System Thinking and System Modeling in the Earth System Science Classroom
Farzad Mahootian, Ph.D., Earth System Science Community Co-Investigator
Gonzaga College High School, 19 Eye St., N.W., Washington D.C. 20001, USA
(202)966-8588, fax (202)336-7164
farzad@ circles.org
INTRODUCTION AND CONTEXT
Earth system science (ESS) is a holistic study of the
Earth. ESS marshals the resources a variety of scientific and
technical fields to explore interactions among the Earth’s
component subsystems in order to understand the Earth as a
system, to explain Earth dynamics and Earth evolution, and
to address the problem of the effects of human actions on
global change. We have begun to understand that because the
Earth is a system, our local actions have global effects, that
human society has the power to change the world, for better
or worse. It is of great importance, both for the sake of the
Earth and for the sake of our own future, to understand the
Earth for what it is: a complex system of interlaced and
interacting subsystems.
In order to investigate the Earth system, teachers and
students need access to expertise in a broad variety of
disciplines: chemistry, physics, computer science, biology,
mathematics, statistics, and political science. A variety of
relatively new skills are also requird networked computing,
tools and techniques for retrieving, visualizing, and analyzing
remote sensing data, and building dynamic systems models.
The question of systems modeling became a central issue in
curriculum development efforts of the Earth System Science
Community (ESSC), a three-year project supported by
N.4SA’s Information Infrastructure Technology and
Applications and High Performance Computing and
Communication programs.
The thrust of the curriculum development effort was to
enable students and teachers to conduct investigations in
global change topics using remote sensing data gathered by
NASA and other science agencies. The curriculum was
project-based [l], with the intention of producing an
authentic and living sense of understanding and participation
in science research [2], [3]. Students and teachers were to
collaborate on-line with their peers in other schools, and
with scientists/mentors in universities and government
science agencies. In this effort students and teachers become
researchers and learn to design and carry out a research
strategy, involving the proposal and articulation of a
hypothesis, the building of a system model, and the search,
retrieval, manipulation, visualization and analysis of
appropriate data. Students conclude their research by testing
their hypothesis with available data, using visualization
software, and information available in print and on-line.
Finally, students C0”unicate the results of their research
by publishing their reports, data, data products, and systems
models. To date, over sixty reports have been published on
the project website (http://www.circles.org/).
The curriculum content and pedagogy was designed and
implemented during the 1993-94 pilot phase in adherence to
the science strategy of NASA’s Mission to Planet Earth, and
to the (U.S.) National Research Council’s (NRC) National
Science Education Standards which were in draft form at the
time [4].
THE ESSC PROJECT IN RETROSPECT
The original purpose of the Earth System Science
Community was to build an investigation-oriented Earth
system science curriculum in which high school and
university students could conduct research projects on global
change issues using Earth observation data and information
over the Internet. Three integrated components were
proposed: 1) an Earth system science curriculum, 2) an
information system over the Internet to support the
curriculum and access to remote sensing data, and 3) a pilot
community of educators, students and scientists who would
help define requirements for improving the curriculum and
information system.
While the first two goals were achieved with a significant
degree of success, it has become clear that the requirements
of a successful on-line community were underestimated. In
this respect, the main lesson learned was that, with proper
encouragement and cultivation, communities can grow
organically from a pre-existing nutritive substrate. The
“substrate” here refers to long-term institutional commitment
to supporting innovative (i.e., non-traditional) courses and
teachers. A paradigm case of such commitment is represented
in the (US) National Science Foundation’s “systemic
initiatives” for science education reform. But in the absence
of such a substrate, the simple influx of temporary dollars
for teacher training and partial release time is an insufficient
and ineffectual way to build on-line communities.
SYSTEM MODELING AND STUDENT LEARNING
A. Introduction
The two most difficult aspects of teaching ESS are the
visualization, analysis, and interpretation of data, on the one
hand, and the use and construction of system models on the
other. The problem of data visualization, in the ESSC
context, is the topic of another paper in this volume (“Issues
of WWW-Based Data Visualization for the Earth System
Science Classroom”).
Systems thinking is “the art and science of making
reasonable inferences about behavior by developing an
increasingly deep understanding of underlying structure.” [SJ
To add a more technical dimension to this definition, we may
define system dynamics as “a method for studying the world
around us. It deals with understanding how complex systems
change over time. Internal feedback loops within the
0-7803-3836-7/97/$10.00 0 1997 IEEE 695
structure of the system influence the entire system behavior.”
[61
It is important to point out that in the ESSC visual
models were used, rather than models that describe the
phenomena mathematically in symbolic language. While
both types of models may produce their result as
visualizations, the former embeds the mathematical relations
within an object-oriented environment that &splays objects
and object-interactions in a manner that is more like the kind
of diagram students and scientist are apt to draw or think of
when discussing systems. The benefits of using modeling
and visual simulation in science education are manifold, and
to a large extent mirror the benefits of this technique in
science research namely, these tools enhance the ability to
observe, think about, experiment with, and discover patterns
and relations that are inaccessible because of spatio-temporal
scale (nanotech or planetary-scale), or inhospitable
environments (the Earth’s interior).
B. The Form and Content of Systems Thinking
Earth system science represents a significant departure
from classical science and science education. Not only does
Earth system science require an interdisciplinary and holistic
approach, it also requires a new focus on the interrelation of
Earth processes. The integrity of the Earth as a system
consists of the interrelatedness of its component subsystems:
hydrosphere, atmosphere, biosphere, lithosphere and
cryosphere. To understand the Earth as a system one must
understand not only the fundamentals about each component
subsystem, but also the processes that interconnect them.
The Earth is not a static system; without the understaudmg
of process we would miss the underlying causes of both
natural and anthropogenic global environmental change. In
short, Earth system science without system modeling is
impossible.
The best way for students to gain a working knowledge
of such complex interrelations is to build and interact with
Earth system models. For example, after learning about the
Earth energy budget and then playing with an Earth energy
model, and altering the cloud amount, and other values, the
student’s mind resonates with an intellectual satisfaction that
results from this correspondence of form and content --
simultaneously learning about the system model and the
modeled system.
The use of modeling software to instruct students about
the Earth system is consistent with the “constructivist”
theory of learning, and with the inquiry- and discovery-based
mode of learning advocated by the NRC [7]. The NRC
makes explicit reference to studying the Earth as a system
[8], and to the use of models in secondary school science
education [9].
C. The Construction of Knowledge
Aside from the fact that the form and content of learning
are well-matched, as they are in the case of system modeling
andESS, what is chief cognitive benefit of using modeling
in education? To paraphrase the great 18th century German
epistemologist, Immanuel Kant, “models without data are
empty, and data without models are blind.” In Kant’s theory
of knowledge [lo], “categories of understanding” (i.e.,
causality, composition, etc., which collectively lay the
foundation for the “laws of nature”) provide conceptual
connectivity to the “forms of perception” (i.e., the o r d h g
principles of space and time, which apply to all objects and
events). Scientific consciousness, according to Kant, is
constructed by one’s appropriate use of the categories of
understanding in association with the forms of perception. In
his philosophy, Kant demonstrated that all knowledge --
indeed, all experience-- is an active, on-going construction.
In this respect the contemporary constructivist theory of
leaming [l 11 finds its ancestry in Kant’s philosophy.
In the context of our discussion of Earth system science,
the forms of perception are analogous to the archives of data
of the Earth’s systems --blind data without meaning or
connection-- while the categories of understanding are
embodied in our system models --which, without data, are
conceptual structures devoid of significance. In their use of
system models and data archives students begin to germinate
scientific consciousness. In their effort to define and
understand the limitations and omissions in their models, and
to refine these in the face of research, data and criticism, they
begin to attain s
System Thinking and System Modeling in the Earth System Science Classroom
Farzad Mahootian, Ph.D., Earth System Science Community Co-Investigator
Gonzaga College High School, 19 Eye St., N.W., Washington D.C. 20001, USA
(202)966-8588, fax (202)336-7164
farzad@ circles.org
INTRODUCTION AND CONTEXT
Earth system science (ESS) is a holistic study of the
Earth. ESS marshals the resources a variety of scientific and
technical fields to explore interactions among the Earth’s
component subsystems in order to understand the Earth as a
system, to explain Earth dynamics and Earth evolution, and
to address the problem of the effects of human actions on
global change. We have begun to understand that because the
Earth is a system, our local actions have global effects, that
human society has the power to change the world, for better
or worse. It is of great importance, both for the sake of the
Earth and for the sake of our own future, to understand the
Earth for what it is: a complex system of interlaced and
interacting subsystems.
In order to investigate the Earth system, teachers and
students need access to expertise in a broad variety of
disciplines: chemistry, physics, computer science, biology,
mathematics, statistics, and political science. A variety of
relatively new skills are also requird networked computing,
tools and techniques for retrieving, visualizing, and analyzing
remote sensing data, and building dynamic systems models.
The question of systems modeling became a central issue in
curriculum development efforts of the Earth System Science
Community (ESSC), a three-year project supported by
N.4SA’s Information Infrastructure Technology and
Applications and High Performance Computing and
Communication programs.
The thrust of the curriculum development effort was to
enable students and teachers to conduct investigations in
global change topics using remote sensing data gathered by
NASA and other science agencies. The curriculum was
project-based [l], with the intention of producing an
authentic and living sense of understanding and participation
in science research [2], [3]. Students and teachers were to
collaborate on-line with their peers in other schools, and
with scientists/mentors in universities and government
science agencies. In this effort students and teachers become
researchers and learn to design and carry out a research
strategy, involving the proposal and articulation of a
hypothesis, the building of a system model, and the search,
retrieval, manipulation, visualization and analysis of
appropriate data. Students conclude their research by testing
their hypothesis with available data, using visualization
software, and information available in print and on-line.
Finally, students C0”unicate the results of their research
by publishing their reports, data, data products, and systems
models. To date, over sixty reports have been published on
the project website (http://www.circles.org/).
The curriculum content and pedagogy was designed and
implemented during the 1993-94 pilot phase in adherence to
the science strategy of NASA’s Mission to Planet Earth, and
to the (U.S.) National Research Council’s (NRC) National
Science Education Standards which were in draft form at the
time [4].
THE ESSC PROJECT IN RETROSPECT
The original purpose of the Earth System Science
Community was to build an investigation-oriented Earth
system science curriculum in which high school and
university students could conduct research projects on global
change issues using Earth observation data and information
over the Internet. Three integrated components were
proposed: 1) an Earth system science curriculum, 2) an
information system over the Internet to support the
curriculum and access to remote sensing data, and 3) a pilot
community of educators, students and scientists who would
help define requirements for improving the curriculum and
information system.
While the first two goals were achieved with a significant
degree of success, it has become clear that the requirements
of a successful on-line community were underestimated. In
this respect, the main lesson learned was that, with proper
encouragement and cultivation, communities can grow
organically from a pre-existing nutritive substrate. The
“substrate” here refers to long-term institutional commitment
to supporting innovative (i.e., non-traditional) courses and
teachers. A paradigm case of such commitment is represented
in the (US) National Science Foundation’s “systemic
initiatives” for science education reform. But in the absence
of such a substrate, the simple influx of temporary dollars
for teacher training and partial release time is an insufficient
and ineffectual way to build on-line communities.
SYSTEM MODELING AND STUDENT LEARNING
A. Introduction
The two most difficult aspects of teaching ESS are the
visualization, analysis, and interpretation of data, on the one
hand, and the use and construction of system models on the
other. The problem of data visualization, in the ESSC
context, is the topic of another paper in this volume (“Issues
of WWW-Based Data Visualization for the Earth System
Science Classroom”).
Systems thinking is “the art and science of making
reasonable inferences about behavior by developing an
increasingly deep understanding of underlying structure.” [SJ
To add a more technical dimension to this definition, we may
define system dynamics as “a method for studying the world
around us. It deals with understanding how complex systems
change over time. Internal feedback loops within the
0-7803-3836-7/97/$10.00 0 1997 IEEE 695
structure of the system influence the entire system behavior.”
[61
It is important to point out that in the ESSC visual
models were used, rather than models that describe the
phenomena mathematically in symbolic language. While
both types of models may produce their result as
visualizations, the former embeds the mathematical relations
within an object-oriented environment that &splays objects
and object-interactions in a manner that is more like the kind
of diagram students and scientist are apt to draw or think of
when discussing systems. The benefits of using modeling
and visual simulation in science education are manifold, and
to a large extent mirror the benefits of this technique in
science research namely, these tools enhance the ability to
observe, think about, experiment with, and discover patterns
and relations that are inaccessible because of spatio-temporal
scale (nanotech or planetary-scale), or inhospitable
environments (the Earth’s interior).
B. The Form and Content of Systems Thinking
Earth system science represents a significant departure
from classical science and science education. Not only does
Earth system science require an interdisciplinary and holistic
approach, it also requires a new focus on the interrelation of
Earth processes. The integrity of the Earth as a system
consists of the interrelatedness of its component subsystems:
hydrosphere, atmosphere, biosphere, lithosphere and
cryosphere. To understand the Earth as a system one must
understand not only the fundamentals about each component
subsystem, but also the processes that interconnect them.
The Earth is not a static system; without the understaudmg
of process we would miss the underlying causes of both
natural and anthropogenic global environmental change. In
short, Earth system science without system modeling is
impossible.
The best way for students to gain a working knowledge
of such complex interrelations is to build and interact with
Earth system models. For example, after learning about the
Earth energy budget and then playing with an Earth energy
model, and altering the cloud amount, and other values, the
student’s mind resonates with an intellectual satisfaction that
results from this correspondence of form and content --
simultaneously learning about the system model and the
modeled system.
The use of modeling software to instruct students about
the Earth system is consistent with the “constructivist”
theory of learning, and with the inquiry- and discovery-based
mode of learning advocated by the NRC [7]. The NRC
makes explicit reference to studying the Earth as a system
[8], and to the use of models in secondary school science
education [9].
C. The Construction of Knowledge
Aside from the fact that the form and content of learning
are well-matched, as they are in the case of system modeling
andESS, what is chief cognitive benefit of using modeling
in education? To paraphrase the great 18th century German
epistemologist, Immanuel Kant, “models without data are
empty, and data without models are blind.” In Kant’s theory
of knowledge [lo], “categories of understanding” (i.e.,
causality, composition, etc., which collectively lay the
foundation for the “laws of nature”) provide conceptual
connectivity to the “forms of perception” (i.e., the o r d h g
principles of space and time, which apply to all objects and
events). Scientific consciousness, according to Kant, is
constructed by one’s appropriate use of the categories of
understanding in association with the forms of perception. In
his philosophy, Kant demonstrated that all knowledge --
indeed, all experience-- is an active, on-going construction.
In this respect the contemporary constructivist theory of
leaming [l 11 finds its ancestry in Kant’s philosophy.
In the context of our discussion of Earth system science,
the forms of perception are analogous to the archives of data
of the Earth’s systems --blind data without meaning or
connection-- while the categories of understanding are
embodied in our system models --which, without data, are
conceptual structures devoid of significance. In their use of
system models and data archives students begin to germinate
scientific consciousness. In their effort to define and
understand the limitations and omissions in their models, and
to refine these in the face of research, data and criticism, they
begin to attain s
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