science research paper sample

Even the most logical structure is of little use if readers do not see and understand it as they progress through a paper. Thus, as you organize the body of your paper into sections and perhaps subsections, remember to prepare your readers for the structure ahead at all levels. You already do so for the overall structure of the body (the sections) in the object of the document at the end of the Introduction . You can similarly prepare your readers for an upcoming division into subsections by introducing a global paragraph between the heading of a section and the heading of its first subsection. This paragraph can contain any information relating to the section as a whole rather than particular subsections, but it should at least announce the subsections, whether explicitly or implicitly. An explicit preview would be phrased much like the object of the document: "This section first . . . , then . . . , and finally . . . "

Although papers can be organized into sections in many ways, those reporting experimental work typically include Materials and Methods , Results , and Discussion in their body. In any case, the paragraphs in these sections should begin with a topic sentence to prepare readers for their contents, allow selective reading, and — ideally — get a message across.

Materials and methods

Results and discussion.

When reporting and discussing your results, do not force your readers to go through everything you went through in chronological order. Instead, state the message of each paragraph upfront: Convey in the first sentence what you want readers to remember from the paragraph as a whole. Focus on what happened, not on the fact that you observed it. Then develop your message in the remainder of the paragraph, including only that information you think you need to convince your audience.

The conclusion

At the end of your Conclusion , consider including perspectives — that is, an idea of what could or should still be done in relation to the issue addressed in the paper. If you include perspectives, clarify whether you are referring to firm plans for yourself and your colleagues ("In the coming months, we will . . . ") or to an invitation to readers ("One remaining question is . . . ").

If your paper includes a well-structured Introduction and an effective abstract, you need not repeat any of the Introduction in the Conclusion . In particular, do not restate what you have done or what the paper does. Instead, focus on what you have found and, especially, on what your findings mean. Do not be afraid to write a short Conclusion section: If you can conclude in just a few sentences given the rich discussion in the body of the paper, then do so. (In other words, resist the temptation to repeat material from the Introduction just to make the Conclusio n longer under the false belief that a longer Conclusion will seem more impressive.)

The abstract

Typically, readers are primarily interested in the information presented in a paper's Introduction and Conclusion sections. Primarily, they want to know the motivation for the work presented and the outcome of this work. Then (and only then) the most specialized among them might want to know the details of the work. Thus, an effective abstract focuses on motivation and outcome; in doing so, it parallels the paper's Introduction and Conclusion .

Accordingly, you can think of an abstract as having two distinct parts — motivation and outcome — even if it is typeset as a single paragraph. For the first part, follow the same structure as the Introduction section of the paper: State the context, the need, the task, and the object of the document. For the second part, mention your findings (the what ) and, especially, your conclusion (the so what — that is, the interpretation of your findings); if appropriate, end with perspectives, as in the Conclusion section of your paper.

Although the structure of the abstract parallels the Introduction and Conclusion sections, it differs from these sections in the audience it addresses. The abstract is read by many different readers, from the most specialized to the least specialized among the target audience. In a sense, it should be the least specialized part of the paper. Any scientist reading it should be able to understand why the work was carried out and why it is important (context and need), what the authors did (task) and what the paper reports about this work (object of the document), what the authors found (findings), what these findings mean (the conclusion), and possibly what the next steps are (perspectives). In contrast, the full paper is typically read by specialists only; its Introduction and Conclusion are more detailed (that is, longer and more specialized) than the abstract.

An effective abstract stands on its own — it can be understood fully even when made available without the full paper. To this end, avoid referring to figures or the bibliography in the abstract. Also, introduce any acronyms the first time you use them in the abstract (if needed), and do so again in the full paper (see Mechanics: Using abbreviations ).

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• Section 2: Literature review 
• Section 3: Methodology
• Section 4: Findings /results
• Section 5: Discussion
• Section 6: Conclusion
• Reference list

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What types of research papers can this template be used for?

The template follows the standard best-practice structure for formal academic research papers, so it is suitable for the vast majority of degrees, particularly those within the sciences.

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A Guide to Writing a Scientific Paper: A Focus on High School Through Graduate Level Student Research

Renee a. hesselbach.

1 NIEHS Children's Environmental Health Sciences Core Center, University of Wisconsin—Milwaukee, Milwaukee, Wisconsin.

David H. Petering

2 Department of Chemistry and Biochemistry, University of Wisconsin—Milwaukee, Milwaukee, Wisconsin.

Craig A. Berg

3 Curriculum and Instruction, University of Wisconsin—Milwaukee, Milwaukee, Wisconsin.

Henry Tomasiewicz

Daniel weber.

This article presents a detailed guide for high school through graduate level instructors that leads students to write effective and well-organized scientific papers. Interesting research emerges from the ability to ask questions, define problems, design experiments, analyze and interpret data, and make critical connections. This process is incomplete, unless new results are communicated to others because science fundamentally requires peer review and criticism to validate or discard proposed new knowledge. Thus, a concise and clearly written research paper is a critical step in the scientific process and is important for young researchers as they are mastering how to express scientific concepts and understanding. Moreover, learning to write a research paper provides a tool to improve science literacy as indicated in the National Research Council's National Science Education Standards (1996), and A Framework for K–12 Science Education (2011), the underlying foundation for the Next Generation Science Standards currently being developed. Background information explains the importance of peer review and communicating results, along with details of each critical component, the Abstract, Introduction, Methods, Results , and Discussion . Specific steps essential to helping students write clear and coherent research papers that follow a logical format, use effective communication, and develop scientific inquiry are described.

Introduction

A key part of the scientific process is communication of original results to others so that one's discoveries are passed along to the scientific community and the public for awareness and scrutiny. 1 – 3 Communication to other scientists ensures that new findings become part of a growing body of publicly available knowledge that informs how we understand the world around us. 2 It is also what fuels further research as other scientists incorporate novel findings into their thinking and experiments.

Depending upon the researcher's position, intent, and needs, communication can take different forms. The gold standard is writing scientific papers that describe original research in such a way that other scientists will be able to repeat it or to use it as a basis for their studies. 1 For some, it is expected that such articles will be published in scientific journals after they have been peer reviewed and accepted for publication. Scientists must submit their articles for examination by other scientists familiar with the area of research, who decide whether the work was conducted properly and whether the results add to the knowledge base and are conveyed well enough to merit publication. 2 If a manuscript passes the scrutiny of peer-review, it has the potential to be published. 1 For others, such as for high school or undergraduate students, publishing a research paper may not be the ultimate goal. However, regardless of whether an article is to be submitted for publication, peer review is an important step in this process. For student researchers, writing a well-organized research paper is a key step in learning how to express understanding, make critical connections, summarize data, and effectively communicate results, which are important goals for improving science literacy of the National Research Council's National Science Education Standards, 4 and A Framework for K–12 Science Education, 5 and the Next Generation Science Standards 6 currently being developed and described in The NSTA Reader's Guide to A Framework for K–12 Science Education. 7 Table 1 depicts the key skills students should develop as part of the Science as Inquiry Content Standard. Table 2 illustrates the central goals of A Framework for K–12 Science Education Scientific and Engineering Practices Dimension.

Key Skills of the Science as Inquiry National Science Education Content Standard

National Research Council (1996).

Important Practices of A Framework for K–12 Science Education Scientific and Engineering Practices Dimension

National Research Council (2011).

Scientific papers based on experimentation typically include five predominant sections: Abstract, Introduction, Methods, Results, and Discussion . This structure is a widely accepted approach to writing a research paper, and has specific sections that parallel the scientific method. Following this structure allows the scientist to tell a clear, coherent story in a logical format, essential to effective communication. 1 , 2 In addition, using a standardized format allows the reader to find specific information quickly and easily. While readers may not have time to read the entire research paper, the predictable format allows them to focus on specific sections such as the Abstract , Introduction , and Discussion sections. Therefore, it is critical that information be placed in the appropriate and logical section of the report. 3

Guidelines for Writing a Primary Research Article

The Title sends an important message to the reader about the purpose of the paper. For example, Ethanol Effects on the Developing Zebrafish: Neurobehavior and Skeletal Morphogenesis 8 tells the reader key information about the content of the research paper. Also, an appropriate and descriptive title captures the attention of the reader. When composing the Title , students should include either the aim or conclusion of the research, the subject, and possibly the independent or dependent variables. Often, the title is created after the body of the article has been written, so that it accurately reflects the purpose and content of the article. 1 , 3

The Abstract provides a short, concise summary of the research described in the body of the article and should be able to stand alone. It provides readers with a quick overview that helps them decide whether the article may be interesting to read. Included in the Abstract are the purpose or primary objectives of the experiment and why they are important, a brief description of the methods and approach used, key findings and the significance of the results, and how this work is different from the work of others. It is important to note that the Abstract briefly explains the implications of the findings, but does not evaluate the conclusions. 1 , 3 Just as with the Title , this section needs to be written carefully and succinctly. Often this section is written last to ensure it accurately reflects the content of the paper. Generally, the optimal length of the Abstract is one paragraph between 200 and 300 words, and does not contain references or abbreviations.

All new research can be categorized by field (e.g., biology, chemistry, physics, geology) and by area within the field (e.g., biology: evolution, ecology, cell biology, anatomy, environmental health). Many areas already contain a large volume of published research. The role of the Introduction is to place the new research within the context of previous studies in the particular field and area, thereby introducing the audience to the research and motivating the audience to continue reading. 1

Usually, the writer begins by describing what is known in the area that directly relates to the subject of the article's research. Clearly, this must be done judiciously; usually there is not room to describe every bit of information that is known. Each statement needs one or more references from the scientific literature that supports its validity. Students must be reminded to cite all references to eliminate the risk of plagiarism. 2 Out of this context, the author then explains what is not known and, therefore, what the article's research seeks to find out. In doing so, the scientist provides the rationale for the research and further develops why this research is important. The final statement in the Introduction should be a clearly worded hypothesis or thesis statement, as well as a brief summary of the findings as they relate to the stated hypothesis. Keep in mind that the details of the experimental findings are presented in the Results section and are aimed at filling the void in our knowledge base that has been pointed out in the Introduction .

Materials and Methods

Research utilizes various accepted methods to obtain the results that are to be shared with others in the scientific community. The quality of the results, therefore, depends completely upon the quality of the methods that are employed and the care with which they are applied. The reader will refer to the Methods section: (a) to become confident that the experiments have been properly done, (b) as the guide for repeating the experiments, and (c) to learn how to do new methods.

It is particularly important to keep in mind item (b). Since science deals with the objective properties of the physical and biological world, it is a basic axiom that these properties are independent of the scientist who reported them. Everyone should be able to measure or observe the same properties within error, if they do the same experiment using the same materials and procedures. In science, one does the same experiment by exactly repeating the experiment that has been described in the Methods section. Therefore, someone can only repeat an experiment accurately if all the relevant details of the experimental methods are clearly described. 1 , 3

The following information is important to include under illustrative headings, and is generally presented in narrative form. A detailed list of all the materials used in the experiments and, if important, their source should be described. These include biological agents (e.g., zebrafish, brine shrimp), chemicals and their concentrations (e.g., 0.20 mg/mL nicotine), and physical equipment (e.g., four 10-gallon aquariums, one light timer, one 10-well falcon dish). The reader needs to know as much as necessary about each of the materials; however, it is important not to include extraneous information. For example, consider an experiment involving zebrafish. The type and characteristics of the zebrafish used must be clearly described so another scientist could accurately replicate the experiment, such as 4–6-month-old male and female zebrafish, the type of zebrafish used (e.g., Golden), and where they were obtained (e.g., the NIEHS Children's Environmental Health Sciences Core Center in the WATER Institute of the University of Wisconsin—Milwaukee). In addition to describing the physical set-up of the experiment, it may be helpful to include photographs or diagrams in the report to further illustrate the experimental design.

A thorough description of each procedure done in the reported experiment, and justification as to why a particular method was chosen to most effectively answer the research question should also be included. For example, if the scientist was using zebrafish to study developmental effects of nicotine, the reader needs to know details about how and when the zebrafish were exposed to the nicotine (e.g., maternal exposure, embryo injection of nicotine, exposure of developing embryo to nicotine in the water for a particular length of time during development), duration of the exposure (e.g., a certain concentration for 10 minutes at the two-cell stage, then the embryos were washed), how many were exposed, and why that method was chosen. The reader would also need to know the concentrations to which the zebrafish were exposed, how the scientist observed the effects of the chemical exposure (e.g., microscopic changes in structure, changes in swimming behavior), relevant safety and toxicity concerns, how outcomes were measured, and how the scientist determined whether the data/results were significantly different in experimental and unexposed control animals (statistical methods).

Students must take great care and effort to write a good Methods section because it is an essential component of the effective communication of scientific findings.

The Results section describes in detail the actual experiments that were undertaken in a clear and well-organized narrative. The information found in the Methods section serves as background for understanding these descriptions and does not need to be repeated. For each different experiment, the author may wish to provide a subtitle and, in addition, one or more introductory sentences that explains the reason for doing the experiment. In a sense, this information is an extension of the Introduction in that it makes the argument to the reader why it is important to do the experiment. The Introduction is more general; this text is more specific.

Once the reader understands the focus of the experiment, the writer should restate the hypothesis to be tested or the information sought in the experiment. For example, “Atrazine is routinely used as a crop pesticide. It is important to understand whether it affects organisms that are normally found in soil. We decided to use worms as a test organism because they are important members of the soil community. Because atrazine damages nerve cells, we hypothesized that exposure to atrazine will inhibit the ability of worms to do locomotor activities. In the first experiment, we tested the effect of the chemical on burrowing action.”

Then, the experiments to be done are described and the results entered. In reporting on experimental design, it is important to identify the dependent and independent variables clearly, as well as the controls. The results must be shown in a way that can be reproduced by the reader, but do not include more details than needed for an effective analysis. Generally, meaningful and significant data are gathered together into tables and figures that summarize relevant information, and appropriate statistical analyses are completed based on the data gathered. Besides presenting each of these data sources, the author also provides a written narrative of the contents of the figures and tables, as well as an analysis of the statistical significance. In the narrative, the writer also connects the results to the aims of the experiment as described above. Did the results support the initial hypothesis? Do they provide the information that was sought? Were there problems in the experiment that compromised the results? Be careful not to include an interpretation of the results; that is reserved for the Discussion section.

The writer then moves on to the next experiment. Again, the first paragraph is developed as above, except this experiment is seen in the context of the first experiment. In other words, a story is being developed. So, one commonly refers to the results of the first experiment as part of the basis for undertaking the second experiment. “In the first experiment we observed that atrazine altered burrowing activity. In order to understand how that might occur, we decided to study its impact on the basic biology of locomotion. Our hypothesis was that atrazine affected neuromuscular junctions. So, we did the following experiment..”

The Results section includes a focused critical analysis of each experiment undertaken. A hallmark of the scientist is a deep skepticism about results and conclusions. “Convince me! And then convince me again with even better experiments.” That is the constant challenge. Without this basic attitude of doubt and willingness to criticize one's own work, scientists do not get to the level of concern about experimental methods and results that is needed to ensure that the best experiments are being done and the most reproducible results are being acquired. Thus, it is important for students to state any limitations or weaknesses in their research approach and explain assumptions made upfront in this section so the validity of the research can be assessed.

The Discussion section is the where the author takes an overall view of the work presented in the article. First, the main results from the various experiments are gathered in one place to highlight the significant results so the reader can see how they fit together and successfully test the original hypotheses of the experiment. Logical connections and trends in the data are presented, as are discussions of error and other possible explanations for the findings, including an analysis of whether the experimental design was adequate. Remember, results should not be restated in the Discussion section, except insofar as it is absolutely necessary to make a point.

Second, the task is to help the reader link the present work with the larger body of knowledge that was portrayed in the Introduction . How do the results advance the field, and what are the implications? What does the research results mean? What is the relevance? 1 , 3

Lastly, the author may suggest further work that needs to be done based on the new knowledge gained from the research.

Supporting Documentation and Writing Skills

Tables and figures are included to support the content of the research paper. These provide the reader with a graphic display of information presented. Tables and figures must have illustrative and descriptive titles, legends, interval markers, and axis labels, as appropriate; should be numbered in the order that they appear in the report; and include explanations of any unusual abbreviations.

The final section of the scientific article is the Reference section. When citing sources, it is important to follow an accepted standardized format, such as CSE (Council of Science Editors), APA (American Psychological Association), MLA (Modern Language Association), or CMS (Chicago Manual of Style). References should be listed in alphabetical order and original authors cited. All sources cited in the text must be included in the Reference section. 1

When writing a scientific paper, the importance of writing concisely and accurately to clearly communicate the message should be emphasized to students. 1 – 3 Students should avoid slang and repetition, as well as abbreviations that may not be well known. 1 If an abbreviation must be used, identify the word with the abbreviation in parentheses the first time the term is used. Using appropriate and correct grammar and spelling throughout are essential elements of a well-written report. 1 , 3 Finally, when the article has been organized and formatted properly, students are encouraged to peer review to obtain constructive criticism and then to revise the manuscript appropriately. Good scientific writing, like any kind of writing, is a process that requires careful editing and revision. 1

A key dimension of NRC's A Framework for K–12 Science Education , Scientific and Engineering Practices, and the developing Next Generation Science Standards emphasizes the importance of students being able to ask questions, define problems, design experiments, analyze and interpret data, draw conclusions, and communicate results. 5 , 6 In the Science Education Partnership Award (SEPA) program at the University of Wisconsin—Milwaukee, we found the guidelines presented in this article useful for high school science students because this group of students (and probably most undergraduates) often lack in understanding of, and skills to develop and write, the various components of an effective scientific paper. Students routinely need to focus more on the data collected and analyze what the results indicated in relation to the research question/hypothesis, as well as develop a detailed discussion of what they learned. Consequently, teaching students how to effectively organize and write a research report is a critical component when engaging students in scientific inquiry.

Acknowledgments

This article was supported by a Science Education Partnership Award (SEPA) grant (Award Number R25RR026299) from the National Institute of Environmental Health Sciences of the National Institutes of Health. The SEPA program at the University of Wisconsin—Milwaukee is part of the Children's Environmental Health Sciences Core Center, Community Outreach and Education Core, funded by the National Institute of Environmental Health Sciences (Award Number P30ES004184). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the National Institute of Environmental Health Sciences.

Disclosure Statement

No competing financial interests exist.

Writing an Introduction for a Scientific Paper

Dr. michelle harris, dr. janet batzli, biocore.

This section provides guidelines on how to construct a solid introduction to a scientific paper including background information, study question , biological rationale, hypothesis , and general approach . If the Introduction is done well, there should be no question in the reader’s mind why and on what basis you have posed a specific hypothesis.

Broad Question : based on an initial observation (e.g., “I see a lot of guppies close to the shore. Do guppies like living in shallow water?”). This observation of the natural world may inspire you to investigate background literature or your observation could be based on previous research by others or your own pilot study. Broad questions are not always included in your written text, but are essential for establishing the direction of your research.

Background Information : key issues, concepts, terminology, and definitions needed to understand the biological rationale for the experiment. It often includes a summary of findings from previous, relevant studies. Remember to cite references, be concise, and only include relevant information given your audience and your experimental design. Concisely summarized background information leads to the identification of specific scientific knowledge gaps that still exist. (e.g., “No studies to date have examined whether guppies do indeed spend more time in shallow water.”)

Testable Question : these questions are much more focused than the initial broad question, are specific to the knowledge gap identified, and can be addressed with data. (e.g., “Do guppies spend different amounts of time in water <1 meter deep as compared to their time in water that is >1 meter deep?”)

Biological Rationale : describes the purpose of your experiment distilling what is known and what is not known that defines the knowledge gap that you are addressing. The “BR” provides the logic for your hypothesis and experimental approach, describing the biological mechanism and assumptions that explain why your hypothesis should be true.

The biological rationale is based on your interpretation of the scientific literature, your personal observations, and the underlying assumptions you are making about how you think the system works. If you have written your biological rationale, your reader should see your hypothesis in your introduction section and say to themselves, “Of course, this hypothesis seems very logical based on the rationale presented.”

• A thorough rationale defines your assumptions about the system that have not been revealed in scientific literature or from previous systematic observation. These assumptions drive the direction of your specific hypothesis or general predictions.
• Defining the rationale is probably the most critical task for a writer, as it tells your reader why your research is biologically meaningful. It may help to think about the rationale as an answer to the questions— how is this investigation related to what we know, what assumptions am I making about what we don’t yet know, AND how will this experiment add to our knowledge? *There may or may not be broader implications for your study; be careful not to overstate these (see note on social justifications below).
• Expect to spend time and mental effort on this. You may have to do considerable digging into the scientific literature to define how your experiment fits into what is already known and why it is relevant to pursue.
• Be open to the possibility that as you work with and think about your data, you may develop a deeper, more accurate understanding of the experimental system. You may find the original rationale needs to be revised to reflect your new, more sophisticated understanding.
• As you progress through Biocore and upper level biology courses, your rationale should become more focused and matched with the level of study e ., cellular, biochemical, or physiological mechanisms that underlie the rationale. Achieving this type of understanding takes effort, but it will lead to better communication of your science.

***Special note on avoiding social justifications: You should not overemphasize the relevance of your experiment and the possible connections to large-scale processes. Be realistic and logical —do not overgeneralize or state grand implications that are not sensible given the structure of your experimental system. Not all science is easily applied to improving the human condition. Performing an investigation just for the sake of adding to our scientific knowledge (“pure or basic science”) is just as important as applied science. In fact, basic science often provides the foundation for applied studies.

Hypothesis / Predictions : specific prediction(s) that you will test during your experiment. For manipulative experiments, the hypothesis should include the independent variable (what you manipulate), the dependent variable(s) (what you measure), the organism or system , the direction of your results, and comparison to be made.

If you are doing a systematic observation , your hypothesis presents a variable or set of variables that you predict are important for helping you characterize the system as a whole, or predict differences between components/areas of the system that help you explain how the system functions or changes over time.

Experimental Approach : Briefly gives the reader a general sense of the experiment, the type of data it will yield, and the kind of conclusions you expect to obtain from the data. Do not confuse the experimental approach with the experimental protocol . The experimental protocol consists of the detailed step-by-step procedures and techniques used during the experiment that are to be reported in the Methods and Materials section.

Some Final Tips on Writing an Introduction

• As you progress through the Biocore sequence, for instance, from organismal level of Biocore 301/302 to the cellular level in Biocore 303/304, we expect the contents of your “Introduction” paragraphs to reflect the level of your coursework and previous writing experience. For example, in Biocore 304 (Cell Biology Lab) biological rationale should draw upon assumptions we are making about cellular and biochemical processes.
• Be Concise yet Specific: Remember to be concise and only include relevant information given your audience and your experimental design. As you write, keep asking, “Is this necessary information or is this irrelevant detail?” For example, if you are writing a paper claiming that a certain compound is a competitive inhibitor to the enzyme alkaline phosphatase and acts by binding to the active site, you need to explain (briefly) Michaelis-Menton kinetics and the meaning and significance of Km and Vmax. This explanation is not necessary if you are reporting the dependence of enzyme activity on pH because you do not need to measure Km and Vmax to get an estimate of enzyme activity.
• Another example: if you are writing a paper reporting an increase in Daphnia magna heart rate upon exposure to caffeine you need not describe the reproductive cycle of magna unless it is germane to your results and discussion. Be specific and concrete, especially when making introductory or summary statements.

Where Do You Discuss Pilot Studies? Many times it is important to do pilot studies to help you get familiar with your experimental system or to improve your experimental design. If your pilot study influences your biological rationale or hypothesis, you need to describe it in your Introduction. If your pilot study simply informs the logistics or techniques, but does not influence your rationale, then the description of your pilot study belongs in the Materials and Methods section.  

How will introductions be evaluated? The following is part of the rubric we will be using to evaluate your papers.

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How to Write a Research Methodology for a Research Paper

Crafting a comprehensive research paper can be daunting. Understanding diverse citation styles and various subject areas presents a challenge for many.

Without clear examples, students often feel lost and overwhelmed, unsure of how to start or which style fits their subject.

Explore our collection of expertly written research paper examples. We’ve covered various citation styles and a diverse range of subjects.

So, read on!

• 1. Research Paper Example for Different Formats
• 2. Examples for Different Research Paper Parts
• 3. Research Paper Examples for Different Fields
• 4. Research Paper Example Outline

Research Paper Example for Different Formats

Following a specific formatting style is essential while writing a research paper . Knowing the conventions and guidelines for each format can help you in creating a perfect paper. Here we have gathered examples of research paper for most commonly applied citation styles :

Social Media and Social Media Marketing: A Literature Review

APA Research Paper Example

APA (American Psychological Association) style is commonly used in social sciences, psychology, and education. This format is recognized for its clear and concise writing, emphasis on proper citations, and orderly presentation of ideas.

Here are some research paper examples in APA style:

Research Paper Example APA 7th Edition

Research Paper Example MLA

MLA (Modern Language Association) style is frequently employed in humanities disciplines, including literature, languages, and cultural studies. An MLA research paper might explore literature analysis, linguistic studies, or historical research within the humanities. 

Here is an example:

Found Voices: Carl Sagan

Research Paper Example Chicago

Chicago style is utilized in various fields like history, arts, and social sciences. Research papers in Chicago style could delve into historical events, artistic analyses, or social science inquiries. 

Here is a research paper formatted in Chicago style:

Chicago Research Paper Sample

Research Paper Example Harvard

Harvard style is widely used in business, management, and some social sciences. Research papers in Harvard style might address business strategies, case studies, or social policies.

View this sample Harvard style paper here:

Harvard Research Paper Sample

Examples for Different Research Paper Parts

A research paper has different parts. Each part is important for the overall success of the paper. Chapters in a research paper must be written correctly, using a certain format and structure.

The following are examples of how different sections of the research paper can be written.

Research Proposal

The research proposal acts as a detailed plan or roadmap for your study, outlining the focus of your research and its significance. It's essential as it not only guides your research but also persuades others about the value of your study.

Example of Research Proposal

An abstract serves as a concise overview of your entire research paper. It provides a quick insight into the main elements of your study. It summarizes your research's purpose, methods, findings, and conclusions in a brief format.

Research Paper Example Abstract

Literature Review 

A literature review summarizes the existing research on your study's topic, showcasing what has already been explored. This section adds credibility to your own research by analyzing and summarizing prior studies related to your topic.

Literature Review Research Paper Example

Methodology

The methodology section functions as a detailed explanation of how you conducted your research. This part covers the tools, techniques, and steps used to collect and analyze data for your study.

Methods Section of Research Paper Example

How to Write the Methods Section of a Research Paper

The research paper conclusion summarizes your findings, their significance and the impact of your research. This section outlines the key takeaways and the broader implications of your study's results.

Research Paper Conclusion Example

Research Paper Examples for Different Fields

Research papers can be about any subject that needs a detailed study. The following examples show research papers for different subjects.

History Research Paper Sample

Preparing a history research paper involves investigating and presenting information about past events. This may include exploring perspectives, analyzing sources, and constructing a narrative that explains the significance of historical events. Check out the history research paper topics blog to get inspired and motivated by these amazing ideas.

View this history research paper sample:

Many Faces of Generalissimo Fransisco Franco

Sociology Research Paper Sample

In sociology research, statistics and data are harnessed to explore societal issues within a particular region or group. These findings are thoroughly analyzed to gain an understanding of the structure and dynamics present within these communities. 

Here is a sample:

A Descriptive Statistical Analysis within the State of Virginia

 For more insights and inspiration, explore the sociology research topics blog to discover intriguing ideas and relevant issues.

Science Fair Research Paper Sample

A science research paper involves explaining a scientific experiment or project. It includes outlining the purpose, procedures, observations, and results of the experiment in a clear, logical manner.

Here are some examples:

Science Fair Paper Format

What Do I Need To Do For The Science Fair?

Psychology Research Paper Sample

Writing a psychology research paper involves studying human behavior and mental processes. This process includes conducting experiments, gathering data, and analyzing results to understand the human mind, emotions, and behavior. However, the key to a successful psychology paper is selecting the right topic. Make sure to pick an intriguing psychology research paper topic that captivates your interest and aligns with your research objectives.

Here is an example psychology paper:

The Effects of Food Deprivation on Concentration and Perseverance

Art History Research Paper Sample

Studying art history includes examining artworks, understanding their historical context, and learning about the artists. This helps analyze and interpret how art has evolved over various periods and regions.

Check out this sample paper analyzing European art and impacts:

European Art History: A Primer

Research Paper Example Outline

Before you plan on writing a well-researched paper, make a rough draft. An outline can be a great help when it comes to organizing vast amounts of research material for your paper.

Here is a research paper outline template:

Here is a downloadable sample of a standard research paper outline:

Research Paper Outline

Good Research Paper Examples for Students

Here are some more samples of research papers for students to learn from:

Fiscal Research Center - Action Plan

Qualitative Research Paper Example

Research Paper Example Introduction

How to Write a Research Paper Example

Research Paper Example for High School

Now that you have explored the research paper examples, you can start working on your research project. Hopefully, these examples will help you understand the writing process for a research paper.

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Nova Allison is a Digital Content Strategist with over eight years of experience. Nova has also worked as a technical and scientific writer. She is majorly involved in developing and reviewing online content plans that engage and resonate with audiences. Nova has a passion for writing that engages and informs her readers.

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Writing a scientific paper.

• Writing a lab report
• INTRODUCTION

Writing a "good" discussion section

"discussion and conclusions checklist" from: how to write a good scientific paper. chris a. mack. spie. 2018., peer review.

• LITERATURE CITED
• Bibliography of guides to scientific writing and presenting
• Presentations
• Lab Report Writing Guides on the Web

This is is usually the hardest section to write. You are trying to bring out the true meaning of your data without being too long. Do not use words to conceal your facts or reasoning. Also do not repeat your results, this is a discussion.

• Present principles, relationships and generalizations shown by the results
• Point out exceptions or lack of correlations. Define why you think this is so.
• Show how your results agree or disagree with previously published works
• Discuss the theoretical implications of your work as well as practical applications
• State your conclusions clearly. Summarize your evidence for each conclusion.
• Discuss the significance of the results
•  Evidence does not explain itself; the results must be presented and then explained.
• Typical stages in the discussion: summarizing the results, discussing whether results are expected or unexpected, comparing these results to previous work, interpreting and explaining the results (often by comparison to a theory or model), and hypothesizing about their generality.
• Discuss any problems or shortcomings encountered during the course of the work.
• Discuss possible alternate explanations for the results.
• Avoid: presenting results that are never discussed; presenting discussion that does not relate to any of the results; presenting results and discussion in chronological order rather than logical order; ignoring results that do not support the conclusions; drawing conclusions from results without logical arguments to back them up. 

CONCLUSIONS

• Provide a very brief summary of the Results and Discussion.
• Emphasize the implications of the findings, explaining how the work is significant and providing the key message(s) the author wishes to convey.
• Provide the most general claims that can be supported by the evidence.
• Provide a future perspective on the work.
• Avoid: repeating the abstract; repeating background information from the Introduction; introducing new evidence or new arguments not found in the Results and Discussion; repeating the arguments made in the Results and Discussion; failing to address all of the research questions set out in the Introduction. 

WHAT HAPPENS AFTER I COMPLETE MY PAPER?

 The peer review process is the quality control step in the publication of ideas.  Papers that are submitted to a journal for publication are sent out to several scientists (peers) who look carefully at the paper to see if it is "good science".  These reviewers then recommend to the editor of a journal whether or not a paper should be published. Most journals have publication guidelines. Ask for them and follow them exactly.    Peer reviewers examine the soundness of the materials and methods section.  Are the materials and methods used written clearly enough for another scientist to reproduce the experiment?  Other areas they look at are: originality of research, significance of research question studied, soundness of the discussion and interpretation, correct spelling and use of technical terms, and length of the article.

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• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

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

Methodology

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

 Statistics

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

Research bias

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

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Science Research Paper

View sample science research paper. Browse other  research paper examples and check the list of history research paper topics for more inspiration. If you need a history research paper written according to all the academic standards, you can always turn to our experienced writers for help. This is how your paper can get an A! Feel free to contact our custom writing service for professional assistance. We offer high-quality assignments for reasonable rates.

Like all effective knowledge systems, science is based on induction: careful empirical observation followed by attempts to generalize. Like all knowledge systems, it is subject to falsification, to the sudden appearance of new realities, or to new forms of information that may overturn established certainties. What distinguishes modern science from earlier knowledge systems is the size of the intellectual arena within which its ideas are generated and tested.

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The English word science derives from the Latin scire, “to know.” In many languages, the word science or its equivalents can be used broadly to mean “a systematic body of knowledge that guides our relations with the world.” This is the sense that is present in phrases such as “the social sciences.” There have existed many different knowledge systems of this type. All animals with brains have, and make use of, structured knowledge of the external world, so in principle we could claim that even animals depend on some form of science.

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Used in a narrower sense, the word science refers to the distinctive body of systematic knowledge about the material world that emerged in Europe within the last five hundred years and that underpinned the technological achievements of modern societies. Many societies have had complex technologies, and many have had rich and rigorous systems of religious and philosophical thought, but what is distinctive about modern science is that its theories have been used to generate extraordinarily powerful and effective technologies. As a recent study puts it, “Modern science is not just a thought-construction among others—it entails both an intellectual and an operative mastery of nature. Whereas empirical technology is a feature of every major civilization, the systematic application of scientific insights to change our natural environment (‘to conquer Nature by obeying her’, as Francis Bacon phrased it) is a creation of Europe alone” (Cohen 1994, 4). Conceived in this sense, science is a distinctively modern way of understanding the world. So, to understand the modern world, we have to understand science.

The idea of a “scientific revolution”—a fundamental transformation in ways of thinking about the world—is central to this view of the role of science in world history. Though it is generally accepted that the roots of modern science can be traced to classical Greece and Mesopotamia (although anticipations of modern scientific thought can be found in many different societies, from China to Mesoamerica, and even in some aspects of Paleolithic thought), it is widely assumed that modern science appeared during the scientific revolution of the sixteenth and seventeenth centuries, and its appearance marked a fundamental intellectual shift. As one survey puts it, “The Scientific Revolution represents a turning point in world history. By 1700 European scientists had overthrown the science and worldviews of Aristotle and Ptolemy. Europeans in 1700—and everyone else not long afterwards—lived in a vastly different intellectual world than that experienced by their predecessors in, say, 1500” (McClellan and Dorn 1999, 203). Over the next few centuries that revolution transformed human attitudes and human relations with the material world.

But the notion of science as a revolutionary new form of knowledge raises some complex problems. Was modern science really that different from earlier systems of knowledge? Why has it given modern societies such astonishing leverage over the material world? And is it really true, as some have claimed, that modern science offers a fundamentally superior way of describing reality?

What Is Different about Modern Science?

Answering these questions is not easy. It has proved particularly difficult to show that science offers a more accurate description of the world than earlier systems of knowledge.

Some of the earliest attempts to explain the efficacy of modern science claimed that its defining feature was careful, objective observation of the material world. Whereas most earlier systems of thought relied heavily on religious revelation or on the traditional authority of earlier writers and thinkers, so these claims go, scientists tried to put aside all preconceived notions and observe the world directly and without bias. To ensure the objectivity and precision of their observations, they devised rigorous and sometimes complex experimental methods. Then, using the results of their observations, they came up with general hypotheses about the nature of reality, using the logical method of induction.

In this view, scientific theories work because they are based on meticulous observation and rigorous logic, which explains why they offer exceptionally accurate and useful descriptions of the world. Galileo Galilei (1564–1642) is often thought to have exemplified the new experimental methods in his observations of the sun and planets through the recently invented telescope and in his experiments rolling balls down sloping planes to study the effects of gravity, while the achievement of Isaac Newton (1642–1727) in formulating general laws of motion is often taken as a paradigm example of the possibilities for radical generalization on the basis of information derived from careful observation. The seventeenth-century English natural philosopher (the contemporary term; now we would say scientist) Francis Bacon (1561–1626) was probably the first to describe the method of induction systematically, but similar arguments about the nature of modern science are still widely held today. Here, for example, is a modern definition of how science works: “Scientists propose theories and assess those theories in the light of observational and experimental evidence; what distinguishes science is the careful and systematic way in which its claims are based on evidence” (Worrall 1998, 573).

There is much truth in the inductivist view of modern science. Though examples of careful, empirical observation can be found in all human societies, never before had so many scientific observations been conducted so systematically and with such care and precision, and never before had natural philosophers tried so rigorously to build from them universal theories about the nature of reality. Unfortunately, though, the method of induction cannot guarantee the truth of scientific theories. In the first place, it is now clear that our minds shape and reorganize information as they receive it; so we can never separate observation from theorization in the neat way presupposed in the simplest models of inductive logic.

But the most fundamental problem is logical. Induction leads us from particular observations about the world to general theories about the world. Yet no observations can embrace all of reality, so induction involves a leap of faith that the small sample of reality that we can observe directly is characteristic of the whole of reality. Though it makes sense to rely on theories based on a large body of empirical evidence, induction can never yield conclusions whose truth is certain. (Bertrand Russell’s famous example was the inductivist turkey, who observed carefully how, each day, her bipedal servants provided food at a particular time; unfortunately, in mid-December, just as the turkey was about to formulate the general hypothesis that food would always appear at the same time, her servants killed her and cooked her for Christmas.) As a result, conclusions based on induction are always subject to modifications, sometimes of the most fundamental kind, as new observations become available. Thus, by carefully observing the position and motion of distant galaxies, using work on variable stars by Henrietta Leavitt (1868–1921), Edwin Hubble (1889–1953) showed that the universe, far from being stable and eternal, is in fact expanding.

Early in the twentieth century, the British-Austrian philosopher Karl Popper (1902–1994) proposed what he hoped was a more reliable apology for science. He argued that science advances through a process of “falsification.” As he pointed out, even if it is impossible to prove the truth of any theory reached by induction, it is possible to prove that some theories are wrong. So Popper argued that science should be trusted not because its conclusions are true in any absolute sense, but because it consisted of theories that had been tested rigorously and had not yet been proved wrong. The best known example of a falsifi- able idea is perhaps the claim put forward by Albert Einstein (1879–1955) that gravity affected light, a claim he suggested could be tested by seeing if the light from distant stars was bent as it passed behind the sun. The claim was successfully tested in 1919 during a solar eclipse, but what interested Popper was that Einstein’s claim was risky: it could have been proved false. Popper argued that ideologies such as Marxism and disciplines such as history did not count as sciences because they did not generate hypotheses that were precise enough to be falsified. Marxism was simply too rubbery: when it was pointed out that the socialist revolution predicted by Marx had failed to materialize, Marxists simply shifted their ground and changed the anticipated date of the revolution.

Unfortunately, even Popper’s attempts to distinguish science from other forms of knowledge were shown to be inadequate as historians of science became aware of the extent to which scientists, too, could cling to outdated theories or tweak their theories to avoid falsification. Despairing of finding any decisive proof of the truth of scientific theories, some philosophers of science gave up. The historian Thomas Kuhn (1922–1996), impressed by the subjectivity and partisanship of real science, argued that the main defining feature of modern science was simply that scientists within each scientific discipline seemed to agree about the discipline’s core ideas. Sciences, he argued, were organized around paradigms, or core ideas, such as Newton’s laws of motion, or the theory of natural selection. Once firmly established these were rarely subjected to the rigorous testing procedures Popper had taken for granted; on the contrary, there was a powerful element of faith in the work of most scientists most of the time. Paradoxically, Kuhn argued that it was this faith in a core idea that explained the effectiveness of scientific research. Unlike historians, who cannot agree about the fundamental laws by which their discipline works, scientists commit to a certain body of theory and this, he argued, explains why they conduct research in a more coordinated and more effective way than historians. For example, biologists, working within the paradigm of natural selection, know that any observation appearing to threaten the fundamental principle of natural selection is important, so such problems attract many researchers, and eventually their work can lead to new insights that usually support the core paradigm.

But not always. In extreme cases, he conceded, the accumulation of new data and new ideas may lead to the overthrow of an existing paradigm. In the late nineteenth century, most physicists assumed the existence of “ether,” a universal medium within which all physical processes took place. Unfortunately, experiments on the speed of light by the U.S. researchers Albert Michelson (1852–1931) and Edward Morley (1838–1923), seemed to show that the ether did not exist—the speed of light was uniform in all directions, whereas the existence of an ether ought to have slowed light beams traveling against the ether’s flow. It was these anomalies that led Einstein to suggest that the Newtonian paradigm had to be revised. So Kuhn distinguished between normal science, the slow, sometimes plodding process by which scientists flesh out the implications of a well-established paradigm, and scientific revolutions, or periods when an established paradigm breaks down and is replaced with a new one.

Though Kuhn’s ideas may have offered a more realistic portrayal of how science actually works, they provided weak support for its truth claims and failed to account for its explanatory power, for it was easy to point to other knowledge systems, including most forms of religion, in which there existed a core body of ideas that were taken on trust but were sometimes violently overthrown. To some, it began to seem that all we could say about science was that it was better at solving the sorts of problems that need to be solved in modern societies. Instrumentalist theories of science argue that it does not really matter whether or not scientific theories are true—all that matters is whether they work. Science is best thought of not as a more or less accurate description of reality, but rather as a tool—the mental equivalent of a stone axe or a computer. Or, to adopt a more precise analogy, it is like a map of reality. As Michael Polanyi has written: “all theory may be regarded as a kind of map extended over space and time.” Similarly, Thomas Kuhn has argued that scientific theory “provides a map whose details are elucidated by mature scientific research. And since nature is too complex and varied to be explored at random, that map is as essential as observation and experiment to science’s continuing development” (Kuhn 1970, 109). Like all knowledge systems, science offers simplified and partial maps of some aspects of the real world. But it is not the same as reality.

A last-ditch attempt to preserve the idea that science can provide an accurate account of reality is the delightful no-miracles argument advanced by the philosopher Hilary Putnam (b. 1926). Putnam argued that if a theory works, then the simplest explanation of that fact is to assume that the theory provides a good description of the real world. On this argument, it is the success of modern science that justifies its claims to provide accurate descriptions of reality. As Putnam puts it, “The positive argument for realism [the doctrine that science provides an accurate description of the real world] is that it is the only philosophy that does not make the success of science a miracle” (Psillos 1999, 71).

The apparent impossibility of finding any rigorous way of defining what is distinctive about modern science suggests that science may not be as different from other systematic forms of knowledge as is often supposed. All knowledge systems, even those of animals, offer maps of reality that provide more or less accurate guides to material reality. Perhaps, as the historian Steven Shapin has argued, the scientific revolution does not mark as clear an epistemological break as was once assumed. Most seventeenth-century scientists were well aware of the continuities between their ideas and those of the medieval and ancient worlds. Indeed, Newton, like many other scientists of his epoch, continued to study alchemy even as he was laying the foundations of what many think of today as true science. Even the notion of a scientific revolution is a modern idea; the phrase was first coined in 1939, by the philosophical historian Alexandre Koyre (1892–1964).

Developments in the twentieth century have done even more to blur the distinction between modern science and other systematic forms of knowledge. Quantum physics and chaos theory have shown that reality itself is fuzzier than was once supposed, a conclusion that has forced scientists to abandon the nineteenth-century hope of attaining a mechanically perfect description of reality. As a result, the differences between the sciences and the social sciences appear much less clear-cut than they once did. This is particularly true of historical scientific disciplines, such as cosmology or biology. Insofar as they try to describe changes in the past, specialists in these fields face the same dilemmas as historians; far from basing conclusions on repeatable laboratory experiments, they try, like historians, to reconstruct a vanished past from fragments left randomly to the present.

As the borders between the sciences and other modern disciplines have blurred, the idea of science as a quite distinct form of knowledge has become harder to defend. Careful observation leading to technological innovation is a feature of most human societies, while general theories about the nature of reality are offered in most forms of religion. Inductivist and falsificationist arguments cannot prove the truth of science; at best they highlight the pragmatic fact that scientific theories work because they are based on a larger body of observational evidence than any earlier knowledge systems and are also subject to exceptionally rigorous truth tests.

That line of argument suggests that we examine modern science’s place in human life historically, seeing modern science as one of many different human knowledge systems that have evolved in the course of world history. From this perspective, it is striking how, over time, human knowledge systems have had to incorporate more and more information, and how the task of distilling that information into coherent theories has required ever more stringent testing of ideas and yielded theories that were increasingly universal and abstract in their form though increasingly elaborate in their details. Perhaps, then, the main distinguishing feature of modern science is its scale.

As Andrew Sherratt (1995) puts it: “‘Intellectual Evolution’ . . . consists principally in the emergence of modes of thinking appropriate for larger and larger human groupings . . . This transferability has been manifested in the last five hundred years in the growth of science, with its striving for culture-free criteria of acceptance . . .” Because it is the first truly global knowledge system, modern science tries to explain a far greater volume and variety of information, and it subjects that information to far more stringent truth tests than any earlier knowledge system.

This approach may help explain the two other distinctive features of modern science: its astonishing capacity to help us manipulate our surroundings and rigorous avoidance of anthropomorphic explanations. For most of human history, knowledge systems were closely linked to particular communities, and as long as they provided adequate explanations of the problems faced by those communities, their credibility was unlikely to be challenged. But their limitations could be exposed all too easily by the sudden appearance of new problems, new ideas, or new threats. This was what happened throughout the Americas, for example, after the arrival of European conquerors, whose ideas undermined existing knowledge systems as effectively as their diseases and military technologies undermined existing power structures. As the scale of human information networks widened, attempts to integrate knowledge into coherent systems required the elimination of culture-specific explanations and encouraged reliance on abstract universals that could embrace larger and more diverse bodies of information and that could appeal to more diverse audiences. As the sociologist Norbert Elias (1897–1990) wrote in an elegant account of changing concepts of time, “The double movement towards larger and larger units of social integration and longer and longer chains of social interdependencies . . . had close connections with specific cognitive changes, among them the ascent to higher levels of conceptual synthesis” (Elias 1998, 179). The change can be seen clearly in the history of religions. As religious systems embraced larger and larger areas, local gods were increasingly supplanted by universal gods claiming broader and more general powers and behaving in more law-like and predictable ways than the local gods they displaced. Eventually, the gods themselves began to be displaced by abstract, impersonal forces such as gravity that seemed to work in all societies, irrespective of local religious or cultural beliefs.

The Emergence and Evolution of Science

The knowledge systems of the animal world are individualistic; each individual has to construct its own maps of reality, with minimal guidance from other members of its species. Humans construct their knowledge systems collectively because they can swap information so much more effectively than other animals. As a result, all human knowledge systems distill the knowledge of many individuals over many generations, and this is one reason why they are so much more effective and more general in their application than those of animals.

This means that even the most ancient of human knowledge systems possessed in some degree the qualities of generality and abstraction that are often seen as distinguishing marks of modern science. Frequently, it seems, the knowledge systems of foragers relied on the hypothesis that reality was full of conscious and purposeful beings of many different kinds, whose sometimes eccentric behavior explained the unpredictability of the real world. Animism seems to have been widespread, and perhaps universal, in small-scale foraging communities, and it is not unreasonable to treat the core ideas of animism as an attempt to generalize about the nature of reality. But foraging (Paleolithic) era knowledge systems shared more than this quality with modern science. There are good a priori reasons to suppose that foraging communities had plenty of well-founded empirical knowledge about their environment, based on careful and sustained observations over long periods of time. And modern anthropological studies of foraging communities have demonstrated the remarkable range of precise knowledge that foragers may have of those aspects of their environment that are most significant to them, such as the habits and potential uses of particular species of animals and plants. Archaeological evidence has also yielded hints of more systematic attempts to generalize about reality. In Ukraine and eastern Europe engraved bones dating to as early as thirty thousand years ago have been found that appear to record astronomical observations. All in all, the knowledge systems of foraging societies possessed many of the theoretical and practical qualities we commonly associate with modern science. Nevertheless, it remains true that the science of foragers lacked the explanatory power and the universality of modern science—hardly surprising given the limited amount of information that could accumulate within small communities and the small scale of the truth markets within which such ideas were tested.

With the appearance of agricultural technologies that could support larger, denser, and more varied communities, information and ideas began to be exchanged within networks incorporating millions rather than hundreds of individuals, and a much greater diversity of experiences and ideas. By the time the first urban civilizations appeared, in Mesopotamia and Egypt late in the fourth millennium BCE, networks of commercial and intellectual exchange already extended over large and diverse regions. Mesopotamia and Egypt probably had contacts of some kind with networks that extended from the Western Mediterranean shores (and perhaps Neolithic Europe) to Sudan, northern India, and Central Asia, in what some authors have described as the first world system.

Calendrical knowledge was particularly important to coordinate the agricultural activities, markets, and public rituals of large and diverse populations. The earliest calendars distilled a single system of time reckoning from many diverse local systems, and they did so by basing time reckoning on universals such as the movements of the heavenly bodies. This may be why evidence of careful astronomical observations appears in developed Neolithic societies in Mesopotamia, China, Mesoamerica (whose calendars may have been the most accurate of all in the agrarian era), and even in more remote environments such as England (as evidenced by Stonehenge) or Easter Island. The development of mathematics represents a similar search for universally valid principles of calculation. It was stimulated in part by the building of complex irrigation systems and large monumental structures such as pyramids, as well as by the need to keep accurate records of stored goods. In Mesopotamia, a sexagesimal system of calculation was developed that allowed complex mathematical manipulations including the generation of squares and reciprocals.

In the third and second millennia BCE, Eurasian networks of commercial and information exchanges reached further than ever before. By 2000 BCE, there existed trading cities in Central Asia that had contacts with Mesopotamia, northern India, and China, linking vast areas of Eurasia into loose networks of exchange. Late in the first millennium BCE, goods and ideas began traveling regularly from the Mediterranean to China and vice versa along what came to be known as the Silk Roads. The scale of these exchange networks may help explain the universalistic claims of religions of this era, such as Zoroastrianism, Buddhism, and Christianity.

The impact of these developments on knowledge systems is easiest to see in the intellectual history of classical Greece. Here, perhaps for the first time in human history, knowledge systems acquired a new degree of theoretical generality, as philosophers tried to construct general laws to describe the real world. As the writings of the historian Herodotus suggest, the Greeks were exposed to and interested in a colossal variety of different ideas and influences, from North Africa, Egypt, Persia, India, and the pastoralist societies of the steppes. The volume and variety of ideas to which Greek societies were exposed reflected their geographical position and the role of Greek traders, explorers, and emigrants forced, partly by overpopulation, to explore and settle around the many different shores of the Mediterranean and the Black Sea. Faced with a mass of new information, Greek philosophers set about the task of eliminating the particular and local and isolating those ideas that remained true in general. Thales of Miletus (c. 625–547 BCE), often regarded as the first of the Greek natural philosophers, offered explanations of phenomena such as earthquakes and floods that are universal in their claims and entirely free of the notion that reality is controlled by conscious entities.

At its best, Greek natural philosophy tried to capture not just this or that aspect of reality, but reality’s distilled essence. This project is most apparent in Greek mathematics and in Plato’s conviction that it is possible to attain knowledge of a perfect real world beneath the imperfections of the existing world. Greek philosophers were particularly interested in the testing of new ideas, a trait that is perhaps inevitable in societies faced with a sudden influx of new forms of knowledge. The rigor with which ideas were tested is apparent in the dialogues of Socrates, in which ideas are repeatedly subjected to Socrates’ corrosive logic (in an ancient anticipation of the notion of falsification), with only the most powerful surviving. Many other societies developed sophisticated methods of mathematical calculation and astronomical observation, and some, such as Song China (960–1279), developed metallurgical, hydraulic, and financial technologies that were unsurpassed until the twentieth century. But few showed as much openness to new ideas or as much interest in the testing of new ideas and theories as the Greeks.

Other societies have responded in similar ways to the exposure to new and more varied ideas. Perhaps Mesopotamia and Egypt, both with relatively easy access to Africa, India and the Mediterranean, count as early pioneers of scientific ideas for similar reasons. And perhaps it is the extensive contacts of medieval Islam that explain the fundamental role of Islam both in exchanging ideas (such as the mathematical concept of zero) between India and the Mediterranean worlds and in preserving and developing the insights of Greek and Hellenic science. Even in the Americas, it may have been the size of Mesoamerican populations and their exposure to many different regional cultures that led to the development of sophisticated calendrical systems from perhaps as early as the second millennium BCE.

Europe in the era of the scientific revolution certainly fits this model. Medieval European societies showed a remarkable openness to new ideas and an exploratory spirit that was similar to that of classical Greece. By the late medieval ages, European contacts reached from Greenland in the west to China in the east. Then, as European seafarers established close links with Southeast Asia in the east and the Americas in the west, Europe suddenly found itself at the center of the first global network of informational exchanges. The unification of the world in the sixteenth century constituted the most revolutionary extension of commercial and intellectual exchange networks in the entire history of humanity. Ideas about navigation and astronomy, about new types of human societies and new gods, about exotic crops and animal species, began to be exchanged on an unprecedented scale. Because Europe suddenly found itself at the center of these huge and varied information networks, it was the first region of the world to face the task of integrating information on a global scale into coherent knowledge systems. In the sixteenth century, European philosophers struggled to make sense of the torrent of new information that descended upon them, much of which undermined existing certainties. Like the Greeks, European thinkers faced the challenge of sorting the ephemeral from the durable, and to do that they had to devise new methods of observing and testing information and theories. It was this project that yielded the observational and experimental techniques later regarded as the essence of scientific method.

Thinkers in the era of the scientific revolution not only developed new ways of studying the world, they also created a new vision of the universe. The new vision was based on the work of three astronomers: Nicholas Copernicus (1473–1543), Tycho Brahe (1546–1601), and Johannes Kepler (1571–1630). Copernicus was the first modern astronomer to suggest that the earth might be orbiting the sun; Brahe’s careful astronomical observations provided the empirical base for Copernicus’s theories, and Kepler’s calculations showed that the new model of the universe worked much better if it was assumed that heavenly bodies traveled in ellipses rather than circles. Galileo used the newly invented telescope to show that heavenly bodies were as scarred and blemished as the earth, an observation that raised the intriguing possibility that the heavens might be subject to the same laws as the earth. Newton clinched this powerful unifying idea by showing that both the earth and the heavens—the very small and the very large— were subject to the same basic laws of motion. And this suggested the possibility that the universe as a whole might run according to general, abstract laws rather than according to the dictates of divine beings. Galileo’s discovery of millions of new stars also suggested that the universe might be much larger than had been supposed, while Anthony van Leeuwenhoek (1632–1723), the pioneer of modern microscopy, showed that at small scales there was also more to reality than had been imagined. Taken together, the theories of the sixteenth and seventeenth centuries transformed traditional views of the universe in ways that threatened to decenter human beings and throw into question God’s role in managing the universe. It was no wonder, then, that many feared that the new science might undermine religious faith.

Since the seventeenth century, the global information exchanges that stimulated the scientific breakthroughs of the scientific revolution have accelerated and affected more and more of the world. The prestige of the new sciences was particularly high in the era of the Enlightenment (seventeenth and eighteenth centuries), and encouraged more and more investigators to study the world using the techniques and assumptions of the scientific revolution. In the eighteenth and nineteenth centuries, scientific investigations yielded powerful new theories in fields as diverse as medicine (the germ theory), chemistry (the atomic theory and the periodic table), the study of electromagnetism (the unified theory of electromagnetism), energetics (theories of thermodynamics), geology, and biology (natural selection).

Scientific research was supported by the creation of scientific societies and journals, the introduction of science courses in universities, and the creation of research laboratories by businesses. The last two developments were both pioneered in Germany. The word scientist was first used in the 1840s. Meanwhile, the spread of scientific approaches to the study of reality and the increasing scope of scientific theory began to yield significant technological innovations in health care, manufacturing, and warfare. Particularly important were innovations in transportation and communications, such as the invention of trains and planes and the introduction of postal services, the telegraph, the telephone, and eventually the Internet, because these innovations expanded the scale and quickened the pace of information exchanges.

In the twentieth century, a series of new scientific theories appeared that refined the orthodoxies of eighteenth- and nineteenth-century science. Einstein’s theory of relativity demonstrated that space and time were not absolute frames of reference, while the quantum theory showed that, at the very smallest scales, reality itself does not behave in the predictable, mechanical ways assumed by earlier theories. Big bang cosmology, which has dominated cosmological thought since the 1960s, demonstrated that the universe, far from being eternal and infinite, had a history, beginning many billions of years ago, while the theory of plate tectonics, which appeared at about the same time, provided the foundations for a unified theory of geology and a detailed history of the formation and evolution of the earth. In biology, Francis Crick (1916–2004) and James Watson (b. 1928) described the structure of DNA in 1953; their work laid the foundations for modern evolutionary theory and modern genetic technologies. Meanwhile, the scale of scientific research itself expanded as governments and corporations began to fund special research facilities, sometimes to fulfill national objectives, as was the case with the Manhattan Project, which designed the first atomic weapons.

Recent scholarship suggests that it is a mistake to see modern science as fundamentally different from all other knowledge systems. Like all effective knowledge systems, it is based on induction: on careful empirical observation followed by attempts to generalize. Like all knowledge systems, it is subject to falsification, to the sudden appearance of new realities or new forms of information that may overturn established certainties. What really distinguishes modern science from earlier knowledge systems is the size of the intellectual arena within which its ideas are generated and tested. Its explanatory power and its qualities of abstraction and universality reflect the volume and diversity of the information it tries to distil, and the rigor of the truth tests to which its claims are subjected in a global truth market.

During the past two centuries, science has spread beyond the European heartland to Russia, China, Japan, India, and the Americas. Today it is a global enterprise, and its accounts of reality shape the outlook of educated people throughout the world. Far from diminishing, the flow of new information that stimulated the original scientific revolution has kept expanding as the pace of change has accelerated and the world as a whole has become more integrated. Early in the twenty-first century, the power of science to generate new ways of manipulating the material world, for better or worse, shows no sign of diminishing. Science has given our species unprecedented control over the world; how wisely we use that control remains to be seen.

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