Course Meeting Times

Lectures: 2 sessions / week, 1.5 hours / session

Course Synopsis

This course is designed to provide students with the critical tools necessary to evaluate the use of models and scientific assessments in decision‐making and policy. Students will gain understanding and awareness of how models work, practice using models to conduct policy‐relevant analyses, and evaluate the effectiveness of models and scientific assessments in decision‐making contexts. This is thus an appropriate course both for students who are planning to develop or build models, as well as those who are potential users of model analyses or output. While many of the examples will be drawn from modeling of earth and environmental systems, the techniques and frameworks applied can be used across multiple issue domains. Guest lecturers throughout the semester will introduce examples from other areas of application. Students are welcome to choose term projects from their own areas of interest.

Course Outline and Content

The course is divided into four sections.The first section introduces the context of the use of scientific assessment and models in policy and decision‐making, and presents the various types of models and assessments used in decision‐making contexts.

The second section gives an overview of modeling and analytical tools useful in constructing and evaluating models, including assessment frameworks. These include ways to evaluate credibility, salience and legitimacy and the effectiveness of information. Frameworks analyzed include vulnerability, scenario‐based approaches and risk assessment.

The third section applies the modeling and analytical tools learned in the previous section to discussion of case studies of models in policy, including cases on acid rain, fisheries, population, climate change, and chemicals.

The fourth and final section will conclude by exploring efforts to model the whole earth system for sustainability decision‐making. Students will also present projects applying course techniques to evaluating or conducting model analyses.

Learning Objectives

This course bridges an important gap between courses that focus on quantitative techniques, and those emphasizing policy and decision‐making. In contrast to other offerings that focus on either techniques or applications, this course presents an integrated approach to designing policy‐relevant models.

By taking this course, students will:

• Gain experience using quantitative modeling techniques, such as box modeling, dispersion modeling, Monte Carlo simulations, statistical modeling, etc.
• Understand model uncertainties, how to quantify them from a modeling perspective, and how to conceptualize and communicate uncertainties in a policy and decision-making context.
• Identify common approaches to modeling from different disciplines, and learn strategies for combining models of social and natural processes.
• Contribute to analyzing and developing "best practices" for the use of models in policy.
• Courses will be conducted with a combination of lectures, discussion and hands‐on learning exercises.

Student Background and Prerequisites

This course is appropriate for graduate students (Master's or PhD level) who are interested in the technical and social processes that underlie the design of models for policy‐relevant applications. I expect that this course will draw students with varied backgrounds, including both natural and social sciences. For example, such students may include (but are not limited to!) those with ongoing research in areas of modeling (including science, engineering, economics, etc.), those studying the role of scientific information in policy processes, or those with career interests in interpreting scientific results for decision‐making.

The common element that all students in this class should have is some experience with quantitative techniques. Quantitative modeling exercises in class and in problem sets will require some knowledge of differential equations. Some experience with using or analyzing the results of quantitative models would also be helpful, but is not required.

Grading

Problem Sets

Students will complete three problem sets during the course of the semester (1: Box Models and Quantitative Techniques, 2: Risk Assessment and Model Communication, 3: Chemical Fate and Transport). Through these problem sets, students will gain practice applying quantitative modeling techniques to policy‐driven questions. Problem sets will consist of both quantitative calculations (some computer‐based) and short‐answer questions.

Model Assessment Project (40% of grade)

A term project will assess a particular model of interest, chosen individually in consultation with the instructor. Students may choose to a) conduct decision‐focused analyses using a quantitative modeling approach, or b) evaluate the use of model information in a decision‐making or policy process. Students will be asked to present their analyses to the class. The project is described further in the next section, and more information on the project will be provided in class.

Participation and In-class Model Exercises (30% of grade)

This class will emphasize hands‐on approaches to models and assessment, and thus class participation will be critical to learning. In‐class model exercises will give students the opportunity to develop experience in using and analyzing modeling tools.

Term Project

Individual term projects (Model Assessment Project) are a critical element of the course. Students will choose a particular decision‐relevant model or decision-making process in which models were used. Students may choose a model‐focused project (in which they will conduct decision‐relevant simulations), or a policy-focused project (in which they will analyze the use of quantitative information in a decision‐making process). For example, in a model‐focused project, a student may choose to identify an area where policies have historically been ineffective, and design and execute a model that could explain the outcome or inform decision-making. In a policy‐focused project, a student could analyze a policy process where models were used or misused, and issue recommendations for future quantitative analyses.

Students will present their term projects to the class at the end of the semester, and will be asked to submit a brief write‐up of the results (in the form of a focused 3‐5 page policy memo) and a detailed PowerPoint presentation.

Guest Lectures

Guest lecturers during the semester will speak about their experience using models in decision‐making processes ("war stories"). Guest lectures will present models in areas other than earth and environmental system modeling, and may present alternative quantitative approaches used in their areas.

Readings

There is no required textbook for this class. A list of assigned readings for each class can be found in the Readings section.