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| Momentous falls, after unique proficiency ranges, ignored |
Systems Theory: when unique encoding is too diluted and disintegrated
Article reference: Why Good Professional Development Still Fails
Consider minimal overlap of an original code origin, like humans. From a narrow set of simplex, develops multidimensional complexity that through every stage of evolution, is triggered by at least a minimum of commutative, momentum-providing permutations like major inventions. History is rife of these examples, where an increasingly stagnant, diluted value set requires an injection of evolutionary impetus.
So where does this value set of humans now stand? Have the scales tipped back from the USA's initial birth, from Europe, to necessitate a scalar upgrade even multiples beyond the addition of the computer? And where does the impetus of original encoding stand, whether labeled DNA or Genomics, in triggering the next evolutionary upgrade in the species scale?
The article linked to above, includes a measurement of volume in a cylindrical value set. Not unlike spin physics in a simplex-to-complex evolutionary scale, such as humans evolving from a single-cell organism, to a spine-based (see the aforementioned "cylindrical value set" for commutative permutations), multidimensional set of complexity; the next stage of evolution arises from integrating the 'larger' code base that is miscalculated in the article's cylinder problem.
Consider that if, indeed, original proficiency encoding eventually arises as a critical evolutionary 'leaping point', through too much ignorance of individual originality, then now is a crucial timeframe to integrate Genomics mapping in education curriculum. Televised programs like AncestryDNA, and the continuing development of Genomics in biological fields, has unveiled further proof that each individual is born with at least a minimal proficiency set, and can be developed as not only a choice past-to-present range scale, but also commutative to future permutations of evolutionary scale.
Gone are the days where ignorant beliefs of automaton cyborgs, eliminate organic humans. Indeed, just the last few years of organic and synthetic integration in various medicinal sets, around the globe, have proven otherwise. So how does the scalable timeline of computer-to-biotech get better integrated into education? What role can edtech play in such a target set?
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