Creative Thinking and
Critical Thinking
in Science

by Craig Rusbult, Ph.D.

The excerpts below are from two parts of
A Detailed Examination of Scientific Method:
the end of Section 5 (generating ideas for theories) and
the middle of Section 6 (generating ideas for experiments).

    from Section 5 of A Detailed Examination of Integrated Scientific Method,

    DOMAIN-THEORIES and SYSTEM-THEORIES.   A theory-based model of an experimental system is constructed from two sources: a general domain-theory (about the characteristics of all systems in a domain) and a specific system-theory (about the characteristics of one experimental system).  During retroduction, either or both of these theories can be revised in an effort to construct a model whose predictions will match the known observations.
    But a system-theory and domain-theory are not independent.  While playing with the possibilities for revising these theories, an inventor may discover relationships between them.  In particular, a domain-theory (about all systems in the theory's domain) will usually influence a system-theory about one system in this domain.
    An interesting example of revising a system-theory was the postulation of Neptune.  In the mid-1800s, data from planetary motions did not precisely match the predictions of a domain-theory, Newtonian Physics.  By assuming the domain-theory was valid, scientists retroductively calculated that if the system contained an extra planet, with a specified mass and location, predictions would match observations.  Motivated by this newly invented system-theory with an extra planet, astronomers searched in the specified location and discovered Neptune.  Later, in an effort to resolve the anomalous motion of Mercury, scientists tried this same strategy by postulating an extra planet, Vulcan, between Mercury and the Sun.  But this time there was no extra planet; instead, the domain-theory (Newtonian physics) was at fault, and eventually a new domain-theory (Einstein's theory of general relativity) made correct predictions for the motion of Mercury.  In these examples, both of the components used for constructing a model were revised; there was a change in the system-theory (with Neptune) and in the domain-theory (for Mercury).  ...< snip >...

    STRATEGIES FOR RETRO-GENERALIZING.   When retroduction [a process of selecting or inventing a theory that can explain known data] is constrained by multiple sources of data [so the theory must be consistent with all of the known data], it may be easier to "cope with the complexity" if a simplifying strategy is used. ... [one such method is then briefly described] ...
    A more holistic strategy is to creatively search the data looking for an empirical pattern that, once recognized, can provide the inspiration and guiding constraints for inventing a composition-and-operation mechanism that explains the pattern.  This process begins with no theory; then there is a descriptive theory (based on an empirical pattern) that can be converted into an explanatory theory.  While searching for patterns, a scientist can try to imagine new ways to see the data and interpret its meaning.  Logical strategies for thinking about multiple experiments, such as Mill's Methods of inquiry, can be useful for pattern recognition and theory generation.

    RETRODUCTION and INDUCTION.   Most of the discussion above has focused on the use of deductive logic during retroduction.  Usually, however, retroduction also involves some inductive logic. ...  The eclectic nature of generative inference should be recognized:  usually, a scientific "inference to the best explanation" involves a creative blending of logic that is both inductive and deductive.

    GENERATION AND EVALUATION.   Although C.S. Peirce (in the 1800s) and Aristotle (much earlier) studied theory invention, as have many psychologists, most philosophers separated evaluation from invention, and focused their attention on evaluation.  Recently, however, many philosophers (such as Hanson, 1958; and Darden, 1991) have begun to explore the process of invention and the relationships between invention and evaluation.  Haig (1987) includes the process of invention in his model for a "hypothetico-retroductive inferential" scientific method.
    Generation (by selection or invention) and evaluation are both used in retroduction, with empirical evaluation acting as a motivation and guide for generation, and generation producing the idea being evaluated.  It is impossible to say where one process ends and the other begins, or which comes first, as in the classic chicken-and-egg puzzle.
    The generation of theories is subject to all types of evaluative constraints.  Empirical adequacy is important, but scientists also check for adequacy with respect to cultural-personal factors and conceptual criteria: internal consistency, logical structure, and external relationships with other theories.

    INVENTION BY REVISION.   Invention often begins with the selection of an old (i.e., previously existing) theory that can be revised to form a new theory.

    ANALYSIS AND REVISION.   One strategy for revising theories begins with analysis; split a theory into components and play with them by thinking about what might happen if components (for composition or operation) are modified, added or eliminated, or are reorganized to form a new structural pattern with new interactions.
    According to Lakatos (1970), scientists often assume that a "hard core" of essential theory components should not be changed, so an inventor can focus on the "protective belt" of auxiliary components that are devised and revised to protect the hard core.  Usually this narrowing of focus is productive, especially in the short term.  But occasionally it is useful to revise some hard-core components.  When searching for new ideas it may be helpful to carefully examine each component, even in the hard core, and to consider all possibilities for revision, unrestrained by assumptions about the need to protect some components.  By relaxing mental blocks about "the way things must be" it may become easier to see theory components or data patterns in a new way, to imagine new possibilities.
    Or it may be productive to combine this analytical perspective with a more holistic view of the theory, or to shift the mode of thinking from analytical to holistic.

    INTERNAL CONSISTENCY.   Another invention strategy is to construct a theory, using the logic of internal consistency, by building on the foundation of a few assumed axiomatic components.
    In mathematics, an obvious example is Euclid's geometry.  An example from science is Einstein's theory of Special Relativity; after postulating that two things are constant (physical laws in uniformly moving reference frames, and the observed speed of light), logical consistency -- which Einstein explored with mental experiments -- makes it necessary that some properties (length, time, velocity, mass,...) will be relative while other properties (proper time, rest mass,...) are constant.  A similar strategy was used in the subsequent invention of General Relativity when, with the help of a friend (Marcel Grossmann) who was an expert mathematician, Einstein combined his empirically based physical intuitions with the powerful mathematical techniques of multidimensional non-Euclidean geometry and tensor calculus that had been developed in the 1800s.
    Although empirical factors played a role in Einstein's selection of initial axioms, once these were fixed each theory was developed using logical consistency.  Responding to an empirical verification of General Relativity's predictions about the bending of light rays by gravity, even though Einstein was elated he expressed confidence in his conceptual criteria, saying that the empirical support did not surprise him because his theory was "too beautiful to be false."

    EXTERNAL RELATIONSHIPS.   Sometimes new ideas are inspired by studying the components and logical structure of other theories.  Maybe a component can be borrowed from another theory; in this way, shared components become generalized into a wider domain, and systematic unifying connections between theories are established.
    Or some of the structure in an old theory can be retained (with appropriate modification) while the content of the old components is changed, thereby using analogy to guide the logical structuring of the new theory.
    Another possibility is mutual analysis-and-synthesis; by carefully comparing the components of two theories, it may be possible to gain a deeper understanding of how the two are related by an overlapping of components or structures.  This improved understanding might inspire a revision of either theory (with or without borrowing or analogizing from the other theory), or a synthesis that combines ideas from both theories into a unified theory that is more conceptually coherent and has a wider empirical scope.
    And sometimes a knowledge of theories in other areas will lead to the recognition that an existing theory from another domain can be generalized, as-is or modified, into the domain being studied by a scientist.  This is selection rather than invention, but it still "brings something new" to theorizing in the domain.  And the process of selection is similar to the process of invention, both logically and psychologically, if (as in this case) selection requires the flexible, open-minded perception of a connection between domains that previously were not seen as connected.

    from Section 5 of A Detailed Examination of Integrated Scientific Method,

    LOGICAL STRATEGIES for experimental design.  To facilitate the collection and interpretation of data for any of the goals described above, logical strategies are available.  Scientists can use hypothetico-deduction or retroduction to make inferences about a domain-theory or system-theory.  Or they can calibrate a new experimental technique with cross-checking logic that [as described earlier in Section 6] compares data from the new technique and a familiar technique.
    Logical strategies -- such as the systematic variation of parameters (individually or in combinations) to establish "controls", to discover correlations, and to determine the individual or combined effects of various factors -- can be useful for designing clusters of experiments to generate data that is especially informative.  One such strategy is Mill's Methods for experimental inquiry.  Complementary "variations on a theme" experiments can be planned in advance, or improvised in response to feedback from previous experimental results.
    By using inductive logic, a descriptive or explanatory theory can be generalized into an unexamined part of a domain.  In making the logical leap of generalizing observations (or principles) from a small sample to a larger population, scientists depend on two main criteria: statistical analysis (by considering sample size, degree of agreement,...) and sampling accuracy (by asking whether the sample accurately represents the whole population).  These criteria can be used for controlled experiments or field studies.
    In addition to these types of logic, each area of science has its own principles for designing experiments.  In certain types of medical or social science experiments, for example, there are usually design features such as "blind" observation and interpretation, or controls for psycho-physical placebo effects and for motivational factors (Borg & Gall, 1989) such as the John Henry Effect, Pygmalion Effect, and Hawthorne Effect.

    VICARIOUS EXPERIMENTATION.   So far, this discussion has not challenged an implicit assumption that the only way to collect observations is to do an experiment.  But one scientist can interpret what another observes, so a "theoretician" can vicariously design-and-do experiments by reading (or hearing) about the work of others, in order to gather observations for interpretation.
    This strategy won a Nobel Prize for James Watson and Francis Crick.  They never did any productive DNA experiments, but they did gather useful observations from other scientists: xray diffraction photographs (from Rosalind Franklin), data about DNA's water content (also from Franklin), data about the ratios of base pairs (from Erwin Chargaff), and information about the chemistry and structure of DNA bases (from Jerry Donohue).  Then they interpreted this information using thought-experiments and physical models, and they retroductively invented a theory for DNA structure.  Even though they did not design or do experiments, a similar function was performed by their decisions about gathering (and paying close attention to) certain types of observations.

    CUSTOMIZED DESIGN.   Effective problem formulation is customized to fit the expertise and resources of a particular research group.  For example, if members of one group are expert at theorizing about a certain molecule, they may use a wide variety of experimental techniques (plus reading and listening) to gather information about their molecule.  Another group, whose members have the expertise (and the expensive machine) required to do a difficult experimental technique, may search for a wide variety of molecules they can study with their technique.

    TAKING ADVANTAGE OF OPPORTUNITIES.   Often, new opportunities for scientific research emerge from a change in the status quo.  A newly invented theory can stimulate experiments with different goals:  to test the theory and, if necessary, revise it;  to explore its application for a variety of systems within (or beyond) its claimed domain;  or to calculate the value of physical constants in the theory.
    New experimental systems can be produced by new events (a volcanic eruption,...) or by newly discovered data (rocks on Mars,...) or phenomena (such as radioactivity in 1896, or quasars in 1960).  New experiments can include field studies of natural phenomena, and controlled experiments such as the labwork used to study dinosaur bones.
    New instrumentation technologies or observation techniques can produce opportunities for designing new types of experimental systems.  When this occurs a scientist's goal can be to learn more about an existing theory or domain by using the new tool, or to learn more about the tool.  Scientists can design their own instruments, or they can use technology developed mainly for other purposes, or they can provide motivation for developing new technologies by making known their wishlist along with a promise that a market will exist for the new products.  Or old technologies can be used in a new way, such as setting up the Hubble Telescope on a satellite above the optically distorting atmosphere of the earth.

    When an area opens up due to any of these changes, for awhile the possibilities for research are numerous.  To creatively take advantage of a temporary window of opportunity, an open-minded awareness (to perceive the possibilities) and speed (to pursue possibilities before they vanish due to the work of others) are often essential.  For example, Humphrey Davy used the newly developed technique of electrolysis to discover 7 elements in 1807 and 1808.  Of course, in science (as in the rest of life) it helps to be lucky, to be in the right place at the right time, but to take advantage of opportunity a person must be prepared.  As Louis Pasteur was fond of saying, "Chance favors the prepared mind."  Many other scientists were working in the early 1800s, yet it was Davy who had the most success in using the new technique for discovery.

    The references cited in this page are located in another page.
 

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