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About the Project

 

What are our goals for elementary and middle school science education? Should we be asking students to learn the concepts and facts that science has generated over the centuries of its history? If so, how do we address the challenge that more and more new knowledge is being produced at ever-faster rates? Should we instead be emphasizing the methods or processes of science? If so, how do we avoid miscommunicating by implying that there is a set of rules (The Scientific Method) that can be applied unproblematically in all situations? Of course, we know that The Scientific Method is a fiction appropriate processes for investigation vary widely with changes in the structure of the domains being investigated (methods for studying evolutionary biology are not the same as methods and processes for studying mechanics), our current state of knowledge, and near-term goals for the investigation. This process-content dichotomy has dominated science education for years, but there is no sign that it is being resolved successfully. Moreover, although national and state standards documents are proliferating, they provide little help for those who believe that science understanding should grow cumulatively and coherently across years of schooling. Instead, almost everywhere, elementary science is regarded as an ever-expanding grab-bag of topics, with no apparent rationale for their selection and less for their organization.

These are the problems that motivated "Modeling Nature," a research project conducted in collaboration between practicing elementary and middle school teachers in Verona and Madison, WI, and researchers at the Wisconsin Center for Education Research at the University of Wisconsin-Madison. The purpose of the research, funded by the National Science Foundation, is to study the conceptual development of elementary and middle school students as they graduate through grades of instruction that is designed coherently and cumulatively around themes that play a central role in science. By themes, we mean "big ideas" that are visible in a wide variety of world phenomena, such as growth and diversity, behavior, structure and form. National standards concur that science literacy involves coming to understand such central themes in a deep way. Yet, how do we orchestrate instruction over years of schooling so that when students come to the end of their formal education, they will really understand these ideas?

We have identified three criteria that have been very helpful to us in answering this question. First, we give preference to themes that support modeling approaches to science. Modeling is what scientists do. It is one of the characteristic ways that science has developed for developing knowledge of the world, its epistemology, if you prefer that word. So when students engage with science by developing, revising, and evaluating models of phenomena that interest them, they are coming to understand how scientific knowledge gets made, not just acquiring "made" or final-form knowledge. A model is an analogy that describes how one system of objects and relations describes another. For example, a compost column can be used as a physical model of decomposition in the larger world. An equation can be used to model growth. No model fits the world perfectly, but we can think of the development of scientific knowledge as a progressive generation and refinement of models of the natural world. When one models, one necessarily models something , so the practice of modeling is always focused squarely on understanding the details of science content and concepts. What we are arguing is that modeling is an authentic representation of what science is all about and that it also fortuitously provides a way of bypassing the process/content dichotomy.

Our second criterion is that themes need to afford both easy entry and a high ceiling . If instruction is to cumulate across years of education, there must be ways for kindergartners and first graders to begin using their own knowledge and sense-making to conduct inquiry and to invent models that are genuinely substantive. At the same time, there must also be ways to generate curricular "lift" and challenge at the higher grades. Ideally, the transition from grade to grade should be smooth and continuous. It is better to avoid themes that allow students to begin readily enough, but eventually arrive at an instructional "dead end." By dead end, we mean a topic that cannot be brought to closure because the next step is well beyond students' current capacities, so the issue has to be abandoned for several grades until students' mathematical or conceptual development "catches up."

Finally, and perhaps this goes without saying, a theme suitable for organizing years of instruction is one that provides a broad foundation that supports development of important ideas in upper-grade science . For example, investigations of growth (of organisms and populations) and diversity can be systematically and profitably sustained across the elementary grades and beyond. Moreover, what students learn in these investigations feeds directly into the big ideas of high school biology. A good understanding of distribution, which can be the linchpin to understanding evolution, can be fostered in the elementary and middle school grades, as students characterize and compare populations. Distribution is key, because evolution is not directly observable, but changes in distributions of populations can be observed, characterized, analyzed, and evaluated as evidence of evolutionary change.

As the comments about distribution suggest, it is not possible to sustain a modeling curriculum in science without a broader mathematical repertoire than is usually developed in the lower grades. Geometry, data, measurement, functions, and uncertainty are taking a central place in early mathematics, and they are necessary resources if students are to pursue more rigorous, modeling-based approaches to science. With a strong foundation in mathematics, we can develop a cumulative approach to science, emphasizing model-based reasoning as the cornerstone of scientific practice and the most promising route toward understanding the themes outlined in the standards. Together, researchers and teachers work to plan and put these forms of instruction in place, and as teaching and learning evolve, we study transitions in student thinking. Our overall purpose is to learn together how students' understanding of "big ideas" in science emerges and takes hold. We generate and publicly share what we are learning together, so that each person's contributions contribute to a broader portrait of the development of student thinking across the grades. A professional development collaboration, which has been in place for half a dozen years, is the primary site for our work together. We work together to better understand mathematics and science and to understand how children think about mathematics and science. We have published one volume of our research, Understanding Real Data in the Classroom (Teachers College Press), and this website is a second forum for sharing our work.

The standards paint a picture of the kind of scientific literacy that can emerge over years of well-planned education supported by thoughtful curricula and excellent pedagogy. However, the standards developed by various professional organizations are too broad to support the development of profound understanding. Our project is an effort to identify and hone in on productive choices of content, models, and forms of professional practicethat ensure that we can cash in the promise of standards-based education in science. To accomplish these goals, research is needed to illuminate the outcomes that can reasonably be expected (both products and processes of student learning) and to enhance understanding of what it takes to achieve them not over a few weeks or months, but over years the time span required for students to grasp profound ideas.


This material is based upon work supported by the National Science Foundation under Grant No. 0337675.
Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

 

Last Updated: April 4, 2006
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