Journal of Applied Developmental Psychology 34 (2013) 195–197
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Journal of Applied Developmental Psychology
Book review The developing psychology of science education Sharon M. Carver, Jeff Shrager, The journey from child to scientist: Integrating cognitive development and the educational sciences, American Psychological Association, Washington, DC, 2012, (cloth, 305 pp., $79.95), ISBN: 978-1-4338-1138-8 Sharon Carver and Jeff Shrager's book, The Journey from Child to Scientist, has a serious and consequential title that at first glance has multiple meanings. The child and scientist may be intellectual opposites and the journey is about how to traverse the space between them—from naïve child who has few of the cognitive tools necessary to grasp the causal structure of the world to the sophisticated scientist who can wield such tools with precision. The broad topography of this journey has been well mapped by Piaget and five decades of research since the seminal work on the formal logico-mathematical operations underlying scientific thinking (Inhelder & Piaget, 1958). Alternatively, the journey may be an expedition touring the similarities of the child's and scientist's mind. Karl Popper (2005) characterized scientific knowledge as “common sense knowledge writ large” (p. xxvi), suggesting important continuities between children, adults, and scientists. The scientist becomes more child-like by relying on her natural intuition and creativity, which are thought to underlie conceptual change in both domains (Gopnik, 1996). Alternatively, the child becomes more scientist-like when empowered and unencumbered to explore a phenomenon, uncovering its underlying structure (Chaille & Britain, 1997; Cook, Goodman, & Schulz, 2011). As it turns out, Carver, a teaching professor in developmental psychology at Carnegie-Mellon, and Shrager, a consulting professor in symbolic systems at Stanford University and a Chief Technology Officer at a biomedical startup, are skeptical of all these meanings. Instead, they have in mind something both more literal and more historical than what is implied by traditional accounts of the metaphors linking children and scientists. Carver and Shrager were both Ph.D. students at Carnegie Mellon University and the book is a festschrift for their graduate advisor, David Klahr. In Carver and Shrager's introductory chapter they highlight Klahr's professional contributions to psychology and education, providing insight as to why the honor bestowed is well deserved and completely appropriate. The connection between the child and scientist, they explain, is Klahr's own journey from the son of a Connecticut jeweler and his wife to a cognitive scientist who infused the study of cognitive development, science education, and even science itself with new tools and fresh ideas about their use. Klahr's own concluding chapter (chapter 13) documents this journey, offering his own assessment of events and people in his childhood, adolescence, and young adulthood, which propelled him down what is now characterized, somewhat inelegantly, as “the STEM pipeline.” Klahr carefully lays out these stories of the events and people who influenced him and the lessons he learned from them. On the face of it, a reader with aspirations to build STEM pipelines for future David Klahrs may be frustrated with the presentation, as it seems to lack anything that looks like a set of construction blueprints. The challenge is the extent to which 0193-3973/$ – see front matter © 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.appdev.2013.02.002
happenstance plays a role in a STEM career path, a point Klahr readily acknowledges about his journey. But there is more here than meets the eye. The story Klahr lays out is one of an innately talented person, who was well prepared to play in a sandbox of possibility and innovation leading him to cutting edge ideas. Klahr's path, and what might be prescribed by the volume's contributors, is probably not so much a passive pipeline that draws students into a STEM profession as it is a well-tended garden that cultivates not only students' STEM knowledge and skills but also their ability to look for, be passionate about, and follow innovative ideas wherever they may lead. Klahr's own cultivation is captured in a story of moving to Pittsburgh in 1962 as an engineer interested in programming. He was moving to work with Herb Simon who, with Alan Newell, was laying the foundation of the Carnegie-Mellon style of cognitive science. As Klahr puts it, a subsequent series of fortuitous events propelled him from an engineer and computer scientist into one of the first cognitive scientists performing the earliest modeling of cognitive developmental processes. Herb Simon, the Nobel Prize winner, looms large in Klahr's life but also hovers over the entire book in laying the foundation of the computational approach to mind and with it the precise specification of mental processes underlying behavior. The computational approach is central to Klahr's understanding of cognitive development and how pedagogy can be used to engineer the growth of scientific thinking. He exemplifies this in his analysis of the puzzle posed by the classic conservation task performance and, on the basis of an elegant computational model of such judgments, he proposes ways it can be promoted spontaneously and the in vivo experiment that can test it. The general insight of a connection between cognitive development and science education is not new, as such connections underpin the many child and scientist metaphors. But Klahr has been at the forefront of a relatively new view of education as engineering, which is part of the learning sciences (Sawyer, 2006) movement. The learning sciences is an interdisciplinary venture to lay bare the cognitive and social foundations of learning and the potential of that knowledge to design effective instructional environments. More than a marriage of scientists and practitioners, this approach is an integration of science and practice that has been applied to problems in pedagogy with a vigor, rigor, and level of success that had not been seen before. The promise of a vigorous, rigorous, and successful application of psychology to teaching is as old as the discipline of psychology itself (Hall, 1894; James, 1925; Thorndike, 1910). The meandering journey taken by the discipline to discover how best to apply psychology to education reflects the second, more historical interpretation of the journey from child to scientist. Only as the discipline matured and psychological theories about “natural” processes of learning and development became more precise has psychology become better aligned to education. This was Klahr's goal, which made him a leader in the learning sciences: To study the precise
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specification of underlying computational processes of well analyzed authentic activities in the complex natural world of classrooms and other learning environments. This so-called Klahrian method, as Kevin Dunbar (chapter 5) calls it, is only as good as the analysis of authentic activities and the modeling of cognitive processes can be successfully performed. The present volume is a testament to the Klahrian method and the insights that have come from its practice by the best of learning scientists. In the first half of the book are chapters that broadly address the computational issues of the mechanisms of science learning in individual students and are informed by research on authentic activities in natural learning environments. Chapters provide examples of how instruction can be tailored to strategically alter children's scientific thinking (Robert Siegler's chapter 2 and Zhe Chen's chapter 3), evidence of the evolutionary-based limits of training scientific reasoning (Frank Keil's chapter 4 and David Geary's chapter 5), and arguments of how neuroscience may offer a better level of description than cognitive computations for engineering changes in scientific reasoning (Kevin Dunbar's, chapter 6 and Annette Karmiloff-Smith's, chapter 7). The second half is composed of chapters that address the contexts of classrooms and the complex social processes underlying science instruction, informed by research in underlying computational processes. These include a wide range, from the nature of scientific practice found in classroom contexts (Dusch and Jimenez-Aleixandre's chapter 12) to a call to make engineering understandings an explicit piece of science education reform (Schunn, Silk, and Apedoe's chapter 10)—a notion supported by recent calls by the National Research Council (NRC, 2012). The mix is powerful evidence of the impact that the integration of well-modeled processes of scientific reasoning and well-crafted science education pedagogies can have in the cultivation of STEM students. An interesting elephant-in-the-room for science educators might be Klahr and Nigam's (2004) contentious conclusion that children learn more about science and experimental design “from direct instruction than from discovery learning” (p. 661). If this and the ensuing debate were a reader's only experience with Klahr's work, it would seem discrepant to see the work of Lehrer and Schauble (chapter 9) under a title line with the phrase “supporting inquiry” (p. 171), and Gelman and Brenneman's chapter (8) which encourages scientific practices in young children that include many features of “inquiry”. The uninitiated reader may wonder how authors who are such proponents of engaging students in their own scientific practices could be included in a celebratory volume of someone who declared “direct instruction” the big winner. Furtak and colleagues take on this elephant in chapter 11, “To Teach or Not to Teach Through Inquiry.” This piece is informative both in helping the science educator to understand previous works by Klahr and others and in revealing the fact that scholars themselves can become confounded by their own nebulous terminology. By investigating Klahr and Nigam's work, as well as the meanings others took from this, it becomes quite clear that the terms “direct instruction,” “inquiry,” and “discovery learning” (among others) have been used carelessly—perhaps even by Klahr himself in some cases. More importantly, we have collectively used the terms to obscure important details of what kind of instruction we are actually trying to document and test. After all, any mode of instruction is not simply “inquiry” or “direct” but rather a constellation of various components that describe the activity of the teacher, the learner, and the classroom ecology; we would do well to understand key details rather than the broader, more nebulous descriptions. Conclusion In the movie, Being There, a dimwitted Chance the Gardener, a.k.a. Chauncey Gardner, rises to national prominence by talking
about his gardening experience, which is interpreted as metaphors for everything from fixing the economy to living a good life. Not to sound like Chance, but there is something deep and important about good gardening that applies to good teaching: Knowing precisely what plants or students need to grow and providing it to them exactly when they need it, how they need it. All this is hard, no doubt, but the garden metaphor reminds us that science education is not about finding the scientist in children or engineering some type of “pipeline” to the STEM professions. Children are (dare we say) children, not little scientists, and do not passively slosh through a preformed pipeline because we stuff them into the correct channels. Rather, as the tended garden metaphor suggests, children grow into a STEM career by being carefully prepared and mentored to play in a sandbox of possibility and innovation. This gardening imagery of the journey from the child to scientist may well replace pipelines and other metaphors that have implicitly guided some science educators in the past. But even the gardening imagery, like the other metaphors, is vague about the specification of the target of STEM education. Some assume that the scientists, mathematicians, and engineers who are targets of science education embody certain normative properties of their disciplines (i.e., rational, logical, formal, etc.) and so the education is really about inducing students' acquisition of those properties. But as Jeff Shrager (chapter 7) reminds us in his chapter, science has properties emerging but separate from the properties of scientists as they engage in disciplinary activities such as collecting data and publishing. Klahr's (2000) own account of scientific reasoning locates actual scientists engaging in real-world scientific problem solving in representational spaces defined by possible hypotheses and evidence. Developing authentic practices of science is a new emphasis in science education reform, as notably and prominently advocated in the recent publication of A Framework for K-12 Science Education: Practices, Crosscutting Concepts, and Core Ideas (NRC, 2012). But still, more discussion is needed specifying the end state of science instruction. That is, perhaps the goal of science education should not be simply to cultivate students with either the normative abilities of STEM disciplines or the abilities to engage in the authentic activities of STEM professionals but rather to create engaged and scientifically literate citizens with the potential to be STEM professionals. The question of the target of the trajectory of science education is an inevitable consequence of the successes, documented in this volume, in engineering students' construction of STEM knowledge and practices. As educators and scientists we have the responsibility and opportunity to prepare students both to contribute to scientific practice and to understand its implications. Although there is still much to be done in sketching out precisely what that preparation looks like, we admire the work of this book's contributors who tell us, collectively, that we know more than ever about how humans create and understand science. Now, we need to embrace all that we know and incorporate it into our own practices so that our own scholarly pursuits can continue to grow from the childlike pursuits of old to the more sophisticated understandings that this volume documents. References Chaille, C., & Britain, L. (1997). The young child as scientist: A constructivist approach to early childhood science education (2nd ed.). New York: Longman. Cook, C., Goodman, N., & Schulz, L. E. (2011). Where science starts: Spontaneous experiments in preschoolers' exploratory play. Cognition, 120, 341–349. Gopnik, A. (1996). The scientist as child. Philosophy of Science, 63, 485–514. Hall, G. S. (1894). The new psychology as a basis of education. Forum, 710–720. Inhelder, B., & Piaget, P. (1958). The growth of logical thinking from childhood to adolescence. New York: Basic Books. James, W. (1925). Talks to teachers on psychology: And to students on some of life's ideals. New York: Henry Holt and Company.
Book review Klahr, D. (2000). Exploring science: The cognition and development of discovery processes. Cambridge, MA: MIT Press. Klahr, D., & Nigam, M. (2004). The Equivalence of Learning Paths in Early Science Instruction: Effects of Direct Instruction and Discovery Learning. Psychological Science, 15, 661–667. National Research Council (NRC) (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC: The National Academies Press. Popper, K. (2005). The logic of scientific discovery. New York: Taylor & Francis e-Library (Original work published 1935). Sawyer, R. K. (2006). The Cambridge handbook of the learning sciences. New York: Cambridge University Press. Thorndike, E. L. (1910). The contribution of psychology to education. Journal of Educational Psychology, 1, 5–12.
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Eric Amsel Department of Psychology, Weber State University, 1202 University Circle, Ogden, UT, USA E-mail address:
[email protected].
Adam Johnston Department of Physics, Weber State University, 2508 University Circle, Ogden, UT, USA Corresponding author. E-mail address:
[email protected].