Referencing Click on the highlighted links in the text for commentary. Education means considerably more than just teaching a student to read, write, and manipulate numbers. Computers, the Internet, and advanced electronic devices are becoming essential in everyday life and have changed the way information is gathered. How this new technology is utilized in the curriculum and managed by teachers will have an important role to play in widening the resource and knowledge base for all students.
References and Further Reading 1. Introduction Most people, philosophers included, think of explanation in terms of causation. Very roughly, to explain an event or phenomenon is to identify its cause.
The nature of causation is one of the perennial problems of philosophy, so on the basis of this connection one might reasonably attempt to trace thinking about the nature of explanation to antiquity.
Among the ancients, for example, Aristotle's theory of causation is plausibly regarded as a theory of explanation. But the idea that the concept of explanation warrants independent analysis really did not begin to take hold until the 20th century.
Generally, this change occurred as the result of the linguistic turn in philosophy. More specifically, it was the result of philosophers of science attempting to understand the nature of modern theoretical science. Of particular concern were theories that posited the existence of unobservable entities and processes for example, atoms, fields, genes, etc.
These posed a dilemma. On the one hand, the staunch empiricist had to reject unobservable entities as a matter of principle; on the other hand, theories that appealed to unobservables were clearly producing revolutionary results. A way was needed to characterize the obvious value of these theories without abandoning the empiricist principles deemed central to scientific rationality.
In this context it became common to distinguish between the literal truth of a theory and its power to explain observable phenomena. Although the distinction between truth and explanatory power is important, it is susceptible to multiple interpretations, and this remains a source of confusion even today.
The problem is this: In philosophy the terms " truth " and "explanation" have both realist and epistemic interpretations.
On a realist interpretation the truth and explanatory power of a theory are matters of the correspondence of language with an external reality.
A theory that is both true and explanatory gives us insight into the causal structure of the world. On an epistemic interpretation, however, these terms express only the power of a theory to order our experience.
A true and explanatory theory orders our experience to a greater degree than a false non-explanatory one. Hence, someone who denies that scientific theories are explanatory in the realist sense of the term may or may not be denying that they are explanatory in the epistemic sense.
Conversely, someone who asserts that scientific theories are explanatory in the epistemic sense may or may not be claiming that they are explanatory in the realist sense. The failure to distinguish these senses of "explanation" can and does foster disagreements that are purely semantic in nature.
One common way of employing the distinction between truth and explanation is to say that theories that refer to unobservable entities may explain the phenomena, but they are not literally true.
A second way is to say that these theories are true, but they do not really explain the phenomena. Although these statements are superficially contradictory, they can both be made in support of the same basic view of the nature of scientific theories. This, it is now easy to see, is because the terms 'truth' and 'explanation' are being used differently in each statement.
In the first, 'explanation' is being used epistemically and 'truth' realistically; in the second, 'explanation' is being used realistically and 'truth' epistemically.
But both statements are saying roughly the same thing, namely, that a scientific theory may be accepted as having a certain epistemic value without necessarily accepting that the unobservable entities it refers to actually exist. This view is known as anti-realism.
One early 20th century philosopher scientist, Pierre Duhem, expressed himself according to the latter interpretation when he claimed: A physical theory is not an explanation. It is a system of mathematical propositions, deduced from a small number of principles, which aim to represent as simply, as completely, and as exactly as possible a set of experimental laws.
To explain is to strip the reality of the appearances covering it like a veil, in order to see the bare reality itself. Science, according to Duhem, does not comprehend reality, but only gives order to appearance. However, the subsequent rise of analytic philosophy and, in particular, logical positivism made Duhem's acceptance of classical metaphysics unpopular.
The conviction grew that, far from being explanatory, metaphysics was meaningless insofar as it issued claims that had no implications for experience.
By the time Carl Hempel who, as a logical positivist, was still fundamentally an anti-realist about unobservable entities articulated the first real theory of explanation the explanatory power of science could be stipulated.
To explain the phenomena in the world of our experience, to answer the question "Why? Hempel and Oppenheim Hempel employs the epistemic sense of explanation.
For him the question "Why? Hempel's Theory of Explanation According to Hempel, an explanation is: Their premises each contain statements of two types: In each, the conclusion is the event E to be explained:Research Methods In research, we often refer to the two broad methods of reasoning as the deductive and inductive approaches.
Research Types Deductive Approach Inductive Approach Inductive Research Approach THEORY TENTATIVE HYPOTHESIS Hill Climbing PATTERN Observations • Inductive reasoning works the other way, moving . Introduction to Primary Research: Observations, Surveys, and Interviews by Dana Lynn Driscoll This essay is a chapter in Writing Spaces: Readings on Writing, Volume 2, a peer-reviewed open textbook series for the writing classroom.
Deductive and Inductive Methods of Research In the quest for logical, supportable and verifiable scientific answers there are two basic methods of reasoning used to approach the subject matter to be studied. Statistical inference is the process of using data analysis to deduce properties of an underlying probability distribution.
Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving vetconnexx.com is assumed that the observed data set is sampled from a larger population..
Inferential statistics can be contrasted with descriptive statistics.
Deductive reasoning refers to a premise drawn by concrete facts while inductive reasoning is based upon loose conclusions of probability. Within the context of the essay “The Right to be Left Alone,” there are a number of examples of deductive and inductive reasoning.
Research findings into the relative benefits of deductive and inductive methods have been inconclusive. Short term gains for deductive learning have been found, and there is some evidence to suggest that some kinds of language items are better 'given than 'discovered'.