176 Rethinking model-based inquiry in terms of weather and climate computer models

Monday, 24 January 2011
Washington State Convention Center
Morgan Brown Yarker, University of Iowa, Iowa City, IA; and C. Forbes

As atmospheric scientists, we depend on Numerical Weather Prediction (NWP) models. We use them to predict weather patterns, to understand external forcing on the atmosphere, and as evidence to make claims about atmospheric phenomenon. Therefore, it is important that we adequately prepare atmospheric science students to use computer models. However, the public should also be aware of what models are in order to understand scientific claims about atmospheric issues, such as climate change. Although familiar with weather forecasts on television and the Internet, the general public does not understand the process of using computer models to generate a weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Since computer models are the best method we have to forecast the future of our climate, scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum.

Inquiry is a recommended approach to teaching science content that involves students taking part in the scientific processes of generating questions, designing experiments, gathering evidence and making claims about science concepts. Model-based inquiry practices involve students learning about concepts through explicit use of scientific models; which means creating, critiquing and modifying models that the students construct. Recent research indicates that students who create their own scientific models have better understanding of a concept than students who use pre-constructed models because it allows them to see 1) how and why the model works as a representation and 2) the predictive power of models. For the purpose of model-based inquiry, a model is generally defined as “representation that abstracts and simplifies a system by focusing on key features to explain and predict scientific phenomena” (Schwarz et al., 2009). Based on this definition, model-based inquiry includes a variety of model types. Some examples of scientific models include Bohr's model of the atom, DNA's double helix, photon energy, and wavelength energy. Although these kinds of models are different than NWP models, there are parallels; specifically, we can use both kinds of models to represent an otherwise complex phenomenon and well as predict outcomes. Generally, the predictive power of models is not emphasized, so outcomes of numerical weather prediction models are not clearly understood. Hence without exposure to the concept of modeling, we cannot expect them to understand, let alone reason about, scientific claims such as the future of climate.

The implementation of a model-based curriculum in the science classroom can be an effective way to prepare students to think critically, problem solve, and make informed decisions as a contributing member of society. Additionally, using model-based inquiry in the form of NWP requires the use of technology in the science classroom, which can also be a useful tool to initiate conceptual growth. Following reform approaches to teaching science, such as constructivist learning theory, computer simulations can be implemented into science classrooms so long as they are not a “step-by-step cookbook” approach. An effective way to help students understand computer models is to begin with helping them create and develop representations of their own conceptual models. In a recent study, a learning progression is developed to describe progressing levels of complexity students' use when representing conceptual models visually. The authors argue that as students become more familiar with developing visual representations of their conceptual understanding of a phenomenon, their constructed models become more complex. As a result, students not only have a better understanding of the science concept, they also have a better understanding of how scientific models are developed, their usefulness, and limitations.

The goal of this project is to take what we already know about using models as a learning tool in the science classroom and apply it to the world of computer modeling. To do this, a professional development course for middle school teachers will be developed to help teachers implement model-based inquiry into their already existing weather and/or climate units. The ultimate goal is to help the teacher participants understand how NWP models work and why they are important to the scientific community so that they have the tools to incorporate NWP models into their current teaching methods. We will accomplish this goal by incorporating content, hands-on activities, and application of content. Specifically, teachers will learn about atmospheric models from professional atmospheric scientists, gain further understanding of models through age-appropriate hands-on activities (that can be used in their own classrooms if they choose), and participants will be responsible for working with a partner to develop units for their classrooms. Having the teachers develop their own unit provides them with time throughout the course to reflect on the new material as well as have a plan of action for implementing NWP models into their own classrooms when the professional development is over. The format of this course has been developed through a review of literature on effective professional development practices in science education.

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