Definition of science and technologyScience from the Latin scientia (knowledge) is a system of acquiring knowledge based on the scientific method, as well as the organized body of knowledge gained through such research. Science as defined here is sometimes termed pure science to differentiate it from applied science, which is the application of scientific research to specific human needs. Show
Technology is a broad concept that deals with a species' usage and knowledge of tools and crafts, and how it affects a species' ability to control and adapt to its environment. In human society, it is a consequence of science and engineering, although several technological advances predate the two concepts. Science refers to a system of acquiring knowledge. This system uses observation and experimentation to describe and explain natural phenomena. The term science also refers to the organized body of knowledge people have gained using that system. Fields of science are commonly classified along two major lines:
These groupings are empirical sciences, which means the knowledge must be based on observable phenomena and capable of being tested for its validity by other researchers working under the same conditions. Differences in EtymologyThe word science comes through the Old French, and is derived from the Latin word scientia for knowledge, which in turn comes from scio - 'I know'. From the Middle Ages to the Enlightenment, science or scientia meant any systematic recorded knowledge. Science therefore had the same sort of very broad meaning that philosophy had at that time. In other languages, including French, Spanish, Portuguese, and Italian, the word corresponding to science also carries this meaning. Today, the primary meaning of "science" is generally limited to empirical study involving use of the scientific method. Technology is a term with origins in the Greek "technologia", "τεχνολογία" — "techne", "τέχνη" ("craft") and "logia", "λογία" ("saying"). However, a strict definition is elusive; "technology" can refer to material objects of use to humanity, such as machines, hardware or utensils, but can also encompass broader themes, including systems, methods of organization, and techniques. The term can either be applied generally or to specific areas: examples include "construction technology", "medical technology", or "state-of-the-art technology". Bigelow’s phrase[1] “the practical applications of science” points to the root of much of the current confusion as to the meaning of technology. In using this phrase to describe technology he effectively placed technology beneath the umbrella of science to such an extent that science and technology are now, as Rose described, seen by many as an “indivisible pair” with technology as the subservient and dependant partner. Thus, for much of the time the pair are wrapped together into a single conceptual package known simply as “science”. This point is emphasised when surfing the Internet for technology-related teaching resources. A plethora of lesson plans exist at sites dedicated to science education. The problem is, though, that many of these lessons should properly be termed “technology” but are all too often referred to as "Applied Science". One source of confusion is the undoubted relationship that exists between science and technology and Sparks pointed out that even though science and technology overlap in an area which might be referred to as “applied science”, there are a number of important differences between the two, even though these differences might not be self-evident to an average member of the general public who, through neglect and through repeated use of the phrase “science and technology” has lost the distinction between “science” and between “technology”. The two cannot be told apart, which is hardly surprising given that, as Mayr put it: “ . . . practical usable criteria for making sharp neat distinctions between science and technology do not exist.”  Our coverage comprises authoritative, highly accessible information on the very latest terminology, concepts, theories, techniques, people, and organizations relating to all areas of science and technology—from astronomy, engineering, physics, computer science, and mathematics, to life and earth sciences, chemistry, environmental science, biology, and psychology. Written by trusted experts for researchers at every level, entries are complemented by illustrative line drawings, equations, and charts wherever useful. Jump to:
Sample resourcesDiscover science and technology on Oxford Reference with the below sample content:
Back to top > Featured authorAndrew M. ColmanAndrew M. Colman is the author of A Dictionary of Psychology (4th edn). He is Professor of Psychology at the University of Leicester and a Fellow of the British Psychological Society. He graduated with a BA (Hons) and an MA in Psychology from the University of Cape Town and a PhD from Rhodes University. He is an author of numerous journal articles and several books, including Facts, Fallacies and Frauds in Psychology, What is Psychology? (3rd edn), Game Theory and its Application in the Social and Biological Sciences (2nd edn), and (with Briony D. Pulford), A Crash Course in SPSS for Windows (4th edn). He edited the two-volume Companion Encyclopedia of Psychology and the 12-volume Longman Essential Psychology series. Author Q&AWhat is the one term or concept that everyone—from students to everyday web users—should be familiar with? Why?I wish that everyone understood the scientific method, and in particular the unique importance of the controlled experiment as a method of scientific discovery. Children should be taught at school what an experiment is and why it is such a powerful way of discovering the truth. Psychology uses various research methods, but the most powerful is undoubtedly controlled experimentation, not because it is more objective or precise than other methods, but because it is uniquely capable of providing evidence of causal effects. The defining features of an experiment are manipulation of a conjectured causal factor, called an independent variable because it is manipulated independently of other variables, and examination of the effect of this on a dependent variable, while simultaneously controlling all other extraneous variables that might otherwise influence the dependent variable. In psychological experiments, extraneous variables can seldom be controlled directly, partly because people differ from one another in ways that affect their behaviour. You may think it’s impossible to control for all individual differences and other extraneous variables, but in fact there is a remarkable solution to this problem. In 1926, the British statistician Ronald Fisher discovered a powerful method of control called randomization. By assigning subjects or participants to an experimental group and a control group strictly at random, and then treating the two groups identically apart from the manipulated independent variable (applied to the experimental group only), an experimenter can control, at a single stroke, for all individual differences and other extraneous variables, including ones that no one has even considered. Randomization does not guarantee that the two groups will be identical but rather that any differences between the groups will follow precisely the known laws of probability. This explains the purpose and function of statistical significance tests in psychology. For any observed difference, a significance test enables a researcher to calculate the probability that a difference at least as large as the observed difference could occur by chance alone. The researcher then knows what the probability is of such a large difference under the null hypothesis – the working hypothesis that the independent variable has no effect. If the probability under the null hypothesis is sufficiently small (by convention, usually less than 5 per cent, often written p < .05), then it is reasonable to conclude that the observed difference is probably not due to chance, and if it is not due to chance, then it must be due to the independent variable, because all other variables that could explain it have been controlled by randomization. If this immensely powerful idea were more widely understood, then people would be less vulnerable to illusory correlation, more sceptical about merely anecdotal evidence, and capable of interpreting findings from any survey research, case study, correlational study, observational study, or quasi-experiment with appropriate caution. What do you think is the most commonly held misconception in your subject area?Although I can’t prove that it’s the most common, the most fashionable misconception is the assumption that phenomena of behaviour and mental experience – the subject-matter of psychology – can be understood and explained exclusively in terms of neural mechanisms. It is sustained by the increasingly popular doctrine that neuroscience can in principle replace traditional psychology, that it is already replacing traditional psychology, or (in its strongest form) that it has already replaced traditional psychology. This is a debilitating form of reductionism, based on the assumption that behaviour and mental experiences are closely correlated with neural processes, especially in the brain; but locating a mechanism in the brain does not amount to explaining the associated psychological phenomenon, as I can easily show with a Gedankenexperiment (thought experiment) and an example from nature. First, imagine a super-intelligent alien trying to understand a working computer busy printing out my Dictionary of Psychology on a laser printer. By merely investigating the physical mechanism of the computer and the printer, it would never understand what the computer was actually doing; or at least its explanation would lack what is most important and interesting about the computer’s behaviour. Second, purposeful behaviour can occur naturally without any involvement of neural mechanisms. For example, the unicellular paramecium, found abundantly in stagnant ponds, moves about, avoids obstacles by swimming round them, gathers food, and retreats from danger. It can turn round in a glass tube to escape, and it can even learn from experience, although some neuroscientists unsurprisingly question whether this is true learning. Yet a paramecium has no nervous system, and its single cell is not even a neuron; therefore, it provides conclusive evidence that neuroscience cannot explain all forms of behaviour. In your opinion, which is the most fascinating entry in your dictionary and why?Being asked to choose the most fascinating entry is like being asked to choose one’s favourite child, and I won’t do it. I find thousands of the entries fascinating, but the entry defining heuristic, together with the various specific heuristics cross-referenced from it, describes ideas that have fascinated others sufficiently to be rewarded with the only two Nobel prizes ever awarded for purely psychological research. A heuristic is a rough-and-ready procedure or rule of thumb for making a decision, forming a judgement, or solving a problem, and we all use heuristics all the time. The US researcher Herbert Simon introduced the term in its modern psychological sense in 1957 to explain how human decision makers with bounded rationality solve problems when they do not have the time or resources to examine all available possibilities thoroughly, and he received the first Nobel Prize for this work. Two decades later, the Israeli-American psychologists Amos Tversky and Daniel Kahneman discovered and investigated experimentally a large number of biases in human thinking that can be traced to particular heuristics, and in 2002 Kahneman was rewarded for this work with the second Nobel Prize, Tversky having died a few years earlier. A typical example is the conjunction fallacy: undergraduate students were shown personality sketches of a hypothetical person called Linda (young, single, deeply concerned about social issues, and involved in anti-nuclear activity) and asked whether it was more probable that Linda was a bank teller or that Linda was a bank teller who was active in the feminist movement. No fewer than 86% of the students judged it more probable that that Linda was a bank teller who was active in the feminist movement, although the probability of a conjunction A and B can never be greater than the probability of A. The fallacy arises from the use of the representativeness heuristic, according to which people estimate the probability that something belongs to a particular class by judging how typical it is of that class. Because Linda seems more typical of feminist bank tellers than of bank tellers in general, many people fall into the conjunction fallacy in this example. Back to top > Featured blogs
A timeline of the dinosaurs A history of the International Space Station For more science and technology blog posts delve in to the OUPblog archives > Back to top > More From OUPStay up-to-date with Oxford University Press by opting in to receive information in several different ways:
Back to top > Is the term used to refer to the systematic application of scientific knowledge in developing and applying technology?Engineering, the systematic application of scientific knowledge in developing and applying technology, has grown from a craft to become a science in itself.
What is systematic application of scientific knowledge?Systematic application of scientific knowledge to practical tasks is termed as 'technology'. It is an activity in which human uses scientific knowledge, tools and procedures to turn resources into desired goods and services to meet the needs and purposes of society.
What is systematic knowledge in science?Systemic knowledge is the holistic understanding of interpersonal expectations or norms, the technical system, and the relationships between the two.
What is the term that refers to the application of scientific information?Applied science is the use of the scientific method and knowledge obtained via conclusions from the method to attain practical goals.
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What term is used to refer to the systematic application of scientific knowledge in developing and applying technology?
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