Scientists spend their days investigatingthe world and making sense of it. Theirgoal is to discover patterns and orderthat will lead to better explanations ofphenomena. Indeed the nature of sci-

entific inquiry shares some of the means andends of the childhood games we played to sat-isfy our curiosity about “what’s going on outthere.” We observed and experimented withhow things work. The uncertainty introducedby changing conditions adds complexity tothe ultimate aim of the game—to perfectour mental models of our surround-ings, which as we grow older, arecontinuously expanding ontime and spatial scales (Holt,1983).

This essay and thosethat follow in future issuesof Research Educationintend to encourage stu-dents, educators and scientiststo discuss their experiences inresearch projects and/or course-work where learning is taking place through theprocess of inquiry. With regard to applying thisprocess in traditional science, mathematics,engineering and technology (SMET) course-work, some critics may ask: why have studentsspend time discovering what is already known(Holt, 1983)? Thus, these essays aim to motivatedialogue about the aspects of science inquirythat should be emphasized in SMET learningand practical ways to address them. In this firstone, we focus on the use of models and obser-vations in inquiry.

At an early age we begin to develop a sci-entific perspective, seeking to explain order inthe world by using the tools of touching, hear-ing, smelling and seeing. By conducting self-

motivated experiments and observations orinvestigations guided by adults, we are pro-vided with data to compare, contrast anddeduce cause-and-effect relationships. How isthis different from the way a physicist studiesthe world?

Armed with physical laws expressed inmathematical equations, physicists can explainnatural phenomena such as how earth achievesenergy balance, sustaining the habitability ofour planet through diverse interactions of thesun’s energy with land surfaces and atmos-pheric components. Yet, the more scientistsare able to explain the world and prove thatdeterministic forces drive it, the more theylearn about the unpredictable or chaotic

behavior of the earth system. Continuousretrieval of Earth images and data by NASAsatellites and ground stations confirm assump-tions that our planet is a complex system ofhuman and natural processes.

Scientists have made significant advance-ments over the past two decades using obser-

vational data as inputs to develop computermodels that simulate the earth’s atmosphereand oceans. By improving these models and

running experiments where human-madeand natural variables are changed to

force possible scenarios in the system,scientists hope to be ableto predict what theworld’s climate will belike in the future. Forexample, an experi-ment with increasedgreenhouse gases,compared to onewith current lev-els, can help

quantify changein the climate system pro-

duced by natural variability and byhuman influence. The value added by this infor-mation to policy-making can result in betterinformed and justifiable decisions on legislativeactions such as regulating clean air and water.

Engaging in this type of scientific endeav-or requires scientists to look beyond thedeterministic characteristics they discoverabout Earth’s physical, chemical and biologi-cal processes and study how they interact withthe natural variability of our atmosphere andoceans to produce earth’s global and regionalclimate. It also demands the collective expert-ise of many disciplines to solve problemswhere the complexities of the system’s behav-

���� Research Education.Spring 2000

researcheducation

CAROLYN HARRIS, Columbia University Center

for Climate Systems Research, is Director of the

GISS Institute on Climate and Planets.

We All Begin as Scientists

CAROLYN HARRIS

Research Education.Spring 2000 ����

iors are interrelated (Gleick, 1987). Today,physicists, economists, engineers, political sci-entists and other scientists are making effortsto study Earth as a system. They believe thatsome day we will be able to explain and makepredictions about this system with a signifi-cant degree of confidence using sophisticatedclimate models and observations from spaceand the planet’s surface.

More and moreresults from modelingexperiments are used inconjunction with obser-vations to explainEarth’s behavior, elevatean issue to the forefrontof the national agenda,and justify decisionsthat impact our lives.Thus, we need to find effective ways togive citizens an appreciation of the Earthas a system, the models and observation-al data used to explain the system, andthe capability and limitations of thesetools. This is inherently linked toinformed perspectives on widely discussedenvironmental issues, including concerns overhealth impacts due to local traffic and trans-portation patterns, and the regional/global

implications of changing patterns of land useresulting from human development.

Before we can understand change in a sys-tem, it is important to identify conditions thatproduce equilibrium or stability in that sys-tem. Both change and equilibrium are influ-enced by external conditions (system inputs)that are used in a model to study interactionsand change (system outputs). In a model

experiment that is run for manyyears into the future, the conditions(inputs) are based on observationaldata.

Understanding how Earth’s con-ditions change is a matter of proba-

bility. When climatemodelers run exper-iments, they lookfor conditions that“load the climatedice” and increaseprobability for glob-al change and aworld that may bewarmer, cooler, wet-

ter or drier. Statistics are a mainstay of scienceused to explain the significance of change. Infact, developing the scientific capability toquantify past, recent and future global change

with a high degree of confidence enhancesour capability for responsible decision-mak-ing. This is increasingly important as immedi-ate costs and benefits of many policies to mit-igate negative changes are likely to be borneunequally by citizens depending on wherethey live.

As science advances, we want all citizensto be able to understand new knowledge sowe can evaluate public issues and societalresponses to them responsibly. It seems bene-ficial to look at the process of science inquirywhere this knowledge is generated, as well asat how young children learn, in seeking strate-gies that lead to this appreciation.Fundamental understanding of scienceinquiry begins in early childhood and canpotentially form a sound foundation for a highlevel of life-long science literacy, interest andmotivation. We have seen that children devel-op their own models and techniques forobservation, seeking explanations of simplesystems. Using models and observations toformulate, test and revise hypotheses aboutrelationships, they begin to understand thephenomena encountered in daily life(Mandinach, 1989).

How we sustain this type of learningthroughout our lives and ensure that itremains an important component of sciencelearning from elementary to higher educationlevels is a challenge that the ICP collaborationamong students, faculty and scientists isuniquely positioned to address. In spring2000, we plan to host discussions lead by ICPfaculty, on the idea of research education andto exchange best practices for its classroomimplementation. We look forward to hearingall perspectives on this idea and creating aforum that benefits teaching and learning. �

CONTRIBUTOR:

ANTHONY DEL GENIO, NASA GISS

REFERENCES

Gleick, James. 1987. Chaos: Making A New Sense of Science. Penguin Books, New York.

Holt, John. 1983. How Children Learn, revised edition. Merloyd Lawrence, New York.

Mandinach, E. 1989. Model-Building and the Use of Computer Simulations of Dynamic Systems.

Educational Computing Research. Col 5(2), pp 221–243.