CONSTRUCTIVISM
What is constructivism?
Constructivism is the epistemology (theory of knowledge) that what we know is based on the ideas that we invent. From this perspective, knowing is more than an awareness of facts (empiricism) or thinking about facts (rationalism) - it is ideas we create to interpret our sense-data and thoughts. But since concepts and language are part of everyone's mentality, some constructivists make the claim that every aspect of all knowledge is invented rather than discovered. The implication is that if "we make it all up" then we could re-make it into something quite different if that suited the "knowledge-creation gatekeepers". Is the epistemological enterprise really so arbitrary? The extent to which knowledge-creation can be arbitrarily controlled depends on the context.
Because social behaviour is largely governed by convention, multiple, discrepant interpretations are possible and plausible - physical and biological processes are more "factual".
When technological procedures are invented and scientific principles are discovered, the processes of summarizing, systemizing, and synthesizing also have constructivist components, but in these cases facts and thinking have important involvement as well. Those who argue or insist that science is largely or predominantly constructivist, are confusing function with origins.
The institution of science was itself "invented", but the role of science is to discover, explain, and forecast phenomena, and the role of technology is to explain, forecast, and control those same phenomena for human purposes. Constructivism cannot account for all of epistemology.
How does constructivism work?
Although empiricists were often fond of the claim that "the facts speak for themselves", this was never actually true, and has recently become demonstrably false. If reliable data are available, it can be processed with spreadsheet software to identify "best fit" to a curve representing a particular pattern or principle. However, one can choose to have the software "interpret" the data in a variety of ways, so that the same data will display "best fit" to a number of different types of curves - the configuration of these best fits can vary considerably, demonstrating positive correlation, negative correlation, linearity, non-linearity, etc . So, one can "invent" one's preferred explanation, and get the software to interpret the data accordingly. By examining previous research we can now see that before the availability of such software, scientists settled on their own preferred explanations in their own minds, and proceeded accordingly. Since some basis for interpretation is always necessary, the construction of knowledge will always be partly arbitrary - and this is where deconstruction (see MindMap Methodology in the Introduction) can help.
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