iou – Soon, during October 4-8, I'll write an introduction to explain why this section is optional so it's in a "gray box",  and I'll revise the entire section, although most of it (all parts except the introduction) will remain approximately as-is, without much revising.

three common Action Sequences – Part 2

iou – The beginning of this introduction (the part with gray text) will be revised – in fact, most of it will be deleted – because it was written before I decided to write the section above, so I want to minimize duplicating, and to coordinate the complementary ideas in Part 1 and Part 2.

These sequences occur because people intuitively do Actions in a logical sequence.  Below you see the middle part of Diagram 3, without the text (in boxes) at top & bottom, so the Actions begin

The shadings convert it into an “isolation diagram” that calls attention to some of the Actions.  The unshaded parts show a sequence that is common because when people finish one Action often the logical “next step” is to use the results from this Action in their next Action.

successive approximations:  When you did the explorations above (of Diagrams 1, 2, 1+2, 3) your understanding improved.  Then your knowledge grew deeper while reading about the flexibility of Design Process.  you have gained during your explorations 

the most common Action Sequence:  People (including you) often do this unshaded sequence because — after you "Generate Options" and "Choose an Option" that you want to Evaluate — the most common way to "Evaluate this Option" is to “DO and compare” when you DO a Mental Experiment (by imagining “what will happen”) to make a Prediction (it's "the results from This Action") that you use (in your "next Action") to Evaluate This Option when you compare Predictions with GOALS in a Quality Check.

three functionally-useful Action Sequences:

a reminder from earlier:  [ iou – This intro-paragraph will be highly condensed, it will be a brief summary of what I said earlier. ]

You don't have to “learn” these sequences because you already know them, you already are using them in your everyday life.  Therefore instead of learning you can just recognize that "Your Actions [that you now are using] are the Problem-Solving Actions you see in the diagrams of Design Process."  Why?  You're using these Action-Sequences because they're functionally useful in helping you make progress toward solving a problem, so they naturally occur when you're deciding “what to do next” to coordinate your Process of Problem Solving.

iou – Below here the sub-sections won't change much, because they're mostly ok as they are now.

Here are three Action-Sequences (⊡ ⊡ ⊡ ⊡ ⊡) that people often use:

⊡ ⊡ ⊡ ⊡ ⊡   As described above {and shown in the highlighted parts of left-side diagram below}, in one kind of Action-Sequence (⊡ ⊡ ⊡ ⊡ ⊡) after you   ⊡ Generate Options you   ⊡ Choose an Option {in a second ⊡-Action};   to Evaluate this Option you can {in a set of ⊡-Actions} DO a Mental Experiment to make Predictions, and {in a fourth ⊡} you compare these Predictions with Goals in a Predictions-Based Quality Check;   and maybe {it's an optional fifth ⊡} you "use QC" by asking "revise Option?" in a Design Cycle.

⊡ ⊡ ⊡ ⊡ ⊡   In another Design Cycle that has analogous ⊡-Actions,* you Generate & Choose, then to "Evaluate this Option" you USE a Physical Experiment {as in right-side diagram} to make Observations that you compare with Goals in an Observations-Based Quality Check;  and maybe you use QC and ask "revise Option?"    {* both Design Cycles have the Actions of...   ⊡ Generate,  ⊡ Choose,  ⊡ DO/USE to make,  ⊡ compare,  ⊡ use revise. }

⊡ ⊡ ⊡ ⊡ ⊡ ⊡   People can do Science-Design in different contexts.  Here I'll describe {and you can see in the center diagram} how you Test Your Theory during a project for General Design:   first, you  ⊡ Generate Options, and   ⊡ Choose an Option that you Evaluate in two ways, when you   ⊡ DO a Mental Experiment to make Predictions, and   ⊡ USE a Physical Experiment to make Observations;   then you  ⊡ compare the Predictions and Observations in a Reality Check and ask “am I surprised?” with The Science Question;   if you answer “yes” (because Predictions are not matched by Observations), maybe you will  ⊡ use RC by asking "revise Theory?" and if you decide Yes you will complete a Science Cycle by using Guided Generation to revise the Old Theory and Generate a New Theory;  but you may decide No because you checked the Reality Check and found errors in its Predictions or Observations, or due to the influence of Cultural-Personal Factors in your Goals for a satisfactory Theory.

In a complete Design Cycle with a Predictions-Based Quality Check the Action-Sequence is... Generate and Choose, DO-make, compare, use.	In a complete Science Cycle with a Reality Check your Action-Sequence is to Generate & Choose, USE-make, compare, use.	In a complete Design Cycle with an Observations-Based Quality Check your Action-Sequence is to Choose, DO-make+USE-make, compare, use.

These three common Action-Sequences (each is ⊡ ⊡ ⊡ ⊡ ⊡) — when you Evaluate in a Predictions-Based Quality Check,  Evaluate in a Reality Check,  Evaluate in an Observations-Based Quality Check — are highlighted (in areas that are unshaded & lightly shaded) in the three isolation diagrams.     { a reminder:  instead of Learning you are Recognizing. }

[[ iou – this duplicates some ideas in Part 1, but I think the ideas in this paragraph "add useful details" to the descriptions in Part 1, so maybe I'll leave most of this paragraph as-is;  and I might use some of the ideas in Part 1. ]]    Why are these Action-Sequences commonly used?  Because in each sequence “the next step” is functionally useful in helping you solve the problem.  How is it useful?  Because in Action-Sequences, including these & others, typically the sequence occurs when the result of one Action is used in the next Action.  For example, after you   ⊡ Generate one or more Options,   ⊡ you Choose an Option that you want to Evaluate;   ⊡ then with an Experiment you make Information (you DO a Mental Experiment to make Predictions, or USE a Physical Experiment to make Observations, or you do both), and   ⊡ you compare the Information you've made (it's the Predictions or Observations) with Goals (in two kinds of Quality Check) or with each other (in a Reality Check);   ⊡ then maybe you use this Evaluative Check to "revise" and Generate a New Option.   /   Then you can – as one alternative – decide to begin a new Action Sequence, when "first [after Generating Options] you Choose an Option to Evaluate."

The rest of this page is a collection of sections that can be read in any order.

iou  –  during September 28-30, I will continue developing-and-revising each section.  As sections become "ok for viewing" they will be moved upward out of this "gray box" that is only temporary.

Design Process is FLEXIBLE

timings are flexible:  This section supplements the flexibility of Design Process that says "this flexibility is always implicit, and it's occasionally explicit as when Diagram 1 begins with "Learn... before-during-after" and has opposing arrows ( ↓↑ ) between the stages of Define and Solve;  these two features communicate the principle that many timings* are not rigidly fixed."  The timing can be "before-during-after" because useful Learning can occur at any time.  And although Define usually precedes Solve (↓), occasionally (↑) you will decide to modify your Defining (for Objective or Goals) while you are Solving.  Design Process describes the usual timing (↓) but acknowledges (with ↑) the occasional timing, because what you usually do isn't what you always do.

* Although "many timings" are flexible, some are not.  Why?  Because in functionally-useful Action Sequences, "typically the sequence occurs when the result of one Action is used in the next Action" so the first Action must occur before its results are used in the next Action.

more – You can read a little more about the flexibility of our “similar but not identical” process, and much more with analogies about using a roadmap (for guided exploring) or a flowchart for actions;  or using music theory (for guided improvising of semi-harmonious melodies), plus the choosing-and-using of tools by a carpenter (or mechanic, electrician, plumber,...), and using simple Lego bricks (to build complex structures) or using simple atoms (to build complex molecules & materials), or using a flowchart to help you make

Design Process is flexible:  This flexibility is always implicit, and it's occasionally explicit as when Diagram 1 begins with "Learn... before-during-after" and has opposite-direction arrows ( ↓↑ ) between the stages of Define and Solve;  these two features communicate the principle that many timings are not rigidly fixed.  In this way and others, Design Process has flexibility;  but it also has a logical structure that gives it descriptive generality so it's able to accurately describe a Process that "is similar for almost everything we do."  These characteristics – flexibility, plus structure & generality – appear to be “in tension” yet they do coexist.  How?  You'll see this in the next section, when you see the logical flow-of-actions in three common Action Sequences.  And explaining why is because the best answer is “No and Yes” when we ask “is there a ‘method’ in Scientific Method?” or ask “is there a ‘process’ in Design Process?”

overlaps-in-timing occur with a mixing of interactive modes.  This is why Diagram 1 has two arrows, ↓↑ , between its top and bottom parts, between the long-term phases of Define a Problem (Learn, Define, Define) and Solve the Problem (Generate, Evaluate).  These two arrows show that although the actions in Define a Problem usually occur early in a process of design (symbolized by the down-arrow being larger), any of these actions — especially to Learn more, but also to re-Define Goals (if this seems useful while you're Solving the Problem, as when [in New] you “recognize what you want when you see it” or you imagine it -- or remember in Old) or to re-Define your Old Objective by revising it — also can be done later.  Or you may want to Define a New Objective (that is "New" because it's very different than your original Old Objective) so you have Defined a New Problem, either instead of the Old Problem or in addition to it.

learn always, in all ways (w broad defns of ALL)

{another question:  What are the benefits when you "Learn... before-and-after you Define your Objective and Define your Goals"? }

Stage A:  Learn before-during-after you Define:  Why should you "Learn... before-during-after you Define your Objective and Define your Goals"?  Because when you Learn-and-Think about your Now-Situation, this will help you decide whether “the best use of your time” is to define a particular PS-Objective (and pursue its PS-Solution) or define another PS-Objective.  You do this Learning before you Define your Objective-and-Goals.  Then during-and-after you Define, your Learning will help you to creatively imagine an optimal Goal-Situation, and to design a better PS-Solution because you "understand more accurately-and-thoroughly."    [ iou – during July 22-31, I'll improve this description. ]

LAKEIN -- • when you learn more before & during the time when you are Defining your Objective for Problem Solving (for PS):  You can "make things better" in many ways, so you have many competitive PS-Objectives to consider.  If you know more about a particular Problem-Situation (and competitive Problem-Situations), this will help you decide whether “the best use of your time” is to choose a particular Problem as your Objective (and to pursue this P-Solution) or to define another Problem as your Objective.

ALSO (elsewhere?) -- Your Actions of Making Decisions – for “what to do next” and for other things – is important in all stages, but especially in S2 when you choose An Option to be The Solution.  (or for some Problems, to be one of The Solutions)   This happens when you compare An Option's Actual Properties (Predicted or Observed) with Desired Properties (defined as your Goals) and you decide the match is “close enough to be satisfactory” even if it isn't a perfect match.     { more about Decision Making in Problem Solving }

TENSION -- flexibile + generalized Process-for-all/all

in dph#dpmoseq2, @dph#flex for defending claims about combo of flexible+structure/generality

  ----- [summarize this] In this way and others, Design Process has flexibility;  but it also has a logical structure that gives it descriptive generality so it's able to accurately describe a Process that "is similar for almost everything we do."  These characteristics – flexibility, plus structure & generality – appear to be “in tension” yet they do coexist.  How?  Explaining this is a major theme in "using Action Sequences" below.  And in describing why the best answer is “No and Yes” when we ask “is there a ‘method’ in Scientific Method?” or ask “is there a ‘process’ in Design Process?”

Flexibility in Timing:  Defining and Solving are not rigid “steps” because Design Process is not rigid.  It's analogous to the flexible goal-directed improvising of a hockey skater, but not the rigid choreography of a figure skater,

LATER in h.htm or home.htm, @dph.htm#flex2 -- DP doesn't show a rigid directionality as with a one-way valve

< using Old and New:

Diagram 3 says "GENERATE Options (Old or New) for a Solution" because you can Invent a New Option, or maybe – instead of “reinventing the wheel” – you will Find an Old Option and “use a wheel” (as-is or modified) if this will be an effective Problem-Solution.  Both of these Actions, by Inventing or Finding, are ways to Generate an Option.

More generally, Old Knowledge (that already exists) can include Options (for a Solution or Theory) and also Problem-Situations & associated Solution-Goals;  plus Experimental Systems (Mental or Physical) & associated Predictions or Observations.

You get Knowledge from Experiences, and your Total Experiences — in your First-Hand Experiences (happening to you) and Second-Hand Experiences (happening to others, but known by you) — include Knowledge that is Old (it's remembered in your personal memory or is found in our collective memory that is “culturally remembered” with books, web-pages, audio & video, etc;  or it's learned directly from another person) and is New (is being experienced now in your sensory perceptions & your thinking-and-feeling, is both conscious and subconscious).     { finding-and-using Old Knowledge is Mode 2A in the 10 Modes of Action }

combining Old and New:  You want the best of both, for productive thinking that effectively combines relevant knowledge with creative thinking and critical thinking.  You want a solid foundation of knowledge about what has been & now is (the Old & Present) plus flexible thinking that lets you freely imagine what could be (the New & Future).  During your Process of Problem Solving when you're trying to Design a Satisfactory Solution, this combination lets you consider the full range of Old Options AND expand this range by creatively inventing New Options.   /   How?  By using five Thinking Strategies Thinking Strategies for creatively using cognition-and-metacognition to Generate New Options. Thinking Strategies to Generate New Ideas.

Predictions and Observations

< how people make Predictions:

inductive reasoning:  The most common way for a person to predict — it happens every time you “imagine what will happen” so Diagram 3 explains that “by imagining a Situation” you "make Predictions" — is by using logical experience-based induction.  You do this by assuming that “what happened before (in similar situations) will happen again.”  Asking “what is similar (in previous Situations & the current Situation) and what is different?” will help you do better Predicting, and have a level of confidence that is more appropriate.

deductive reasoning:  But in some Situations a person uses logical theory-based deduction.  How?  Based on a Personal Theory (that often agrees with a Scientific Theory, but not always)* you use if-then logic by thinking “if My Theory (about how the world works, and what will happen) accurately corresponds to reality and what I expect to occur does occur, then       will happen” and you fill the blank with your Prediction.    {more about deductions}

deductive-plus-inductive:  People usually combine these two kinds of logic (inductive & deductive) when we make Predictions, with the balance differing from one Prediction-Situation to another.  This also happens in computer simulations — in forecasts for weather or climate;  for football (in predictions about games, pre-game analysis of videos & data,...);  with GPS (in suggestions for routes, predictions of ETA's);  and in other simulations — that use a combination induction-and-deduction, with the balance differing from one kind of simulation to another.

things we predict :  Obviously people predict “what will happen” or (more accurately) “what probably will happen” and you use these Predictions in Reality Checks.  But in "what will happen" the "what" often predicts the characteristics of an Option that is being Evaluated (in a Quality Check) as a possible Problem-Solution.  And when your objective is to design a Strategy – especially when it's a Strategy to improve a Relationship – you may predict the behaviors of people, of yourself or others, or both.  Or during Experimental Design you can predict “what might happen” and “what could be learned” if you do an Experiment.  And there are other possibilities, like those described in a research report about these four paragraphs that I will format – by writing a Table of Contents and making links (in that page and in this section) – during September 23-25.

how you make Observations:

When you DO a Mental Experiment "by imagining" you always "make Predictions."  By contrast, a Physical Experiment just "lets you make Observations" because sometimes you USE the Experiment to make Observations, but you don't have to do this, so you don't always do it.

How and What?  In some Experimental Situations you can make Observations directly with your internal human senses (to see, hear, touch, taste, smell) and/or indirectly with external measuring-instruments (a ruler, weighing scale, watch, thermometer,...).  These two source-types let you get information that is qualitative or quantitative, can be represented verbally (with words,...) or visually (in graphs, photos or videos,...) or mathematically (with numbers, equations,...) or in other ways.

[ I'll

simultaneously Observing-and-Predicting:

This occurs continuously in your everyday life because your Actions can be mainly (but not only) Mental, or mainly (but not only) Physical, or plenty of both with Physical-plus-Mental.

It will be easier to understand the what-how-why by thinking about examples from “ball sports” like basketball, football, and soccer.  A basketball player who has the ball is making Observations (about where all players are now) AND is making Predictions (about where they will be soon) that are being compared with Goals (in Quality Checks) so they can make an Action-Decision about where to pass the ball, or to dribble it or shoot it.  A skilled player can do the Problem-Solving Actions in Diagram 3 very quickly (in their system of subconscious-plus-conscious) so they can make a quick Action-Decision that is likely to be productive.  At the same time, all other players (offensive & defensive) are Observing-Predicting-Comparing so they also can make productive Action-Decisions about where they will move and what they will do.

In your everyday Actions, you do similar “simultaneous Observing-and-Predicting” in a wide variety of different ways.

Defining Goals

Defining Goals is special kind of "Prediction" (actually it's "Predicting" because it isn't true Predicting but has many similarities along with a key difference), not Predn for probab of happening, but for imagining the desirability of future Goal-State state IF it happens. / true Predn --> WHAT might happen + PROBAB (HOW LIKELY)

into #eae

With a broad definition of Experiment most of your everyday Experiences involve Mental Experimenting and/or Physical Experimenting.  The "and/or" includes "and" because people often do both kinds of Experimenting simultaneously. / pure Mental (common) but pure Physical (uncommon, usually is Physical-plus-Mental, P-and-M, @ws#dpmo-Intro for Actions, M P M-and-P)

Experiments produce Experiences

<< In the context of Design Process, an Experiment is any situation that produces Experiences and provides an opportunity to generate Experimental Information when you make Predictions (by imagining in a Mental Experiment) or you make Observations (during the actualizing in a Physical Experiment);  i.e. any Prediction-Situation is a Mental Experiment, and any Observation-Situation is a Physical Experiment.  Therefore instead of seeing "Experiment" (in Diagrams 2 & 3) and thinking “I don't do experiments,” you can recognize that most of your daily Experiences do involve Mental Experimenting and/or Physical Experimenting.

Experimental Design

Designing Experiments is a useful skill.  A general strategy for inventing new Experimental Systems (E-Systems) is to creatively Generate Options for many possible E-Systems and “run them” in quick-and-easy Mental Experiments — to imagine “what kinds of things might happen, and what could we learn that might be interesting or useful” to make Predictions — and maybe Choose an E-System to actualize in a Physical Experiment.  And you can learn about old E-Systems, and choose to actualize one of them, as-is or modified.  Or shift from this divergent search to a convergent search with focus, by asking “what do I want to know, and what Experiments will help me get this Information with useful Predictions or Observations?”

And for learning that is deeper and wider,

h.htm#levelsexp    ws.htm#dp4exp #dpmo2c    dp-xp.htm#i    my PhD work (in science.htm & details.htm-ToC)

information — these topics (and others) are examined in Mode 2A and Mode 2C.

You do a wide variety of Experiments (for Science, Design, and in other areas of life.

You can do a wide variety of Experiments, with “Science Experiments” and “Engineering Experiments” + “Design Experiments” and Other Experiments.

The objective of Experimental Design is an Experimental System that (as explained in Stage 4 of Design Process) is an Option-in-a-Situation for General Design, and a Model-Using Situation for Science-Design.

As with all design, when you are Designing Experiments you use iterative Cycles of Design to creatively Generate Options for Experimental Systems (by finding old E-Systems in personal or collective memory and by creatively inventing new E-Systems), and critically Evaluate these Options.  Then (as in Diagram 4a`) you "Choose an Experimental System that you can run mentally and/or physically" when you "imagine in a Mental Experiment" and/or "actualize in a Physical Experiment".

Early in a process of Generating-and-Evaluating, you imagine different options-in-situations (= Experimental Systems) and ask “if we do this, what kinds of things might happen, what would we observe, and what could we learn? could this new information (from Predictions or Observations) be useful for the project? or at least interesting?  could it be a crucial experiment that helps us distinguish between competing Model-Options, or competing Solution-Options?”  This early phase of mental imagining is a creatively divergent search, a quick-and-cheap way to consider a wide variety of System-Options.  Then you can decide whether, for some Experimental Systems, you want to invest more effort in a careful planning of details (re: how to control its variables, what to observe and how), or making Predictions that are more thorough and precise/accurate, or shifting to Physical Experiments that usually require larger investments of time and money.  Or you can build a prototype of an Option (what+how and why of proto-typing) to use for quicker/cheaper physical experimenting.

Experimental Design

improve your Designing of Experiments

the skill of Designing Experiments:

EMPATHY -- People are somehow involved in most projects for General Design (when your objective is a product, activity, relationship, or strategy) so designing an E-System that lets you gather human feedback – by asking “what do you think?” or observing behaviors – provides valuable information that will help you think with empathy so you can more thoroughly-and-accurately understand other people.  And when you're designing metacognitive Thinking Strategies for yourself, you'll want to improve your understanding-of-yourself with self-empathy by using cognitive/metacognitive observations of the situation, your actions, and the results.   /   also:  When you are observing another person, trying to understand what they are thinking & feeling – as when a teacher wants to provide wise guidance – maybe it's useful to think of your actions as external empathetic metacognition.   {it's external and empathetic because your goal is to understand another person, and it's metacognition because you're thinking about their thinking}  {relationships between empathy & metacognition – can we have self-empathy & do other-metacognition?}

and in and/or --> player in most "ball sports" (eg QB or Point Guard, any soccer player) with real-time processing

* It's also useful to choose broad definitions for Problem and Problem Solving, and to broadly define education as learning from life-experiences.     { more about Experiments-and-Experiences }

LIFE --> experiences so you can learn from experience

DESIGNING YOUR LIFE

designing Experiments and Experiences

designing your Experiences and Life (Experiences-and-Life ?)

from ws#dpmo2cde, an also @ Action Sequences ---- In any process of design, whether the problem-solving objective is to design a Solution (in General Design) or an explanatory Model (in Science-Design), experimenting (mentally & physically) is a focus for many modes of action, in 2C-2D-2E, 3A-3B, 2A-2B, because...

designing your life-experiences ---- to broadly define education as learning from life-experiences, i.e. learning from the life-experiments you choose and that "happen to you" due to external causes. internal + external, choice and not, voluntary and forced // @Lakein's Question, use of time

causation internal & external, you cause or don't or partials

connect with old/new ---- more:  If you want to do optional explorations — of how your total experiences include your first-hand experiences (happening to you) and second-hand experiences (happening to others, but known by you), and include what is old (is being remembered in your personal memory or found in our collective memory, in what is “culturally remembered” with books, web-pages, audio & video, etc) and is new (is being experienced now in your sensory perceptions & your thinking-and-feeling), and the causal relationships between experiments & experiences;  plus logically designing Experiments (everyday or scientific) so they will provide usefully-relevant

education is learning from experience:  In the past, when I've made a mistake and then asked “why?” my answer often included “ineffective process” because I had not done some Problem-Solving Action(s) effectively.  Therefore – in an effort to grow by learning from experiences – I've found it beneficial to develop-and-use a Metacognitive Checklist for Problem-Solving Actions.  And others (you, students,...) also can benefit from developing-and-using a checklist to improve their process of problem solving.

two related goals – for proactivity and thus consistency:  When you use metacognition proactively (with a checklist and in other ways) by “paying attention” throughout your day, usually this will help you perform more consistently so you can “do things better {in your present moments}” instead of thinking “oops” and asking “why {during past moments} did I make the mistake?”

LAKEIN'S QUESTION - dpmo1a

choose to use:  Many times during every day, Your Defining-of-Objectives is an important part of Your Daily Living.  You can “make things better” in many ways, so you have many different Choices of An Objective (for The Problem To Solve, for What To Make Better) but your time is limited.  Therefore when you ask “what is the best use of my time now? and later?” you always want to choose well because as Ben Franklin wisely advised, "do not squander time, for it's the stuff life is made of."  One option is to “change directions” by deciding to...

delay or stop:  Instead of continuing until you Solve The Problem, you can decide to delay working on this problem-solving project for awhile, so you can use your valuable time in other ways, and maybe get the benefits of creativity-stimulating incubation.*  Or you can decide to stop working on the problem, to abandon it ;   or instead of an explicit decision to stop, “other things keep happening so life keeps you busy” and you never return to working on this problem.

using Science-Design

although m-exp more common, sometimes p-exp more important because P's can be wrong, --> need for RC's

iou – Currently this section is just a detailed outline of ideas that will be developed-and-revised during September 23-27.

Here are three contexts for using Science-Design:

     • during General Design:  You use a functional Reality Check (in a functional check of a Theory that's being used to make Predictions) when you are "surprised" because Predictions are not matched by Observations, during a Project for General Design.

     • in Everyday Science:  in a Project for Science-Design, when during everyday life a Theory is being Evaluated by a non-expert.  Or in a classroom, when a teacher designs POE Activities so students can Predict-Observe-Explain and Learn.

     • in Professional Science:  in a Project for Science-Design, when a Theory is being Evaluated by experts.  They...  can work in academia or business;  publish in research journals (for science or medicine);  do Experiments and apply for research grants,...

checking a Reality Check:  In any context, instead of responding to a failed Reality Check (with Predictions ≠ Observations) by simply concluding “my theory is wrong” you can examine each thing that's involved in the Reality Check, because the lack of close matching could be due to errors in...  • the Predictions (in the Inductive Logic or Deductive Logic);   • the Observations (in Designing the Experiment, Doing the Experiment, or Making Observations);   • the logic of comparing Predictions with Observations;   • the Main Theory (used to make Predictions) or Supplementary Theories (that also are used).  All of these possibilities can be considered when you ask “why was the matching not closer?”

Students use scientific reasoning often in life, whenever they hear a claim and ask “what is the evidence-and-logic supporting this claim?”  In all areas of life, they can use Science to improve their Theories about “how the world works” and improve the accuracy of their Predictions about “what will happen.”  And they can develop a logically appropriate humility – with justifiable confidence that is not too little, and not too much – when estimating the plausibility status of claims for truth claims for truth that are made by themselves and by others.  In these three ways, their better understandings will help them make wise decisions while pursuing their goals in life.

but this can lead to AD HOC Theory-Revisions, rationalizing to ignore an unwanted failed Reality Check

• psychology:  wanting to reduce the unpleasant cognitive dissonance they feel when they recognize an inconsistency between two personal theories, or two personal actions, or a theory and action.     reduce our cognitive dissonance. 

• sociology:  wanting to maintain their status (or improve it) within a personally-important group, if almost all group members believe a Theory;  in this context, they are motivated to also believe this Theory (for loyalty signaling that is virtue signaling?) to retain current allies or gain new allies, to "win victories for us" in battles of us-against-them.    (@da-ur.htm#mr)

Evaluation Criteria that can be Goals for the desired characteristics of a satisfactory Theory.   /   @my PhD work, ISM with three kinds of — Empirical Factors (in Reality Checks), Cultural-Personal Factors (e.g. the psychological & sociological factors above in Everyday Science; these also occur in Professional Science, plus others, e.g. getting funding for research grants, getting publications in research journals & getting tenure; for these, just @ws.htm#sp and sp-cr.htm)

using Science-Design (with Reality Checks) during General Design

move this into h.htm#rc2, and just @ here?

We rarely do Science-Design .  We rarely design an Experiment to intentionally test (and possibly falsify) one of our many theory-beliefs about “how the world works,” because we usually don't want to discover that one of our beliefs is wrong;  each of has a psychological preference for retaining our current beliefs.  We often don't want to change a belief so we find ways to defend the belief, even if a Reality Check indicates that we should change it.  Why?  In some areas of life – especially areas that are personally important – we resist change due to a psychological motivation of wanting to reduce our cognitive dissonance.  But even if we don't intentionally test our beliefs, we often “do science” unintentionally while we're trying to make things better (with General Design) when we Predict-then-Observe and are surprised when they don't match, in an unplanned Science Question.

cut from earlier main section -- that is aka The Reality Question when we do Science-Design during General Design or in other contexts.   that also can be called The Reality Question.     {testing a theory as sub-Objective?  we can do Science-Design during General Design [dph.htm#rc] or in other contexts [dph.htm#rcds]  ---- when we do Science-Design during General Design or in other contexts.

[ use in #m3a2 ?  ---  Science-during-Design:  Design Process accurately describes the common way we use science-and-design together.  Our everyday “science during life” is naturally explained by the integrative structure of Design Process because the central core of its evaluative logic (when 3 Elements are used in 3 Comparisons) shows the way we naturally do both General Design (aka Design, the usual term) and Science-Design (aka Science, usually) together.  By contrast, most other models-for-process describe a process of either Design or Science, but not both.  The smooth integrating of Design-AND-Science (in Design Process) will help students develop a smooth integrating of Design-AND-Science (in their thinking) while they are solving problems.

{ Why do we use Reality Checks most often during General Design for a Reality Question, not during Science-Design for a Science Question? }

why is there a "?" after revise in "revise?"

Why?  When you "revise Option" you will Generate a New Option that usually (but not always) is similar to the Old Option.  But instead you may want to

* When you're motivated to design a better Problem-Solution (with a better match between Actual Properties and Desired Properties) so you ask "revise Option?" you have reasons to say Yes (as explained above) but also to say No.  Why?  One reason is if you think that instead of Generating a similar New Option (by revising an Old Option) you want to try Generating a New Option that is "more different"

and (to show that the have two arrows, these are intended to show the model's flexibility, because (with "before-during-after") (showing that timings are not fixed with an "first do this, then do that" rigidity) to indicate that timings are not a fixed "first do this, then do that" that   and it's always implicit. 

and why I call it Science Process

inherent tension between structure and flexibility is explicitly described below in my descriptions of Action Sequences, which . 

iou – many kinds of science: @ws#trsci-->h#trsci(sci-vs-Sci);  here it's best to imagine it's for your use  • during General Design (RC to Check own T used to make Predns);  to check T's of Science (in School, in Profession);  to Check T's in everyday life

ask "revise Theory?" in a Science Cycle by using Guided Generation that in Science is Retroductive Generation.

we can use Design Process for

Cognition & Metacognition, during

Problem Solving & Self-Regulating

The HomePage explains how Design Process can be used for cognition (and thus for metacognition) in Problem Solving (and thus for Self-Regulating).  Research has due to the widespread use of Self-Regulated Learning (SRL) to teach metacognitive Self-Regulation;  scientific research has shown that SRL is very effective for helping students improve their academic skills (in a wide variety of ways) and their social-emotional skills.

Here I'll let you discover how its cognitive Action-verbs — learn, define & define, generate, choose,... (used for Problem Solving) — can be supplemented with other cognitive Action-verbs (plan, monitor, observe, re-plan) that we use for Metacognition.   /   A teacher can use this modification of Diagram 1* in Design Process (DP) to help students develop-and-apply the metacognitive thinking strategies of Self-Regulated Learning (SRL), when they teach SRL-with-DP.     { * it's DP that is modified for teaching SRL so it's DP-for-SRL }

To understand this diagram by self-discovering, you can ask-and-answer questions about the...

meanings & objectives for colors:  What are the symbolic meanings of the color-codings for blue and green?  i.e. What is the “mode of action” for all blue Actions, and for all green Actions?  And what is the purpose (the Objective) of the blue Actions, and the green Actions?   /   Also think about “what and why” for the other colors, for the purple, red, and brown.

experiments and cycles:  Why are there multiple Mental Experiments in the Mini-Cycle (to Generate-and-Evaluate by using Predictions-Based Quality Checks), but only a single Physical Experiment in the Overall Cycle (to Generate-and-Evaluate, using an Observations-Based Quality Check)?   And which two terms can occur due to Reality Checks during the Physical Experiment?

Although you probably don't need it, these questions are “answered” with my explanations in the HomePage, along with other comments about SRL-with-DP.    [ iou – They will be answered during October 1-4. ]

BROAD DEFINITIONS

@home.htm#ps -- #ob -- #teaching

problem & problem solving -- education -- experiments (pred & obs) science/Science & eng/Eng -- theory (+ model) -- put into WHITE BOX

the educational benefits of using broad definitions

I use broad definitions because it's educationally beneficial.  How?  The main benefit is that with broad definitions for problem (it's any opportunity to make things better in any area of life) and problem solving (it happens whenever we do make something better), almost everything we do is a problem solving.  In this way, broad definitions (for Problem & Problem Solving) lead to a broad scope (for Problem-Solving Activities);  and this helps us produce many benefits for students by increasing transfers of learning (between areas & through time) and by building bridges (from school into their lives) that improve their motivations & confidences.

One way to actualize the wide scope, --> perceptn/internalizn by stus

A broad definition of engineering (even wider than in the NGSS Standards) will help us integrate education for STEM & non-STEM in a wide-spiral curriculum that will encourage more students to broaden their perspectives so they become open to “careers in STEM” when they improve their self-image, reduce the self-limitations on their personal goals, and this will improve educational equity.

definitions that are broad in NGSS Science Standards  -- in order to "emphasize practices [used in engineering] that all citizens should learn – such as [a list of useful practices] defining problems in terms of criteria and constraints, generating and evaluating multiple solutions, building and testing prototypes, and optimizing – which have not been explicitly included in science standards until now."

I agree -- and are even broader in Design Process -- parallel structure but shorter

In a useful broad definition, an Experiment is any situation that produces Experiences and provides an opportunity to make Predictions and make Observations;  i.e., any Prediction-Situation is a Mental Experiment, and any Observation-Situation is a Physical Experiment.

With a broad definition of Experiment most of your everyday Experiences involve Mental Experimenting and/or Physical Experimenting. 

DP -- 3 contexts for doing Science-Design: Reality Checks during General Design; in everyday thinking (ws#trlife); for sci (eg POE in k-12) or profsnl-Sci

          broad defn of Theory (connects/communicates)

expmts-and-experiences, Preds & Obs

education + expmts/experiences

And it lets us build two-way educational bridges between school and life, to increase the motivations of students.  Because solving problems (by making things better) is useful in all areas of life, improved problem-solving skills are useful in all areas, producing (with widespread agreement) many benefits that improve our quality of life.

what?   With educationally-useful broad definitions, a problem is an opportunity to make things better in any area of life, and problem solving happens when we do make something better.   /   Yes, this differs from a common perception that a problem always begins with “a bad situation” because with my definition your feelings about the current now-situation could range from dismal thru lukewarm and wonderful to awesome.  If your actions produce a “move toward a better place” anywhere within the wide range — whether it's a change from dismal to lukewarm, or from wonderful to awesomely spectacular — it's problem solving because the situation has become better.

why?   People solve problems because we want to make things better.  Or we want to avoid letting things get worse, because we can make things better by increasing quality or maintaining quality, by either promoting a helpful change or resisting a harmful change. 

what?   We begin a Design Project (it's a Problem-Solving Project) by asking “what do we want to make better?”  With this decision, we Define an Objective by choosing to design (to invent or modify or find, or find-and-modify) a better product, activity, relationship, and/or strategy (in General Design) and/or (in Science-Design) a better explanatory theory to answer questions about “how things work in the world” and thus “what happens & why it happens” to help us understand the how-what-why of reality.  These objectives – extending far beyond traditional “design fields” – include almost everything we do in life.     { more about the wide variety of objectives }

BROAD DEFINITIONS in Problem-Solving Education

Why are broad definitions useful for Problem-Solving Education?

By using BROAD DEFINITIONS (of problem & problem solving, education & experiment)* we can help students discover that their problem-solving experiences include almost everything they do in life.  This WIDE SCOPE lets us build two kinds of educational bridges — between life & school, and between subject areas in a wide-spiral curriculum — to improve transfers (of ideas-and-skills) and transitions (of attitudes).  By building-and-using these bridges, we can help a wider diversity of students (for better educational equity) by giving them a wider variety of experiences, and showing them how to learn more from their experiences, to improve their attitudes (confidence, motivations,...) and problem-solving skills in all areas of life.

* This homepage begins with definitions — of problem {as any opportunity to make things better} and problem solving {whenever you try to make things better, in any area of life} and education {it's learning from your experiences (in all areas of life, not just in school) so you can improve, so you can be more effective in making things better} — and continues with my broad defining of experiment {as any situation that produces experience, that lets you mentally make predictions or physically make observations, so an experiment is any prediction-situation or observation-situation, which includes almost everything in your own first-hand experiences and in the second-hand experiences of others}. 

Each of us is a learner, and (in many situations) a teacher.  Broadly defined, you are being a teacher whenever you help another person get more life-experiences, and/or learn more from their life-experiences, whether or not you're doing this consciously, whether or not you're doing it as your profession.  And if you are a professional teacher, you'll have many opportunities to help others learn more.   {my goal for this website is to help you teach more effectively, so == iou [to be continued]}

more:  It's educationally useful to combine broad definitions with the simplicity of Design Process* so we can more effectively show students the WIDE SCOPE of problem-solving experiences.  Later, when we help them learn-and-use the symmetry of Design Process (with analogous Mental Experiences & Physical Experiences) we are helping them develop a deeper UNDERSTANDING of their problem-solving process, and this Understanding also (along with Wide Scope) promotes transfers of ideas-and-skills in school* and into everyday life.

EXTRAS  —  The main benefits of broad definitions are summarized above.  Other benefits & broad definitions are examined in other parts of the website:  My broad definition of strategy (it's one kind of problem-solving objective, along with products, activities, relationships, and explanatory theories) includes all of the decisions (small & large, in personal and professional contexts) that you frequently make in everyday life.

* With a broad definition of design thinking, students frequently use a creative-and-critical process of design thinking — a Design-Thinking Process (a Design Process) that is Problem-Solving Process — whenever they DEFINE a Problem and try to SOLVE the Problem by creatively Generating Options (for a Problem-Solution) and critically Evaluating Options, in iterative Cycles of Design.If we broadly define our goals (for the performing & learning & enjoying of students) this can stimulate creativity in our goal-directed designing of curriculum & instruction.

MORE — Below, each title (Theories, Models,...) is a link that lets you learn more in the longer summary for Mode 3B.

Theories:  When scientists are doing science-design (aka science), usually their intended meaning for Theory is an Explanation that has wide scope (a large application-domain) and strong support from evidence-and-logic.  More generally with an educationally-useful broad definition, a Theory is any attempt to understand “how the world works,” and we use our theories (scientific & personal, about a wide range of situations in life) to help us make wise decisions in life.   /   In education, teaching both definitions (explaining their similarities & differences) offers many benefits — so we should teach both definitions — especially for transfers of learning from school into life.  Here in Mode 3B, I mainly use the narrow scientific definition, but elsewhere I also use the broader general definition that often is more useful for communication and for education.   /   an update in 2025:  I've begun using a broad definition that "is more useful for communication and for education."  Therefore in the context of Design Process a theory is “a personal theory” about how the world works, which may or may not be consistent with the theories of mainstream science.

Models:  In science, Theories and Models are similar when both describe the composition-and-operation of an Experimental System (E-System).*   But in science they can differ in status (usually high for a Theory, ranging from low to high for a Model) and scope (usually narrower for a Model, especially when a System-Model is constructed by applying a general Theory to make a Model for one E-System, or one type of E-System).  Often, a Theory is simplified to form a Model, and the same Theory can be used in Models with different inclusions/exclusions, simplifying approximations, and representations.  Or models can be formed in other ways, as with experience-based inductive reasoning that "what happened before, in similar situations [for similar E-Systems], will happen again."

Model-Representations:  Our external representations of a Model can take many forms, with each being useful for different purposes.  And each of us personally constructs our own Mental Models that are internal representations of a Model.

* theory & model both have a wide range of definitions, in Science Standards and elsewhere.

due to the relationship between my two goals for Design Process — I want it to be educationally useful, and to be useful it must be descriptively accurate

from ws.htm#dp -- my goals for Design Process:  My model of Design Process – which includes Science Process because science is a special type of design – is intended to be useful for description (to accurately describe the problem-solving process of design) and for education that will help people, in schools & outside, improve their understanding and (more important) their performing, so they can

• understand, more accurately & thoroughly, the process of thinking-and-action they use in design and science;

• perform, more effectively, when they are solving problems (in design) and answering questions (in science).

The remaining ideas are "cuts from earlier sections" that will be used elsewhere in the website:

Skillfully Coordinating your Process of Problem Solving

[ Actions = cognitive tools, MC is used to optimize (maximize, improve) tool-choosing wisdom and tool-using effectiveness ]

* In a simple model for problem solving, you choose an Objective (for what you want to improve) and understand “what is” in the NOW-State, and imagine “how it could be better” in a future GOAL-State.  Then you do “problem solving” to convert The Now-State into a Desired Goal-State.    /    I found this Old Model – it's “public domain” (is not part of Design Process) – by searching our collective memory.  Its simplicity gives it practical cognitive utility and educational value.     { terms:  a Current Situation & Future Situation also can be called Now-State & Goal-State.   And other terms are possible. }