“teaching decision-making to future scientists and teaching science to future decision-makers: the...
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“Teaching Decision-Making to Future Scientists and
Teaching Science to Future Decision-Makers: The Princeton
University Experience”
Gregory van der Vink & Peter Folger
Teaching Public Policy in Earth Sciences Workshop – AGU, April 22, 2006
Disclaimer and Reference
Opinions are those of the authors and do not necessarily represent those of any institution with which he is affiliated.
Based on 15 years of teaching upper-level Geoscience decision-making courses at Princeton University• Geo399: “Environmental Decision-Making”• Geo499: “Dealing with Natural Disasters”
Princeton University 250th Anniversary Professor for Distinguished Teaching
Course Objectives
Improve scientific literacy of non-scientists (e.g. future policy-makers, business executives, citizens)
And
Improve the political, social, economic, literacy of future scientists
(make scientists more effective in having their work
benefit society – “citizen scientists”)
Definition of scientific literacy
NSF defines scientific literacy not only as knowledge of the tenets and methods
of science, but also the impact of science on society.
Boundary Conditions
Not every student will become (or wants to become) a scientist –
a producer of scientific information.
(and that’s OK)
Boundary Conditions
But every student will be a future consumer of scientific information.
These students are our future decision-makers.
Courses for non-majorsor
for majors who will not be professional scientists
Few producers, many consumers
Science background is valuable for many careers
• Law• Diplomacy• Business• Education• Every profession
[and to be good citizens]
Traditional Focus
As educators, we focus on the future producers of scientific information
But
we generally ignore the future consumers of that information
Different Emphasis
For future consumers (policy-makers, business leaders, etc.) Emphasis is not on learning facts of science, but rather on gaining an understanding of the scientific process, valid inference, representative sampling, data discrimination, etc.,
For future scientists
Emphasis is on how science interacts with public policy.
Format for consumers
Courses for non-science majors should be different from the
traditional courses intended to train science professionals
Goals for understanding
Scientific process Valid inference Representative sampling Boundary values Data discrimination
• Signal vs. noise• Outliers• Scatter• Random vs. systematic
“Take-away” understanding –example 2
Science is a human endeavor
“A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die”
– Max Planck
“Take-away” understanding –example 3
Science is not about facts: - Science is a process
- Science is a way of addressing problems
No need to “dilute”
Many non-science students:
Engineers
Economists
Political scientists
Etc,
have high-level quantitative skills and have experience addressing complex issues with many factors (variables).
Less is more
Avoid the “mile-wide, inch-deep” structure of many introductory courses.
Select a few, difficult, unresolved issues with societal implications and have the students work thorough them (go deep).
Format for consumers
Expose students to primary data Have students analyze data Have students make decisions based on
messy, incomplete, ambiguous data. Experience requirement to make
decisions based on their interpretation of the data available at the time of the decision.
High content
Format for consumers
Data will be incomplete and ambiguous Data sets will be inconsistent Decisions will involve long-equations
with many variables from different disciplines.
Answers must be scientifically valid, but also politically, economically, socially realistic.
Intellectually challenging
Format for consumers
• 10% what we hear• 15% what we see• 20% what we see & hear• 40% what we discuss• 80% what we experience• 90% what we teach
Give students experience – making decisions and defending those decisions.
Long-term impact
Format for consumers
“Socratic” Method Real Case Studies
Long-term Impact
HighContent
IntellectuallyChallenging
Scientific:
Global seismicity (Guttenberg/Richter)
Seismic magnitude
Frequency of events
Energy/magnitude
Seismic transmission
Verifying the Comprehensive Nuclear Test-Ban Treaty
Value-added:
Probability/confidence levels
Different scientists can look at the same data, arrive at different conclusions
Technical assessments are permeated with value judgments
Verifying the Comprehensive Nuclear Test-Ban Treaty
Why bother?
Improve scientific literacy of future non-scientists
Improve political/economic/social/engineering literacy of future scientists
Enrich academic department
Instill an understanding of, and appreciation for, science (and the methods of science) in the next
generation of our society’s leaders.