Explained and exemplified. When we say 'narrative', we don't necessarily mean 'write in the style of your favourite author'. A narrative, in the context of academic writing, is a central thread that runs through each of your result pieces. The idea is to have a beginning, a middle and an end to your ...
We ask for stories, broad or focused, in interviews and focus groups. We collect narratives from hand-written diaries or online posts. Once research is completed, we find ways to tell stories that bring findings to life. In this Sage Research Methods Community collection, find open-access articles and ideas from researchers about how to use ...
I distilled my research and cast of characters in my manuscript to identify six key elements of a story: (1) protagonist, (2) antagonists, (3) conflict, (4) scene, (5) resolution and (6) stakes.
5. The Theme. The theme of a story is the central idea or belief that the author wishes to convey. In a research report, the theme is largely found in the discussion of the results and the conclusions drawn from the findings, including implications for future research.
This Library Guide offers assistance in writing research papers on short stories. It provides information on short fiction as a literary genre, important elements of short fiction including things to look for in reading a story, and other information.
Re-Read the Story! Once you've selected a short story, re-read the story very closely, looking for themes, symbols, imagery, etc. Use a highlighter or a pen to mark interesting parts of the story that you want to use in your paper. Write notes in the margins. (If you can't write in your book, take notes on a separate sheet of paper).
ENG 102: Short Story Research. This guide is designed to help you complete a research paper about a short story in English 102. Follow the steps below in order - each step builds on the one before it, guiding you through the research project. We offer research advice/tips, as well as recommended sources, citation help, etc.
Research stories share your research in a way that is understandable and interesting to a non-expert, public audience. Unlike a research report, a research story focuses on telling the narrative of your process, the significance of your research to others, and your personal engagement with your research. This handout will help you frame your ...
Summary of the main message of the paper, building on the findings and implications, in relation to the problematization in the Introduction. Closure can have an uplifiting spirit, to leave the reader with a spirit that they have read something important. Acknowledgments: Funding: List of sources of financial support that made the research ...
Gale Literary Sources integrates full-text literary content with metadata and subject indexing and provides workflow tools to analyze information. You can research authors and their works, literary movements and genres. Search across your library's Literature databases to find full text of literary works, journal articles, literature criticism ...
6 min read. Tags: Fiction Research, Fiction Writing. The most basic understanding of "fiction" in literature is that it is a written piece that depicts imaginary occurrences. There is this unspoken assumption that fiction, because it is of imagined events, has nothing to do with reality (and therefore researching for a novel is not important).
This research page provides access to resources essential to successfully completing your short story research paper assignment. Please read the assignment information to the right carefully and use the sources provided in each of the tabs above: Instructional Videos; Electronic Resources; MLA Style
Whether you are writing a research paper on a short story for a high school or college level class, the process of researching the story is essentially the same, though an instructor in a college course will likely expect more. Read the short story thoroughly, making notes when necessary, before you begin researching ...
Digital storytelling is an emerging research method increasingly used to gather qualitative data. However, it is not commonly used to communicate research findings to stakeholders (De Jager et al., 2017).Being responsible for the comparative analysis and results dissemination of the ICT4COP 1 research project, which investigated community policing (COP) and police-reform in post-conflict ...
For scientific papers, the introduction is a perfect opener to engage the audience and get them excited to read your research or your review paper. If it takes nearly two pages to reach the research question or thesis statement or if the introduction is filled with technical jargon or casts certain work in an unfavorable light, then you will ...
The paper seeks to identify the cluster of essential features for a working definition of the short story, in an attempt to establish short fiction as a fully independent literary genre.
Of course, scientific story telling is not easy. Aside from the fact that few scientists are trained in writing, there are two major problems. First, we have to tell the truth, a restriction s tory-tellers do not face. Second, we have to deal with restrictive formats, such as length limits, figure limits, and mandated order of sections.
Introduction. Storytelling has been part of human life for as long as we know. The power of stories has been acknowledged since the times of Aristotle, and is still embraced by modern philosophers: "You can't really change the heart without telling a story" (Martha Nussbaum, (Nussbaum, Citation 2007)).Stories are special in making people aware of their shared values and they call to ...
Scholars rarely structure research studies in a way that can be followed like a story; they are complex and detail-intensive and often written in a descriptive and conclusive narrative form. However, in the social and behavioral sciences, journal articles and stand-alone research reports are generally organized in a consistent format that makes ...
Starting a research paper can seem overwhelming, but breaking it down into manageable steps can make the process much easier. This guide will walk you through each stage, from choosing a topic to finalizing your paper, ensuring you stay organized and focused. Whether you're new to research or looking to improve your skills, these steps will ...
Three faculty-led teams, including two from the SPHHS, are featured on the UMass Amherst website in a story on the innovative ways UMass Amherst researchers are working to promote health equity. The teams, each of which received a 2024 Large-Scale Integrative Research Award (LIRA) from the Office of the Vice Chancellor for Research and Engagement, are seeking to close societal health ...
MARTIN: So he and his colleagues got different kinds of paper - book paper, photo paper, Post-it notes - and they found a substitute for skin. JENSEN: We built a little robot, a little ninja ...
More Research Stories. New directors for UD's growing fintech endeavors. August 29, 2024. Article by Beth Miller. A bold approach toward sustainable manufacturing . August 21, 2024. Article by UDaily Staff. Coastal anthropogenic carbon. August 20, 2024. Article by Adam Thomas. See More Stories.
Researchers such as Tomov who work at the intersection of psychology and technology have even introduced computational models that attempt to capture how RL plays out in the brain. In a new paper published in Neuron, Tomov and his co-authors used functional magnetic resonance (fMRI) to compare their algorithmic theory against real-world imaging.
The research assessed the output of the model for accuracy and completeness to see if it was generating quality information. It was looking to see if the AI was "hallucinating," which is when an AI provides inaccurate or misleading information. The AI may have incomplete or incorrect data; there may be biases in the data or the old ...