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- Herausgeber: John Wiley & Sons
- Kategorie: Bildung
- Sprache: Englisch
- Veröffentlichungsjahr: 2015
In Powerful Learning, Linda Darling-Hammond and an impressive list of co-authors offer a clear, comprehensive, and engaging exploration of the most effective classroom practices. They review, in practical terms, teaching strategies that generate meaningful K-2 student understanding, and occur both within the classroom walls and beyond. The book includes rich stories, as well as online videos of innovative classrooms and schools, that show how students who are taught well are able to think critically, employ flexible problem-solving, and apply learned skills and knowledge to new situations.
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Table of Contents
Cover
Title
Copyright
FOREWORD
ABOUT THE AUTHORS
INTRODUCTION: TEACHING AND LEARNING FOR UNDERSTANDING
INTENDED AUDIENCE
PRINCIPLES OF LEARNING FOR EFFECTIVE TEACHING
ADAPTING STRATEGIES TO KINDS OF LEARNING
1: HOW CAN WE TEACH FOR MEANINGFUL LEARNING?
THE NEED FOR INQUIRY-BASED LEARNING TO SUPPORT TWENTY-FIRST-CENTURY SKILLS
INQUIRY-BASED LEARNING
AN HISTORICAL PERSPECTIVE ON INQUIRY-BASED LEARNING
COLLABORATIVE SMALL GROUP LEARNING: EVIDENCE AND BEST PRACTICES
RESEARCH ON INQUIRY LEARNING APPROACHES
CHALLENGES OF INQUIRY APPROACHES TO LEARNING
CONCLUSION
2: READING FOR UNDERSTANDING
THE ROLE OF THE READER IN INTERACTING WITH TEXT
DEVELOPING MINDFUL ENGAGEMENT
RICH TALK ABOUT TEXT
INTEGRATED INSTRUCTION
CONCLUSION
3: MATHEMATICS FOR UNDERSTANDING
AN IMAGE
A BRIEF HISTORY: THE CONSEQUENCES OF ROTE LEARNING AND THE CONTEXT FOR CHANGE
ISSUES IN IMPLEMENTING MATHEMATICS FOR UNDERSTANDING
CONCLUSION
4: TEACHING SCIENCE FOR UNDERSTANDING
UNDERSTANDING SCIENCE: WHERE THINGS STAND NOW
WHAT DOES IT MEAN TO UNDERSTAND SCIENCE?
THE CHALLENGE OF UNDERSTANDING SCIENCE
CONCLUSION
5: CONCLUSION: CREATING SCHOOLS THAT DEVELOP UNDERSTANDING
PRINCIPLES OF TEACHING FOR UNDERSTANDING
THE POLICY CONTEXT
APPENDIX
BIBLIOGRAPHY
SUBJECT INDEX
NAME INDEX
Credits
End User License Agreement
List of Tables
APPENDIX
TABLE 1 Design Principles for Supporting Inquiry-Based Approaches
TABLE 2 Forms and Functions of Assessment for Inquiry-Based Approaches
TABLE 3 Forms and Functions of Group Work for Inquiry-Based Approaches
List of Illustrations
Introduction: Teaching and Learning for Understanding
FIGURE 1 The Tetrahedral Model of Learning
3: Mathematics for Understanding
FIGURE 1 Percentage of Students Who Met or Exceeded the Standard, New Standards 4th-Grade Math Exam
FIGURE 2 Percentage of Students Who Scored Well Below the Standard
FIGURE 3
4: Teaching Science for Understanding
FIGURE 1 Average PISA Science Literacy Scores for Fifteen-Year-Olds, by Country.
FIGURE 2 Average PISA 2003 Scores for Fifteen-Year-Olds, by Ethnicity Subgrouped by Discipline and Problem-Solving Skills.
FIGURE 3 A WISE Reflection Prompt.
5: Conclusion: Creating Schools That Develop Understanding
FIGURE 1
Guide
Cover
Table of Contents
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POWERFUL LEARNING
WHAT WE KNOW ABOUT TEACHING FOR UNDERSTANDING
LINDA DARLING-HAMMOND
BRIGID BARRON
P. DAVID PEARSON
ALAN H. SCHOENFELD
ELIZABETH K. STAGE
TIMOTHY D. ZIMMERMAN
GINA N. CERVETTI
JENNIFER L. TILSON
MILTON CHEN
Copyright © 2008 by John Wiley & Sons, Inc. All rights reserved.
Published by Jossey-BassA Wiley Imprint989 Market Street, San Francisco, CA 94103-1741 www.josseybass.com
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400, fax 978-646-8600, or on the Web at www.copyright.com. Requests to the publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, 201-748-6011, fax 201-748-6008, or online at http://www.wiley.com/go/permissions.
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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 2008371.102–dc22
2008009921
FIRST EDITION
FOREWORD
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 ChenExecutive DirectorGeorge 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.
Online discussion questions for Powerful Learning are available at: www.josseybass.com/go/powerfullearning
ABOUT THE AUTHORS
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.
INTRODUCTION: TEACHING AND LEARNING FOR UNDERSTANDING
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.
INTENDED AUDIENCE
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.
PRINCIPLES OF LEARNING FOR EFFECTIVE TEACHING
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:
Students come to the classroom with prior knowledge that must be addressed if teaching is to be effective.
If what they know and believe is not engaged, learners may fail to grasp the new concepts and information that are taught, or they may learn them for purposes of a test but not be able to apply them elsewhere, reverting to their preconceptions outside the classroom. This means that teachers must understand what students are thinking and how to connect with their prior knowledge if they are to ensure real learning. When students from a variety of cultural contexts and language backgrounds come to school with their own experiences, they present distinct preconceptions and knowledge bases that teachers must learn about and take into account in designing instruction. Teachers who are successful with all learners must be able to address their many ways of learning, prior experiences and knowledge, and cultural and linguistic capital.
Students need to organize and use knowledge conceptually if they are to apply it beyond the classroom.
To develop competence in an area of inquiry, students must not only acquire a deep foundation of factual knowledge but also understand facts and ideas in the context of a conceptual framework, and organize knowledge in ways that facilitate retrieval and application. This means teachers must be able to structure the material to be learned so as to help students fit it into a conceptual map and teach it in ways that allow application and transfer to new situations. The teaching strategies that allow students to do this integrate carefully designed direct instruction with hands-on inquiries that engage students actively in using the material, incorporate applications and problem solving of increasing complexity, and require ongoing assessment of students’ understanding for the purpose of guiding instruction and student revisions of their work.
Students learn more effectively if they understand how they learn and how to manage their own learning.
A “metacognitive” approach to instruction can help students learn to take control of their own learning by having a set of learning strategies, defining their own learning goals, and monitoring their progress in achieving them. Teachers need to know how to help students self-assess their understanding and how they best approach learning. Through modeling and coaching, teachers can teach students how to use a range of learning strategies, including the ability to predict outcomes, create explanations in order to improve understanding, note confusion or failures to comprehend, activate background knowledge, plan ahead, and apportion time and memory. Successful teachers provide carefully designed “scaffolds” to help students take each step in the learning journey with appropriate assistance, steps that vary for different students depending on their learning needs, approaches, and prior knowledge.
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:
Creating
ambitious and meaningful tasks
that reflect how knowledge is used in the field
Engaging students in
active learning,
so that they apply and test what they know
Drawing
connections to students’ prior knowledge
and experiences
Diagnosing student understanding in order to
scaffold the learning process
step by step
Assessing student learning continuously
and adapting teaching to student needs
Providing clear
standards
, constant
feedback
, and opportunities for work
Encouraging
strategic and metacognitive thinking
, so that students can learn to evaluate and guide their own learning
ADAPTING STRATEGIES TO KINDS OF LEARNING
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.
FIGURE 1 The Tetrahedral Model of Learning
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.
TEACHING WITH LEARNING IN MIND
What kind of content is worth having students spend their time learning?
What are the goals for learning?
Are the assessments of learning consistent with the goals?
Who is being taught?
How might teaching techniques need to change for students with differing sets of prior skills and knowledge?
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.
1
This example is drawn from Bransford, Darling-Hammond, and LePage (2005), pp. 18–20, and was modified with help from John Bransford, for clearer explication of the biological principles involved.
1HOW CAN WE TEACH FOR MEANINGFUL LEARNING?
Brigid Barron and Linda Darling-Hammond
THE NEED FOR INQUIRY-BASED LEARNING TO SUPPORT TWENTY-FIRST-CENTURY SKILLS
Enthusiasm for approaches to instruction that connect knowledge to the contexts in which it will be applied has been on the upswing since the 1980s. Recommendations from an array of organizations have emphasized the need to support twenty-first-century skills through learning that supports inquiry, application, production, and problem solving. More than a decade ago, the SCANS Report (Secretary’s Commission on Achieving Necessary Skills, 1991) suggested that for today’s students to be prepared for tomorrow’s workplace they need learning environments that allow them to explore real-life situations and consequential problems. These arguments have been echoed in scholarly research (for example, Levy & Murnane, 2004), national commission reports (such as NCTM, 1989; MLSC et al., 1996), and policy proposals (see NCREL EnGauge, 2003; Partnership for 21st Century Skills, 2002), urging instructional reforms to help students gain vital media literacies, critical thinking skills, systems thinking, and interpersonal and self-directional skills that allow them to manage projects and competently find resources and use tools.
For these capacities to be nurtured, the reports argue, students must be given opportunities to develop them in the context of complex, meaningful projects that require sustained engagement, collaboration, research, management of resources, and development of an ambitious performance or product. The rationale for these recommendations has come in part from research demonstrating that students do not routinely develop the ability to analyze, think critically, write and speak effectively, or solve complex problems from working on constrained tasks that emphasize memorization and elicit responses that merely demonstrate recall or application of simple algorithms (Bransford, Brown, & Cocking, 1999; Bransford & Donovan, 2005). In addition, there is a growing body of research indicating that students learn more deeply and perform better on complex tasks if they have the opportunity to engage in more “authentic” learning.
A set of studies have found positive effects on student learning of instruction, curriculum, and assessment practices that require students to construct and organize knowledge, consider alternatives, apply disciplinary processes to content central to the discipline (such as use of scientific inquiry, historical research, literary analysis, or the writing process), and communicate effectively to audiences beyond the classroom and school (Newmann, 1996). For example, a study of more than twenty-one hundred students in twenty-three restructured schools found significantly higher achievement on intellectually challenging performance tasks for students who experienced this kind of “authentic pedagogy” (Newmann, Marks, & Gamoran, 1995). The use of these practices predicted student performance more strongly than any other variable, including student background factors and prior achievement.
This is promising, but the checkered history of efforts to implement “learning by doing” makes clear the need for greater knowledge about how to successfully manage problemand project-based approaches in the classroom (Barron et al., 1998). The kind of teaching suggested by these descriptions is not straightforward and requires knowledge of the characteristics of successful strategies and highly skilled teachers to implement them. In this chapter, we focus on the design and implementation of inquiry-based curriculum that engages children in extended constructive work, often in collaborative groups, and subsequently demands a good deal of self-regulated inquiry.
INQUIRY-BASED LEARNING
The family of approaches that can be described as inquiry-based includes project-based learning, design-based learning, and problem-based learning.
The research we review spans the K–12 years, college, and graduate education and can be found across core disciplines and in interdisciplinary programs of study1. Two major conclusions emerge:
Small group inquiry approaches can be extremely powerful for learning. To be effective, they need to be guided by thoughtful curriculum with clearly defined learning goals, well-designed scaffolds, ongoing assessment, and rich informational resources. Opportunities for professional development that include a focus on assessing student work increase the likelihood that teachers will develop expertise in implementing these approaches.
Assessment design is critical. Designing good assessment is an important issue for revealing the benefits of inquiry approaches as well as for promoting the success of learning. Specifically, if one looks only at traditional learning outcomes, such as memorization of information or responses to multiple-choice questions, inquiry-based and traditional methods of instruction appear to yield similar results. Benefits for inquiry learning emerge when the assessments require application of knowledge and measure quality of reasoning. Consequently, we also take up a discussion of performance assessment and its role in both supporting and evaluating meaningful learning.
Our discussion within this chapter is organized into four sections.
First, we provide a historical perspective on inquiry-based learning in the context of the ongoing calls to develop inquiry and collaborative capacities in learners.
Next, we summarize research on collaborative small group learning. Our review focuses primarily on studies that offer data on the outcomes of cooperative or collaborative learning approaches. However, we also look at the kinds of interaction between children that lead to deeper learning and better group problem solving, and what we have learned about how teachers can support productive interactions.
In the third section, we summarize what we know about the forms of inquiry-based approaches (project, design, and problem-based) with respect to learning outcomes, supportive activity structures, and classroom norms.
Finally, we close with common design principles and recommendations about approaches to assessment.
AN HISTORICAL PERSPECTIVE ON INQUIRY-BASED LEARNING
Projects as a means for making schooling more useful and readily applied to the world first became popular in the early part of the twentieth century in the United States. The term project represented a broad class of learning experiences. In early works one sees the label applied to activities as diverse as making a dress, watching a spider spin a web, and writing a letter. The key idea behind such projects was that learning was strengthened when “whole heartedness of purpose was present” (Kilpatrick, 1918).
Enthusiasm and belief in the efficacy of such approaches for schoolaged children has waxed and waned, with project-based learning having been rejected as too unstructured during several eras of “back to the basics” backlash, or policymakers having argued that applied projects are only needed for vocational training. Critics of the progressive movement held that discovery learning approaches led to “doing for the sake of doing” rather than doing for the sake of learning. There is a growing consensus that authentic problems and projects afford unique opportunities for learning, but that authenticity in and of itself does not guarantee learning (Barron et al., 1998; Thomas, 2000).
The key is how these complex approaches are implemented. For example, in the curricular reforms of the post-Sputnik years, initiatives using inquiry-based approaches (typically called “discovery learning” or project learning) were found to produce comparable achievement on basic skills tests while contributing more to students’ problem-solving abilities, curiosity, creativity, independence, and positive feelings about school (Dunkin & Biddle, 1974; Glass et al., 1977; Good & Brophy, 1986; Horwitz, 1979; McKeachie & Kulik, 1975; Peterson, 1979; Resnick, 1987; Soar, 1977). This kind of meaning-oriented teaching, once thought to be appropriate only for selected high-achieving students, proved to be more effective than rote teaching for students across a spectrum of initial achievement levels, family income, and cultural and linguistic backgrounds (Braddock & McPartland, 1993; Garcia, 1993; Knapp et al., 1995).
However, new curriculum initiatives focused on inquiry using complex instructional strategies were found more often to promote a significant increase in learning gains among students taught by the early adopters—teachers who were extensively involved in designing and piloting the curriculum and who were given strong professional development. These effects were not always sustained as curriculum reforms were “scaled up” and used by teachers who did not have the same degree of understanding or skill in implementation.
At the present time, there is still controversy over whether inquiry-oriented approaches are effective and efficient for developing the student’s basic knowledge of a domain. Implementation issues continue to be a concern for both practitioners and researchers and complicate research. Examples include studies that have suggested that “direct instruction”—usually understood as traditional lecture-based approaches—is preferable to “discovery learning.” The sources of confusion are shown in a study by Klahr and Nigam (2004), which taught middle school students to set up controlled experiments and then measured the students’ knowledge of experimental design and their ability to set up experiments that could appropriately control for potentially confounding variables. They labeled their conditions “direct instruction” and “discovery learning.” However, both conditions included features of discovery learning, including the chance for students to explore the materials and try together to set up experiments. In their discovery learning condition, the researchers simply instructed the participating sixth graders to design experiments to evaluate variables related to the speed of a ball traveling down a ramp. In the direct instruction approach, the children were taught about the importance of not confounding variables in the context of demonstration experiments. This lesson was given after they had tried to set up experiments on their own.
Although the researchers’ conclusions suggested that the direct-instruction approach yielded better learning, they failed to acknowledge that this approach included both a great deal of experimentation and some direct instruction. In addition, critics of the study’s conclusion point out that in a real classroom situation children would be given much more guidance and scaffolding than took place in their discovery-learning condition. Thus the study does not prove that classroom-based inquiry approaches are do not work but only that they are more successful when combined with necessary instruction. This combination of appropriately timed direct instruction with the results of inquiry has also been found in other studies to be superior to either approach alone (see, for example, Bransford, Brown, & Cocking, 1999, box on p. 46). We return to this important principle later in the chapter.
Classroom research does indicate that well-designed, carefully thought-out materials and connected classroom practices are needed to capitalize on inquiry-based approaches. Without careful planning, students may miss opportunities to connect their project work with key concepts underlying a discipline. For example, Roth (2006) found that in an engineering-based curriculum for elementary school students engineering principles were unlikely to be discovered simply by successfully engineering solutions to problems such as building bridges or towers. Similarly, Petrosino (1998) described his observation of students building rockets in a science curriculum highlighting interesting products and a high level of engagement but no growth in learning the principles of flight. However, a slight variation in the task that required students to determine the variables related to how far a rocket will travel led to a dramatic increase in students’ conceptual knowledge relative to the original project.
In recent years, the research base on inquiry approaches has grown to include both comparative studies and more descriptive classroom investigations of teaching and learning processes. There is a growing consensus on the importance of a number of design principles that characterize successful inquiry-based learning environments and that can be used by teachers as they embark on developing or enacting new curriculum. We summarize the relevant research base beginning with collaborative approaches to learning and then moving to three specific approaches to designing inquiry experiences: project-based learning, design-based learning, and problem-based learning. (See Table 1 of the Appendix for a summary of design principles that have emerged from classroom research.)
COLLABORATIVE SMALL GROUP LEARNING: EVIDENCE AND BEST PRACTICES
The technique of having small groups of students work together on learning activities has its roots in part in an experiment that was aimed at supporting friendships across ethnic groups following desegregation (Aronson & Bridgeman, 1979). This effort was based on theories of interpersonal relationship formation developed in the field of social psychology (Deutsch, 1949), and it proved successful not only at developing relationships but also at improving achievement.
Cooperative small group learning is one of the most studied pedagogical interventions in the history of educational research. E. G. Cohen (1994b) defines cooperative learning as “students working together in a group small enough that everyone can participate on a collective task that has been clearly assigned” (p. 3). This definition includes what has been called cooperative learning, collaborative learning, and other forms of small group work. This context for learning has been the subject of hundreds of studies and several meta-analyses (P. A. Cohen, Kulik, & Kulik, 1982; Cook, Scruggs, Mastropieri, & Castro, 1985; Hartley, 1977; Johnson, Maruyama, Johnson, Nelson, & Skon, 1981; Rohrbeck, Ginsburg-Block, Fantuzzo, & Miller, 2003). Overall these analyses come to the same conclusion: there are significant learning benefits for students when they are asked to work together on learning activities as compared to approaches where students work on their own (Johnson & Johnson, 1981, 1989).
For example, in a comparison of four types of problems presented to individuals or cooperative teams, researchers found that teams outperformed individuals on all types and across all ages (Quin, Johnson, & Johnson, 1995). Problems varied in terms of how well defined they were (a single right answer versus open-ended projects such as writing a story) and whether they were more or less reliant on language. Individual experimental studies have shown that groups outperform individuals on learning tasks, and further that individuals who work in groups do better on later individual assessments as well (Barron, 2000b, 2003; O’Donnell & Dansereau, 1992).
There are desirable outcomes for students in other areas of their lives as well, including improvement in student self-concept, social interaction, time on task, and positive feelings toward peers (P. A. Cohen et al., 1982; Cook et al., 1985; Ginsburg-Block, Rohrbeck, & Fantuzzo, 2006; Hartley, 1977; Johnson & Johnson, 1989). Ginsburg-Block and colleagues (2006) focused on the relationship between academic and nonacademic measures. They found that both social and self-concept measures were related to academic outcomes. Larger effects were found for interventions that used same-gender grouping, interdependent group rewards, structured student roles, and individualized evaluation procedures. They also found that low-income students benefited more than high-income students, and urban students benefited more than suburban. Racial and ethnic minority students benefited even more from cooperative group work than nonminority students, a finding that has been repeated over several decades (see Slavin & Oickle, 1981). Ginsburg-Block and colleagues (2006) conclude that those dimensions of group work that support academic outcomes also yield social and self-concept benefits.
Most recently, the focus has gone beyond the practical benefits of collaboration for individual learning to recognize the importance of helping children develop the capacity to collaborate as necessary preparation for all kinds of work. For example, the Science for All Americans, Project 2061 (American Association for the Advancement of Science, 1989) suggests that a core practice of scientific inquiry is collaborative work; schools should be preparing students for this kind of work through classroom activities that require joint efforts.
The collaborative nature of scientific and technological work should be strongly reinforced by frequent group activity in the classroom. Scientists and engineers work mostly in groups and less often as isolated investigators. Similarly, students should gain experiences sharing responsibility for learning with each other. In the process of coming to understandings, students in a group must frequently inform each other about procedures and meanings, argue over findings, and assess how the task is progressing. In the context of team responsibility, feedback and communication become more realistic and of a character very different from the usual individualistic textbook-homework-recitation approach [AAAS, 1989, p. 202].
Challenges of Small Group Work in Classrooms
Although there is much consensus about the desirability of developing collaboration skills, and research is clear about the general benefits of small group interaction for learning, this does not mean that helping small groups engage in high-quality discussion and sharing is easy. Research has identified at least three major challenges for cooperative learning in classrooms: (1) developing norms and structures within groups that allow individuals to work together; (2) developing tasks that support useful cooperative work; and (3) developing discipline-appropriate strategies for discussion that support rich learning of content.
A number of studies have pointed out the importance of structure for positive group outcomes. Yager, Johnson, and Johnson (1985) examined the effect of structured and unstructured oral discussions with mixed-ability second-grade cooperative learning groups. Groups were randomly assigned and stratified on the basis of sex and ability level. Each class consisted of three twelve-minute sections: teacher instruction, oral discussion, and class discussion. During the oral discussion, the unstructured group was told to work together on the material introduced by the teacher; the structured group received roles of learning leader and learning listener. The role of the leader was to give a synopsis of the day’s lesson, and the listeners were to ask questions to push the leader to give a full explanation. The structured group achieved higher scores on unit tests given at day nine and day eighteen, and on the retention test given eighteen days after the end of the unit. Given that the assessments were taken individually, the researchers concluded there is group-to-individual transfer of knowledge.
Gillies (2004) also studied structured and unstructured groups in ninth-grade math classes in Australia. The students in the structured groups were trained in cooperative social skills before working in groups on the mathematics unit. The unstructured groups were told to work together but not given any further direction. All students received a teacher-created math assessment at the end of the unit and a questionnaire recording their perceptions of the group process. The students in the structured group performed better on the math assessment and exhibited more cooperative and on-task behavior than did the unstructured groups.
Calling students’ attention to how their group is functioning appears to facilitate better group outcomes. In a study of group processing, Yager, Johnson, Johnson, and Snider (1995) observed positive gains in achievement for low-, middle-, and high-ability third graders who were given processing time to discuss how their group was working and what could be done to improve their efficacy. The control group also engaged in cooperative group work without the opportunity for group processing, thus illuminating how specific cooperative learning interactions produce more positive outcomes.
The nature of the task also appears to matter. For example, Nystrand, Gamoran, and Heck (1993) did a study across nine schools and fifty-four ninth-grade English classes of the effects of small groups on achievement. They noticed that, in this sample, those who stayed in small groups longer had lower achievement. It turned out that these students were in groups assigned to tasks that amounted to “collaborative seatwork,” not permitting student autonomy and student production of knowledge. The lowest-rated groups on these dimensions were those assigned grammar work rather than analysis of literature. These groups scored lower on the final assessment than those who were in groups that allowed them “to interact over the substance of their problem, defining tasks as well as solutions, and constructing interpretations”(p. 20). The researchers argued that adolescents need tasks allowing them to “compare ideas, develop a train of thought, air differences, or arrive at a consensus on some controversial issue” for them to deepen their knowledge and understanding (p. 22).
Teachers must maximize opportunities to concretely connect the work to key concepts
Once groups know how to work together, and they have a task worth working on, they still need to learn how to have content-rich discussions that are productive of serious learning. A review of nineteen studies that focused on the nature of small group discussions in science (Bennett, Lubben, Hogarth, Campbell, & Robinson, 2005) concluded that the studies consistently show that “students often struggle to formulate and express coherent arguments during small group discussions, and demonstrate a relatively low level of engagement with tasks.” The authors note that five of the seven most highly rated studies make the recommendation that teachers and students need to have explicit opportunities to learn the skills associated with developing arguments and with effective small group discussion.
In a separate review of ninety-four studies, which focused on better understanding the conditions for high-quality discussion,2 the same group of authors (Hogarth, Bennett, Campbell, Lubben, & Robinson, 2005) concluded: “A successful stimulus for students working in small groups to enhance their understanding of evidence has two elements. One requires students to generate their individual prediction, model or hypothesis which they then debate in their small group (internally driven conflict or debate). The second element requires them to test, compare, revise or develop that jointly with further data provided (externally driven conflict or debate).”
Findings of this kind suggest that teachers should play an active role in helping groups learn to coordinate their work on productive tasks and learn how to talk about what they are perceiving in terms that reflect the modes of inquiry in the discipline.
