Design Process - in Education and Life

Part 1

Recognizing Opportunities and Solving Problems
What is a problem? In the context of design, a problem is any situation where you have an opportunity to make a difference, to make things better; and problem solving is converting an actual current situation (the NOW-state) into a desired future situation (your GOAL-state),

Whenever you are thinking creatively-and-critically about ways to increase the quality of life (or avoid a decrease in quality) you are actively involved in problem solving.
By contrast with the most common definition, in which a problem is always “something bad” that needs to be fixed, we can define a problem more broadly, as any "perceived gap between the existing state and a desired state (from BusinessDictionary)." In this approach, problem solving is any effort — ideally it's proactive, but it can also be responsive — that either minimizes a negative (a decrease of quality) or maximizes a positive (an increase of quality).

Objectives of Design — Products, Activities, Strategies, and/or Theories
In every area of life, creativity and critical thinking are essential. These mutually supportive skills are intimately integrated in the problem-solving methods used in a wide range of “design” fields — such as engineering, architecture, medicine, mathematics, music, art, literature, education, philosophy, history, business, athletics, law, and science — where the objective is to design (to find, invent, or improve) a product, activity, strategy, or theory. Broadly defined, this includes almost everything in life. For example,

PRODUCTS: Although we usually think of a product as an object (like a bicycle or refrigerator), it also could be a repaired object (a car that now works better than it did before), a work of art (like a painting, song, or story), an e-mail message to a colleague, an inspirational talk for a community group, or an educational game or website. The product being designed and constructed might even be the food you're preparing for a dinner party, a tasty casserole for a potluck picnic, or an apple pie entered in a contest at the county fair.

ACTIVITIES: An activity (event, situation) produces a context for experiences. This can occur in many settings, as in a party (when you decide where and when, for how long, who to invite, what to do, plus music, food & drinks) at your house or office; or it could be an entertainment event (small or large), a bike ride or walk, a double date, a group bike ride or visit to a museum or basketball game, a meeting (in person or by teleconference) at work or with a community group. In science, engineering, and many other contexts, a special type of activity is an experiment that lets you make predictions and observations. In education, instructional activities — before, during, or after a class, spanning a wide range of possibilities — play a major role in teaching.

STRATEGIES: Similarly, you can design strategies for a wide variety of situations — including educational (as a learner or teacher), social, romantic, athletic, political, military, legal, financial, entrepreneurial, agricultural, and ecological — involving competition and/or cooperation. You can plan a strategy for winning a game, providing a service, running a charity, or growing crops to feed a nation. Or the purpose of a plan may be to improve a personal or professional relationship, to make a friend or be a friend, to plan a party or prepare for an interview.
Policy Making: This can occur in a wide variety of contexts, in a family, community group, church, school, for-profit business, nonprofit organization, or government.
Decision Making: When you make personal decisions, you are designing strategies for living, for the actions that will help you achieve your goals in life. Similarly, educational decisions are strategies designed to achieve educational objectives, and business decisions are strategies for achieving business objectives, and so on. This use of design for making personal and professional decisions is one reason I claim that we use design for "almost everything in life." You'll find another reason in the subsection below, because we also use design principles to improve physical skills.

MENTAL-and-PHYSICAL STRATEGIES: Physical Strategies deserve their own subsection because we can use two basic types of strategies, mental and physical, plus overlapping mental-and-physical combinations. In a Mental Strategy (discussed above) you make decisions about the actions you will do, and then you actualize the strategy by applying it to do these actions. A Physical Strategy is similar, but there is a more direct connection between deciding and doing, with more emphasis on the quality of doing when you apply the strategy. But in reality, instead of purely-physical strategies we typically use Mental-and-Physical Strategies.
For example, my first major instructional application of Design Process was A Problem-Solving Approach to Improving Pronunciation when learning a foreign language. In this problem-solving approach you use Quality Checks (the essence of Design Process) by comparing your actual pronunciation with the goal-pronunciation you want, and doing whatever is required (by “experimenting” with the way you are speaking) to move your actual speaking-sounds in the direction of the goal-sounds you want. In pursuing these goal-sounds, some conscious thinking may be useful, but your main focus is on the results, on the sound that you produce by applying the “physical strategies” that your body (your mouth, tongue, lips, vocal chords,...) is using when it makes physical adjustments in its attempts to achieve the sounds you want. You are mainly focusing on the results of strategy-application, not the strategy itself.
When I looked at this approach and asked “is the objective of improved pronunciation a product, activity, strategy, or theory?” my first response was “none of these, it's a physical skill.” But I wanted to avoid making a new category if this isn't necessary, so I mentally converted "a physical skill" into “an application of a procedure (for using your mouth,... to make sounds)” which is “an application of a strategy (for using your mouth,...).” And this categorization, with physical skill = procedure = procedure-strategy = strategy, fits nicely with the design-process use of Quality Checks to evaluate the quality a strategy and also the quality for an application of this strategy, as in speaking. { Or if you prefer, speaking could be categorized as a physical skill, and then the possible objectives for design would be expanded to include physical skills, in addition to products, activities, strategies, and theories. }
Then I thought more generally about mental/physical skills that are mostly-physical. A strategy for improving pronunciation is similar to a strategy for improving a backhand stroke in tennis, where goals are defined (hit the ball over the net and into the court,...) and some broad features of the procedure-strategy are consciously decided (what kind of grip you will use, with one hand or two,...) but most details of the procedure-strategy are determined by your body, when it “does experiments” and you observe the results, and make adjustments (consciously and unconsciously) in response, in an attempt to achieve your goals.
Or, in a context with more available options and thus more complexity, we can think about mutual relationships between the mental strategies and physical strategies that are combined in the mental-and-physical skill of musical improvisation.
The process of learning by observing-and-improving is similar (but with adjustments) for all mental/physical skills, such as learning how to dance, play music, throw a ball, or drive a car. This generality of strategy-applications is one more reason for my claim that we use design for almost everything we do in life.
a personal comment: This overlapping of mental strategies & physical strategies is also one more reason for me to be excited about design, because for a long time I've been fascinated by a wide range of teaching and learning, by the variety of physical-and-mental skills that we use for learning-and-doing in athletics, arts, and academics. This long-time personal fascination is described in my page about "things I like to do, watch, or study" in Sports and Sport-Science.

THEORIES
In the context of design, a theory is defined broadly to include all efforts to understand, and explanations (to yourself and others) of what is happening in your design-situation.
Theories are not just for scientists, because... You often use design in daily life, and during design you often use theories, whenever you make a prediction by asking yourself “what will happen if ___ ?” or “will we get the contract” or “who will win the game” or by thinking “the teacher will like this paper I'm writing because when it's finished it will be ___ .” When you are surprised by what happens, your predictions have failed in one of the many reality checks of life. This is an indication that perhaps you should revise your theories, or learn how to apply them more skillfully when you make predictions.
During your continual self-education, in school and outside, you can build a solid foundation of knowledge (with a wide range of useful-and-accurate theories, plus the ability to use your theories skillfully) so you can make accurate predictions that, along with your good values, will help you make wise decisions.
Even in science, theories are only one objective of scientists. As explained in Part 3, in science our objective is to "improve our knowledge about nature, to... generate information (with experiments) and develop explanations (in theories) that are accurate representations of nature." And to put things in perspective, "In their daily work, scientists rarely design large-scale generalized mega-theories, such as the theories of gravity, invariance, or evolution developed by Newton, Einstein, or Darwin. Instead, they typically are applying generalized theories that already are accepted, in their study of particular experimental systems for which they are designing small-scale specialized sub-theories. ... Or scientists simply accept the mega-theories & sub-theories developed by others, so they can make observations and learn more about nature in the experiments (controlled or uncontrolled) they are designing and running. {from An Introduction to Scientific Method}" {more about mega-theories & supplementary theories}

COMBINATIONS
In most design projects, either the objective is mixed (combining some aspects of a product, activity, strategy, and/or theory) or you must design several of these (product,...) as sub-projects during the process of design. For example,
After a design project you can write a report (product) about a policy (strategy), or a notification about a meeting (activity), or directions explaining how to use a digital camera (product).
Usually the design of a new product is accompanied by strategies. For example, making and selling a musical CD (a product) requires the coordinating of many strategies — for artistic research and development (writing and arranging songs, deciding which ones to record, and sequencing them on the CD), for rehearsing and performing, engineering and editing, financing and manufacturing, marketing and distributing — to achieve objectives that are artistic, technical, and financial.
Later in this page the process of design is described for designing a product (a hybrid minivan) but the same basic process could also be used for strategies (e.g. marketing your company's minivan) or activities (e.g. a company party celebrating the minivan's launch) or theories (e.g. why people make car-purchasing decisions) and activities
And if you're opening a new restaurant, making delicious food is just one part of a complete strategy for business success. You'll want to think about (and predict using your theories about restaurants) which combination of products, activities, and strategies — of foods, atmosphere, service, prices, location, special events, marketing,... — will bring in new customers, send them out satisfied, and keep them coming back for more.

APPLICATIONS IN EDUCATION
For an outline of possibilities, Using Design Activities for Problem-Solving Instruction.

Part 2

The Process of Design — Two Quick Overviews

• You begin a design project by recognizing an opportunity and defining a problem-solving objective for an improved product, activity, strategy, or theory. Then you generate-and-evaluate options (that are candidates for a problem-solution) until you find an option that is a satisfactory solution, or you abandon the search.

basic diagram of Integrate Design Method • Here is another overview of design, with a little more depth.
Define a Design Project and Define Goals: Decide what you want to design by choosing an overall Objective. For simplicity (so you won't have to read “product, activity, strategy, and/or theory” over and over) we'll imagine that the objective is a product. Then define your Goals for an ideal product, for the properties — the composition (what it is), functions (what it does), and performances (how well it does the functions) — that you want the product to have.
Generate Information and Generate Options: You generate information, old and new, by searching for already-known old information (by finding it in your own memory or in our collective memory) about old products and the properties of each product, and by creatively inventing ideas for new products, which usually are variations of old products. You also generate new information by thinking about a product (old or new) by making Predictions about its properties, or by using experiments (controlled, semi-controlled, or uncontrolled, in the lab or in the field) so you can make Observations. And you search for Theories that will help you understand these products and their properties.
Evaluate Options, using Quality Checks: You choose an Option (for a solution to the problem) and you critically evaluate this product-Option by comparing its predicted properties with the desired properties you have defined as your Goals for the product, or by comparing its observed properties with your desired properties. When you do this you are using Quality Checks (with quality defined by your goals) by comparing Predictions with Goals to get predictive feedback in a Mental Quality Check, or comparing Observations with Goals to get empirical feedback in a Physical Quality Check.
Evaluate Theories, using Reality Checks: By comparing your Predictions (which are based on your Theories about reality) with Observations (of reality) you can do a Reality Check that provide feedback about how closely “the way you think things are” (according to your Theories) matches the reality of “the way things really are.” Using these reality-based Theory Evaluations, you may decide to revise one or more of your Theories.
Coordinate your Design-Actions: During the process of design, sometimes you Evaluate the Process by using your awareness of the current now-state (where you are) and desired goal-state (where you want to go, where the problem has been solved) so you can make Action-Decisions (about what to do next) that will help you make progress toward the goal-state. These decisions let you Coordinate your Design-Actions (the actions of Defining, Generating, and Evaluating, as outlined above, and Coordinating) so you can be more effective in solving the problem.
All of these actions, when you Define-Generate-Evaluate and Coordinate, can help you solve the problem. Eventually, based on your comparisons of option-properties with desired goal-properties, you may find a product-option that you decide is satisfactory so you consider the problem to be solved. Or you may decide to abandon the search for a solution.

The process of design is examined in more detail later, in The Process of Design - A Deeper Exploration and by using Modes of Thinking-and-Action that are examined in-depth in An Overview of Design Process.

And we can learn from other perspectives on design and Design Process as illustrated in tips-and-principles for stimulating ideas (about Defining Goals, Generating Options, and more) from other views of design, including the new K-12 Science Standards, Science Buddies, and Stanford Design Program.

Five Types of Strategies
Four of these strategies have a label that describes the strategy with a small letter (p, e) and a capital letter (C or MC, L or T):
you Coordinate Design-Actions during a process of design (p) by using Cognition (C, in pC) and MetaCognition (MC, in pMC), with the sub-strategies of pC and pMC combined into a coordinated strategy of Cognition-and-Metacognition, pC/pMC;
you can design educational strategies (e) as a Learner (L, in eL) or Teacher (T, in eT).
In addition, you often design non-educational strategies (ne).

pC = process-of-design strategy using Cognition: During a process of design, some of your cognition (thinking) is a coordinating of strategies for the process of design, when (as described above) you evaluate your process of design, and make action-decisions about what to do now, and later. / In addition, most of the thinking you do for the non-coordinating Design Actions (of Defining, Generating, and Evaluating) is cognitive, not metacognitive.
pMC = process-of-design strategy using MetaCognition: During pC your planning can include some thinking about the thinking you use when you make decisions about actions, and perform actions. This introspective reflection is metacognition that can help you improve the quality of your thinking.
Venn Diagram showing relationships between the five strategies eL = educational strategy for Learning: You also use cognition-and-metacognition in a personal design project when your objective is to improve the quality of your thinking-and-learning in a wider context (that goes beyond a particular design project) because you are motivated to improve your life with a problem-solving strategy of goal-directed intentional learning, as explained in the introductory summary.
eT = educational strategy for Teaching: This strategy has two components. First, teachers can do eT indirectly by motivating students to consistently invest time & effort in their own eL, and helping them do their eL better. Second, teachers can do eT directly by trying to improve the quality of their own teaching (including their indirect eT) in a personal design project that is analogous to eL.
ne = non-educational strategy: Or the objective of design can be a non-educational strategy, such as those described earlier for situations that are social, romantic, athletic, financial, ecological,... or mental-and-physical.

Above, the Venn Diagram shows relationships between two types of strategies, process-of-design and result-of-design:
The first 2 strategies (pC and pMC, combined in pC/pMC) are used during a process of design, whether the objective is a strategy (on the left side) or (on the right side) a product, activity, or theory. The last 3 strategies (eL, eT, ne) are objectives of design, so they are a result of design.
The first 4 strategies are explored more deeply in a section (Using Cognition & Metacognition for Design and in Education) with subsections about Combining Cognition with Metacognition in the Process of Design, plus Learning Strategies and Teaching Strategies.

The Process of Design — A Deeper Exploration ( to supplement the two overviews above )
The first step in problem solving is to recognize that a problem exists, because you have looked at a situation as it is now and you can imagine a future in which things have changed and improved. Or perhaps you can imagine a future in which things have changed but have become worse, and you want to avoid (or minimize) these changes. Either way, if you want to take advantage of your opportunity to make a difference, you will generate-and-evaluate ideas (and associated actions) that will help you make progress toward a solution. These ideas and actions are explained in this section.

Flexible Goal-Directed Improvising: Design Process is not a rigid step-by-step routine that must be followed. Instead, it's a logical framework that is useful for describing the flexible improvising, guided by goals, that occurs during the process of design. { Later, there is more about the improvising in design & science that occurs by using modes, not steps. }

An Example to show the Process of Design
Imagine a "time machine" experience taking you back to 1981. This was early in the developmental history of hybrid cars that can run on gasoline and/or electricity, before they were commercially available for sale, when this idea's potential value had not yet been converted into practical actual value. At this time, three decades ago, you are part of a design team whose objective is to develop this distinctive type of vehicle into a hybrid minivan. To solve this design problem you will use the general method that was summarized earlier in the two overviews and is shown in this diagram, which shows 3 elements (Goals, Predictions, Observations) being compared in 3 ways:

a beginning: Based on old observations, you have decided that a hybrid minivan is an idea worth developing into a project. In making this decision you have taken the first step in design, to choose an overall objective. In this case the objective is to design a hybrid minivan, and maybe to manufacture, market, and sell it.
Then you define goals that are more specific than the general meta-goal (the overall objective) by asking "What do we want? What kind of properties should our product have, for its composition (what it is), functions (what it does), and performances (how well it does the functions)?" In addition to these specifications for desired properties, usually we must consider practical constraints such as a low cost, ease of manufacturing, and (for the design process itself) meeting time-deadlines. / For this minivan, you would set goals for functions of the van's body (such as making it easy to remove the seats, and to load large objects through the doors) and engine (able to run on either gasoline or electricity or both,...), performances (for body durability & aerodynamics, crash safety,... and for gas mileage, acceleration,... plus handling, braking,...), aesthetics (so it looks good) and marketing appeal (so lots of people will buy it), expenses (initial cost for a factory transition from conventional to hybrid, and marginal cost for each additional car), plus criteria such as quality control and reliability.
You generate ideas for options by selecting an old product or inventing a new product. Usually, to invent a "new" product you modify an old product. Your new hybrid will have some old components — existing bodies and seats (similar to those in vans and station wagons), engines and transmissions, electrical storage devices,... — that you can modify and combine in new ways. You will think creatively about different ways to use these components (or new components you'll invent) to improve your car in all ways, especially by letting it use gasoline-and-electricity cooperatively to improve the car's efficiency.
Then you run an experiment — either a mental experiment (in your mind) to produce predictions about what you think will happen, or a physical experiment (in the world) to produce observations about what really happens — that will produce useful information. / To test a new body style for fuel efficiency, you might make a prediction based on what you know (from previous physical experiments) about the fuel efficiency of similar bodies. Or you may want to test the body in a wind tunnel so you can observe its aerodynamic properties. Or you could build a prototype, thus transforming your body-idea into a body-reality, then drive it and observe the actual gas mileage. / Similarly, you can predict the body's consumer appeal based on the response to similar bodies in the past. Or you can observe people's responses when you show them a drawing (or a prototype you've built) and you ask, "How do you like this? Would you buy it?" Or you could ask these questions after letting them drive a prototype for awhile.

You evaluate an option using Quality Checks — with your goals defining "quality" — by comparing goals with predictions from a Mental Experiment (to examine the match between predicted properties and the goal-properties you want, in a Mental Quality Check) or by comparing goals with observations from a Physical Experiment (to examine the match between observed properties and the goal-properties you want, in a Physical Quality Check).

The evaluative thinking used in these Quality Checks is often called critical thinking, but it's important to recognize that "critical" thinking is not necessarily negative, and does not always lead to criticism. Evaluative critical thinking often leads to an enthusiastically positive conclusion about an option. And when a conclusion is partially negative, this can be productive when it leads to beneficial change. If criticism is offered with a sincere intention to be beneficial, this is constructive criticism and it usually has a positive effect, especially when it's accurate and is received humbly with a non-defensive attitude.
During a comparative evaluation of competing options, you do Quality Checks for each option:

Option 1

Option 2

Option 2b

Option 3
etc

Your evaluations of various options can change with time, when you have gathered more information about the options. Evaluations of a product-option may lead you to modify it to make a new option (such as 2b above, invented by modifying 2) that can then be tested-and-evaluated using Quality Checks. And you may decide that a revision of some goals-for-properties is beneficial, or even necessary.
Eventually you may decide that one (or more) of your options is satisfactory, and (in another set of decisions) that you should begin manufacturing, marketing, and selling it. Or you may want to delay work on this project for awhile, or even decide that it's not worth continuing so you abandon it. Or you might convert it into a new project by revising your overall objectives, based on what you have learned during the process of design.

During the process of design you often make action decisions about what to do next, guided by an awareness of the current state of the problem, so you can Coordinate your Design-Actions in one of the Modes of Thinking-and-Action described later, but first we'll look at another aspect of Design Process.

Reality Checks
In an activity that sometimes isn't necessary when designing a product, activity, or strategy, but is often helpful, you do a Reality Check by comparing predictions with observations in order to evaluate a theory. The purpose of a Reality Check is to test the empirical quality of your theories by checking their predictive accuracy to see how closely “the way you think things are” (according to your theories) matches the reality of “the way things really are.”
Basically, a Reality Check provides evidence to help you estimate the practical utility of a theory (or a set of theories) in helping you make accurate predictions. For example, how closely do your theory-based predictions for fuel efficiency match your observations of the actual fuel efficiency? Or, after you have begun selling the minivan, how close is the match between observations (of the number of people actually buying minivans) and your predictions (for the number of purchasers) based on your theories about consumers? If the observations and your predictions don't match well, this indicates a flaw in your theories or in your method of applying the theories to make predictions.

Three Comparative Evaluations are shown in the diagram below, which is the diagram above with a few additions — labels for the three evaluations (Mental Quality Check, Physical Quality Check, Mental-and-Physical Reality Check), a lower part about THEORY(s), and 2 types of Retroductive Logic, using each of the 3 evaluations:

Diagram for Integrated Design Method, showing relationships between Design and Science

Retroductive Logic
combines Creativity with Critical Thinking
to retroductively generate Theories, Solution-Options, and Experiments
The diagram above shows two uses of retroductive logic, to generate Options and Theories. First we'll look at the creative-and-critical process used to Generate Theories.
In the context of Design Process — and therefore Science Process (i.e., Scientific Method) — a Generation of Theories has a broad meaning: scientists can generate a theory by finding-and-selecting an old theory, inventing a new theory by revising (and thus improving) an old theory or, less commonly, by inventing a theory that is mainly-new. (probably it's psychologically impossible to invent a theory that is totally-new)
• The usual strategy for selecting an old theory, or inventing a new theory, is to use retroductive logic (retroduction) in which a scientist repeatedly uses if-then logic to make theory-based Predictions,* over and over, each time “trying out” a different theory in an attempt to find a theory whose Predictions will match the Observations that already are known. The bold fonts emphasize the reason that two arrows for "retroductive logic" point toward THEORY, coming from both Predictions and Observations. The arrow for "if-then logic" shows the method for using THEORIES to make Predictions.
* A section about Prediction by using Mental Experiments explains how scientists make Predictions "by using if-then logic in one or more ways, by using deduction (with deductive logic that assumes theories about the system), simulation (as in running a computerized model of the system), or experience (by assuming that ‘what happened before, in similar situations, will happen again’), or in other ways." And this section links to pages where you can learn more about the art-and-science of predicting, including the use of Supplementary Theories in a System-of-THEORIES.
Why does the diagram say "THEORY(s)" rather than THEORY or THEORIES? My use of "THEORY(s)" is a compromise, due to a difference: one THEORY is generated by using retroductive logic; but when using if-then logic to make Predictions, a System-of-THEORIES is used, although typically one THEORY is the focus of testing in a Reality Check (this THEORY is also the one being "generated by retroductive logic") because you are assuming the truth of other theories, which are Supplementary Theories in this context. / Thinking about a system of theories is also useful for understanding how scientists typically use theories in their research. Scientists rarely discover a MAJOR new theory; instead they explore ways to extend existing major theories into new areas where the combination of old-and-new (the old major theory, and new supplementary theories for the new area) allows the construction of new knowledge while preserving the old knowledge, when we learn better ways to apply the old theory in a new area.

• Designers also use retroductive logic to generate Solution-Options (that are potential solutions for a problem) during design: a designer makes Predictions about the properties of many different Options that are being divergently generated (by finding old options or inventing new options) in an attempt to find an Option whose predicted properties will closely match the desired properties that are the Goals. During retroductive logic a designer uses both Predictions and Goals, so arrows go from both of these into Generate Options. Do you see the similarity between our evaluation-guided retroductive generation of Theories (using evaluative Reality Checks) and our evaluation-guided retroductive generation of Options (using evaluative Mental Quality Checks)? But there is a major difference, because Retroductive Generation can be Convergent or Divergent and a retroductive search for Solution-Options (or Experimental Systems) is typically more divergent than a search for Theories.
• Creative-and-critical retroductive logic is also used to design Experimental Systems. Scientists (or designers) do Mental Experiments with a variety of Experimental Systems, to quickly explore many possibilities — by imagining the Observations that could be produced with each experiment, in a divergent search for Observations that might be interesting and useful — so they can decide which Experimental Systems are worthy of further pursuit by doing Physical Experiments that, compared with quick-and-cheap Mental Experiments, typically require much larger investments of time and money.

Modes of Thinking-and-Action
The process described above is a design process that uses the 9 modes of thinking-and-action (1A, 1B,... 4A) you see below.
Earlier, these modes were briefly described — but without the labels (1A,...) — in a quick overview of design. You can learn more about the modes and their interactive relationships in An Overview of Design Process.
Modes, not Steps: The distinction between modes and steps is important, because Design Process is not a fixed sequence of steps that must be followed in a particular order, it's a logically organized framework for goal-directed improvisation, as explained earlier. It's useful to compare two kinds of ice skating — with Design Process being analogous to one (a flexibly improvising hockey skater) but not the other (a rigidly choreographed figure skater) — when we ask Is there a “method” for design?

Here are the 9 modes of thinking-and-action used in the process of design:
DEFINITION
1A. CHOOSE AN OVERALL OBJECTIVE (what you want to design) for a design project
1B. DEFINE GOALS (for the desired properties of a satisfactory problem-solution)
GENERATION
2A. FIND (PREPARE by searching for old information about solution-options & relevant theories)
2B. INVENT (to generate ideas for new options, usually by modifying old options)
2C. PREDICT (in mental experiments to produce predictions that are new information)
2D. OBSERVE (in physical experiments to produce observations that are new information)
EVALUATION
3A. EVALUATE OPTIONS using QUALITY CHECKS (compare goals with predictions or observations)
3B. EVALUATE THEORIES using REALITY CHECKS (compare predictions with observations)
COORDINATION
4A. EVALUATE THE PROCESS and MAKE ACTION-DECISIONS (for what to do & when in modes 1-4)

Part 3

In early 2012, I began developing a new website with
many improvements (by revising, adding, cutting),
so I strongly recommend that you
read it instead of this page.

Design and Science
Science is important in our modern world, exerting a major influence on how we live and think. A useful way to improve our understanding of science, and also design, is by comparing them with each other to see their similarities and differences.
What is the main connection between design and science? Broadly defined, a designer is anyone who tries to design (to select, invent, or improve) a product, activity, strategy, or theory. Because the essential objective of science is to design theories about nature (as one aspect of improving our understanding of nature), science is just a special type of design, devoted to answering one kind of question. { In the context of design, which includes science, what is a theory? }

A designer wants to make things better by defining problems and seeking solutions.
A scientist wants to improve our knowledge by asking questions and seeking answers.

When we are comparing design and science, it will be useful to adopt an OBJECTIVES-and-METHODS approach:

First, we can distinguish between two types of OBJECTIVES, the designing of products or activities or strategies (in conventional design) and the designing of theories (in science):

two types of design: Conventional Design and Science

Second, when we look at methods of evaluation, these METHODS also differ in design and science. As described above in The Process of Design, goals and predictions and observations can be compared in three ways: two of these comparisons are the main evaluation methods in design, and one comparison is the main evaluation method in science.

Objectives and Methods
In conventional DESIGN the main objective is to solve a problem by developing an improved product, activity, or strategy, and our most useful methods-of-evaluation are QUALITY CHECKS that compare goals with predictions, and goals with observations, in evaluations to determine how closely a particular product-option matches our criteria for quality, which are defined by our goals.
In SCIENCE our long-term overall objective is to improve our knowledge about nature, to search for truth by generating information (with experiments) and developing explanations (in theories) that are accurate representations of nature. During a search for explanations we sometimes use QUALITY CHECKS to compare goals for the desired properties of a theory (empirical, conceptual, and cultural-personal) with predictions (of a theory's properties) or observations (about a theory's properties), but the foundation of Scientific Method is using REALITY CHECKS that compare theory-based predictions with observations.

Engineering and Science — Comparing Cousins
Although it can be interesting to compare science with a wide range of design fields, it seems most immediately useful to compare science with its closest cousin in conventional design, which is engineering.
Comparing objectives, we see that science tries to understand nature, while engineering tries to improve technology. Notice the two differences: understanding versus improvement, and nature versus technology. But there are also similarities, interactions, and overlaps. The understanding gained by science is often applied in technology, and science often uses technology, especially for making observations but also in other ways. Sometimes in science or engineering — for example, when we try to understand the chemistry and physics of combustion in automobile engines — we study the behavior of nature in the context of technology.
And because the definitions we're using distinguish between science and design on the basis of objectives-and-methods (purpose-and-process), not careers, a scientist sometimes does engineering, and an engineer sometimes does science.

Diagram for Integrated Design Method, showing relationships between Design and Science

Design & Science — What are the similarities and differences?
In a page about educational applications of design I claim that "when students use Design Process they already are using all of the main components of Science Process (Scientific Method)." Some of these components are explained below.
Quality Checks are used in all design, in both conventional design and science. In science, 3 types of factors (empirical, plus conceptual and cultural-personal) are used to define the desired goal-properties of a theory, and are therefore used as criteria during evaluation. The empirical quality of a theory, evaluated using Reality Checks, is the most important goal-criterion when designing a theory; but scientists also consider goal-criteria for conceptual quality and cultural-personal quality, which are evaluated in Quality Checks. The relative weighting of these criteria vary from one theory-designing situation to another.
Another major activity for scientists is designing experiments, because observations are required for Reality Checks. Improving our knowledge about nature (with observations) is an essential foundation for improving our understanding of nature (in theories).
In both design and science, an important part of the problem-solving process is gathering information. This is the purpose of two modes for thinking-and-action in design: "PREPARE by searching for old information [that already is known]" and use "physical experiments to produce observations that are new information" in Modes 2A and 2D. It's useful to think of science as the designing of accurate theories (the ultimate objective) and useful experiments (a sub-objective that's necessary for scientific theorizing), so a Designing of Experiments is an important part of Scientific Method.
Despite the difference in OBJECTIVES (it's a product, activity, or strategy in conventional design, but is a theory in science) and METHODS (Design mainly uses Quality Checks, while Science mainly uses Reality Checks), there are many similarities in PROCESS between Conventional Design and Science. In both activities there is goal-directed thinking with a creative generation and critical evaluation of ideas when defining Objectives and Goals, and also when designing Experimental Systems that can be used (in a Mental Experiment or Physical Experiment, or both) to produce Predictions and/or Observations that are compared with Goals (in a Mental Quality Check and/or Physical Quality Check) and with each other (in Reality Checks). But there is an important practical difference because "a retroductive search for Solution-Options [in conventional design] or Experimental Systems [in conventional design or science] is typically more divergent than a search for Theories [in science]."
Reality Checks are used in conventional design. For example, when the objective is a minivan the designers could check the predictive accuracy of their theories for fuel efficiency or the buying behavior of consumers. But I consider these to be science-within-design, with Reality Checks performing a useful design-function by helping designers improve the accuracy of their predictions, and thus the utility of their Quality Checks (which are the focus of design-thinking) that compare predictions with goals. The essence of conventional design is Quality Checks, not the functionally useful science-within-design provided by Reality Checks.
By contrast, the essence of science is Reality Checks because they provide empirical evidence (i.e. observation-based evidence) about the truth or falsity of a theory. Reality Checks are the solid foundation of science, the main basis for evaluating empirical factors that (for most scientists, in most situations) are the most important goal-criteria for evaluating the quality of a theory. In their evaluations of a theory, scientists also consider conceptual factors (which include the scientific utility of a theory for stimulating productive experimental or theoretical research) and cultural-personal factors (which include the personal utility of a theory), so these factors are included in my model of scientific method. But usually empirical factors are much more important, especially in the long run.
I say "Reality Checks are the main basis for evaluating empirical factors" because they're not the only basis. In my model of Scientific Method, the Empirical Factors include a Degree of Agreement (this is directly tested in Reality Checks) that asks “what is the agreement between experimental Observations and theory-based Predictions?”, and also a Degree of Predictive Contrast (this is determined by comparing a theory's predictions with the predictions of other theories) that asks “what is the contrast between the predictions of this theory and predictions of plausible alternative theories?” to consider the possibility that two or more theories could make accurate predictions for an experimental system.

Objectives and Methods
In my objectives-and-methods view of design and science, we ask two questions: 1) Is the design-objective a product, activity, or strategy (in conventional design) or a theory (in science)?” 2) “Is the evaluation-method a Quality Check (used in all types of design, in both conventional design and science) or a Reality Check (used in science or for science-within-design)? / And I suggest thinking about crossover actions that occur because designers sometimes “do science” to test their theories, and scientists sometimes “do conventional design” to develop products, activities, or strategies. These crossover actions are explained below.*
But some other scholars adopt a view in which crossovers are impossible by definition, because they define design as “whatever ‘designers’ do” and science as “whatever ‘scientists’ do.” They offer another perspective on design and science. I don't think their view is intrinsically worse than mine, or better, it's just different. But I do think my approach offers significant educational benefits. It can lead to deeper understandings of design & science in the context of Design Process & Science Process, and it can help students learn the thinking skills used in design & science, so my objectives-and-methods approach may be more functionally useful for education.
* In conventional design, sometimes (during a process of conventional design where the main objective is a product, activity, or strategy) designers do science, when they compare theory-based predictions with reality-revealing observations, in Reality Checks that provide feedback about their theories. Similarly, sometimes (during a process of science where the main objective is a theory or experiment) scientists do design, when they use Quality Checks to invent-or-improve a product (such as a commercial application of their research, or a measuring-instrument that helps them make experimental observations) or an activity or strategy.
In their everyday work, the usual objectives of scientists are to design experiments that let them make observations (and get funding grants!) and design theories that explain the observations, so we can understand what is happening and why. The diagram below (which is the lower part of the basic diagram for Design Process) shows relationships between predictions, observations, and theories, and two related types of logic, if-then logic and retroductive logic, that are described earlier.

Remembering-or-Inventing Theories in Design Method

The ideas in this section continue in other pages — Using Evaluation in the Process of Design & Science (then continue onward to check Section 3a, Combining Creativity & Critical Thinking in Design) and Building Educational Bridges from Life to Design to Science and Beyond — and are explored more deeply in Design Process & Scientific Method.

Part 4

In early 2012, I began developing a new website with
many improvements (by revising, adding, cutting),
so I strongly recommend that you
read it instead of this page.

Using Design-and-Science in Education: The rest of this page — Frameworks for Improvisational Thinking, Problem-Solving Methods in Design & Science, Educational Applications of Design & Science — examines possibilities for using design-and-science in education, and explains why we should teach Design Process before Science Process (i.e., before Scientific Method).

Frameworks for Improvisational Thinking
To improve our UNDERSTANDING and TEACHING of thinking skills, I've developed two related models that are integrative (showing the integration between mutually supportive aspects of a process) for the methods of thinking-and-action used in design and science, which blend creative-and-critical thinking skills into an overall thinking process that is useful for solving problems. These frameworks for goal-directed improvisational thinking — Integrative Design Process (outlined above) and Integrative Scientific Method — were designed to achieve two main objectives: A) allow an accurate description of methods, of what designers & scientists think-and-do when they are solving problems, thus improving our UNDERSTANDING; B) help students increase the quality of their own thinking skills by helping them master the methods of thinking used by designers & scientists, thus improving our TEACHING. These two objectives, Understanding (A) and Education (B), are discussed below.

A — Problem-Solving Methods (in Design and Science)
The process of thinking-and-action used in design is outlined earlier. diagram of Integrated Scientific Method
The similar methods used in science — for a designing of theories & experiments — are examined in An Introduction to Scientific Method and An Overview of Integrated Scientific Method plus an in-depth detailed overview that includes (when you modify the URL by replacing #i with #7) an examination of problem solving in the context of science.
In this model, Scientific Method has 9 parts that can be used during a Process of Science, as you can see in the diagram: 3 parts [123] for evaluation factors (empirical, conceptual, cultural-personal), and 3 [456] for the designing (generation & evaluation) of theories and experiments, and 3 [789] for the process of science (problem-solving projects, thought styles, productive thinking).
Process versus Method: When we ask “Is a process used in science?” the answer is “certainly” and everyone agrees. But is there a method? The word “method” sometimes leads to a skeptical response that is answered in my page about the goals (and non-goals) for my model of scientific method. It explains why Integrated Scientific Method is not The Scientific Method (which doesn't exist, because no single method is used by all scientists at all times) but instead is an integrative model for commonly used scientific methods of thinking-and-actions. It describes the flexible improvisational methods of science by comparing a figure skater and hockey skater: The rigid choreography of a figure skater is not similar to the process of science. But science is analogous to a hockey skater's goal-directed structured improvisation that is guided by principles but is continually open to real-time adjustments due to changes in the situation, because "even though hockey skaters have a strategic plan, this plan is intentionally flexible, with each skater improvising in response to what happens during the game."
Scientific Method (= Science Process) and Design Process both describe a goal-directed process of flexible improvisation, not a rigid step-by-step choreographed sequence.

B — Educational Applications of Design and Science
An important function of education is helping students learn how to think more effectively. In our efforts to achieve this goal, one useful instructional tool is the classroom use of activities involving design and science, because doing these activities requires the creative generation and critical evaluation of ideas, thus giving students valuable experience that will improve their creative-and-critical thinking skills.

Metacognition for Improved Self-Education
When you learn about thinking/learning (from others & by self-observation) and you use your own personally customized theories about thinking/learning, when you ask “how can I learn more effectively?” and think about thinking so you can make strategy decisions to guide your thinking-and-actions, this is metacognition. If students are motivated to learn so they can improve their own lives, they will adopt a strategy of intentional learning by investing extra mental effort beyond what is required just to complete a schoolwork task, with the intention of achieving personal goals for learning. Metacognition can be a valuable part of this problem-solving approach to self-education that is a strategy for converting an actual current state (of knowledge) into a desired future state (of improved knowledge).
To learn more about metacognition, you can use Metacognition and Problem Solving in Education. It links to parts of three other pages (this one, plus Active Learning Theories & Teaching Strategies and An Overview of Design Process) and combines ideas from all three pages in responding to a question — “How can we design curriculum & instruction that will help students learn more effectively, by using metacogntion and in other ways?” — throughout the page, and especially in Section 7.

Design before Science
As a concept, Scientific Method is more familiar than Design Process. But as an activity, design is more familiar, for most students, in what they have experienced in the past and what they can imagine for the future. Design makes a concrete connection with the past (so students can build on the foundation of what they already know) and with the future (so they will be motivated to learn skills that will help them achieve their own personal goals for life). Therefore, it seems logical to teach design process before science process. {details}

Teaching Design Process by moving from Simplicity to Complexity
As outlined in the page-opening summary, teachers can introduce the concepts of Design Process gradually, beginning with a simple Two-Step Cycle, moving on to 3 Comparisons, and then deciding how deeply to explore 9 Modes of Design. This 3-level progression, from simple to basic to detailed, is examined in An Overview of Design Process, both verbally and with verbal-visual representations at the 3 levels.

Curriculum Coordination with Design Process
My model of Integrated Design Method could play a valuable role in a wide spiral curriculum that has wide scope (to allow a coordination across different subject areas of related learning experiences) and uses spiral repetitions (to allow a coordination over time of related learning experiences). Design Process will help students understand the coherent integration of thinking skills within each design experience, and also the connections between different experiences. The beginning of this page (asking What is a problem?) describes the design opportunities in many diverse areas of life. Although these areas may seem unrelated, Design Process can be used to show students that similar problem-solving strategies are used in each area. This understanding — and the use of Design Process in reflection activities that enourage students to be aware of what they are thinking-and-doing, thus enhancing “what is learned” from their experiences — can help students transfer their skills from one area to another. Design Process provides a common context for instruction in different areas, facilitating mutual support in a synergistic system, with a coordinated strategy for producing a more effective teaching of thinking skills and problem-solving methods across the curriculum. { For more about the potential value of these ideas, especially for K-12 education, Problem Solving & Metacognition in Education for Thinking Skills and Comparing Four Frameworks for Thinking Skills Education }

An Introduction to Design Process:

creative-and-critical Problem Solving in every area of life,

benefits for education (to improve motivations & skills-transfers),

and relationships with Science Process (Scientific Methods) & Engineering.