Design and Science
in Education and Life

by Craig Rusbult, Ph.D.

Problem Solving in Life 
The Joy of Thinking 
The Logic of Science 
The Methods of Science 
The Process of Design 
Comparing Design and Science 
Design and Science in Education
 

This overview-page is a sampler.  You can explore the ideas in
more depth in the full pages that you'll find on the right sidebar.

 


 
 
    Problem Solving in Life
      We're designed for thinking, and it's exciting to use our minds skillfully.  Thinking is a grand adventure, and we'll explore two ways to think: in design and science.
      Design is a way to solve problems.  In common language, a "problem" is usually bad.  But in design, a problem is an opportunity to make a difference, to make things better.  Whenever you are thinking about ways to increase the quality of life (or avoid a decrease in quality), you are actively involved in problem solving.
      In every area of life, generative thinking (to generate ideas) and evaluative thinking (to evaluate ideas) are essential.  These mutually supportive skills are integrated in the problem-solving methods used in a wide range of design fields — such as engineering, architecture, medicine, music, art, literature, philosophy, history, law, business, athletics, and science — where the goal is to design a product, strategy, or theory.  In fact, design includes almost everything in life.
      A product can be an object (like a refrigerator, bicycle, or car) but it also could be a repaired object (a car that works better than before), a work of art (a painting, song, or story), a letter to a colleague, an inspirational talk for a community group, or a casserole for a potluck picnic.
      Similarly, a strategy is needed in a wide variety of situations — educational (as a learner or teacher), social, athletic, political, military, legal, financial, or agricultural — involving competition and/or cooperation.  You can plan a strategy for winning a soccer game, making a friend or being a friend, planning a party, running a charity, starting a business, or growing crops to feed a nation.  When you make a decision in any area of life, you are designing a strategy for living, for helping you achieve goals.
      Design and Science:  If we define design as the process of designing products or strategies, and science as the designing of theories about nature, the main objective of design is to improve what is humanly constructed, while the main objective of science is to understand what is divinely constructed.

 
 
    The Joy of Thinking 
      Design includes almost everything in life, so you can find many ways to enjoy the excitement of design thinking, to experience the satisfaction of solving a problem and achieving a practical goal.  Since the beginning of human history, people have been designing strategies for better living, and designing products to carry out these strategies more effectively.  For example, strategies for getting food (by hunting and farming) were more effective when using products (spears and plows).  Design continues to be useful in the modern world.
      Science is also useful, in two ways.
      First, the understanding gained by science is often used by designers when they develop new products or strategies.  The technological results of "applied science" are familiar.
      Second, science can help us fulfill a deep human need, because it is one way to search for answers when, inspired by our curiosity, we ask questions about what, how, and why.  Most of us want to know the truth, so an intrinsically appealing goal is the design of scientific theories that are true, that correctly describe what is happening now and what has happened in the past.

      In our search for truth in nature, we are motivated by curiosity about how things work, a desire to solve mysteries.
      One fascinating mystery story is the discovery of quantum mechanics, an elegantly simple theory that is very strange and very successful.  A brief summary will help you understand why, after decades of uncertainty and mental struggle, a pioneer who began the adventure "rejoices over the beauties that his eye discovers."
      The history of quantum ideas began in 1900 when...
      In 1905, Albert Einstein, in an effort to explain the puzzling observations in...
      If electrons are waves, and an electron-wave in an atom is analogous to a sound-wave in a bugle, this explains...
      You can see the joy of scientific discovery in letters between two scientists who played key roles at the beginning and end of this grand adventure.  Max Planck, who found the first piece of the puzzle, describes his pleasure in seeing the elegantly simple wave equation: "I am reading your paper in the way a curious child eagerly listens to the solution of a riddle with which he has struggled for a long time, and I rejoice over the beauties that my eye discovers." Erwin Schrodinger replies by agreeing that "everything resolves itself with unbelievable simplicity and unbelievable beauty, everything turns out exactly as one would wish, in a perfectly straightforward manner, all by itself and without forcing." They struggled with a problem, solved it, and were thrilled.  It's fun to think and learn!
      But this is not the end of the story.  There were more puzzles to solve, and...  Today, scientists are still exploring the mysteries and applications of quantum mechanics.

• For the rest of the story (with the "..."s filled in) you can read The Joy of Science. (or The Mysteries of Quantum Mechanics)
 


 
 
    The Logic of Scientific Method
      Are the joys of science only for the special few, for geniuses like Planck and Einstein, de Broglie and Schrodinger?  No, you can also share in the adventure of science, because the thinking used in science is not strange and mysterious, it's the same thinking you use in daily life.  In scientific logic, as in daily life, you use reality checks to decide whether "the way you think the world is" matches "the way the way the world really is."  We'll begin by looking at the two things being compared in a reality check: observations and predictions.

      Experiments and Observations
      In science, information about nature comes from experiments that allow observations.  Consider two types of experimental situations:...

      Theories and Predictions
      A theory is a human attempt to describe and/or explain our observations of what happens, or (in historical science) what has happened.  A descriptive theory claims only to describe what happens.  An explanatory theory claims to describe what happens and also why it happens.
      With a descriptive theory, predictions are made by...
      An explanatory theory claims to explain "how and why things are happening"...
      With either type of theory, the if-then inference is similar.  You think, "In this situation, IF the system behaves as expected (according to the theory), THEN we will observe ___" and what you put in the blank is your theory-based prediction.
      When scientists make an if-then inference, they can move from IF to THEN in a variety of ways.  They might...
      Scientists can make theory-based inferences about "what will happen and what will be observed" either before or after observations are known. ...  But inferences with either timing are logically equivalent if each is obtained using valid logic, and in science both are called predictions.

      Theory Evaluation
      The foundation of scientific logic is the reality check.  By observing reality and using logic, scientists can decide whether a theory about "the way it is" corresponds to "the way it really is."
      A physical experiment allows observations of what nature actually does, and a mental experiment lets us make predictions about what nature will do. ...
      Multiple Independent Confirmations:  When a theory makes correct predictions in a wide variety of independent areas, and alternative theories make incorrect predictions, this provides strong evidence that the repeatedly confirmed theory is true.
      Usually, empirical factors (based on reality checks) are the main factors in theory evaluation.  But scientists also consider conceptual factors such as a theory's logical characteristics (like internal consistency and structural simplicity) and its relationships with other currently accepted scientific theories.  Scientists are also influenced by cultural-personal factors (such as personal desires, group pressures, philosophical or religious views, and cultural thinking habits) but most scientists think the quality of science decreases when these factors affect the results of theory evaluation.
      The overall result of theory evaluation is an estimate of theory status.  This status, which can range from very low to very high, indicates the scientists' confidence in a theory.  Most philosophers think that, according to formal logic, it is impossible to prove a theory is either true or false, but scientists can develop a rationally justified confidence in their conclusions.

      Theory Generation
      The focus now shifts from evaluation to generation, when we ask "Where do scientific theories come from?"
      Usually, scientists work with theories that already exist.  But earlier in the history of science these theories had to be generated.  And sometimes...
      A descriptive theory is generated when scientists recognize a pattern, when they notice that...  But how do we react, thinking as scientists, when we see that some objects — such as a helium balloon, bottle rocket, or bird — do not fall?  We can...  And we can...
      An explanatory theory is usually generated by a process of creative thinking in which imagination is guided by the logic of reality checks.  In prediction we ask a cause-to-effect question: "In this situation, if these causes are operating, what will be the observed effects?"  The if-then reasoning is reversed in retroduction when we ask an effect-to-cause question: "In this situation, if these effects were observed, what causes could have been operating?"  This reversed question inspires a search in which we...  The goal is to find a theory that will pass the reality check, to find a theory that, if true, would explain what has been observed.
      You can be a scientist, generating your own theory to explain...

• For the rest of the story (with the "..."s filled in) and more, you can read An Introduction to Scientific Method.
 


 
 
    The Methods of Science
      Is there a scientific method?  If "method" means "a single method, used in the same way by all scientists at all times," the answer is NO.  Some details change with time and culture, and vary from one area of science to another, so there is nothing that could be called The Scientific Method. But some scientific methods are commonly used by scientists.
      The methods used in science are functional; scientists use methods to achieve goals.  For most scientists, the main goal is to find truth.  They want to construct theories that are true, that correspond with reality by correctly describing what really happens in nature.  In a search for true theories, the main thinking tools — the generation and evaluation of theories, using observation, imagination, and logic — are described above in "The Logic of Science."
      But scientists do more than just generate and evaluate theories.  They also design and do experiments, plan big research projects and small daily activities, describe (by writing and talking) their own research, learn (by reading and listening) about the research of others, discuss ideas with other scientists, and more.  Basically, scientists do whatever they think will help them achieve their goals.
      The methods of science are flexible, not rigid.  Consider two types of ice skaters.  The sequential actions of a figure skater are precisely planned and, if there are no mistakes, predictable.  By contrast, even though hockey skaters have a strategic plan, the plan is intentionally flexible, with each skater improvising in response to what happens during a game.  The methods used in science are analogous to the flexible "structured improvisation" of a hockey skater, not the rigid choreography of a figure skater.
 

      Debates about Science
      The main methods of scientific thinking, such as reality checks based on observations and logic, are used by all scientists.  But details can vary from one area of science to another, and from one scientist to another.
      Scholars, including scientists and those who study science (in philosophy, history, sociology, psychology, and education), have vigorous discussions about the methods used in science.  There are debates, for example, about cultural-personal influences in evaluations of scientific theories, about whether the effects are significant and are desirable.  Most scientists think these effects should be minimized, but some scholars (especially those who have adopted a postmodern perspective) think cultural-personal factors should be a part of scientific theory evaluation.  There is an abundance of hot debates: Should scientific method be eks-rated?
      Philosophers of science also ask, "What is required for an adequate explanation?"  They would say that...  For these questions, scientists still don't have satisfactory answers.
 

      Historical Sciences are Scientific
      Were you there?  Did you see it?  If you say "no" does this mean that you can't know anything about what happened?  Or do you think that detectives can sometimes solve mysteries?  Can historical science be authentically scientific?
      Some variations in scientific methods are due to differences between operations science (to study the current operation of nature, what is happening now) and historical science (to study the previous history of nature, what happened in the past).  Both types of science are similar in most important ways, especially in their use of scientific logic, but there are minor differences.
      Although repeatable controlled experiments can be done in operations science, this is not possible for historical events.  But limitations on historical data have inspired scientists to develop methods that reduce the practical impact of these limitations, and historical sciences — in fields such as astronomy, radiometric physics, and geology, which can be used to calculate the age of the earth and the universe — are authentically scientific.
      In historical science, one way to "reduce the practical impact" is to use repeatable uncontrolled experiments.  For example, observations of many Cepheid stars from many parts of the universe have shown that all Cepheids have similar properties, allowing them (and supernovas, which have their own consistencies) to be useful for measuring astronomical distances.  These consistencies let scientists develop reliable descriptive theories, which can become explanatory theories that usually are related to (and are consistent with) explanatory theories in operations science.

      Because theory-based inferences are usually called predictions, the non-scientific meaning of "prediction" can lead to the mistaken impression that a scientific prediction must be made before an event occurs.  But in historical science the timing of prediction is not a cause for concern, since predictive theory-based inferences can be logically valid even if they are made after an event has occurred, or after observations are known.  In historical science, the goal is to describe and explain what did happen, not predict what will happen.  In operations science a descriptive theory states that "what happened before will happen again."  In historical science a descriptive theory might predict that "what happened in this situation also happened in other similar situations," or it might propose only that "this is what happened."
      In some historical situations, only undirected natural process is involved, and a mechanistic explanatory theory can provide an adequate description and explanation.  In other situations, "what happens" depends on the decisions and actions of an agent.  This introduces an element of unpredictability, but a historical detective using scientific reasoning (in psychology, sociology, anthropology, archaeology, history, or forensics) only has to determine what did occur, not predict what will occur, in a descriptive theory.  And in an agency explanatory theory, proposing that "agent action was involved" is the scientific conclusion of a historical detective.

      Can scientists logically infer the existence of things they cannot observe?  Yes, if an unobservable cause produces observable effects.  This principle of cause-and-effect logic is used in operations science.  Even though electrons and ideas cannot be observed, modern theories propose electrons (in chemistry) and ideas (in psychology) .  Why?  Because our observations are explained in the most satisfactory way by theories proposing the existence of unobservable causes (electrons and ideas) that produce the effects we observe.
      Similarly, in historical science we can logically infer the existence of causes we did not observe if these unobserved causes produced effects we can observe.  Therefore, when skeptics ask "Were you there? Did you see it?", they are ignoring the principle that scientific logic depends only on having observable effects, not observable causes.  Because of this principle, even if an event or process was not directly observed, it does not necessarily weaken the credibility of a scientific theory proposing that the event or process did occur.

• This section is in Part 1 of a three-part series, set in the context of questions about creation, asking "Is historical science really science?"
 


 
 
    The Process of Design
      The first step in solving a problem is recognizing that it exists.  You recognize a problem when you understand the way a situation is now, and you can imagine a future in which things have changed and improved.  Or maybe you can imagine a future in which things have changed but have not improved, and you want to avoid these changes.  Either way, if you want to take advantage of your opportunity to make a difference, you will generate and evaluate ideas-and-actions that help you make progress toward solving the problem.
      Imagine that you are trying to design a product, and your overall objective is "an improved refrigerator."
      You define your quality-GOALS by defining the desirable properties of a satisfactory product.  In this case, what kind of "improvements in the refrigerator" do you want?  Your goals are based on your knowledge of what is, and your imagination about what could be.
      Usually, the search for a solution begins by remembering old products, by searching your own memory and our collective memory (in books, websites,... and in other people) for existing products.  For each old product, you collect OBSERVATIONS of the product's properties, and ask "How closely do these known properties match my goals for the properties of a satisfactory product?"  In this question, you are comparing observations with goals in a quality-check that lets you determine how well a product meets your quality-goals, which are your criteria for defining quality.
      You can widen your range of options by imagining new products.  Usually, a new product is invented when, guided by goals, you begin with an old product and make changes.  Based on what you know about the old product and new changes, you can do mental experiments to predict the properties of a new product.  Or you can predict the properties of an old product in a new situation.  In either case, you use your PREDICTIONS by asking "How closely do the predicted properties match my quality-goals?"  In this quality-check, you are comparing predictions with goals.
      You can also gain knowledge by testing a product (old or new) in a physical experiment that lets you make OBSERVATIONS about properties.  Then you can ask, "How closely do the known properties match my quality-goals?"  In this quality-check, you are comparing observations with goals.
      Design Decisions:  You use quality checks (by comparing quality-goals with observed properties or predicted properties) to evaluate each potential product, old or new.  Eventually, you may find a product that satisfactorily achieves your goals, and you consider the problem solved.  Or you continue searching, or abandon the search.

      The same process of action-and-logic is used for designing a product or strategy.  But the process is different for designing a theory, as discussed in the following section.

• For more about the process of design, read An Introduction to Design Method.
 


 
 
    Comparing Design and Science
      If we define design as the designing of products or strategies, and science as the designing of theories, how are design and science related?  What are the similarities and differences, in process and purpose?  The actions-and-logic used in design and science are summarized in this diagram:
 


 

    DESIGN Method:  During the process of design, you set quality-GOALS for desired properties, use physical experiments to make OBSERVATIONS, and use mental experiments to make PREDICTIONS, so you can do QUALITY CHECKS either by comparing observations (of known properties) with goals (for desired properties) or by comparing predictions (of expected properties) with goals (for desired properties).  If you want to understand design method better, study the diagram and this brief summary to get an overview of "the big picture" and then re-read the previous section about The Logic of Design.
    SCIENTIFIC Method:  During the process of science, as explained earlier and shown in the diagram, OBSERVATIONS (from physical experiments) are used to imaginatively generate a THEORY, which can be used with if-then logic (in a mental experiment) to make PREDICTIONS, so you can do a REALITY CHECK by comparing observations with predictions, to test whether "the way you think it is" (assuming the theory is true) corresponds to "the way it really is."
    Comparing Process:  The methods used in science and design are related, yet different.  The three elements of thinking — goals, observations, and predictions — can be compared in three ways.  Two comparisons (of observations with goals, and predictions with goals) are used in design for quality checks.  One comparison (of observations with predictions) is used in science for a reality check.
    Comparing Purpose:  In design, the main objective is to develop a product or strategy, to invent or improve something that is humanly constructed.  In science, the main objective is to develop theories, to understand nature that (I think) is divinely constructed.
    Comparing Process-and-Purpose:  In design, we use quality checks to decide whether a particular product (or strategy) satisfactorily achieves our quality-goals for the product (or strategy).  In science, we use reality checks to test whether a theory corresponds with reality, whether it is true.  The process is different because the purpose is different.
    Comparing Overlaps:  Often, the results of science can be applied in the designing of products or strategies, but this is not the main objective of science.  During design it may be useful to improve a theory that is being used while developing a product or strategy, but theory development (which is the main objective in science) is not the main objective in design.
    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 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 purpose-and-process (objectives-and-methods), not careers, a scientist sometimes does engineering, and an engineer sometimes does science.

• If you're curious, you can read more about Design and Science.
 


 
 
    Design and Science in Education
      An Educational Bridge:  Reality checks, which are used in both design and science, serve as a bridge from design to science, and this will make it easier to learn scientific method. 
      If you are serving as a teacher (if you are helping someone else learn) you can watch for an appropriate time, during a design project, to ask a science question: When predictions and observations are compared, do they match?  Since this question is a reality check, which is the logical foundation of science, you have an opportunity to explain the logic of science: experiments and observations, theories and predictions, and (for the evaluation and generation of theories) reality checks.  Of course, you won't do all of this at once.  Pacing is important.  But most components of scientific method are already being used in design method, and this will make it much easier to learn scientific method.
      Design before Science:  Because design "includes almost everything in life," it's easy to find design projects that are fun-and-useful for a student, who is thus motivated to think and learn.  The process of scientific thinking also becomes fun-and-useful when design and science are connected by using reality checks as a bridge.  This bridge allows a smooth transition from design method to scientific method, which is introduced in a way that is easy, fun, and comfortable, not difficult, boring, and scary.  As a concept, Scientific Method is more familiar than Design Method.  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.  Because the everyday lives of students have been filled with design thinking, design makes a concrete connection with their past (so they can build on the foundation of what they already know) and with their future (so they will be motivated to learn skills that will help them achieve their own goals for life).  Therefore, it seems logical to teach design method before scientific method.
      Learning from Reality:  In a reality check, sometimes there is a close match between predictions and observations, and this gives us confidence in the theory being tested.  When there is not a close match, this can help us change our thinking so it more closely corresponds with reality, which is very useful in science and design, and in life.

• Another page explains, more thoroughly, why we should teach design before science.
 

 

 


 
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Thinking Skills in Education:
Scientific Method, Problem Solving, and Design Method

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