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Quality Control (to improve an Actualization)

What is ACTUALIZATION and QUALITY CONTROL ?

Actualization:  In most design projects, an idea for an option (that is a potential solution) must be actualized by converting this idea into a reality.  An idea can be actualized by making (or obtaining) a product, doing an activity, applying a strategy, or using a theory.  In a “big picture” view, actualizing a Design Project` goes beyond just finding a solution, to consider all aspects of implementation, which may require long-term planning.

Quality Control:  You can try to control (to observe-and-improve) the quality of actualization by using Quality Control, which is an important part of Problem Solving.  For example,

 

Actualizing a Product:  Imagine that you've designed a product, and it works well (in principle) if it's made well, but (in reality) too often the manufacturing process makes a defective product with flaws that cause it to be unsatisfactory.  So you develop a strategy for Quality Control, and you apply this strategy.  If your efforts to improve the Quality of Actualization are not successful, you may have to search for a different manufacturing method or (if this isn't practical) maybe even a different product.

Actualizing a Strategy:  When a strategy is used, it's converted from a strategy-idea into an actualized strategy-in-action.  For example, if you develop a strategy for a job interview, your strategy can be effective only if you convert it into skillful action during the interview.  The interview's results — how it influences “views about you” by the potential employer, and “views about the job situation” by you — depend on the quality of your actualized strategy, on how well you convert the strategy from an idea into strategy-guided action.  A useful principle, summarized as “Situation + Actualized Strategy → Results”, is illustrated (and explained) with a strategy for basketball and a Strategy for Learning.

Actualizing an Activity:  This is similar to actualizing a strategy, because it's converting an idea into action.

 

Actualizing an Attitude:  What if you want to change your own attitude, your way of thinking, your ideas?  This is different because if your objective is an attitude, which is an idea, it cannot be “actualized” by changing it from a mental idea into a physical reality.  But it can be converted from a mentally-planned possibility (In the future) into a physically-actualized reality (in the present).  This actualizing happens each time you think using the desired attitude, each time you think in a way that is consistent with your plan, with your strategy for thinking. [each time your thinking includes the desired attitude] [each time the way you want to think becomes the way you are thinking] [ IOU - I wrote this paragraph late tonight, September 6, and I'll revise it tomorrow.] [I think this will require a shift from defining actualization as "converting from mental into physical" (which doesn't work when the objective is a mental idea) to "converting from possible into actual" or "...from a possibilitiy into a reality" or "from a mentally-planned possibility into a physically-actualized reality"]

 

Actualizing a Theory is different because the action occurs in your mind, in two stages at • and •.

• Before you can “think with a theory” you must mentally actualize the theory by converting an external theory-idea into an internal theory-idea, by constructing your own mental model of a theory, so you can remember-and-use the theory.  This theory-actualization is education, which can occur in or out of school, with or without help from others.

In science and design, we can use Quality Control to achieve two main types of goals;  we want theories to be true, and also useful in several ways, including cognitive utility.*

One goal is truth.  We want a theory to help us think about “what happens” in a way that is true (at least approximately)* because it corresponds to the reality of what happens.  This accurate understanding is one aspect of a theory's cognitive utility.

• Another aspect of cognitive utility is using your mental model of a theory (constructed in the first stage of theory-actualization) to make accurate predictions, in a second stage of theory-actualization.  In the design-thinking we use for “almost everything we do” (so doing it well has practical utility in many areas of personal life & professional life), accurate predictions are needed for evaluative Mental Quality Checks (which are used to make decisions and guide inventions) and in science for evaluative Reality Checks (also used to make decisions and guide inventions).  Therefore, an important part of "thinking with a theory" is developing effective strategies to convert theory-ideas into theory-based predictions.

One foundation of modern science is an assumption that these two aspects of cognitive utility, accurate understanding and accurate predicting, are causally correlated.  Most scientists assume that the most probable reason for a theory's predictive accuracy is that this theory is approximately true.

A theory with cognitive utility — so we can skillfully use the theory for thinking (for understanding, predicting, and in other ways) — helps us do the Productive Thinking that occurs when we effectively combine creative thinking, critical thinking, and knowledge-of-ideas.

 

* In addition to truth and cognitive utility (with accurate understanding & predicting), scientists (and engineers, philosophers, educators,...) also have other goals for a theory, including research utility and personal utility.  As explained below, achieving these goals depends on the quality of a theory and also the quality of its actualizations.

* Often we expect "approximate truth" because we recognize that when a theory is applied to a real-world system to construct a theory-based model of the system there will be some simplification.

 

Actualizing a Design Project — Quality Control

In quality control for a design project — for the process of design and results of design — you think about "the big picture... trying to imagine the entire project-process from beginning to end... [for all] stakeholders... and decide how you can improve its actualized quality."

 


 

Situation + Actualized StrategyResults

Imagine that you're a basketball coach, and you design a strategy to win a game.  When you play the game, what causes its results?  If your team wins (or loses), maybe your team just has better players (or worse players) compared with players on the other team;  or the results might be strongly influenced by your strategy, or the quality of your players' strategy-application during the game;  and other causal factors might significantly influence the results.

This table shows useful principles for thinking about an Actualized Strategy that is one factor in producing Results:

  Situation 
 + 
( Strategy + Strategy Application )
  → 
 Results   
  Situation 
 + 
 ( Actualized Strategy )  
  → 
 Results   
—  Experimental System  —
  → 
 Results   
 
The colors are symbolic.  Analogous to mixing pigment colors (with blue + red producing purple), a combination of "Strategy + Strategy Application" forms the Actualized Strategy that — along with all other causal factors (which I'll call the Situation) in the external context that a strategy-designer cannot control — causes the Results.   /   a summary:  The observed Results depend on the Strategy (could it be effective IF it's done well?) and Strategy-Application (is it done well?) plus the Situation (what other factors are operating in the overall context of strategy-application?).

Usually, many factors influence a Result, as in the basketball game.  Distinguishing between the effects of multiple factors is important when you are deciding — during a process of design to develop a strategy — whether to change an Actualized Strategy (by revising the Strategy and/or its Application) in an effort to achieve a better Result.

 

 

Actualization and Experiments — What are the connections?

In general design, obviously you cannot use an idea (for an option) in a Physical Experiment.  You must use an actualized option` that is a physically existing product, or an activity being done, or a strategy being used.

And a Mental Experiment will be more effective if you vividly imagine doing a Physical Experiment with an actualized option, with a physical product, or an activity (or strategy) that is being put into action.

 

Experimental Systems

To define an Experimental System — for a Mental Experiment or Physical Experiment — we combine two rows of this table (its left-bottom and left-middle) to form an equation:

Experimental System  =  Situation + Actualized Strategy
 

An experiment can be done physically (by using an Actualized Strategy) or mentally (by imagining what would occur with an Actualized Strategy).

In this equation, an "Actualized Strategy" is an "Actualized Strategy-Option" during a process of design in which multiple Strategy-Options are being generated and evaluated.  This broader perspective, within an overall process of design, is shown in the first equation below.  In the second equation, Actualized Strategy-Option is generalized into an Actualized Option for any type of objective, because (as in the bottom four equations) it could be an Option for a Strategy, Activity, or Product, or (in a different type of actualization) a Theory.

 
Experimental System  =  Situation + Actualized Strategy-Option
Experimental System  =  Situation + Actualized Option
 
Experimental System  =  Situation + Actualized Strategy-Option
Experimental System  =  Situation + Actualized Activity-Option
Experimental System  =  Situation + Actualized Product-Option
Experimental System  =  Situation + Actualized Theory-Option

 

This diagram begins with my defining-equation for an experimental system:

 

Experimental Systems = Situation + Actualized Options - used in Physical or Mental Experiments

 

Then it shows that:

an experimental system can be used in a physical experiment (to make observations) or a mental experiment (to make predictions), and

two inputs (experimental system and a system of theories) are used to make predictions in a mental experiment.