• Introduction

  • The Process of Science
  • Did you know?

    Did you know that science is not just a collection of facts to be memorized? The real process of science is a creative way of uncovering knowledge and interpreting the meaning of new discoveries. It is an approach to solving problems that can help us make better decisions in everyday life.

    Summary

    "What is science and how does it work?" This module introduces the Process of Science series, which answers this question, and presents the scientific process as a way of thinking that can help in everyday decision making. A brief overview is given of key concepts that guide the Process of Science module series.

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  • The Culture of Science

  • The Nature of Scientific Knowledge
  • Did you know?

    Did you know that it was not Magellan, Columbus, or even Copernicus who first proposed that the world was round? Rather, 2,000 years before these Europeans, Greek philosophers referred to the Earth as a sphere. An accumulation of evidence over the centuries confirmed that the Earth was round long before explorers sailed around the world.

    Summary

    This module explores the nature of scientific knowledge by asking what science is. It emphasizes the importance of a scientific way of thinking and shows how observation and testing add to the body of scientific knowledge. Focusing on astronomy and physics, the module highlights the work of scientists through history who have contributed to our understanding of the age of the universe as a means of conveying the nature of scientific knowledge.

    Key Concepts
    • Science consists of a body of knowledge and the process by which that knowledge is developed.
    • The core of the process of science is generating testable explanations, and the methods and approaches to generating knowledge are shared publicly so that they can be evaluated by the community of scientists.
    • Scientists build on the work of others to create scientific knowledge.
    • Scientific knowledge is subject to revision and refinement as new data, or new ways to interpret existing data, are found.

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  • Scientists and the Scientific Community
  • Did you know?

    Did you know that while the personal interests of scientists may seem to have nothing to do with science, the opposite is true? The process of understanding and explaining the natural world is a very human endeavor. As such, it can be influenced by a scientist's cultural outlook, personal challenges, and even hobbies.

    Summary

    Science benefits from diverse interests and different points of view. This module explores at the human side of science. With a look at the unique background and motivations of individual scientists, it is clear how personal experience, varied perspectives, creativity, and even chance contribute to progress in science.

    Key Concepts
    • Science is a human endeavor. It benefits from the creativity, curiosity, and diligence of individual scientists, and is also subject to human error.
    • Scientists are diverse in many ways, and their personal experiences – including cultures, backgrounds, and chance – influence the paths they follow.
    • Scientists benefit from mentoring and collaboration, working in communities within, or across, institutions and disciplines.

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  • Scientific Ethics
  • Did you know?

    Did you know that war crimes during World War II led to the Nuremberg Code, a set of ethical principles that still guides scientific research today? Although most scientists behave ethically, cases of fraud and misconduct highlight the need for a system of ethics to ensure proper behavior and reliable research in science.

    Summary

    Ethical standards are a critical part of scientific research. Through examples of scientific fraud, misconduct, and mistakes, this module makes clear how ethical standards help ensure the reliability of research results and the safety of research subjects. The importance and consequences of integrity in the process of science are examined in detail.

    Key Concepts
    • Ethical conduct in science assures the reliability of research results and the safety of research subjects.
    • Ethics in science include: a) standards of methods and process that address research design, procedures, data analysis, interpretation, and reporting; and b) standards of topics and findings that address the use of human and animal subjects in research.
    • Replication, collaboration, and peer review all help to minimize ethical breaches, and identify them when they do occur.

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  • Scientific Institutions and Societies
  • Did you know?

    Did you know that science doesn't happen in isolation? We may picture scientists working alone to make discoveries, but being part of a larger community is essential to science. Even in the 16th century, Galileo, like modern scientists, relied on support from the university where he taught, funding from wealthy supporters, and membership in a scientific academy.

    Summary

    Scientific institutions and societies play an essential role in the process of science and contribute to the building of scientific knowledge. This module explores these different bodies and discusses three types in detail: research institutions, professional societies, and funding institutions. Specific examples highlight how these institutions are essential to progress in science.

    Key Concepts
    • The community of science includes institutions and professional societies that support scientists physically, financially, and intellectually.
    • Research institutions include universities, national laboratories, government agencies, and corporations that all provide physical space and support for scientific research.
    • Professional societies promote interactions between individuals across institutions by organizing meetings and publications.
    • Governments, private industry, and other institutions provide financial support for scientific research through grants and research contracts.
    • All of these institutions affect the direction of scientific research, and may even bias it, by setting research priorities.

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  • Ideas in Science

  • Theories, Hypotheses, and Laws
  • Did you know?

    Did you know that the idea of evolution had been part of Western thought for more than 2,000 years before Charles Darwin was born? Like many theories, the theory of evolution was the result of the work of many different scientists working in different disciplines over a period of time.

    Summary

    Theories are not based on one scientist's work but on an accumulation of evidence and ideas from many scientists over time. This module discusses how scientific theories are built and revised. It uses the development of the theory of evolution through natural selection to illustrate how theories are built through a process of testing, expanding, and refining.

    Key Concepts
    • A scientific theory is an explanation inferred from multiple lines of evidence for some broad aspect of the natural world and is logical, testable, and predictive.
    • As new evidence comes to light, or new interpretations of existing data are proposed, theories may be revised and even change; however, they are not tenuous or speculative.
    • A scientific hypothesis is an inferred explanation of an observation or research finding; while more exploratory in nature than a theory, it is based on existing scientific knowledge.
    • A scientific law is an expression of a mathematical or descriptive relationship observed in nature.

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  • Scientific Controversy
  • Did you know?

    Did you know that science is full of controversy? And that controversy in science can be a good thing? A scientific controversy is more than a disagreement between scientists. In fact, controversies are found in all scientific fields and usually lead to progress in science.

    Summary

    Controversy isn't always a bad thing. It exists in every field of science and in many cases clarifies and advances our scientific understanding. This module explains what scientific controversies are and how they differ from other kinds of controversy. Using the example of climate change, the module identifies factors that lead to controversies in science and explains how they are resolved.

    Key Concepts
    • A scientific controversy is a sustained, public debate among the broader scientific community in which arguments are based on evidence.
    • Controversies cause progress in science by encouraging research on the topic in question.
    • Controversies are resolved when the evidence overwhelmingly favors one argument.
    • Scientific controversies are distinct from political, ethical, and personal controversies, though sometimes they overlap or can have complex interactions.

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  • Creativity in Science
  • Did you know?

    Did you know that creative thinking is found in every field, from art to business and even to science? Creativity plays a critical role in the process of science. The really big problems in science are usually too difficult to solve directly, but creative thinking allows scientists to re-imagine these complex problems and break them down into smaller, solvable parts.

    Summary

    Success in science requires a creative mind. This module explores the nature of creativity in the scientific process. It details various discoveries and explains how creativity played a significant role in each. The importance of logical thinking and background knowledge to the creative process is discussed.

    Key Concepts
    • Some of the most important questions in science are either too large or too complex to answer directly, so scientists break them down into smaller, solvable questions.
    • Many times, the questions that scientists research involve the simplest cases.
    • Scientists use creativity to determine which smaller questions are likely to yield results, imagine possible answers to their questions, and devise ways to test those answers.
    • To be creative, scientists need background knowledge, which they gain by learning about past scientific work, talking to colleagues, and tapping their own experience.

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  • Research Methods

  • The Practice of Science
  • Did you know?

    Did you know that even though people talk about "the scientific method," there is more than one way to do research? Examples throughout history, even as early as 5000 BCE, reveal that the practice of science is not a simple step-by-step path that leads to certain answers. Rather, the real scientific method is much less predictable and much more interesting.

    Summary

    Scientists use multiple methods to investigate the natural world and these interconnect and overlap, often with unexpected results. This module gives an overview of scientific research methods, data processing, and the practice of science. It discusses myths that many people believe about the scientific method and provides an introduction to our Research Methods series.

    Key Concepts
    • The practice of science involves many possible pathways. The classic description of the scientific method as a linear or circular process does not adequately capture the dynamic yet rigorous nature of the practice.
    • Scientists use multiple research methods to gather data and develop hypotheses. These methods include experimentation, description, comparison, and modeling.
    • Scientific research methods are complementary; when multiple lines of evidence independently support one another, hypotheses are strengthened and confidence in scientific conclusions improves.

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  • Experimentation in Scientific Research
  • Did you know?

    Did you know that experimental design was developed more than a thousand years ago by a Middle Eastern scientist who studied light? All of us use a form of experimental research in our day to day lives when we try to find the spot with the best cell phone reception, try out new cooking recipes, and more. Scientific experiments are built on similar principles.

    Summary

    Manipulating and controlling variables are key aspects that set experimentation apart from other scientific research methods. This module highlights the principles of experimentation through examples from history, including the work of Alhazen in 1000 CE and Louis Pasteur in the 1860s.

    Key Concepts
    • Experimentation is a research method in which one or more variables are consciously manipulated and the outcome or effect of that manipulation on other variables is observed.
    • Experimental designs often make use of controls that provide a measure of variability within a system and a check for sources of error.
    • Experimental methods are commonly applied to determine causal relationships or to quantify the magnitude of response of a variable.

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  • Description in Scientific Research
  • Did you know?

    Did you know that not all scientists conduct experiments? Anthropologist Jane Goodall was doing scientific research when she spent years in African forests watching chimpanzees and recording her systematic observations. Description has been used to develop theories in many scientific fields, including astronomy, geology, and primatology.

    Summary

    Observation is an important tool for scientific researchers, and describing what is observed is a valuable method of research. This module explains key features of scientific description and discusses how this method is used in the process of science. Examples from history illustrate the use of description, from the geologic exploration of the US in the 1800s to 20th century studies of primate behavior.

    Key Concepts
    • Description involves the systematic observation and cataloging of components of a natural system in a manner that can be utilized and replicated by other scientists.
    • Description is commonly used as a research method to explain unique natural systems (such as in ecology or chemistry), large-scale phenomena (such as in astronomy), or past events (such as in geology or forensic science).

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  • Comparison in Scientific Research
  • Did you know?

    Did you know that when Europeans first saw chimpanzees, they thought the animals were hairy, adult humans with stunted growth? A study of chimpanzees paved the way for comparison to be recognized as an important research method. Later, Charles Darwin and others used this comparative research method in the development of the theory of evolution.

    Summary

    Comparing and contrasting is a critical research tool for making sense of the world. Through scenarios in which scientists would likely choose to do comparative research, this module explores the differences and similarities between comparison and experimentation. Studies of the link between cigarette smoking and health illustrate how comparison along with other research methods provided solid evidence that cigarette smoke is a major cause of lung cancer.

    Key Concepts
    • Comparison is used to determine and quantify relationships between two or more variables by observing different groups that either by choice or circumstance are exposed to different treatments.
    • Comparison includes both retrospective studies that look at events that have already occurred, and prospective studies, that examine variables from the present forward.
    • Comparative research is similar to experimentation in that it involves comparing a treatment group to a control, but it differs in that the treatment is observed rather than being consciously imposed due to ethical concerns, or because it is not possible, such as in a retrospective study.

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  • Modeling in Scientific Research
  • Did you know?

    Did you know that scientific models can help us peer inside the tiniest atom or examine the entire universe in a single glance? Models allow scientists to study things too small to see, and begin to understand things too complex to imagine.

    Summary

    Scientific modeling is a research method scientists use to replicate real-world systems – whether it's a conceptual model of an atom, a physical model of a river delta, or a computer model of global climate. This module describes the principles that scientists use when building models and shows how modeling contributes to the process of science.

    Key Concepts
    • Modeling involves developing physical, conceptual, or computer-based representations of systems.
    • Scientists build models to replicate systems in the real world through simplification, to perform an experiment that cannot be done in the real world, or to assemble several known ideas into a coherent whole to build and test hypotheses.
    • Computer modeling is a relatively new scientific research method, but it is based on the same principles as physical and conceptual modeling.

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  • Data

  • Data Analysis and Interpretation
  • Did you know?

    Did you know that scientists don't always agree on what data mean? Different scientists can look at the same set of data and come up with different explanations for it, and disagreement among scientists doesn't point to bad science.

    Summary

    Data analysis is at the heart of any scientific investigation. Using weather as an example, this module takes readers through the steps of data collection, analysis, interpretation, and evaluation. The module explores how scientists collect and record data, find patterns in data, explain those patterns, and share their research with the larger scientific community.

    Key Concepts
    • Data collection is the systematic recording of information; data analysis involves working to uncover patterns and trends in datasets; data interpretation involves explaining those patterns and trends.
    • Scientists interpret data based on their background knowledge and experience; thus, different scientists can interpret the same data in different ways.
    • By publishing their data and the techniques they used to analyze and interpret those data, scientists give the community the opportunity to both review the data and use them in future research.

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  • Uncertainty, Error, and Confidence
  • Did you know?

    Did you know that when scientists use the word "uncertainty," it does not mean that they are unsure about their research results? Likewise, when scientists talk about "error," they do not mean that their research is flawed. Scientists actually measure error and report it along with their findings.

    Summary

    There is uncertainty in all scientific data, and even the best scientists find some degree of error in their measurements. This module uses familiar topics - playing baseball, shooting targets, and calculating the age of an object - to show how scientists identify and measure error and uncertainty, which are reported in terms of confidence.

    Key Concepts
    • Uncertainty is the quantitative estimation of error present in data; all measurements contain some uncertainty generated through systematic error and/or random error.
    • Acknowledging the uncertainty of data is an important component of reporting the results of scientific investigation.
    • Uncertainty is commonly misunderstood to mean that scientists are not certain of their results, but the term specifies the degree to which scientists are confident in their data.
    • Careful methodology can reduce uncertainty by correcting for systematic error and minimizing random error. However, uncertainty can never be reduced to zero.

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  • Statistics in Science
  • Did you know?

    Did you know that the field of statistics has its roots in gambling? Or that statistics cannot prove or disprove whether something is true?

    Summary

    Scientific research rarely leads to absolute certainty. There is some degree of uncertainty in all conclusions, and statistics allow us to discuss that uncertainty. Statistical methods are used in all areas of science. The module explores the difference between (a) proving that something is true and (b) measuring the probability of getting a certain result. It explains how common words like "significant," "control," and "random" have a different meaning in the field of statistics than in everyday life.

    Key Concepts
    • Statistics are used to describe the variability inherent in data in a quantitative fashion, and to quantify relationships between variables.
    • Statistical analysis is used in designing scientific studies to increase consistency, measure uncertainty, and produce robust datasets.
    • There are a number of misconceptions that surround statistics, including confusion between statistical terms and the common language use of similar terms, and the role that statistics employ in data analysis.

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  • Using Graphs and Visual Data in Science
  • Did you know?

    Did you know that the phrase "a picture is worth a thousand words" certainly applies to science? Complex data can be very hard to understand without being displayed in a visual form, so scientists commonly use visual displays to help during data analysis.

    Summary

    Understanding graphs and other visual forms of data is an important skill for scientists. This module describes how to read and interpret graphs and introduces other types of visual data. With a look at various examples, it is clear how trends can be grasped easily when the data is shown in a visual form.

    Key Concepts
    • Visual representations of data are essential for both data analysis and interpretation.
    • Visualization highlights trends and patterns in numeric datasets that might not otherwise be apparent.
    • Understanding and interpreting graphs and other visual forms of data is a critical skill for scientists and students of science.

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  • Scientific Communication

  • Understanding Scientific Journals and Articles
  • Did you know?

    Did you know that scientific literature goes all the way back to 600 BCE? Although scientific articles have changed some – for example, Isaac Newton wrote about the fun he had with prisms in a 1672 scientific article – the basics remain the same. This ensures that published research becomes part of the archive of scientific knowledge upon which other scientists can build.

    Summary

    Using a brief history of scientific writing, this module provides an introduction to the structure and content of scientific journal articles. Key differences between scientific journals and popular media are explained, and basic parts of a scientific article are described through a specific example. The module offers advice on how to approach the reading of a scientific article.

    Key Concepts
    • Scientists make their research available to the community by publishing it in scientific journals.
    • In scientific papers, scientists explain the research that they are building on, their research methods, data and data analysis techniques, and their interpretation of the data.
    • Understanding how to read scientific papers is a critical skill for scientists and students of science.

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  • Utilizing the Scientific Literature
  • Did you know?

    Did you know that when scientists refer to the "literature," they are not talking about the works of Shakespeare? The scientific literature goes back to the 6th century BCE, when ancient Babylonians recorded lunar eclipses on clay tablets. Science builds on previous findings, so understanding how scientists utilize the scientific literature is key to understanding how science works.

    Summary

    Scientific literature is central to the development of science as a whole. This module explains what scientists mean when they refer to the scientific literature and offers specific examples of how scientists use it to (1) discover what other work has been done on a topic, (2) cite sources of their data, and (3) show how their interpretations relate to existing knowledge.

    Key Concepts
    • The scientific literature provides an archive of research, which scientists make use of throughout the process of investigation.
    • Scientists reference the literature to indicate what other work has been done on a research topic, to cite sources of data that they use, and to show how their interpretations integrate with the published knowledge base of science.
    • New research questions can be investigated by reanalyzing or compiling data from the literature.
    • While individual scientists can make errors, the knowledge base of science as reflected in the scientific literature is self-correcting as new studies and new interpretations come to light.

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  • Peer Review in Scientific Publishing
  • Did you know?

    Did you know that each year the worldwide community of scientists volunteers hundreds of thousands of hours reviewing each other's work before it goes to print? It would be nearly impossible for an editor of a science journal to have the expertise to evaluate every manuscript. But thanks to peer review, a single issue of a scientific journal can have articles on topics as different as the geography of distant planets and the genetic makeup of dogs.

    Summary

    Peer review is an important part of the process of science. This module describes the history of peer review and shows how the review process helps validate the work of scientists and ensure that quality standards are met. The process is illustrated by actual correspondence among authors, reviewing scientists, and the editor of a scientific journal.

    Key Concepts
    • Scientific manuscripts and funding proposals are reviewed by several peer scientists who are familiar with the field of research and who make recommendations on whether or not the work should be published and/or funded.
    • Peer review works on many levels and is a fundamental component of the process of science.
    • After publication, scientific papers and other forms of research dissemination are further scrutinized by the scientific community when scientists read or try to reproduce the research.
    • Scientists conduct peer review as part of their responsibility to the scientific community, and are themselves evaluated by the peer review process.

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  • The How and Why of Scientific Meetings
  • Did you know?

    Did you know that scientific journals can take more than a year to publish an article after it is submitted? This is one reason why scientific meetings are so important to the process of science. Meetings allow researchers to share work in the scientific community and get feedback before a study is submitted for formal review.

    Summary

    Scientific meetings and conferences play an important role in the process of science. This module describes the history of scientific societies, beginning with the Royal Society of London in 1660. Specific examples illustrate why scientists go to meetings, how these gatherings influence research, and why attending meetings can be important for students and new scientists.

    Key Concepts
    • Scientific meetings bring scientists from all over the world together to communicate the results of new research.
    • The growth of scientific meetings is closely tied to the growth and development of scientific societies since the 1800s.
    • Individual scientists attend meetings in order to get feedback and disseminate their work, make connections with scientists in their field and beyond, and learn about new research, tools, and ideas.

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