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Credits appear on page 275
Library of Congress Cataloging-in-Publication Data
Powerful learning : what we know about teaching for understanding / foreword by Milton Chen ; Linda Darling-Hammond … [et al.]. – 1st ed.
p. cm.
Includes bibliographical references and index.
ISBN 978-0-470-27667-9 (alk. paper)
1. Learning. 2. Effective teaching–United States. I. Darling-Hammond, Linda, 1951-LB1060P6796 2008
371.102–dc22
2008009921
FIRST EDITION
Our Foundation began in 1991 with an ambitious mission: to demonstrate how innovative learning environments in classrooms, supported by powerful new technologies, could revolutionize learning. As an organization founded by George Lucas, we believed that the same benefits of technology that were transforming business, health care, entertainment, and manufacturing could be applied in education. Industrial assembly-line models based on the productivity of individual workers were giving way to more collaborative ways of organizing work in teams. Information was being shared more readily and rote tasks were being automated. And this was in the days before the Internet.
In two decades, the world has moved ahead dramatically, but our schools remain caught in a web of educational thinking and systems that originated a century ago—or, some would say, even earlier. The instructional model of the teacher and the textbook as the primary sources of knowledge, conveyed through lecturing, discussion, and reading, has proven astonishingly persistent. Even the traditional form of classroom seating, with students arrayed in rows—a configuration that prevents group work and conversation—is still common. In my boyhood classroom of the sixties, changing the classroom layout might have been impossible, because the chairs and desks were bolted to the floor. Today, with furniture that is movable, there’s no excuse. It’s clear we first need to unbolt our thinking.
Fortunately, this “dominant paradigm” is showing signs of wear. In our own work of finding and telling the stories of innovative learning in and out of schools, we see many more examples of individual teachers and principals, as well as some districts and even states, implementing new forms of project-based curricula and performance-based assessment. In these classrooms, students are organized in teams, where they must address such open-ended and complex questions as “What is the air and water quality in your community?” “How would you design a school of the future? or a hybrid car?” For these projects, students gather and sift information from many sources, analyze data, and produce products of their investigation for presentation to their peers, families, and communities, in person and on the Web.
These classrooms also benefit from new pipelines for teacher development, starting in schools of education, so that teachers can embrace their new role as learning coach and manager, rather than solely as direct instructor. As in the modern workplace, these classrooms function as a digital environment, where technology enables access to a much wider world of information and students are able to express their multiple intelligences and build on their strengths and interests as learners.
As a Foundation, we have understood the critical importance of developing a research basis for these innovations. We have spent more than a decade documenting examples of project-based learning and cooperative learning in classrooms, as well as in informal and after-school settings; and publishing documentary films, Edutopia magazine, and a multimedia Web site (www.edutopia.org). Yet, for these many individual examples to take root in more places, their effectiveness must be demonstrated in educational research. Importantly, policymakers investing funds in the curriculum, instruction, and assessment required to bring these innovations to scale have to base their policies on documented results. These beliefs led to our support for this volume.
With it, Linda Darling-Hammond and her colleagues at Stanford University; the University of California, Berkeley; and the Lawrence Hall of Science have taken an important step forward for the field. Their review of the literature on teaching practices such as project-based learning; cooperative learning; and specific instructional strategies in literacy, mathematics, and science summarizes what is known and what new research is needed. Their analyses take advantage of important new developments in cognitive research in the past decade, such as the landmark volume How People Learn, published by the National Academy of Sciences in 1999. Although they point to studies of the effectiveness of these strategies, they also temper the results with an important caveat: effectiveness relies heavily on the quality of the teachers implementing them.
I hope this book will lead to greater shared understanding of the research record on innovative classroom practices. At the same time, it should lead to efforts to invest in the new forms of research designs and measures needed to study these practices and their ways of organizing students and their learning. Perhaps ironically, the types of meaningful learning experiences described here return us to a much earlier time, when learning was more connected to daily life and where young people learned in the company of their elders as well as with each other.
On behalf of our Foundation, I express our appreciation to the authors for their contributions to this important book: Linda Darling-Hammond and Brigid Barron, at Stanford University; David Pearson, Alan Schoenfeld, Timothy Zimmerman, and Gina Cervetti, at the University of California, Berkeley; and Elizabeth Stage and Jennifer Tilson, at the Lawrence Hall of Science. They have brought their acknowledged wisdom as thoughtful and creative leaders in the field of education and educational research to this work. Powerful Learning should provoke new thinking about the kinds of “powerful research” needed to support creation of many more twenty-first-century schools and school systems.
Milton Chen
Executive Director
George Lucas Educational Foundation
The George Lucas Educational Foundation (GLEF) is a nonprofit foundation that gathers and disseminates the most innovative models of K–12 teaching and learning in the digital age. The foundation serves its mission through a variety of media—a magazine, videos, books, e-newsletters, DVDs, and a Web site: www.edutopia.org.
Linda Darling-Hammond is Charles E. Ducommon Professor of Education at Stanford University, where she serves as co-director of the School Redesign Network and the Stanford Educational Leadership Institute. Her research, teaching, and policy work focus on teaching quality, school reform, and educational equity. She is co-founder of a charter high school in East Palo Alto that seeks to offer powerful teaching and learning opportunities to students who are historically under-served in American schools. Among her nearly 300 publications are the award-winning books The Right to Learn, Teaching as the Learning Profession, and Preparing Teachers for a Changing World.
Brigid Barron is an Associate Professor of Education at Stanford University. She studies collaborative learning in and out of school. Her work appears in books and journals including Journal of Educational Psychology, Journal of Experimental Child Psychology, Human Development, Journal of the Learning Sciences, and Communications of the Association for Computing Machinery, International Journal of Technology and Design. She has co-edited a book on the use of video as data in learning sciences research. She co-leads the LIFE center (Learning in Informal and Formal Environments), funded by the National Science Foundation in 2005. Barron is PI for a new grant funded by the MacArthur Foundation that will follow students longitudinally as they participate in programs designed to develop their technological fluency through activities such as game design, robotics, and digital movie making.
Gina N. Cervetti is a Literacy Curriculum and Research Specialist at the University of California, Berkeley’s Lawrence Hall of Science. She is a literacy specialist, program director, and researcher for the NSF-funded Seeds of Science/Roots of Reading project. Her current research agenda concerns the role of text in learning science and the potential of science-literacy integration to support students’ development of academic literacy.
P. David Pearson is Dean of the Graduate School of Education, and a professor in the area of Language and Literacy. He conducts research and teaches graduate courses in the area of reading processes, pedagogy, and assessment with the hope of creating greater access and opportunity for our nation’s poorest children. Pearson has written and co-edited several books about research and practice, most notable being the Handbook of Reading Research, now in its third volume (with a fourth in development) and an edited volume on Effective Schools and Accomplished Teachers.
Alan H. Schoenfeld is the Elizabeth and Edward Conner Professor of Education at the University of California, Berkeley. A mathematician by training, he studies mathematical thinking, teaching, and learning. His major goal is to help create learning environments that open up the riches of mathematics for all students. Among the books he has written and edited are his classic volume Mathematical Problem Solving, The National Council of Teachers of Mathematics’Principles and Standards for School Mathematics, and Assessing Mathematical Proficiency.
Elizabeth K. Stage is the director of the Lawrence Hall of Science, the University of California, Berkeley’s public science center. The Hall conducts research, develops curriculum materials, and works with teachers and other educators to accomplish its mission of inspiring and fostering the learning of science and mathematics for all, especially those with limited access. Her work in standards and assessment, professional development, and promoting quality science experiences in after-school settings reflect her focus on that mission.
Jennifer L. Tilson is a literacy curriculum developer and researcher for the NSF-funded Seeds of Science/Roots of Reading project at the University of California, Berkeley’s Lawrence Hall of Science. Her work focuses on developing effective practices for embedding literacy instruction in the rich context of science, and on methods for teaching scientific language to increase access to academic discourse for all students.
Timothy D. Zimmerman is an academic researcher at the University of California, Berkeley’s Lawrence Hall of Science. Trained as a marine biologist and learning sciences researcher, he studies ocean sciences teaching and learning in both formal (classrooms) and informal (aquariums, museums, field trips, etc.) contexts, often incorporating educational technology. His work advances the teaching of ocean sciences concepts, often omitted from K–12 curricula, and promotes a scientifically literate society capable of making environmentally-sound decisions.
Linda Darling-Hammond
Since A Nation at Risk (1983) was published a quarter century ago, mountains of reports have been written about the need for more powerful learning focused on the demands of life and work in the twenty-first century. Whereas 95 percent of jobs in 1900 were low-skilled and required just the ability to follow basic procedures designed by others, today such jobs make up only about 10 percent of the U.S. economy. Most of today’s jobs require specialized knowledge and skills, including the capacity to design and manage one’s own work; communicate effectively and collaborate with others; research ideas; collect, synthesize, and analyze information; develop new products; and apply many bodies of knowledge to novel problems that arise (Drucker, 1994).
Furthermore, the nature of work will continue to change, and ever more rapidly. Whereas during much of the twentieth century, most workers held two or three jobs during their lifetime, the U.S. Department of Labor (2006) estimates that today’s average worker holds more than ten jobs before the age of forty. The top ten in-demand jobs projected for 2010 did not exist in 2004 (Gunderson, Jones, & Scanland, 2004). Thus we are currently preparing students for jobs that do not yet exist, to use technologies that have not yet been invented, and to solve problems that we don’t even know are problems yet.
Meanwhile, knowledge is expanding at a breathtaking pace. It is estimated that five exabytes of new information (5,000,000,000,000,000,000 bytes, or 500,000 times the volume of the Library of Congress print collection) was generated in 2002, more than three times as much as in 1999. Indeed, in the four years from 1999 to 2002 the amount of new information produced approximately equaled the amount produced in the entire history of the world previously (Varian & Lyman, 2003). The amount of new technical information is doubling every two years, and it is predicted to double every seventy-two hours by 2010 (Jukes & McCain, 2002). As a consequence, effective education can no longer be focused on transmission of pieces of information that, once memorized, constitute a stable storehouse of knowledge. Education must help students learn how to learn in powerful ways, so that they can manage the demands of changing information, technologies, jobs, and social conditions.
These new demands cannot be met through passive, rote-oriented learning focused on basic skills and memorization of disconnected facts. Higherorder goals demand what some analysts have called “meaningful learning” (Good & Brophy, 1986)—that is, learning that enables critical thinking, flexible problem solving, and transfer of skills and use of knowledge in new situations. Nations around the world are reforming their school systems to meet these new demands, revising curriculum, instruction, and assessment to support the more complex knowledge and skills needed in the twenty-first century, skills needed for framing problems, seeking and organizing information and resources, and working strategically with others to manage and address dilemmas and create new products.
What do we know about the kind of teaching that produces more powerful learning? Based on research on learning and teaching conducted over the last fifty years, this book summarizes much of what is known about effective teaching and learning strategies in three major subject areas—reading and literacy, mathematics, and science—as well as selected strategies that are used across domains and in interdisciplinary contexts, including project-based learning, performance-based assessment, and cooperative learning. We also look at the factors and conditions that can influence the effectiveness of these strategies. Finally, we examine the quality of the research base in these areas, and we identify gaps that exist in our knowledge base and how future research might address them.
This book is intended for the policymakers whose decisions shape our educational systems, and the teachers, administrators, and other educators who determine what happens in schools and classrooms. Researchers concerned with effective education will also find this book useful for their studies. It gives evidence about the outcomes of successful educational strategies, examples of what they look like in practice, and insights about how they can become the norm, rather than the exception, in our schools.
Any discussion of teaching needs to start with what we know about learning, especially the kind of intellectually ambitious learning demanded in today’s knowledge-based society. As the National Academy of Sciences summary of how students learn (Donovan & Bransford, 2005) notes, there are at least three fundamental and well-established principles of learning that are particularly important for teaching:
These key principles of learning are evident in the research that has emerged on effective teaching. Looking across domains, studies consistently find that highly effective teachers support the process of meaningful learning by:
Having identified some general principles about learning and teaching, it is important to acknowledge that effective teaching strategies differ with the kind of learning. As Bransford, Darling-Hammond, and LePage (2005) point out, the appropriateness of using particular types of teaching strategies depends on
(1) the nature of the materials to be learned; (2) the nature of the skills, knowledge, and experiences that learners bring to the situation; and (3) the goals of the learning situation and the assessments used to measure learning relative to these goals. These variables are represented in the model seen in Figure 1, developed by James Jenkins. One important point of the model is that a teaching strategy that works within one constellation of these variables may work very poorly if one or more factors are changed.
For our discussion, the kind of learning sought is especially critical to examine: Does it aim for rote understanding and recall, or does it aim for the kind of meaningful learning that would allow learners to use what they’ve learned to solve problems? For example, what if we wanted to teach students about veins and arteries?1 The text presents the facts that arteries are thicker than veins and more elastic, and they carry blood rich in oxygen from the heart. Veins are smaller, less elastic, and carry blood back to the heart. What’s the best way to help students learn this information? The Jenkins model reminds us that the answer to this question depends on who the students are, what we mean by “learning” in this context, and how we measure the learning that occurs.
If we want to ensure only that students remember certain key facts about arteries—for example, that they are thicker than veins and more elastic—then one strategy would be to use a mnemonic technique such as teaching students to remember the sentence “Art(ery) was thick around the middle so he wore pants with an elastic waist band.” If students understand the vocabulary being used, this technique would “work” for remembering these specific facts.
Suppose, however, that we want students not only to remember certain facts but to understand why they are important with respect to bodily functioning. This involves a change in learning goals and assessments, as well as teaching and learning strategies. To learn with understanding, students need to learn why veins and arteries have certain characteristics. For example, arteries carry blood from the heart, blood that is pumped in spurts. This helps explain why they would need to be elastic (to handle the spurts). In contrast, veins carry blood back to the heart and hence need less elasticity due to a lessening of the spurts.
Learning to understand relationships such as why arteries are elastic and arteries are less so should facilitate subsequent transfer. For example, imagine that students are asked to design an artificial artery or vein. Would it have to be elastic? Students who have only memorized information have no grounded way to approach this problem. Students who have learned with understanding know the functions of elasticity and hence are freer to consider possibilities such as relatively nonelastic materials that can still handle differences in pressure (adapted from Bransford & Stein, 1993).
This example illustrates how memorizing versus understanding represent distinctive kinds of learning, and how changes in these goals require different types of teaching strategies. To understand how arteries function, students would have to examine how they work in the context of the cardiovascular system and other bodily functions. They would need to link this knowledge to other knowledge they have acquired about physical properties of matter (aspects of force and gravity that are implicated in the need to pump fluid from the legs to the heart), and they would likely need opportunities to construct or analyze models of how this operates. The details of teaching strategies also vary with the knowledge, skills, attitudes, and other characteristics that students bring to the learning task. For example, younger students may not know enough about pumping, spurts, and elasticity to learn with understanding if they are simply told about the functions of arteries. They may need to see dynamic simulations that display these properties and consider examples that draw on aspects of the world that are already familiar (such as how elastic works in a rubber band). Seeing and experiencing things concretely is often an important prerequisite to learning to use information in more abstract or general ways.
Research examining whether “something works” should take into consideration each perspective of the Jenkins framework. In the box are a few critical questions to help position the teacher.
A sophisticated understanding of the content, the learner, and the goals of instruction is important for effective teaching. As we proceed, we highlight these concerns as we discuss general strategies for teaching and learning for understanding and describe how they play out in a number of subject matter domains.
MILTON CHEN