The impulse to investigate the natural world is deeply rooted in our earliest childhood experiences. This notion has long guided researchers to uncover the cognitive mechanisms underlying the development of scientific reasoning in children.
Until recently, however, research in cognitive development and education followed largely independent tracks. A major exception to this trend is represented in the multifaceted work of David Klahr. His lifelong effort to integrate a detailed understanding of children's reasoning and skill acquisition with the role of education in influencing and facilitating scientific exploration has been essential to the growth of these fields.
In this volume, a diverse group of stellar contributors follow Dr. Klahr's example in examining the practical implications of our insights into cognitive development for children in the classroom. Authors discuss such wide-ranging ideas as the evolution of "folk science" in young children and the mechanisms that underlie mathematical understanding, as well as mental models used by children in classroom activities.
The volume's lessons will have profound implications for STEM education, and for the next generation of scientists.
Contributors
Foreword
Preface
Introduction: The Journey From Child to Scientist — The Psychology of Science, Science Education, and the Impact of David Klahr
Sharon M. Carver and Jeff Shrager
- From Theory to Application and Back: Following in the Giant Footsteps of David Klahr
Robert S. Siegler
- The Learning of Science and the Science of Learning: The Role of Analogy
Zhe Chen
- Does Folk Science Develop?
Frank C. Keil
- The Evolved Mind and Scientific Discovery
David C. Geary
- Educational Neuroscience: Applying the Klahrian Method to Science Education
Kevin Niall Dunbar
- Is Development Domain Specific or Domain General? A Third Alternative
Annette Karmiloff-Smith
- Simulating Discovery and Education in a Soccer Science World
Jeff Shrager
- Moving Young "Scientists-in-Waiting" Onto Science Learning Pathways: Focus on Observation
Rochel Gelman and Kimberly Brenneman
- Supporting Inquiry About the Foundations of Evolutionary Thinking in the Elementary Grades
Richard Lehrer and Leona Schauble
- Engineering in and for Science Education
Christian D. Schunn, Eli M. Silk, and Xornam S. Apedoe
- To Teach or Not to Teach Through Inquiry
Erin Marie Furtak, Richard J. Shavelson, Jonathan T. Shemwell, and Maria Figueroa
- Epistemic Foundations for Conceptual Change
Richard A. Duschl and Mariá Pilar Jiménez-Aleixandre
- Patterns, Rules, and Discoveries in Life and in Science
David Klahr
Index
About the Editors
Sharon M. Carver, PhD, is a developmental psychologist who serves as a teaching professor at Carnegie Mellon University and the director of the Psychology Department's early childhood laboratory school, The Children's School. With David Klahr, she codirects the university's doctoral Program in Interdisciplinary Education Research (PIER).
Dr. Carver earned an AB in psychology from Princeton University and a PhD in psychology from Carnegie Mellon University, where her advisor was David Klahr.
Dr. Carver's research focus is on the explicit specification of learning goals, the alignment of instruction and assessment with those goals, and the application of diverse teaching strategies to facilitate transfer. She seeks to enhance the reciprocal impact of theory and research in multiple disciplines to strengthen the learning of children, educators, families, university students, and researchers.
Jeff Shrager, PhD, is a consulting associate professor of symbolic systems at Stanford University, and chief technological officer of CollabRx, Inc., a biomedical informatics startup.
A computational psychologist of science, Dr. Shrager seeks to understand how science works and to build human–computer networks that facilitate scientific discovery.
Dr. Shrager holds degrees in computer science and cognitive and developmental psychology from The University of Pennsylvania and Carnegie Mellon University, respectively, and has conducted research in cognitive and developmental neuroscience, informal science education, scientific computing, human learning, artificial intelligence, molecular microbial marine biology and genomics, nonlinear mathematics, and many other areas.
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