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10 Modes of Thinking-and-Action in Design Process

I recommend first reading the summary` of this page.

Two Levels of Skills — Individual and Whole-Process

An Overview of Design Process` ends with the 10 Modes, explaining why "the modes are not steps" and how to use the modes for teaching, and listing the 10 modes in 4 categories (define, generate, evaluate, coordinate) to provide a quick overview of the thinking-and-actions used in Design Process.

The Overview — which shows, visually & verbally, a "big picture" of the logical framework — is supplemented, in this page, with details that will help students master individual skills in each mode, and improve their whole-process skills when they develop-and-use Coordination Strategies for making action-decisions (by asking “what is the best use of my time right now?” and “what should I do next?”) to produce an effective flow of thinking-and-actions during an overall process of design.

words and numbers:  The modes can be labeled using words ("Choose an Objective,"...) or numbers (1A,...), or both.  The benefits of using only words, or words-and-numbers (with numbers identifying the mode-category, 1 2 3 4) and sub-category (1A, 1B and 2A,...), are discussed in Mode-Words & Mode-Numbers.  This page will use both, but most mode-numbers (all except those in section titles) are in aqua font, which makes it easier for you to think about them or ignore them, whatever you think will be most useful.

1A — Choose an Objective

Grounded in your knowledge of what is, and inspired by thinking about what could be, you Choose an Objective by deciding what you want to design. 

Recognize and Decide:  To begin a Design Project, you must recognize a problem (it's an opportunity to make things better` by designing a better product, activity, strategy, or theory) and then decide to pursue a solution because — after you have carefully considered the potential benefits and probability of success, evaluating these compared with alternatives (the other ways you could use your limited resources of time, money, and people, plus available knowledge & technology) — you make a strategy-decision that “yes, this design project will be a wise investment of resources.”

1B — Define Goals for a Solution

Define your Goals for the desired properties of a problem-solution that is ideal, or is at least satisfactory, by asking “What do we want?”

It's useful to think about two types of properties:  the desired characteristics of a solution (i.e., of what we hope will be a better product, activity, strategy, or theory) and the constraints on a project (for its process).

  • If the design-objective is a product, ask “what characteristics should the product have, for its composition (what it is), functions (what it does), and performances (how well it does the functions)?

  • To define characteristics for an activity, ask “what, who, when, where, and how” in the context of “why”.

  • For a strategy, ask “when the strategy is actualized by converting it into action,* what results do we want?”   /   * Therefore, also ask “do we have the skills required to actualize the strategy well enough to get these results?” }

  • The goals for a theory are examined later, in Theory Evaluation.

In addition to specifications for these characteristics of a solution, your Goals for desired Properties also include practical constraints on a solution (for its production cost, selling price,...) and on the process of design, including budgets for its use of resources (people, time & wages, capital investments,...) and deadlines (or sub-deadlines during the project) for dates of completion.

Thinking with Empathy is useful in all phases of a Design Project, especially in Modes 1A & 1B.

A Wider View of Objectives  (in Mode 1A)

Consider the Big Picture:  For each design project, try to imagine the entire project-process from beginning to end — asking “what will be required at each stage of the process?” — and define the stakeholders that you want to consider when making decisions in your project.

Quality Control for a Problem-Solution:  In most design projects, a problem-Solution must be actualized by converting it from an idea into reality, which occurs when you make a product, do an activity, use a strategy, or apply a theory.  At some point in a process of design (at the beginning or later, maybe after you have chosen a problem-Solution) your goals (in 1B) can include criteria for Quality Control to help you control (observe-and-improve) the quality of actualization for a Solution.

Quality Control for the Process of Design:  Think about the entire “big picture” for the process-of-design during your project, and decide how you can improve its actualized quality.  You can try to improve the quality of thinking-and-action within each mode and the coordination between modes to achieve goals of using your time more effectively and finding a better solution.    {Coordinating a Process of Design}

Sub-Objectives for Sub-Projects:  To achieve your overall objective in a project, often you must achieve sub-objectives in sub-projects.  One example is...

Communication:  In many projects, actualizing a solution will require communication (so it becomes a sub-objective)* in order to sell the solution, or explain it, or for other purposes.  And, of course, members of a design team will communicate with each other during a process of design, to improve their collaboration.   /   * Communication is an activity guided ==

view only this page -  put into left frame     ATTENTION !    The sections above and below – about EMPATHY – have been moved into another page.  Empathy and Metacognition These related ways of thinking — to understand others and yourself — are very useful in all areas of life, including education.  This section — first in Goals & Perspectives, then in RESULTS and PROCESS, and Using Empathetic Feedback in a Classroom — will examine ideas & strategies that can help a teacher and students develop better empathy-ecology in their classroom.   Goals & Perspectives Empathy and Metacognition have similar goals (to understand thinking & feeling) but different orientation-perspectives, re: external and internal.     • With empathy you try to understand the thinking & feeling of others, who are external to you.     { two empathies and a result: cognitive empathy (used "to understand" thinking & feeling) plus emotional empathy (to feel) can produce empathic concern. }     • With metacognition (self-empathy) you try to understand your own internal thinking (& feeling).     { In its basic definition, with metacognition you "think about your thinking."  But in practice, thinking & feeling are related, often with strong mutual influences.  Therefore, typically it's useful to “think about your thinking & feeling.” }   External & Internal, for You and Others:     everyone – you and others – thinks with externally-oriented empathy, to understand the thinking & feeling of other people;     everyone – you and others – thinks with internally-oriented metacognition, to understand your own thinking & feeling.   The external & internal understandings constructed by you are summarized in the 1st & 2nd rows-of-cells in this table. The 3rd & 4th cell-rows describe the external & internal understandings constructed by another person. terms RESULT (who and WHO) RESULT (what) (external) EMPATHY by you, for ANOTHER PERSON,  is your external empathetic understanding of another,  of THEIR thinking & feeling. (internal) METACOGNITION by you, for YOURSELF, aka SELF-EMPATHY, is  your internal metacognitive understanding of self, of YOUR thinking & feeling.  (external) EMPATHY by another person, for YOU, is their external empathetic understanding of another, of YOUR thinking & feeling. (internal) SELF-EMPATHY by another person, for THEMSELF,  is their internal metacognitive understanding of self, of THEIR thinking & feeling.   Metacognition and Self-Empathy:  These terms have the same meaning, in this page.  More generally, when these terms are used by others, typically with metacognition the emphasis is more heavily on thinking, and with self-empathy it's on feeling (but also thinking). other terms:  a metacognitive understanding is aka personal metacognitive knowledge that is one aspect of a person's overall general-and-personal metacognitive knowledge.  {implications of terms: understanding & knowledge}   By analogy, empathetic understanding also can be called empathetic knowledge, although the term metacognitive knowledge is used much more often.   RESULTS  —  Perspectives and Understandings By comparing understandings of YOU in the 2nd & 3rd cell-rows, or of THEM in the 1st & 4th rows, you can see how understandings (of YOU, or of THEM) depend on point-of-view perspectives (on whether the constructing is done by you, or by them). two pov-perspectives on YOU, in rows 2 & 3:  You use internal metacognition (self-empathy) to construct your understanding of YOUR thinking & feeling.  And another person uses external empathy to construct their understanding of YOUR thinking & feeling.  It can be interesting to compare these two understandings, asking “How do I view me? How do they view me?” and “What are the similarities? and differences?” and “Why do the differences occur?” and “Which understanding is more accurate? and in what ways?” three pov-perspectives on ANOTHER PERSON, in rows 1 & 4 & _:  You also can make comparisons and ask questions (about similarities & differences, and accuracy), re: understandings of ANOTHER PERSON – “How do I view THEM? How does this person view THEMSELF?  And, not shown in the table, how do other people view THEM?”   When we compare empathy (to understand others) with metacognition (to understand self), we see many similarities and analogous relationships in the PROCESS used (below) and (above) the RESULT produced.    ATTENTION !    The sections above and below – about EMPATHY – have been moved into another page.  PROCESS  —  constructing Empathy & Metacognition Now we'll shift attention from RESULTS to PROCESS. We construct our understandings (of others & self) in a social context, so it's useful to distinguish between... Understanding and Feedback:  We construct (i.e. we develop) feedback in a two-step process.  First we use empathy or metacognition to construct understanding that we use, after evaluative filtering, to provide feedback for others, with communication.   {Understanding and Feedback, Part 2}   You construct your external EMPATHY (it's your understanding of ANOTHER PERSON) when you internally interpret all of the evidence you find.   You can use three kinds of evidence:  your observations of the person;  feedback about the person from other people;  feedback about self from the person. You construct your internal SELF-EMPATHY (to get your understanding of YOURSELF) when you internally interpret all of the evidence you find.   You can use two kinds of evidence:  your observations of yourself;  and feedback about you from others.   {an option: If the table below is too wide for easy reading in your browser window, you can temporarily view this page in a new full-width window.}   The first 4 rows in the tables above (for RESULTS) and below (for PROCESS) are matched, re: who is trying to understand WHO.  Below,     The 1st and 2nd rows summarize-and-organize the processes you use to construct your understandings of ANOTHER and YOURSELF.     The 3rd and 4th rows describe how, using the same processes, another person constructs their other-understanding of YOU, and their self-understanding of THEMSELF.  The 5th row shows how they construct their other-understanding of ANOTHER PERSON, of someone who isn't YOU or THEM, and thus is a THIRD PERSON. terms PROCESS (of finding evidence) PROCESS (of interpreting) (external) EMPATHY by you, trying to understand A PERSON, is constructed by you, using found-evidence that is empathetic observations-of-person by you, empathetic feedback-about-person from others, metacognitive feedback-about-person from the person,  internally interpreted by you. [to construct other-understanding about THEM] (internal) SELF-EMPATHY by you, trying to understand YOURSELF, is constructed by you, using found-evidence that is metacognitive observations-of-self by you, empathetic feedback-about-you from others, internally interpreted by you. [to construct self-understanding of YOURSELF] (external) EMPATHY by a person, trying to understand YOU, is constructed by them, using found-evidence that is  empathetic observations-of-you by them, metacognitive feedback-about-yourself from you,* empathetic feedback-about-you from others, internally interpreted by them.  [to construct other-understanding about YOU] (internal) SELF-EMPATHY by a person,  trying to understand THEMSELF, is constructed by them, using found-evidence that is metacognitive observations-of-self by them, empathetic feedback-about-them from others   that can include feedback-about-them from you,* internally interpreted by them. [to construct self-understanding of THEMSELF] (external) EMPATHY by a person, trying to understand A THIRD PERSON, is constructed by them, using found-evidence that is  empathetic observations-of-third by them, metacognitive feedback-about-third from third, empathetic feedback-about-third from others   that can include feedback-about-third from you,* internally interpreted by them.  [to construct other-understanding about a THIRD PERSON] Did you notice that the 3rd & 5th rows are analogous but with one difference?   (what is it? the 5th-row process can include one extra evidence that is "feedback-about-third from you")   Understanding and Feedback  —  These are related, but different.  They occur in sequence:     1. First you use empathy and observations-of-performance, trying to get accurate understandings of another person(s), and of their performance(s).     2. Then if you want to provide helpful feedback,* you will wisely filter your understandings by not saying everything you are thinking, but only what will be helpful.  You do this by deciding, for each person or group, what to say (and not say), when and how, or whether to say nothing.  The goal is to be helpful by providing formative feedback with an intention, and hopefully a result, of being kind and beneficial.   /   * Unfortunately, sometimes (if a person doesn't want to be kind-and-beneficial) the feedback is intended to be un-helpful.     1-during-2:  An empathetic understanding (developed in Step 1) is used (in Step 2) during the process of filtering, when you're deciding the details (the what/when/how-and-whether) of providing feedback that will be helpful.   MORE - Other useful strategies for providing helpful feedback are in two places:  Developing a Creative (and critical) Community by trying to minimize any "harshness" in feedback-providing and feedback-receiving;  Evaluation is Argumentation that in a group requires "the social skills of communication" when you combine Evaluative Thinking with a Persuasion Strategy and Communication Skills, along with productive Attitudes while Arguing.   Using Empathetic Feedback in a Classroom The three *s — above in the table-for-process and below in descriptions of each * — are three kinds of "feedback... from you."  Imagine that you are a teacher, and two of your students are Sue ("a person", aka "them") and John ("a third person", aka "third"). How will you use these 3 kinds of empathy-based feedbacks?  If you're an effective teacher, then (in cell-Rows 4, 5, and 3)...     * You want to provide feedback that will help Sue construct a better self-understanding of HERSELF.  (This is her SELF-EMPATHY, aka her METACOGNITION, in Row 4.)   /   a new term: Sue's own internal METACOGNITION (by "thinking about Sue's thinking) is being supplemented by your feedback-to-her about her, which is aka external metacognition because it's the "thinking about Sue's thinking" that is externally supplied by you, as an empathetic observer.     * You want to provide feedback that will help Sue (and other students) construct a better other-understanding of JOHN.  (This is her EMPATHY for A THIRD PERSON in Row 5.)   /  You can provide feedback-to-others about all of your students, individually and collectively, to influence each student's other-understandings of their fellow students, and attitudes toward them.     * You want to provide feedback that will help Sue construct a better other-understanding of YOU.  (This is her EMPATHY for YOU in Row 3.)  With a particular feedback, you want to help a student understand themself (Row 4), or another student (Row 5), or you (Row 3).   Building an Ecology of Empathy in a Classroom All of these *-feedbacks are one part of the complex personal interactions (simplistically symbolized in the diagram) that occur in every classroom.  In this context, "better self-understanding" and "better other-understanding" will help all of you — Teacher, Student (like Sue or John), and students (in the whole class, or in smaller groups) — develop a better ecology of empathy in your classroom. In the interactions-diagram, arrows indicate a variety of interactions, including communications that are verbal (with *-feedbacks and in other ways) and non-verbal:     two arrows point away from the Teacher (you) who can communicate with only one Student (like Sue) or with two or more students.     two arrows point away from the Student (Sue) who can communicate with you, or with one or more other students.     two arrows point away from students (John & others) who can communicate with you, or with any other Student(s).   {note: A complex diagram that is more-complete would show more kinds of interactions between students, as individuals and in groups.}   A skilled teacher will provide guidance for students in how to "wisely filter" their communications (using feedback and in other ways) with the teacher and each other, so their interactions will be helpful.  A wise evaluating-and-filtering should be based on a foundation of healthy interpersonal motivations, with each student wanting to be kind, wanting to affect others in beneficial ways. Shared Goals and Individual Goals:  In ideal educational teamwork the teacher and all students will have shared educational goals of “greatest good for the greatest number” with optimal learning-performing-enjoying for everyone in the classroom.  But each student also will have their own personal goals that include wanting to improve their interpersonal relationships and personal education. Habit 5 of Highly Effective People is "Seek first to understand, then to be understood."  As a teacher, you can use this habit/principle in (at least) two ways:     When you provide feedback, in Step 1 you try to understand Sue, as a foundation for Step 2 when you help her understand your view of her and what she is doing and how she can improve.   {your feedback is one aspect of stimulating and guiding students}     In the third *-feedback you try to understand Sue, so (with your *-feedback about yourself) you can help her understand you.   view only this page -  put into left frame     ATTENTION !    The sections above and below – about EMPATHY – have been moved into another page.  Building Empathy-Ecology for a Classroom I.O.U. - Below are some ideas that eventually, maybe by mid-2018, will be developed more fully. a humble disclaimer:  This section is just ideas, and most of the ideas (maybe all of them) aren't really new.  I'm just describing some goals of skilled teachers, and some strategies they already are using to effectively pursue their goals.   Important foundational ideas, essential for this section, are in other parts of the website: • empathy-ecology performs a valuable function in a system of strategies for teaching by helping a teacher provide formative feedback that will help students improve their performing-enjoying-learning and their system of self-perceptions and...     more generally, will help guide our goal-directed designing of coordinated curriculum & instruction. • definitions for empathy(s) & metacognition and their Process (of construction) & Result (in understanding) and their uses (by teacher & students) in developing a classroom ecology.  /  [[here are ideas that will be developed later: motivational teamwork for cooperation-collaboration in education, at all levels, including Teaching Strategies for students (re: how they influence the learning of other students, directly with peer teaching, and indirectly/unofficially);  being motivated, as on a sports team, to establish an education-culture for better learning/performing/enjoying;  a HMW for students, in activity where they ask "How Might We" design our own ideal culture/environment for optimal learning, to pursue a “greatest good for the greatest number of students” and for the teacher.]] strategies for thinking (in a wide variety of contexts) by learning from experience, and...     related strategies for teaching. based on their understanding of personal motivation teachers can use motivational persuasion to help students recognize that school experiences (when they're well designed) can help them learn for life so they will want to adopt a problem-solving approach (to "make it better" in their life) for their own personal education.  When students are personally motivated to learn, it will be much easier for teachers & students to build educational teamwork in a classroom and a school.   Educational Ecologies (in Educational Ecosystems) occur at many levels, in large-scale systems — in a nation, state, district, school, department — and, on a smaller scale, in a classroom with its ecosystem of interactions between each Student and other students and the Teacher, as shown simplistically in this diagram, to produce 6 kinds of formative feedback — from one person (or group) to another — based on empathetic understandings of what others are feeling & thinking in their hearts & minds.  Each person also tries to understand, with metacognitive self-empathy, their own feeling & thinking, their own life-goals and life-strategies, for what they want (in their goals) and how to get it (with their strategies).   {a process of developing classroom ecology should be based on a foundation of kind attitudes and compassionate intentions to be benefically helpful} Ideally, the shared goal when building empathy-ecology in a classroom will be improving the total school experience to produce an optimal performing-enjoying-learning overall, with “greatest good for the greatest number” but also respect for all individuals.  For each student, and the teacher(s), the shared mutual objective is to build educational teamwork that will be helpful in achieving individual goals, and group goals.  All can work together in creative collaboration to construct a classroom community with a learning-friendly atmosphere, so students can learn in the ways they want to learn and are able to learn.   I.O.U. reminder - Soon, hopefully by mid-2019, these ideas (and related ideas) "will be developed more fully," including my exploration of what others are doing — in principle and in applications — with different aspects of educational ecology.

A Mixing of Modes – 1A/1B with Other Modes

Because "the modes are not steps" there is a frequent overlapping of modes when thinking in one mode is combined with thinking in other modes.  For example,

Although 1A is numerically first in a sequence of mode-numbers (1A, 1B,... 4A), Mode 1A is not the beginning of thinking-and-action in a process of design.  When you Choose an Objective (Mode 1A) you already should be "grounded in a knowledge of what is" due to Preparation (in 2A) — by finding information about the Problem Situation, and currently available Options for a Solution — that is an essential foundation for making intelligent decisions about Objectives and Design Projects.*  When you are "inspired to think about what could be" (by inventing new options in 2B), knowing more about "what is" (in 2A) will help you imaginatively Predict (2D) whether new Option-Properties could "make it better" than with existing Options, and decide (using Evaluations in 3A & 3B) if trying to achieve these Goal-Properties (1B) is worth investing your valuable resources in a design project.  As you can see, making choices about a Design Project (in 1A) is itself a Design Project, using all modes of thinking-and-action.

Another aspect of mode-mixing occurs in Mode 1B:  your desired Goal-Properties (for characteristics & constraints) become a focus for action during a process of design, because your Goals provide “aiming points” to guide the creative Invention of Ideas (2B) and their critical Evaluation with Quality Checks (3A) in which quality is defined by your Goals, which are the evaluation criteria.

* Later, you'll see how responses to Evaluation (each involving a decision about “what to do next” by choosing a Design-Action) occur in all of the other modes, including (in 1A) revising objectives or defining a new spinoff project.  And one mode – Coordination of Design-Actions – is devoted to making decisions.

2A — PREPARE by Finding Old Information

PREPARATION:  In an effort to understand the current problem-situation more accurately and thoroughly, you SEARCH for (and FIND) useful old information that already exists, or (from the perspective of your knowledge) already is known.  In this context, old does not necessarily mean obsolete;  old just means information that already exists or already is known, so it is not newly generated. {GENERATING of Old-plus-New}   Of course, you should critically evaluate all information, both old and new, to decide whether it is reliable and is potentially relevant because it might be useful in your process of problem-solving design.

Two Kinds of Memory:  During a SEARCH, you can FIND information in two ways;  you can REMEMBER information in your own memory, or LOCATE it in our collective memory, in what is remembered by other people and is recorded (culturally remembered?) in books, journals, newspapers, web-pages, audio & video recordings,...

What kinds of old information can you search for and find?

Options and Properties:  Search for old Options that are candidates for a problem-solution.  Then, for each old Option — especially for options that seem promising because they seem to have some of your desired goal-properties — you find (by remembering and/or locating) old information about its Properties, in old Predictions (for predicted Properties,...) and old Observations (of observed Properties,...).

Experimental Systems:  How were the old Predictions and old Observations generated?  Maybe these old Experimental Systems will be useful for Experimental Design (in 2C) so you can generate new Predictions (2D) and new Observations (2E).

Theories:  To help you understand old information and generate new information, search for old Theories (descriptive or descriptive-and-explanatory) about relationships between products & properties, experimental systems & predictions or observations.  Using accurate Theories will help you make accurate Predictions (2D).

Conceptual Knowledge and/or Procedural Knowledge:  The information above is Conceptual Knowledge (ideas).  But you may also want to find information about Procedural Knowledge (skills);  this information can be useful when it's about skills you will use for your Design Project, or (more directly) when the objective of your Design Project is improved skills, which occurs when you are developing strategies to improve learning skills or other types of skills.

Ideas-and-Skills Knowledge, for Ideas and/or Skills:  Generally, for all types of design — whether the objective is a better theory (in science) or (in general design) a better product, activity, or strategy, including a strategy to improve skills — Preparation helps you find information that will improve your ideas-and-skills knowledge for Conceptual Knowledge and/or Procedural Knowledge.

Timings:  You can Prepare, by finding old ideas-and-skills information, both before and after you Choose an Objective (in 1A) and Define Goals (in 1B), as explained earlier in Mixing of Modes.

Generating includes finding old and inventing new, as explained below.

2B — INVENT Options for a Solution

Generation of Options, Old and New:  You solve a problem by deciding, based on your evaluations, to accept an option (for a product, activity, strategy, or theory) as a satisfactory solution;  this option can be an old Option you have selected (to be evaluated), or a new Option you have invented.  The process of Generating Options, both old & new, is sometimes called Ideation.

Invention by Revision or Innovation:  You can invent a new Option by revising an old Option, or by inventing an option that is “more new” so, by definition, it’s more innovative.  Both ways to invent are creative.  Two general strategies for creatively inventing options — with Guided Invention using Evaluation, and Free Invention — are examined in Creative-and-Critical Productive Thinking which includes Thinking with Empathy.

EXPERIMENTS — we Design (2C), Do (2D-2E), and Use (3A-3B)

The next 5 sections (2C-2D-2E, 3A-3B) are the second part of a multi-page exploration of experiments, because they're important for all design, in General Design and especially in Science-Design.  The exploring begins in Design Process` where "Two-Step Cycles of Design" and "3 Comparisons" explain how Experiments (Mental & Physical) generate new information (Predictions & Observations) that is used in evaluative Quality Checks (Mental & Physical) and Reality Checks.*   And it continues below, in Sections 2C and 2D-2E with designing-and-doing Mental & Physical Experiments, and in 3A-3B with Evaluations that use information from Mental & Physical Experiments.

* These explanations combine verbal information (in the web-page) with verbal/visual information (in diagrams).  In the rest of this page it can be useful to study the diagrams along with reading, so I recommend opening the diagrams in a separate window (not just in the right-side frame) so they will remain open when other pages move into the right frame, by clicking this link or by right-clicking on the diagrams-page when it's in a frame.  Also, two commentaries for “guided exploration” are in the appendix of Verbal-and-Visual Instruction.

2C — DESIGN Experiments (Mental & Physical)

The objective of Experimental Design — which is a sub-project within an overall Design Project, and is an important sub-objective of science — is to design Experimental Systems to use in Mental Experiments (2D) and/or Physical Experiments (2E).  As in other types of design, you define Goal-criteria (1B) for Experimental Systems that will be useful because they help you make progress in your overall Design Project;  you Prepare (2A) and Generate System-Options (old and new, 2A & 2B);  and you Evaluate Options using Quality Checks (3A) by comparing your Predictions

options for Experimental Systems are evaluated by using Quality Checks,

An Overview of the Process — Part 1

Experimental Design begins with quick-and-rough Mental Experiments in which you imagine different situations and ask “if we do this, what kinds of things might happen, and what might we learn?”  Each situation is an Experimental System.  This early phase is a divergent search for systems that will produce new information (Predictions or Observations) that could be useful for your design project, or at least interesting.  It's a way to consider a variety of possible system-options, quickly and cheaply.

Then you can decide if, for some systems, you want to invest more effort in careful Mental Experiments — so you can make improved Predictions that are more thorough, precise and accurate, beyond just imagining "what kinds of things might happen" — or in Physical Experiments that usually require larger investments of time and money.  For systems that are judged worthy of more effort you can carefully plan the details for what an Experimental System will include, how you will control its variables, what you will observe and how.

Generation - Guided and Free:  The mental process of generating options for Experimental Systems is examined in Creative-and-Critical Productive Thinking` which describes principles for Guided Generation & Free Generation, and their applications for Experimental Design or (in other aspects of a design process) for Products, Activities, Strategies, or Theories.

Old and New:  Generation includes Invention (of new options) and Selection (of old options), because old Experimental Systems can be useful for new experiments (Mental and Physical) to generate new Predictions (2D) and new Observations (2E).

Experiments and Experimental Systems

What is an experiment?  Designers use a broad range of experiments, so in Design Process the definition is broad;  an Experiment is any way to generate new information, whether this occurs inside or outside a laboratory, with control that is total or minimal.

In general design, an Experimental System is a combination:  it's an Option (for a product, activity, or strategy) operating in the context of an experimental Situation:  Experimental System = Option + Situation.   This definition is discussed in Connections between Experiments and Actualized Options.

You run a Mental Experiment by imagining what will happen with an Option-and-Situation so you can make Predictions.  You run a Physical Experiment by physically actualizing an Option-and-Situation so you can make Observations.

Using Analysis to Generate Options for Experiments

Because an Experimental System has two components, there are two basic strategies for fixing one while varying the other.  You can...

• Change the Situation:  In general design, your objective is a product, first choose a product-Option and then ask “how many situations can I put it into?” (or “how many things can I do to it?”) in an effort to creatively generate options for experiments that might produce useful information (predictions or observations) about this product-Option;  if the design-objective is an activity or strategy, similar “situation questions” are asked.  In science when the objective is a theory, you ask “in what situations could a Theory-Option be used to explain what happens?” and these theory-situations are options for experimental systems.

• Change the Option:  Or you can first choose an experimental Situation, and use it for testing various product-Options;*  this lets you compare the results (predicted or observed) for these Options. (* or Options for an activity, strategy, or theory)   /   A common use of this strategy is for creative-and-critical retroduction when you "do Mental Experiments, over and over, each time ‘trying out’ a different Option."   In general design, usually the Situation remains constant while only the Solution-Option changes;  but you could "change the Situation" and then try different Options.   In science, a theory is not part of the experimental system, so in retroduction you just use different Theory-Options to make predictions, looking for predictions that match the known observations.

Analysis of Experimental Errors — for Evaluation & Generation

Designers can examine sources of systematic errors and random errors in an experiment, to evaluate the quality of observations, including their accuracy & precision.  These evaluations can be used to estimate the credibility of observations from this experiment, or to revise-and-improve it, or generate other new options for experiments.   {examples of data analysis to use for instruction}

Experiments for General Design and Science-Design

Improving-and-Understanding:  An experiment can be useful for General Design (which includes Engineering) and also for Science-Design.  How?  Some experiments help you evaluate (and then improve with guided revision`) the quality of a Solution-Option, and also understand (by developing a better Theory-Option) the factors that affect the quality of a Solution.  This leads to "crossover thinking-and-actions" in which "an engineer sometimes does science" in a project that is mainly General Design, and "a scientist sometimes does engineering" in a project that is mainly Science.

Understanding Nature:  For example, in a schoolroom activity with the objective of designing a slow-dropping parachute made from one or more coffee filters, when students generate Solution-Options by varying different factors (surface area,...) they are comparing Solution-Options (trying to find the best parachute) and also generating Theory-Options about the factors that affect a parachute's rate of dropping.  This kind of dual-purpose experiment is one way that engineers can learn more about nature in the context of technology — as when they study the chemistry-and-physics of combustion in car engines, or of semiconductors in computer chips — because they think an improved understanding of nature will help them improve their designing of technology.

Understanding Humans:  Or, in all General Design (not just what we commonly define as engineering) a common goal is to develop strategies for selling a designed Solution (a product, activity, strategy, or theory) to other people.  When you are designing a strategy for “marketing” you should have an accurate-and-thorough understanding of how other people will respond.  One way to improve your understanding is by using your physical experiments as opportunities to learn.  When you do an experiment by using a strategy for marketing, you can compare your observations (of responses) with your predictions (of responses), and ask “is the matching satisfactory?”  If you conclude “no”, then you can revise your theory-about-responses so your understanding will improve.   {better understanding is useful for all human-related objectives, not just for marketing}

Quick Transitions:  During either type of project, you can quickly shift back and forth between types of Experimental Design (with an Option Operating in a Situation for General Design, or a Theory-Using Situation for Science-Design) and types of Evaluation (using Quality Checks for General Design, or Reality Checks for Science) by doing whatever seems most likely to produce progress, with a skillful Coordination of Thinking-and-Actions.

Mutually Supportive Goals:  In science the main Goals and Sub-Goals are Theory Design and Experimental Design.  These two design-objectives are closely related because improving our knowledge about nature (with experiments) is an essential foundation for improving our understanding of nature (in theories).  Although in science the long-term ultimate goal is Theory Design, the sub-goal of Experimental Design is very important in the everyday activities of scientists.

MORE — Designing Experiments so we can make Useful Predictions & Observations

2D — PREDICT by using a Mental Experiment

comments-and-IOU:  This section will be revised sometime, but until then you should read the revised section in the page-summary.   In addition to editing the current content (below), here are some ideas that will be in the revised version:   why predictions are model-based (rather than "theory-based"), with a System-Model made by applying a Theory to a specific Experimental System;   why a Model is typically made by assuming several theories (including supplementary Theories) not just one Theory;   showing how a Hypothesis (which in Design Process is a set of claims about a System-Model) is related to a Model, Theory, and Prediction, with similarities & differences,..., and coping with inconsistent terminology;   explain how we predict by interpolation & extrapolation, for all if-then methods (deduction, simulation, induction);   the practical cognitive utility of fluency-in-predicting (with mental skill in being able to make predictions quickly, easily, accurately) which makes it more likely that predictions will be used more often.

Interpolation and Extrapolation:  Any if-then prediction can be an interpolation — for a system within the application-domain in which observations are known, or a model is assumed to be valid — or an extrapolation outside this domain.

Choose an Experimental System (in 2C), do a Mental Experiment, and make Predictions using if-then logic by reasoning that “IF the system behaves as expected (according to my theories of “how things behave”), THEN my Prediction (my logical expectation) is that       will happen and       will be observed.”  How?  You can predict using if-then logic in one or more ways, with theory-based deduction (using deductive logic that assumes theories about the experimental system) or theory-based simulation (as in running a computerized model of the system) or experience-based induction (by assuming that what happened before, in similar situations, will happen again), or in other ways.  A comparison of predictions made in two or more ways provides feedback about the quality of these predictions and the methods-of-prediction;  additional feedback that is even more valuable comes from comparisons with observations, in Reality Checks.

Fluency-and-Skill in Predicting is useful in many ways during design, for critical evaluation in Quality Checks & Reality Checks, and for creative-and-critical Guided Generation.  If you can make predictions quickly, easily, and accurately, you are more likely to use predictions more often.

Quality Control for Predicting:  Why?  Predictions are important because they are used throughout a process of design (for Reality Checks, Mental Quality Checks, Guided Generation) in both Science and General Design.   How?  The Quality of your Predicting depends on the Quality of your Model and the Quality of your Model-Applying (your Model-Actualizing) in the two-step process of constructing a System-Model and using it to make Predictions.  When you use Quality Control (to check-and-improve your predicting) you can check the Quality of Your Predicting by:  asking others (do they make the same Predictions, for the same System-and-Model?);  comparing the Predictions you make using two or more methods-of-prediction (with deductions, simulations, and/or inductions);  using Reality Checks for feedback about your Model and/or your Model-Application.   {Reality Checks can be especially useful when you construct a theory-based model for a simulation-Prediction, because this type of Theory Application can be especially difficult.}

MORE — Designing Theories & Models, and Making Predictions

2E — OBSERVE by using a Physical Experiment

Choose an Experimental System (designed in 2C), do a Physical Experiment, and make Observations.

This section is short because it builds on everything in 2C - Experimental Design`.

In a Physical Experiment, an Option must be physically actualized "by making (or obtaining) a product, doing an activity, applying a strategy, or using a theory."

For example, if the objective is a product and you want to learn more about its properties by doing a Physical Experiment, you obtain the product-Option (if it already exists) or build it (if this is necessary, or is easier or cheaper) as a physical prototype.

Adjustments:  The sophistication of Physical Experiments tends to increase during a design project.  In an early ideation phase, sometimes useful information can be generated in Physical Experiments that are quick, easy, and cheap – for example, by using a rough prototype (or simple mockup) of a product.  Later, it may be more useful (or even necessary) to develop-and-test prototypes that more closely resemble the eventual solution, to find its flaws and improve its details.

3A — EVALUATE Options by using Quality Checks

A Review of the Basics:  Evaluation is the logical foundation of design (which includes science), so it's a main theme of Design Process in "Two-Step Cycles of Design" and "3 Comparisons."  In the old-and-new table the bottom row (“use it”) shows that "all known information, old or new, can be used for evaluation in Quality Checks" that compare an Option's Properties (predicted or observed) with Desired Properties (defined by your Goals).

Making Decisions:  Quality Checks → Quality Status

In a design project, for general design or science, solving a problem requires making decisions.

If one Option (for a problem-Solution) has Properties that are a very close match with your Goal-Properties, much closer than for all other Options — and if you are confident that your generation of options (by finding in 2A and inventing in 2B) has been thorough, so generating a better option is unlikely — the decision is easy.

But in most projects you'll have multiple competitive options, each with different strengths and weaknesses.  How can you compare these options and make a wise decision?  A general approach that you may find useful begins with a question:

When all things are considered, by including all available information from all Quality Checks (mental & physical), how do you assign a Quality Status for each Option — by giving a higher Quality Status to Options that have a closer match with Goals — to help you make decisions about a Solution for the Problem that is the focus of your Design Project?

Combining Evaluations from Multiple Quality Checks

The three tables below illustrate a three-part strategy for a thorough evaluation in which you “consider all things” by using all available information, old and new, from multiple Quality Checks in which you compare many Predictions & Observations (from many Experiments, both Mental & Physical) with many Goals, for each of the competitive many Options you are considering.

Flexibility in Order-of-Evaluation:  I call this a "three-part strategy" instead of a “three-step strategy” because you have flexibility in sequencing.  If you "consider all things by using all available information" it doesn't matter whether you consider all Goals first (or second or third), or all Experiments first, or all Options first.  Therefore the three parts are labeled "• • •" instead of "1 2 3".

• In the four mini-diagrams below the colors show Mental Quality Checks (made by comparing a Predicted Property with a Goal-Property) and/or Physical Quality Check (comparing an Observed Property with a Goal-Property) to evaluate one Option, based on information from one experiment, which can be a Mental Experiment and/or Physical Experiment.   /   note:  Here in Mode 3A, "Quality Check" is being defined broadly when a theory is evaluated, because (as explained in Mode 3B) a Reality Check is a special kind of Quality Check.  When theories are evaluated, the usual goal-criteria for defining quality include Mental-and-Physical Reality Checks plus other goal-criteria (Predictive Contrast, Conceptual Factors, Cultural-Personal Factors) that are used in evaluative Quality Checks for a theory.

• Multiple Goals:  The four mini-diagrams show multiple Quality Checks (Mental & Physical) made by comparing an experiment's Predictions & Observations in order to assign a Quality Status for many Goals:  for Goal A, and for Goal B,...

Weighting of Goals:  Typically you define the "quality" of an Option with many Goal-criteria, each for a different Goal-Property, aka a different Goal.  You can do a Quality Check for every Goal.  You assign a priority to each Goal by asking “how important is this Goal, compared with other Goals?” so you can give a “heavier weighting” to higher-priority Goals when you combine the evaluations from multiple Quality Checks to estimate an overall Quality Status for the Option.

• Multiple Experiments:  The four mini-diagrams below show Quality Checks that compare Goals with the Predictions and/or Observations from each of many Experiments (mental & physical, old and new), with each Experiment done using the same Option:

• Multiple Options:  After you have used the two strategies above to consider all information — with comparisons based on multiple Goals, using information from multiple Experiments — to determine a Quality Status for each Option, you make comparative evaluations for many Options:

Based on these evaluations, you decide how to determine/assign an overall Quality Status for each Option.

Then what?  Evaluations can be useful in many ways, leading to a variety of potentially productive design-actions:

Many Responses to Evaluation

Evaluation by using a Quality Check (3A) or Reality Check (3B) can stimulate many types of action-responses.  You might:

• continue evaluating (in 3A or 3B) by doing a more thorough analysis using data from Multiple Experiments about Multiple Options, as outlined above, to assign a Quality Status for each option;

• recognize a “knowledge gap” where useful information is missing, which is a motivation to find more old information (2A), or design Experiments (2C) and do Experiments to produce new information with Predictions (2D) or Observations (2E);

• Generate more Options (2A, 2B) with Free Generation and Retroductive Guided Generation by selecting old Options or by inventing new Options using revision and/or innovation.  When "there is a tough competition [between multiple Options] because each Option offers different benefits, with each better for achieving some Goal-Properties and not others," (in 2B) you can try to combine the best features of two (or more) options into a hybrid option;  but if this isn't possible you may have to decide (in 3A or 3B) which Goals are most important, or you might want to...

• revise some Goal-Properties (1B);

• make decisions about the overall project  —  continue working on it, or delay work for awhile, or (in 1A) abandon the project, or (also in 1A)...;   convert the project into a related project by revising its overall objectives, or supplement it with a new spinoff project;   either of these (revising objectives, or defining a spinoff project) could be the result of asking “what kinds of problems might the current options solve?” in retroductive guided invention to generate new projects;   decide that one Option (or more) is a satisfactory Solution, and maybe you then begin work on sub-projects to manufacture, market, distribute, and sell it;

• make action-decisions  —  pause and think about what to do next (in 4A);  because so many options-for-action are available here, and at many other points in a process of design, a skillful Coordination of Design-Actions is important.

3B — EVALUATE Theories by using Reality Checks

I.O.U. — This section will be radically revised sometime, but until then you should read the revised Section 3B in the Page-Summary.

A Review of the Basics:  "Evaluation is the logical foundation of design (which includes science)" and in one of the "Three Comparisons" you compare Predictions with Observations in a Reality Check for the quality of a Theory.  As explained in Design and Science, General Design and Science both use Quality Checks

     Quality Checks (in 3A) are the central focus of General Design, although it also uses Reality Checks.

     Reality Checks (in 3B) are the central focus of Science-Design (Science), but it also uses Quality Checks.

If you're not a scientist, why do you need theories?

A theory is any effort to understand, to describe-and-explain (for yourself & others) what you have observed, in daily life or during a process of design. ...  With a wide range of useful-and-accurate theories, plus the ability to use your theories skillfully, you can make accurate predictions that, along with your good values and priorities, will help you make wise decisions [in life and in design].    {quoted from Objectives of Design and Motivations to Learn}

What can you learn from a Reality Check?

The purpose of a Reality Check (Theory Check) is to provide empirical feedback about how closely “the way things are in your thinking” (when you make Predictions using your Theories) matches “the way things are in reality” (when you make Observations in a Physical Experiment).

Reality Checks test the practical utility of a Theory (or set of interacting Theories) in helping you make accurate predictions.  A failed Reality Check — when your predictions and observations don't match well — indicates a flaw in your theories, or the way you're using theories to make predictions with theory/model-based deduction or simulation, or experience-based inductive extrapolation.  Based on this feedback from Reality Checks, you can revise your theories or use-of-theories to improve the accuracy of your predictions and the wisdom of your decisions.

A Reality Check is a special type of Quality Check

In the context of these Evaluation Factors, a Reality Check is just one of the two sub-factors (it measures empirical Degree of Agreement, but not empirical Degree of Predictive Contrast) in the Empirical Factors that are one of three "factors" used as Goal-criteria in Quality Checks to evaluate a theory. 

Putting Things in Perspective:  During an explanation of how Science is Design I claim that "Science emphasizes Reality Checks... but also uses Quality Checks" because Reality Checks are usually the most important Goal used for evaluating a theory, but are not the only Goal.

How Quality Checks are used in Science

In science, when we Design a Theory our theory evaluation is based on three types of factors — empirical, conceptual, cultural-personal (described below) — and we use Quality Checks to ask “how closely does this theory match our goals for an ideal theory, when we do a Quality Check for each factor and its sub-factors?”  This is one reason that, in science, even though Reality Checks are the central focus... it also uses Quality Checks."

When a theory is evaluated — when we try to consider all information and assign a Theory Status (a Quality Status that can range from very low to very high) for every theory that is being considered — how much emphasis is placed on each factor and sub-factor?  The characteristics of evaluation factors, and their relative weighting, vary in the practices of scientists and in views of science.  These variations can be described, using Science Process & Design Process, with customized elaborations of a generalized framework.

Another use of Quality Checks is for Designing Experiments that are useful because these experiments will help you make progress in Designing Theories (the long-term main objective of Science) or finding a problem-Solution (the main objective in General Design) by Designing a Product, Strategy, or Activity.

The sub-section below (which will be revised-and-expanded later, maybe in late 2015) supplements a summary of Evaluation Criteria by describing these same criteria in an alternative framework (developed in my PhD work) in terms of three Evaluation Factors.  For details about this framework, you can read about Theory Evaluation in Sections 1-4 of an introductory overview and detailed overview that are condensations of my PhD work.

Three Types of Evaluation Factors

When theories are evaluated using Quality Checks, the Goal-criteria we use to define Quality are three types of Evaluation Factors — Empirical, Conceptual, Cultural-Personal — that each contain sub-factors:

Empirical Factors are the Degree of Agreement between predictions & observations (tested in Reality Checks) that usually is the most important evaluative factor,** plus Degree of Predictive Contrast by asking “how much do predictions of competitive theories differ?” which matters because two or more theories could make accurate predictions for an experimental system.

Conceptual Factors are a theory's Internal Characteristics (its internal consistency, logical structure, types of entities & actions,...) and External Relationships with other theories (logical consistencies, sharing of system-domains,...), plus Scientific Utility due to its cognitive utility for stimulating productive thinking (by forming useful mental & external representations) that includes predicting, and (arising from cognitive utility) its research utility for stimulating productive theoretical or experimental research.

Cultural-Personal Factors include psychological motives & practical concerns that produce personal utility, plus metaphysical or ideological criteria, thought styles of a community (including influences by its authorities), and more.

* Degree of Agreement (aka Predictive Accuracy) is not the only evaluative factor, as explained in the summary of Evaluation Criteria which describes other criteria — types of entities-and-actions, or Degree of Predictive Contrast — and closes by linking to here for "other reasons" that ( I.O.U. ) you'll find here later, that will include these other reasons to change an estimate of plausibility:   if a theory's External Relationships with other theories is a logical inconsistency that would require rejecting other theories that are considered plausible-and-useful;   if utilities (whether "scientific" or extra-scientific such as many of the cultural-personal factors) cause some scientists to lower the status of a theory, so (to reduce cognitive dissonance) they attribute their status-lowering to a lowered scientific plausibility, not to their actual extra-scientific motives.

* Coping with Probabilities

Trying to estimate a Degree of Agreement can be challenging — logically, mathematically, and scientifically — when we compare observations with probabilistic predictions, as in the “25% recessive traits” of Mendelian Genetics.  Skills for coping with the challenge of statistical comparisons are described in Designing Theories & Models, and Making Predictions which includes Statistical Analysis, distinctions between related terms (theory, model, hypothesis, predictions,...), and much more.

4A — COORDINATE the Process of Design

This mode — when you develop-and-apply cognitive/metacognitive Coordination Strategies for a process of design — is the key to combining individual thinking skills into whole-process skills.  In my opinion, it's where teaching Design Process will be most helpful for students.

In this mode you observe the process of design, and make an action-decision by asking “what is the best use of my time right now?” (considering both urgency & importance) and choosing an immediate action that occasionally is a planning of longer-term actions.  How?

Aware Observation of your Process:  You try to understand “what is happening” by observing where you are now (the current situation, the Now-State) and knowing where you want to go (your Goal-State).

You compare the now-state and goal-state, searching for differences — “what still needs to be done?” — so you can move toward a goal-situation where the problem has been solved.

Below is another diagram, showing you making progress with problem-solving actions (PS) that help you achieve a sub-GOAL (which then becomes your current NOW) and then more sub-GOALS until you achieve your overall GOAL.

But this diagram implies a linearity that is too simplistic, because most projects involve a complex branching into sub-projects and then a combining of sub-projects. / I.O.U. for December — This paragraph needs to be written more clearly, maybe with some of these ideas - [[showing progress by "moving towards" a solution, in a diagram, might require complex diagrams in which one sub-project provides input for other sub-projects (with branching) or when inputs from several sub-projects come together(with funneling) in another sub-project]] [[maybe the second diagram should be eliminated, and just explain that in the first diagram "PROBLEM SOLVING" is a multi-step process, and link to "Reducing Inaccurate Stereotypes" for further explanations]]

Generate and Evaluate, Decide:  You creatively generate action-options (for what you can do in all modes, in 1-4), critically evaluate action-options, and wisely make action-decisions about actions (and associated thinking) that will help you make progress in solving the design problem, by moving from NOW toward your GOAL.

Timing:  Improvised planning (in 4A) is mixed with action in other modes, and its timing is an important aspect of regulating metacognition: "When you're not deeply engaged in a flow of productive thinking-and-action, this interlude can be a good time to ask ‘what should I do next, and how?’ to coordinate your actions and stimulate your thinking."  Or...

Collaborative Teamwork:  Sometimes one person (serving as a teacher, coach, or supervisor) coordinates actions for a group (of students, players, or workers), as described in Collaborative Design Process with Effectively Coordinated Teamwork.

Quality Control:  The purpose of coordinating actions in all modes (in 1A through 3B, plus 4A itself) is to improve the quality of your design process — inside each mode, and between modes (with productive interactions) — to achieve the goals of using your time more effectively and finding a better solution.

The rest of this page, in 4 related sections — Conditional Knowledge, Logical Organization, Visual-Verbal Instruction, Integrated Sequences — shows how Design Process can help students improve their strategies for coordinating design-actions.

Conditional Knowledge

When you are coordinating your actions in a process of design, an essential tool is conditional knowledge — knowing the conditions-of-application when a skill (or idea) can be useful — because this knowledge helps you find a match between “WHAT needs to be done” and “HOW to get things done.”  You decide “WHAT needs doing” by comparing your now-state and goal-state, as described above`.  You'll know “HOW things can get done” by developing, for each of your skills, a conditional knowledge about its functional capabilities (what it can help you accomplish) and its conditions-of-application.  To make an effective action-decision, use your conditional knowledge to find a match between a recognized need (for things you need to do) and a capability (for how to do things).

How can you develop-and-use conditional knowledge?  For each skill you learn, know how to use it, plus when to use it and why.  Ask “what can it help me accomplish?” and “what are its conditions of application? in what contexts (indicated by what kinds of condition-clues) is it likely to be useful?”  Creatively imagine if-then scenarios for potential applications in the future (by thinking “if the situation is      , then I can use this skill”) and learn the clues for recognizing how to match various situations-and-skills.

Tools for Problem Solving:  An expert in any field (a mechanic, electrician, carpenter, plumber,...) has a variety of tools, each useful in its own ways, and knows why, when, and how to use each tool.  To become a problem solver (a mechanic,... scientist, engineer,...) who is expert — who can do whatever is needed, when it's needed — you master a variety of problem-solving skills by knowing how to use each skill/tool, and also why-and-when to use it.

Basically, improving conditional knowledge is a way to improve transfer of learning by increasing your ability to remember-and-use your knowledge (conceptual and/or procedural) in new situations in the future.  How can you do this?  In the present, intentionally learn by asking “what can I learn now, including conditional knowledge, that will help me in the future?”  In the future, intentionally recall by asking “what have I learned in the past that can help me now?” and searching for a WHAT-and-HOW match between the situation (what needs to be done) and your skills (your capabilities to do these things).

One way to improve conditional knowledge (which form the basis of action-coordinating strategies) is to develop a better understanding of the...

Logical Organization of Actions in Design Process

During a process of design, different types of thinking-and-actions are combined in productive ways.  These functional interactions are logically integrated into a coherent framework in my model of Design Process, so in the past I sometimes have called it Integrated Design Process, analogous to Integrated Science Process.

When we teach the logically organized principles of Design Process — represented verbally (in words) and verbally-and-visually (in diagrams) — this logical organization of knowledge (conceptual and/or procedural) offers many educational benefits (for understanding, recalling/transfering, and developing expertise) and is one of the many reasons to say “yes” when asking “should we use Design Process in education?”

Some useful organizational features of Design Process – in its Verbal-and-Visual Instruction and Integrated Action-Sequences – are described below.

Verbal-and-Visual Instruction

Research shows that a skillful combining of verbal & visual instruction is more effective for helping students learn, compared with either by itself.  This combination is a central feature of Design Process;  to see it, return here after you study the left frame (visual) and right frame (verbal) for Two-Step Cycles and 3 Comparisons`.

In the diagrams` — 2a/2d, 3, 4a-4b, and 5, which all show the same model of Design Process at different levels of detail, with differing perspectives and emphases — an especially valuable organizing feature is using spatial patterns and color symbols to show parallels between the left-side mental Predictions (made in Mental Experiments, used in Mental Quality Checks) and right-side physical Observations (made in Physical Experiments, used in Physical Quality Checks) that are compared in mental-and-physical Reality Checks (aka Theory Checks).  Also, mental & physical have shared planning in Experimental Design, which is used for both Mental Experiments & Physical Experiments, as shown in Diagram 4b.

Design and Science:  A related use of color symbolism is to show similarities & differences between the problem-solving process used in General Design (mainly using Quality Checks) and in Science (mainly using Reality Checks).

Science:  Science Process is a special type of Design Process, and similar organizations (in space and with colors) are used for Design Process, as described above, and for Science Process for Science in "Verbal-and-Visual Explorations of the 9 Aspects" in Science Process` which also shows the actions (to generate & evaluate) in a Design of Theories (#1-2-3-4, 5) and a Design of Experiments (#6).

Design:  Diagram 4b uses additional space-and-color symbolisms to show deeper levels of organization in Design Process, as described below.

Integrated Action-Sequences in Design (short-term & long-term)

For design or science, there is no single step-by-step sequence that is rigidly followed and uniformly used, so we say "no" when asking "is there a method?`"   BUT one reason to say "no and yes" is that some combinations of actions do occur during design, in sequences that can be long or short:

• Many models of design describe phases of design (examples & discussion) due to tendencies of timing, with some actions usually tending to happen early in a process of design, and others later.  This is long-term sequencing if we use a broad definition of sequence.

• Design Process includes integrated short-term sequences.  The best place to see the most common sequences is Diagram 4b.  You can study 4b in three ways:

by reading the descriptions below while seeing Diagram 4b` in the right frame;

by reading/reviewing a more thorough visual-and-verbal explanation` in Stage 4 of the Overview of Design Process, and then (with your Back-Button) returning to this section;

or by opening Stage 4 in a separate new window and arranging the two windows so you can see both, so you can shift back & forth between reading Stage 4 and this section plus Diagram 4a`.

Overall, the description below is less thorough than in Stage 4.  But it's more thorough in describing the combinations-of-actions that form sequences, and explaining how sequences are useful for coordinating design, and how sequences are used flexibly during design.

Here are the major short-term sequences that are used during a process of design:

Moving downward on the left side (and center), Design an Experiment, do a Mental Experiment, make Predictions that are used (by comparing with Goals) in an evaluative Mental Quality Check or (by comparing with Observations) in an evaluative Reality Check.  Typically all of these are done together, in this sequence.  Notice the two-way branching-out at the end, because Predictions can be used in either type of EVALUATION, or both.

Similarly, on the right side you see the analogous two sequences (due to branching-out because Observations can be used in two kinds of Evaluation) but (allowed by the two-way funneling-in before Design an Experiment) with Physical Experiments instead of Mental Experiments.

Next we'll look at what happens before the left-side sequence, and after it, to complete a cycle of creative-and-critical Retroduction.  If you want to review the logic of Retroduction, a summary is in Stage 4 of the Overview of Design Process.  Stage 4 explains why you see purple (symbolizing Retroduction) only on the left side of Diagram 4b, not the right side;  it's because a retroductive generation of ideas requires mental Predictions.  In retroductive reasoning, creative Generation is directly guided by the Predictions used in Mental Quality Checks, but is only indirectly guided by Physical Quality Checks, as indicated by the two blue arrows (one solid and the other dotted) that point down from them and then over-and-upward to Generation of Solution-Options.   Another type of Generation is directly guided by the Predictions used in Reality Checks;  this is shown by a yellow-green arrow pointing from it to Generate Theory-Options.   Notice the two cycles of creative-and-critical Retroduction, with purple text & blue arrows/lines (to Generate Solution-Options), or purple text & yellow-green arrows/lines (to Generate Theory-Options).

Finally, evaluations can lead you to Make Decisions about Overall Project such as deciding to continue, delay, abandon, or revise it, or decide that an Option is a satisfactory Solution.  And throughout a process of design, you Make Action-Decisions by using Coordination Strategies that guide your combining of sub-process actions (individual or in integrated sequences) to form an effective overall process.  As explained in the preceding sub-sections, developing a deep understanding of Design Process — with Aware Observation of your Process plus Conditional Knowledge (about individual actions & integrated sequences) that is Logically Organized — will help a designer coordinate their process of design by making effective action-decisions.

Flexible Use of Sequences:  During a productive process of design, sequences are used flexibly — so Design Process does not describe a "step-by-step sequence that is rigidly followed" — because expert designers make real-time choices about “what to do next” based on awareness of “what is happening now” at each point in a process of design.  Flexibility is possible due to branchings (that require choices) and cycles (because actions & sequences can be re-used), plus the many responses to Evaluation which include action in all modes of design-thinking, not just the retroductive Generation of Options (in Modes 2A & 2B) that is described above and is featured in Diagram 4b.

a concluding summary for Mode 4A:  This integrative mode of thinking-and-action, which is done to "COORDINATE the Process of Design," is "where teaching Design Process may be the most helpful for students" (and it's one of the many reasons we should teach Design Process) because "developing-and-applying cognitive/metacognitive Coordination Strategies is the key to converting individual thinking skills into whole-process skills."