Micro-Distinctions: Measureable Distinctions

Making distinctions is at the heart of the Rapid Skill Transfer Protocol (see “Distinguishing Distinctions – A Definition”).  And, for the purpose of efficiently and effectively transferring skill, I found that distinctions actually come in a couple of flavors and are likely to each be suited to different applications.

What are distinctions and micro-distinctions and what is the difference between them?

There are the coarser-level, garden variety-type distinctions (see “Glossary“) in which the value of the characteristic/property/variable has a broad descriptor.  As a result of the loose nature of the terms used, they’re likely to be able to be interpreted to have multiple meanings, and can, therefore, be quite ambiguous – for example, what exactly is “fast” vs “slow?”  Different people are quite likely to interpret those values of the speed characteristic quite differently – is “fast” 50 MPH, or is it 100 MPH?

A micro-distinction (see “Glossary“), on the other hand, is very fine-grained in nature, and has the criteria that it must be able to be measured or quantified in some way.  This helps greatly to remove any ambiguity – for example, the precise value of “at a rate of x feet/second” or “positioned at a 45 degree angle” articulates the target outcome very precisely in a way that all can agree upon.

Why is making micro-distinctions important?

In regards to the individual building blocks of skill transfer, being able to quantify a precise value of your characteristic/property/variable gives a much greater precision in the skill transfer process – there’s no ambiguity – the instructor can articulate precisely how she wants the student to perform and to what standards, and the student knows precisely what they’re expected to do and whether they’ve achieved that standard or not.

Making measureable micro-distinctions also allows for control and testing in order to facilitate an evolution in the best practices used for any given skill set, over the entire skill set.  Using micro-distinctions, rather than just rough distinctions, allows the expert the opportunity to test the various values for any given variable, within any given skill transfer segment, to find the BEST value to use for the desired outcome.  This can be done on each and every skill transfer segment to find the best values for each and every dimension of the skill transfer sequence.  I expect the end result will be the skill set evolving to better and better “best practices” for the benefit of anyone desiring to acquire that skill.

How do you know whether to use a distinction or a micro-distinction?

There’s one especially important consideration regarding distinctions, one that I don’t have an answer to as of yet.  I suspect it will be important for the Subject Matter Expert to know when to use a simple distinction and when it’s best to drill down and make a micro-distinction for a given characteristic.  The question is whether using a micro-distinction in a given context is a meaningful distinction, or whether it is so needlessly fine-grained as to be meaningless?  (eg Is it necessary to know the exact primary color constituents of the color orange to press the orange button, or can I just say, “push the orange button”?)  It’s something I’ll have to work on, answering the question, “What is the test you use to determine when to use a more or less precise descriptor?”  But THAT will have to be left for another day!!  🙂

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