Suggestions for quick fixes in science education come from every imaginable group and take every imaginable form. We have seen group learning, discovery learning, management by objectives, local (or state) control, quality processes, smaller class size, computers, networks, the World Wide Web, teacher certifications, school uniforms, assessments, integrated science, increased science requirements, new standards, and a myriad of other "solutions" offered for improving science understanding.

Although none of these approaches succeeds by itself, our national fascination with immediate rewards fuels a continuous quest for a simple, straightforward, solution to a problem that is particularly vexing, because it is extremely complex.

The reality is that complex problems demand multifaceted solutions.

Fixing science education--like curing cancer, managing energy usage, or creating transportation systems--requires designing multiple approaches, supporting local adaptations, and synthesizing experiences into a coherent framework.

Drawing upon our experience over the last ten years with the Computer as Learning Partner (CLP) project, we offer this book as a guide. Rather than a quick fix, we advocate a process of continuous improvement for science education in which teachers, scientists, educational researchers, technology specialists, curriculum designers, and students work together as partners to improve learning outcomes.

For fifteen years the Computer as Learning (CLP) partnership has studied how students learn science and how to make scientific knowledge accessible‹and relevant‹to them, not only for the time spent in the middle school or high school classroom but also for the rest of their lives.

This book relates our findings and provides an instructional framework that new partnerships can use to get a head start on curriculum design. We advocate forming partnerships for this endeavor, because the problems of science education require expertise from many disciplines and because we need large-scale efforts in schools, districts, and states in order to have a serious impact.

We cannot possibly teach students all the science we want them to know in science courses. Instead, we need to prepare students to continue to learn science after they complete their classes. The question is how to set them on a path towards lifelong science learning.

Many middle school science texts, for example, attempt to "cover" everything. They feature over forty topics like mechanics, genetics, plate tectonics, electricity, heat, the periodic table, photosynthesis, light, and the circulatory system--one for each week of the school year. This fleeting coverage of topics means that many students memorize, isolate, and forget the science they encounter. Yet groups setting science education standards have difficulty agreeing that any topic be dropped.

One of the major goals of our Computer as Learning Partner partnership has been to discover how topics can be taught to foster lifelong learning. How can we enable students to learn additional science topics when the need arises?

As we follow Lee, Chris, Pat, and Sasha, four students who studied the Computer as Learning Partner from 8th grade through high school, we see the range of paths that individuals might take as they attempt to understand science. We describe how these students respond to class instruction and use computers, teachers, and peers as learning partners. By the end of the eighth grade, all these students have made progress in understanding science, but have not integrated what they know in some areas. Each student has drawn upon some aspects of the CLP curriculum but not others. After analyzing how the curriculum was designed to meet their varied needs, we revisit the students in high school to see whether CLP has provided a firm foundation for each student. Chapters 1, 6, and 7 clarify how middle school students integrate their scientific ideas and illustrate how the various aspects of CLP contribute to the process.

Another question our CLP partnership has addressed is how to make science personally relevant. Today, science students often complain that the science they learn in school plays no role in their lives, and they report little interest in continuing to learn science. They note that obje cts in motion may well "remain in motion" at school, but they come to rest at home!

To promote lifelong learning, we must offer students courses that provide scientific ideas they can revisit, reuse, and refine after they finish science classes. They need connections between the problems they face in their lives and the material they study in class. And they need an understanding of the character of science to guide their future learning. The Computer as Learning Partner curriculum responds by providing students with problems that are personally relevant and an approach to learning that they can use throughout their lives.

What do we mean by personally relevant problems? Problems that individuals care about can bring science to life and motivate students to carry out lifelong investigations. For example, determining how to survive in the wilderness, discovering how sunglasses work, or distinguishing among nutritional options engage students in the work of science: considering alternatives, gathering evidence, and identifying research questions.

Ultimately, we hope lifelong learners will identify new problems for themselves and continuously revisit the ideas from their science classes. We refer to students who orchestrate their own science learning as autonomous learners. In Chapter 5, we describe ways that science courses can encourage students to become autonomous. We show how science courses can include projects that permit students to apply what they learn, identify what they need to know, and find answers to their questions.

Our classroom interviews and observations revealed that middle school students come to class with many disparate and often contradictory ideas that apply to the same scientific problem. For example, while scientists agree that temperature is a measure of heat and that heat is the amount of energy in a material, students have a variety of views. When asked to distinguish heat from temperature, students might have four or more answers, each of which they use some of the time. Thus, they might believe that heat and temperature are interchangeable, because we say "turn up the heat" and "turn up the temperature" to mean the same thing. They might believe that "heat" is the higher temperature on a thermometer. Or they might remember that they can feel heat in a hot wind, and so conclude that heat is a substance and temperature, a "measure." In contrast, they might conclude from television coverage of the "heat index" that heat is a "measure," like temperature.

To help students become lifelong science learners, we can encourage them to integrate what they know rather than to hold disparate views like these.

What do we mean by knowledge integration? We mean that process of comparing ideas, distinguishing cases, identifying the links and connections among notions, seeking evidence to resolve uncertainty, and sorting out valid relationships. Students who integrate their ideas seek coherence among diverse perspectives and converge on robust ideas that they can apply widely. Knowledge integration drives scientific research, just as it drives student learning. Our goal in promoting lifelong learning is to help students continuously link and connect ideas.

How can we link knowledge integration to personally relevant problems? By identifying pragmatic science principles and pivotal cases that apply to the problems students face and by using these principles and pivotal ideas to help synthesize the ideas that students bring to class.

What do we mean by pragmatic science principles? Scientific principles are pragmatic when they synthesize a rich set of practical experiences and can be used to deal with new practical problems. To distinguish between heat and temperature, for example, one pragmatic science principle would state: "When only mass differs, the temperature of the larger mass will change more slowly." Students might confirm this principle by observing that a large tureen of soup stays at a higher temperature longer than a small bowl of soup. They could apply this principle to practical questions like: "To keep ten pizzas hot, should we stack the pizza boxes up or spread them out?" Or, "Why is it better to put a burned hand in a pot of cold water than to wrap it in a wet cloth?" Or, "Should we turn on the shower or fill the tub with hot water to warm the bathroom?"

What are pivotal cases? When students try to integrate what they know, but lack sufficient information, they might flounder or even reach a conclusion that scientists would dispute. How can we support and encourage knowledge integration that leads to more robust, cohesive, and scientifically normative thinking? We identify cases that, when added to the mix of notions students bring to science class, serve to stimulate the process of sorting out diverse ideas. For example, if students believe that "metals feel cold and can impart cold," we can use this notion to a broader investigation of insulation and conduction by asking them to investigate how metals feel in a hot car.

Instructional designers at all levels wonder which cases will be pivotal. Good choices help students with their struggle to make sense of science. We also worry about what level of analysis of a scientific problem will be most appropriate. . For example, the CLP partnership debated whether to describe heat energy at the molecular level, as was typical of middle school texts, or at the level of heat flow. In Chapter 2, we describe how and why we selected heat flow over molecular-kinetic theory.

As Richard Feynman describes in his book, the choice of level of analysis for college-level physics:

"...what should we teach first? Should we teach the correct but unfamiliar law with its strange and difficult conceptual ideas, for example, the theory of relativity, four-dimensional space-time, and so on? Or should we first teach the simple Œconstant-mass¹ law, which is only approximate, but does not involve such difficult ideas? The first is more exciting, more wonderful, and more fun, but the second is easier to get at first, and is a first step to a real understanding of the second idea. This point arises again and again in teaching physics." (Feynman, R. P. (1995). Six Easy Pieces. New York: Addison-Wesley, p. 3.

Much of our CLP partnership effort was devoted to selecting the pivotal cases, the level of analysis for pragmatic science principles, and the personally relevant problems that enable most students to integrate their knowledge successfully. Our conclusions appear throughout the book.

Today¹s science curriculum is often "decreed" by standards committees, textbook adoption committees, or curriculum authors. Yet, no fixed set of instructional materials can succeed with all learners, in all settings, for all time. Furthermore, "decreed" materials often lack connections to the personally relevant problems that interest students and lead to lifelong science learning.

Learners, settings, technologies, and science itself all change regularly. In addition, we continuously gain new understanding of effective pedagogy from classroom research, from teachers, and from students.

Instead of instruction based on a "decreed" curriculum, we need instruction that is informed by iterative redesign and continuous improvement. We need design teams that bring together individuals with diverse experience who can all contribute to a flexible, responsive curriculum.

We advocate partnerships composed of experts in the science disciplines, classroom instruction, educational technology, pedagogy, school policy, and related topics who come together to design curriculum materials, develop assessment materials, carry out experiments in diverse classrooms, refine the curriculum based on these experiments, report their findings to others, and continue this process.

In Chapters 2 through 5, we describe how our partnership designed, tested, and refined the Computer as Learning Partner curriculum over fifteen years. To illustrate our thinking processes, we discuss our failures as well as our successes, and we describe the design studies that helped us select among alternatives. We synthesize our experiences into what we call the Scaffolded Knowledge Integration framework; and we provide some specific guidance in the form of pragmatic pedagogical principles that synthesize our experiences in ways we hope can be readily applied.

We described knowledge integration earlier as the process of linking, connecting, distinguishing, sorting out, reorganizing, and reconsidering scientific ideas to achieve coherence. Scaffolded Knowledge Integration (SKI) refers to an instructional process that enables individual learners to engage regularly, effectively, and continuously in knowledge integration and lifelong learning.

We chose the term scaffolded because successful instruction supports students and enables them to integrate their knowledge, just as scaffolding around a building supports construction workers and enables them to improve the building. Scaffolding enables learners to identify their notions about a scientific topic, consider some experiments, make connections to pivotal ideas, and integrate their perspective into a more robust and coherent view.

What are pragmatic pedagogical principles? Pedagogical principles are pragmatic when they synthesize a rich set of practical, instructional experiences and can be used to deal with new practical problems. Our pragmatic pedagogical principles are intended to give a head start to new partnerships designing science materials. For example, one pragmatic principle in Chapter 3 is: "Explain scientific processes and demonstrate mistakes." This principle is part of making science thinking visible to students.

Too often, instructors only describe an outcome or a solution without explaining how knowledge was integrated to reach it. In our programming research, we discovered that many instructors only described a brilliant correct solution. In calculus or geometry, frequently only the successful proof is provided. As a result, some students conclude that knowledge integration, the process of sorting out alternatives, indicates a lack of skill in science.

When instructors explain the scientific process and demonstrate (and explicate) mistakes, they model knowledge integration and enable students to recognize this process in their own reasoning. Each of the pragmatic pedagogical principles in the book offers instructors ways to use their own practical experiences to scaffold knowledge integration.

As a key element of our discussion of scaffolded knowledge integration, we focus attention on the ways in which computers can help instructors implement each of our pragmatic pedagogical principles. For example, scientific visualization software can help explain a scientific process and demonstrate mistakes. Our heat bars visualization, described in Chapter 3, helps many students by introducing pivotal cases.

Just as science curricula must be adaptable and responsive, so must science teachers be lifelong designers of science instruction. In Chapter 8, we discuss how teachers benefit from a personal plan for fluency in information technology. We also discuss how teachers can participate in partnerships for designing science curricula like CLP, school technology plans, or other educational innovations.

Pedagogical content knowledge

Devising personally relevant problems, pivotal cases, or pragmatic scientific principles that build on student ideas goes way beyond the scope of current university science courses. Even teachers with the most comprehensive science background will encounter many topics, questions, and problems that they cannot explain.

As we discuss in Chapter 9, science teachers need to develop pedagogical content knowledge. By this we mean knowledge that helps the instructor understand the ideas students bring to science class. Teachers with pedagogical content knowledge of thermal phenomena will understand when students assert that "metals impart cold." For each science topic, teachers continuously face students with -----novel ideas. The challenge is to develop responses that keep these students engaged in knowledge integration. As we suggest in Chapter 9‹and support on our web site--one way for teachers to advance pedagogical content knowledge is to band together in electronic communities with others working on the same topic. We also propose a variety of group and individual resources that teachers can use to continually integrate their knowledge.

Local adaptations of instruction

Science teachers can help students become lifelong science learners by adapting instruction to local conditions. For example, students studying energy might investigate local options for home insulation and examine the role of insulation decisions in energy conservation. Students in environmental science might study local ecosystems, such as prairies, rain forests, deserts, or urban parks. Often teachers create local adaptations that could be used by others but lack ways to report their findings. Others may face difficult instructional challenges and wish for support from peers or outside experts. We hope to help teachers form partnerships to address these issues.

In Chapters 8 and 9, we describe how technological tools and web resources can support partnerships. By taking advantage of a web site to report experiences and locate information, teachers can overcome isolation and build on each other¹s experiences.

Looking ahead, we hope this book will motivate those concerned about the future of science education to learn from our failures, build on our successes, and join together in similar partnerships to improve science learning, science instruction, and science education research.

In the spirit of innovation, we dedicate this book, with deepest admiration and appreciation, to Doug Kirkpatrick, our pioneering "Mr. K."

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