In this part of the page, a model of
Integrated Scientific Method (ISM)
is described in nine sections that,
since they are not "steps in a process,"
can be explored in any order you want:
1. Hypothetico-Deductive Logic, and
Empirical Factors in Theory Evaluation
2. Conceptual Factors in Theory Evaluation
3. Cultural-Personal Factors in Theory Evaluation
4. Theory Evaluation and
5. Theory Generation
6. Experimental Design (Generation-and-Evaluation)
7. Problem-Solving Projects
8. Thought Styles
9. Mental Operations
In the text that follows,
bold red print
is used for an element in the ISM-diagram,
non-bold red print shows concepts that are
not in the diagram.
A Model of "Integrated
Scientific Method" |
1. Hypothetico-Deductive Logic, and Empirical Factors
in Theory Evaluation
This tour of ISM (Integrated
Scientific Method) begins with hypothetico-deductive
logic, the foundation for modern science that provides a "reality
check" to guide the invention, evaluation, and revision of theories. |
| In ISM an
experimental system (for a controlled
experiment or field study) is defined
as everything involved in an experiment, including what is being studied,
what is done to it, and the observers (which can be human or mechanical).
When a physical experiment is
done with the experimental system, observation detectors are used to obtain
observations.
isolation-diagram for Physical Experiments
details |
A theory
is a humanly constructed representation intended to describe or explain
the observed phenomena in a specified domain
of nature. By combining a domain-theory
(about all systems in a domain, based on a theory
and supplementary theories) with a
system-theory (about one experimental system),
scientists construct an explanatory model
that is a simplified representation of the system's composition
(what it is) and operation (what it does).
After an explanatory model is defined, a thought
experiment can be done by asking, "IF this model is true,
THEN what will occur?", thereby using deductive
logic to make predictions.
Or, based on a descriptive
model that is limited to observable properties and their relationships,
scientists can make predictions by using inductive
logic, by making a deductive generalization that "IF this situation
is similar (or identical) to previous situations, THEN we should expect
a result that is similar (or identical)."
Usually, predictions (and evaluations) are based
on logic that is both deductive and inductive. isolation-diagram for Mental Experiments |
| The dual-parallel
shape of the hypothetico-deductive "box" (whose 4 corners are
defined by the model and system, predictions and observations) symbolizes
two parallel relationships. The left-side process (done by mentally
running a theory-based model) parallels
the right-side process (done by physically running a real-world
experimental system). There is also a parallel between
the top and bottom of the box. At the top, a hypothesis
is a claim that the model and system are similar in some respects and to
some degree of accuracy. At the bottom is a logical
comparison of predictions (by the model) and observations (of
the system); this comparison is used to evaluate the hypothesis, based on
the logic that the degree of agreement
between predictions and observations may be related to the degree of similarity
between model and system. But a theory can be false even if its predictions
agree with observations, so it is necessary to supplement this "agreement
logic" with another criterion, the degree
of predictive contrast, by asking "How much contrast exists
between the predictions of this theory and the predictions of plausible
alternative theories?" in an effort
to consider the possibility that two or more theories could make the same
correct predictions for this system. isolation-diagram
for Hypothetico-Deductive Logic |
Estimates for degrees of agreement
and predictive contrast are combined to form an empirical
evaluation of current hypothesis. This evaluation and the
analogous empirical evaluations of previous hypotheses
(that are based on the same theory as the current hypothesis) are empirical factors that influence theory evaluation.
diagram for ISM isolation-diagram
for Empirical Factors details
|
2. Conceptual Factors in Theory Evaluation
In ISM the conceptual
factors that influence theory evaluation are split into internal
characteristics and external relationships.
Scientists expect a logical
internal consistency between a theory's own
components. And when evaluating a theory's logical
structure, one common criteria is simplicity,
which is achieved by postulating a minimum number of logically interconnected
theory-components. Also, in each field of science there are expectations
for the types of entities and actions that should (and should not) be included
in a theory. These "expectations about components" can be
explicit or implicit, due to scientists' beliefs about ontology
(what exists) or utility (what is useful).
The external
relationships between theories (including both scientific and
cultural-personal theories) can involve an overlapping of domains or a sharing
of theory components. Theories with domains that overlap are in direct
competition because they claim to explain the same systems. Theories
with shared components often provide support for each other, and can help
to unify our understanding of the domains they describe. There is
some similarity between the logical structures for a theory
(composed of smaller components) and for a mega-theory
(composed of smaller theories), and many conceptual criteria can be applied
to either internal structure (within a theory) or external relationships
(between theories in a mega-theory). isolation-diagram
for Conceptual Factors ISM-diagram
details
|
3. Cultural-Personal Factors in Theory Evaluation
During all activities of
science, including theory evaluation, scientists are influenced by cultural-personal factors. These factors
include psychological motives and practical concerns
(such as intellectual curiosity, and desires for self esteem, respect from
others, financial security, and power), metaphysical
worldviews (that form the foundation for some criteria used in
conceptual evaluation), ideological principles
(about "the way things should be" in society), and opinions
of authorities (who are acknowledged due to expertise, personality,
and/or power).
These five factors interact with each other, and
operate in a complex social context that involves individuals, the scientific
community, and society as a whole. Science and culture are mutually
interactive, with each affecting the other. The effects of culture,
on both the process of science and the content of science, are summarized at the top of
the ISM diagram: "scientific activities... are affected by culturally
influenced thought styles."
Some cultural-personal influence is due to a desire
for personal consistency between ideas, between
actions, and between ideas and actions. For example, scientists are
more likely to accept a scientific theory that is consistent with their
metaphysical and ideological theories. In the diagram this type of
influence appears as a conceptual factor, external
relationships... with cultural-personal theories.
isolation-diagram for Cultural-Personal Factors
ISM-diagram details
|
4. Theory Evaluation
A theory
is evaluated in association with supplementary
theories, and relative to alternative
theories. Inputs for evaluating
a theory come from empirical, conceptual, and cultural-personal
factors, with the relative weighting of factors varying from one situation
to another. The immediate output of theory evaluation is a theory status that is an estimate of a theory's
plausibility (whether it seems likely to be
true) and/or usefulness (for stimulating scientific
research or solving problems). Based on their estimate of a theory's
status, scientists can decide to retain
this theory with no revisions, revise
it to generate a new theory, or reject
it. When a theory is retained after evaluation, its status can be
increased, decreased, or unchanged. A theory can be retained for the
purpose of pursuit (to serve as a basis for
further research) and/or acceptance (as a proposed
explanation, for being treated as if it were true). According to formal
logic it is impossible to prove a theory is either true or false, but scientists
have developed analytical methods that encourage them to claim a "rationally
justified confidence" for their conclusions about status. Each theory has two types of status: its own intrinsic
status, and a relative status that is
defined by asking "What is the overall appeal of this theory compared
with alternative theories?"
isolation-diagram for Theory Evaluation
ISM-diagram details |
5. Theory Generation
Generating
a theory can involve selecting
an old theory or, if necessary, inventing
a new theory. The process of inventing a new theory usually occurs
by revising an existing "old theory."
Some strategies for invention are: split an old theory into
components that can be modified or recombined in new ways; borrow
components (or logical structure) from other theories; generalize
an old theory, as-is or modified, into a new domain; or apply the
logic of internal consistency to build on the foundation of a few assumed
axiom-components. Often, a creative analysis
of data (to search for patterns) is a key step in constructing a
theory. |
| Theory
generation is guided by evaluation factors that are cultural-personal, conceptual,
and empirical. There is a close relationship between the generation
and evaluation of a theory. { Similarly, the generation and evaluation
of an action (such as designing or executing an experiment) are closely
related. } |
Empirical
guidance is used in the creative-and-critical process of retroduction
-- a thinking strategy in which the goal is to generate
(to propose by selection
or invention) a theory whose predictions will match known
observations. If there is data from several experiments,
retroduction can aim for a theory whose predictions are consistent with
all known data. During retroduction a scientist, curious about puzzling
observations and motivated to find an explanation, can adjust either of
the two sources used to construct a model: a general domain-theory
(that applies to all systems in a domain) and a specific system-theory
(about the characteristics of one system). Usually, a scientific "inference to the best explanation" involves
a creative use of logic that is both inductive and deductive.
With retroduction or hypothetico-deduction
(which are similar, except that in retroduction a model is proposed
after the observations are known), similar logical limitations apply.
Even if a theory correctly predicts the observations, plausible alternative
theories might make the same correct predictions, so with either retroduction
or hypothetico-deduction there is a cautious conclusion:
IF system-and-observations, THEN MAYBE model
(and theory). This caution contrasts with the definite conclusion
of deductive logic: IF theory-and-model, THEN prediction.
isolation-diagram for Theory Generation
ISM-diagram details
|
6. Experimental Design (Generation-and-Evaluation)
In ISM an "experiment"
is defined broadly to include both controlled experiments
and field studies. Three arrows point
toward generate experiment, showing
inputs from theory evaluation (which can motivate and guide design), gaps in system-knowledge (that can be filled
by experimentation, and provide motivation) and "do
thought experiments..." (to facilitate the process of design).
The result of experimental design (which combines
generating an experiment with evaluating an experiment) is a "real-world
experimental system" that can be
used for hypothetico-deductive logic.
Sometimes experiments are done
just to see what will happen, but an experiment is often designed to accomplish
a specific goal. For example, an experiment (or a cluster of related
experiments) can be done to gather information about a system or experimental
technique, to resolve anomaly, to provide support for an argument, or to
serve as a crucial experiment that can distinguish
between competing theories. To facilitate the collection and interpretation
of data for each goal, logical strategies are available. For example,
scientists can think ahead to questions that will be raised during evaluation,
about issues such as sample size and representativeness, or the adequacy
of controls.
Often, new opportunities for
experimenting (and theorizing) emerge from a change in the status quo.
For example, opportunities for field studies may arise from new events (such
as an ozone hole) or new discoveries (of old dinosaur bones,...).
A new theory may stimulate experiments to test and develop the theory, or
to explore its application for a variety of systems. Or a new observation
technology may allow new types of experimental systems. When an area
of science opens up due to any of these changes, opportunities for research
are produced. To creatively take advantage of these opportunities
requires an open-minded awareness that can imagine a wide variety of possibilities. |
Thought-experiments, done to quickly explore
a variety of possibilities, can help scientists evaluate potential experimental
systems and decide which ones are worthy of further pursuit with physical
experiments that typically require larger investments of time and money.
Thought-experiments play a
key role in three parts of ISM: in experimental design, retroduction, and
hypothetico-deduction. In each case a prediction is produced from
a theory by using deductive logic, but there are essential differences in
timing and objectives. And sometimes mental experiments are done for
their own sake, to probe the implications of a theory by deductively exploring
systems that may be difficult or impossible to attain physically.
isolation-diagram for Experimental Design
ISM-diagram
|
7. Problem-Solving Projects
The activities of science
usually occur in a context of problem solving,
which can be defined as "an effort to convert an actual current state
into a desired future state" or, more simply, "converting a NOW-state into a GOAL-state."
If the main goal of science is knowledge about nature, the main goal
of scientific research is improved knowledge, which includes observations
of nature and interpretations of nature.
Before and during problem formulation, scientists prepare
by learning (through active reading and listening) the current now-state
of knowledge for a selected area, including observations, theories, and
experimental techniques. Critical evaluation of this now-state may
lead to recognizing a gap in the current knowledge, and imagining a potential
future state with improved knowledge. When scientists decide to pursue
a solution for a science problem (characterized by deciding what to study
and how to study it) this becomes the focal point for a problem-solving
project.
Problem
formulation -- by defining a problem that is original, significant,
and can be solved using available resources -- is an essential activity
in science. During research a mega-problem
(the attempt by science to understand all of nature) is narrowed to a problem (of trying to answer specific questions
about one area of nature) and then to sub-problems
and specific actions. In an effort to
solve a problem, scientists generate, evaluate, and execute actions
that involve observation (generate and do experiments, collect data)
or interpretation (analyze data, generate and evaluate theories);
action generation and action
evaluation, done for the purpose of deciding what to do and when,
is guided by the goal-state (which serves as an aiming point in searching
for a solution) and by an awareness of the constantly changing now-state.
Evaluation of actions [or theories] can involve persuasion
that is internally oriented (within a research group) or externally oriented
(to convince others). isolation-diagram
for Problem Solving ISM-diagram
details
|
8. Thought Styles
All activities in science,
mental and physical, are affected by thought styles
that are influenced by cultural-personal factors, operate at the levels
of individuals and sub-communities and communities, and involve both conscious
choices and unconscious assumptions. A collective
thought style includes the shared beliefs, among a group of scientists,
about "what should be done and how it should be done." Thought
styles affect the types of theories generated and accepted, and the problems
formulated, experiments done, and techniques for interpreting data.
There are mutual influences between thought styles and the procedural "rules
of the game" that are developed by a community of scientists, operating
in a larger social context, to establish and maintain certain types of institutions
and reward systems, styles of presentation, attitudes toward competition
and cooperation, and relationships between science, technology and society.
Decisions about which problem-solving projects to pursue -- decisions (made
by scientists and by societies) that are heavily influenced by thought styles
-- play a key role in the two-way interactions between society and science
by determining the allocation of societal resources (for science as a whole,
and for areas within science, and for individual projects) and the returns
(to society) that may arise from investments in scientific research.
Thought styles affect the process and content
of science in many ways, but this influence is not the same for all science,
because thought styles vary between fields (and within fields), and change
with time. isolation-diagram for Thought
Styles ISM-diagram
details
|
9. Mental Operations
The mental operations used
in science can be summarized as "motivation and memory, creativity
and critical thinking." Motivation
inspires effort. And memory --
with information in the mind or in "external storage" such as
notes or a book or a computer file -- provides raw materials (theories,
experimental techniques, known observations,...) for creativity
and critical thinking. At its best, productive
thinking (in science or in other areas of life) combines knowledge
with creative/critical thinking. Ideally, an effective productive
thinker will have the ability to be fully creative and fully critical, and
will know, based on logic and intuition, what blend of cognitive styles
is likely to be productive in each situation. isolation-diagram for Mental Operations
ISM-diagram details
|
For a discussion of ISM that is more complete and precise,
read the Detailed Examination of Scientific Method, which will
open in a separate new window when you click this link ( DETAILS
).
The "detailed examination"
page also includes references
for some sources (and stimulaters) of my ideas.
|
highlighted in white,
1a. constructing an experimental system
to do a physical experiment that produces observations: |
|
| In ISM an experimental
system (for a controlled experiment
or field study) is defined as everything involved
in an experiment, including what is being studied, what is done to it, and
the observers (which can be human or mechanical). When a physical experiment is done with the experimental
system, observation detectors are used to obtain observations. |
|
1b. using theories to construct
a mental model (of a system)
to do a thought-experiment that produces predictions: |
|
| A theory
is a humanly constructed representation intended to describe or explain
the observed phenomena in a specified domain
of nature. By combining a domain-theory
(about all systems in a domain, based on a theory
and supplementary theories) with a
system-theory (about one experimental system),
scientists construct a model that is
a simplified representation of the system's composition
(what it is) and operation (what it does).
After a model is defined, a thought experiment
can be done by asking, "IF this model is true, THEN what will occur?",
thereby using deductive logic to make
predictions. |
|
1c. doing HYPOTHETICO-DEDUCTIVE LOGIC
by comparing predictions with observations to estimate the
degree of agreement for a hypothesis
and determining the predictive contrast between alternative hypotheses
and empirical factors that influence theory evaluation:
|
|
This tour of ISM begins with
hypothetico-deductive logic, the foundation
for modern science that provides a "reality check" to guide the
invention, evaluation, and revision of theories. .....
The dual-parallel shape of
the hypothetico-deductive "box" (whose 4 corners are defined by
the model and system, predictions and observations) symbolizes two parallel
relationships. The left-side process (done by mentally running a
theory-based model) parallels the right-side
process (done by physically running a real-world
experimental system). There is also a parallel between
the top and bottom of the box. At the top, a hypothesis
is a claim that the model and system are similar in some respects and to
some degree of accuracy. At the bottom is a logical
comparison of predictions (by the model) and observations (of
the system); this comparison is used to evaluate the hypothesis, based on
the logic that the degree of agreement
between predictions and observations may be related to the degree of similarity
between model and system. But a theory can be false even if its predictions
agree with observations, so it is necessary to supplement this "agreement
logic" with another criterion, the degree
of predictive contrast, by asking "How much contrast exists
between the predictions of this theory and the predictions of plausible
alternative theories?" in an effort
to consider the possibility that two or more theories could make the same
correct predictions for this system. |
| Estimates for degrees of agreement
and predictive contrast are combined to form an empirical
evaluation of current hypothesis. This evaluation and the
analogous empirical evaluations of previous hypotheses
(that are based on the same theory as the current hypothesis) are empirical factors that influence theory evaluation. |
|
2. conceptual factors (internal
characteristics and external relationships) that influence theory
evaluation: |
|
2. Conceptual Factors
in Theory Evaluation
In ISM the conceptual
factors that influence theory evaluation are split into internal
characteristics and external relationships.
Scientists expect a logical
internal consistency between a theory's own
components. And when evaluating a theory's logical
structure, one common criteria is simplicity,
which is achieved by postulating a minimum number of logically interconnected
theory-components. Also, in each field of science there are expectations
for the types of entities and actions that should (and should not) be included
in a theory. These "expectations about components" can be
explicit or implicit, due to scientists' beliefs about ontology
(what exists) or utility (what is useful).
The external
relationships between theories (including both scientific and
cultural-personal theories) can involve an overlapping of domains or a sharing
of theory components. Theories with domains that overlap are in direct
competition because they claim to explain the same systems. Theories
with shared components often provide support for each other, and can help
to unify our understanding of the domains they describe. There is
some similarity between the logical structures for a theory
(composed of smaller components) and for a mega-theory
(composed of smaller theories), and many conceptual criteria can be applied
to either internal structure (within a theory) or external relationships
(between theories in a mega-theory). |
|
3. cultural-personal factors that
influence theory evaluation: |
|
3. Cultural-Personal
Factors in Theory Evaluation
During all activities of
science, including theory evaluation, scientists are influenced by cultural-personal factors. These factors
include psychological motives and practical concerns
(such as intellectual curiosity, and desires for self esteem, respect from
others, financial security, and power), metaphysical
worldviews (that form the foundation for some criteria used in
conceptual evaluation), ideological principles
(about "the way things should be" in society), and opinions
of authorities (who are acknowledged due to expertise, personality,
and/or power).
These five factors interact with each other, and
operate in a complex social context that involves individuals, the scientific
community, and society as a whole. Science and culture are mutually
interactive, with each affecting the other. The effects of culture,
on both the process of science and the content of science, are summarized at the top of
the ISM diagram: "scientific activities... are affected by culturally
influenced thought styles."
Some cultural-personal influence is due to a desire
for personal consistency between ideas, between
actions, and between ideas and actions. For example, scientists are
more likely to accept a scientific theory that is consistent with their
metaphysical and ideological theories. In the diagram this type of
influence appears as a conceptual factor, external
relationships... with cultural-personal theories. |
|
4. evaluating theories: |
|
4. Theory Evaluation
A theory
is evaluated in association with supplementary
theories, and relative to alternative
theories. Inputs for evaluating
a theory come from empirical, conceptual, and cultural-personal
factors, with the relative weighting of factors varying from one situation
to another. The immediate output of theory evaluation is a theory status that is an estimate of a theory's
plausibility (whether it seems likely to be
true) and/or usefulness (for stimulating scientific
research or solving problems). Based on their estimate of a theory's
status, scientists can decide to retain
this theory with no revisions, revise
it to generate a new theory, or reject
it. When a theory is retained after evaluation, its status can be
increased, decreased, or unchanged. A theory can be retained for the
purpose of pursuit (to serve as a basis for
further research) and/or acceptance (as a proposed
explanation, for being treated as if it were true). According to formal
logic it is impossible to prove a theory is either true or false, but scientists
have developed analytical methods that encourage them to claim a "rationally
justified confidence" for their conclusions about status. Each
theory has two types of status: its own intrinsic
status, and a relative status that is
defined by asking "What is the overall appeal of this theory compared
with alternative theories?" |
|
5. generating theories (by selection or revision-invention,
using retroductive logic): |
|
5. Theory Generation
Generating
a theory can involve selecting
an old theory or, if necessary, inventing
a new theory. The process of inventing a new theory usually occurs
by revising an existing "old theory."
Some strategies for invention are: split an old theory into
components that can be modified or recombined in new ways; borrow
components (or logical structure) from other theories; generalize
an old theory, as-is or modified, into a new domain; or apply the
logic of internal consistency to build on the foundation of a few assumed
axiom-components. Often, a creative analysis
of data (to search for patterns) is a key step in constructing a
theory. |
| Theory generation is guided
by evaluation factors that are cultural-personal, conceptual, and empirical.
There is a close relationship between the generation and evaluation of a
theory. { Similarly, the generation and evaluation of an action (such
as an experiment) are closely related. } |
Empirical guidance is used
in the creative-and-critical process of retroduction
-- a thinking strategy in which the goal is to generate
(to propose by selection
or invention) a theory whose predictions will match known
observations. If there is data from several experiments,
retroduction can aim for a theory whose predictions are consistent with
all known data. During retroduction a scientist, curious about puzzling
observations and motivated to find an explanation, can adjust either of
the two sources used to construct a model: a general domain-theory
(that applies to all systems in a domain) and a specific system-theory
(about the characteristics of one system).
With retroduction or hypothetico-deduction
(which are similar, except that in retroduction a model is proposed
after the observations are known), similar logical limitations apply.
Even if a theory correctly predicts the observations, plausible alternative
theories might make the same correct predictions, so with either retroduction
or hypothetico-deduction there is a cautious conclusion:
IF system-and-observations, THEN MAYBE model
(and theory). This caution contrasts with the definite conclusion
of deductive logic: IF theory-and-model, THEN prediction. |
|
6. designing experiments (by generating-and-evaluating): |
|
6. Experimental Design
(Generation-and-Evaluation)
In ISM an "experiment"
is defined broadly to include both controlled experiments
and field studies. Three arrows point
toward generate experiment, showing
inputs from theory evaluation (which can motivate and guide design), gaps in system-knowledge (that can be filled
by experimentation, and provide motivation) and "do
thought experiments..." (to facilitate the process of design).
The result of experimental design (which combines
generating an experiment with evaluating an experiment) is a "real-world
experimental system" that can be
used for hypothetico-deductive logic.
Sometimes experiments are done
just to see what will happen, but an experiment is often designed to accomplish
a specific goal. For example, an experiment (or a cluster of related
experiments) can be done to gather information about a system or experimental
technique, to resolve anomaly, to provide support for an argument, or to
serve as a crucial experiment that can distinguish
between competing theories. To facilitate the collection and interpretation
of data for each goal, logical strategies are available. For example,
scientists can think ahead to questions that will be raised during evaluation,
about issues such as sample size and representativeness, or the adequacy
of controls.
Often, new opportunities for
experimenting (and theorizing) emerge from a change in the status quo.
For example, opportunities for field studies may arise from new events (such
as an ozone hole) or new discoveries (of old dinosaur bones,...).
A new theory may stimulate experiments to test and develop the theory, or
to explore its application for a variety of systems. Or a new observation
technology may allow new types of experimental systems. When an area
of science opens up due to any of these changes, opportunities for research
are produced. To creatively take advantage of these opportunities
requires an open-minded awareness that can imagine a wide variety of possibilities. |
Thought-experiments,
done to quickly explore a variety of possibilities, can help scientists
evaluate potential experimental systems and decide which ones are worthy
of further pursuit with physical experiments that typically require larger
investments of time and money.
Thought-experiments play a
key role in three parts of ISM: in experimental design, retroduction, and
hypothetico-deduction. In each case a prediction is produced from
a theory by using deductive logic, but there are essential differences in
timing and objectives. And sometimes mental experiments are done for
their own sake, to probe the implications of a theory by deductively exploring
systems that may be difficult or impossible to attain physically. |
|
7. generating and evaluating actions to help solve
a problem that has been defined.
8. thought styles (for individuals, sub-communities,
and communities).
9. thinking productively (creatively-and-critically). |
|
7. Problem-Solving
Projects
The activities of science
usually occur in a context of problem solving,
which can be defined as "an effort to convert an actual current state
into a desired future state" or, more simply, "converting a NOW-state into a GOAL-state."
If the main goal of science is knowledge about nature, the main goal
of scientific research is improved knowledge, which includes observations
of nature and interpretations of nature.
Before and during problem formulation, scientists prepare
by learning (through active reading and listening) the current now-state
of knowledge for a selected area, including observations, theories, and
experimental techniques. Critical evaluation of this now-state may
lead to recognizing a gap in the current knowledge, and imagining a potential
future state with improved knowledge. When scientists decide to pursue
a solution for a science problem (characterized by deciding what to study
and how to study it) this becomes the focal point for a problem-solving
project.
Problem
formulation -- by defining a problem that is original, significant,
and can be solved using available resources -- is an essential activity
in science. During research a mega-problem
(the attempt by science to understand all of nature) is narrowed to a problem (of trying to answer specific questions
about one area of nature) and then to sub-problems
and specific actions. In an effort to
solve a problem, scientists generate, evaluate, and execute actions
that involve observation (generate and do experiments, collect data)
or interpretation (analyze data, generate and evaluate theories);
action generation and action
evaluation, done for the purpose of deciding what to do and when,
is guided by the goal-state (which serves as an aiming point in searching
for a solution) and by an awareness of the constantly changing now-state.
Evaluation of actions [or theories] can involve persuasion
that is internally oriented (within a research group) or externally oriented
(to convince others). |
8. Thought Styles
All activities in science,
mental and physical, are affected by thought styles
that are influenced by cultural-personal factors, operate at the levels
of individuals and sub-communities and communities, and involve both conscious
choices and unconscious assumptions. A collective
thought style includes the shared beliefs, among a group of scientists,
about "what should be done and how it should be done." Thought
styles affect the types of theories generated and accepted, and the problems
formulated, experiments done, and techniques for interpreting data.
There are mutual influences between thought styles and the procedural "rules
of the game" that are developed by a community of scientists, operating
in a larger social context, to establish and maintain certain types of institutions
and reward systems, styles of presentation, attitudes toward competition
and cooperation, and relationships between science, technology and society.
Decisions about which problem-solving projects to pursue -- decisions (made
by scientists and by societies) that are heavily influenced by thought styles
-- play a key role in the two-way interactions between society and science
by determining the allocation of societal resources (for science as a whole,
and for areas within science, and for individual projects) and the returns
(to society) that may arise from investments in scientific research.
Thought styles affect the process and content
of science in many ways, but this influence is not the same for all science,
because thought styles vary between fields (and within fields), and change
with time. |
9. Mental Operations
The mental operations used
in science can be summarized as "motivation and memory, creativity
and critical thinking." Motivation
inspires effort. And memory --
with information in the mind or in "external storage" such as
notes or a book or a computer file -- provides raw materials (theories,
experimental techniques, known observations,...) for creativity
and critical thinking. At its best, productive
thinking (in science or in other areas of life) combines knowledge
with creative/critical thinking. Ideally, an effective productive
thinker will have the ability to be fully creative and fully critical, and
will know, based on logic and intuition, what blend of cognitive styles
is likely to be productive in each situation. |
