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Dive into the research topics where Leona Schauble is active.

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Featured researches published by Leona Schauble.


Educational Researcher | 2003

Design Experiments in Educational Research

Paul Cobb; Jere Confrey; Andrea A. diSessa; Richard Lehrer; Leona Schauble

In this article, the authors first indicate the range of purposes and the variety of settings in which design experiments have been conducted and then delineate five crosscutting features that collectively differentiate design experiments from other methodologies. Design experiments have both a pragmatic bent—“engineering” particular forms of learning—and a theoretical orientation—developing domain-specific theories by systematically studying those forms of learning and the means of supporting them. The authors clarify what is involved in preparing for and carrying out a design experiment, and in conducting a retrospective analysis of the extensive, longitudinal data sets generated during an experiment. Logistical issues, issues of measure, the importance of working through the data systematically, and the need to be explicit about the criteria for making inferences are discussed.


Developmental Psychology | 1996

The development of scientific reasoning in knowledge-rich contexts.

Leona Schauble

In this study of the development of scientific reasoning, 10 5th-6th-grade children (5 boys and 5 girls) and 10 noncollege adults conducted experiments over 6 half-hour sessions to explore the causal structure of 2 physical science domains. Feedback in these systems, though relevant to discriminating among hypotheses, was noisy as a result of varying effect sizes and measurement error. After 2 hr on each task, both age groups demonstrated changes in their understanding of the content and in their strategies for generating and interpreting evidence. In general, the adults outperformed the children. Neither valid strategies nor correct beliefs alone was sufficient to guarantee success, suggesting that regarding experimentation either as domain-general induction or as domain-specific learning may oversimplify its complexity.


Journal of Research in Science Teaching | 1997

Building functional models: Designing an elbow

David E. Penner; Nancy D. Giles; Richard Lehrer; Leona Schauble

Previous work suggests that children largely perceive science as the passive observation and recording of events. In contrast, studies of practicing scientists show a concern with building and testing models. In this study we investigated the role of a design context for developing childrens understanding of science as the construction and revision of models. Grade 1-2 children were given the task of building a model that works like a human elbow. Via discussion, model building, evaluation, and revision, children came to understand that not only motion but also constraints on motion were important qualities to include in their models. Moreover, review of classroom activity and analysis of the postmodeling interview sug- gest that as early as first grade, childrens model-evaluation skills may be quite amenable to development: In comparison to a nonmodeling peer group, modelers were largely able to ignore perceptual qualities when asked to judge the functional qualities of models. Further, they showed an understanding of the modeling process in general that was similar to that of children 3-4 years older. J Res Sci Teach 34: 125-143, 1997. Recent studies suggest that children perceive science largely as a passive process of ob- serving and recording events. In their view, good scientists are those who attend acutely and make accurate and complete records of all that they observe (Carey, Evans, Honda, Jay, & Unger, 1989; Songer & Linn, 1991). Yet, accounts of the work of professional scientists paint a far different picture, one dominated by building and testing models (e.g., Giere, 1988; Hestenes, 1992). In these accounts, model building and testing are essential to the development of theory—models both channel observations and drive the resulting interpretations (Hestenes, 1992). In contrast, childrens views of models, like their views of scientific practice in general, reflect a belief that observation is theory-free and unproblematic. Thus, children tend to view models primarily as physical copies of phenomena, rather than as tools in the service of theory construction and testing (Grosslight, Unger, Jay, & Smith, 1991). In this study, we investigated the role of a design context for developing childrens appreci- ation of science as a model-construction and model-revision process. We chose the design focus because the process of design affords the potential for children to construct, apply, debate, and


The Journal of the Learning Sciences | 1998

From Physical Models to Biomechanics: A Design-Based Modeling Approach

David E. Penner; Richard Lehrer; Leona Schauble

In this study, we used a design context for developing childrens understanding of the natural world via the designing, building, testing, and evaluation of models. In this instance, we asked children to design models of the human elbow. Childrens models were then used as the basis for an exploration of the biomechanics of the human arm. The investigation of biomechanical principles is a major extension of our earlier research. By building on childrens design-based models, we were able to engage students in an investigation of the relation between force and the location of the attachment point of the biceps. In so doing, we were able to provide children with opportunities to develop their understanding of the relations between mathematics and science through the construction and interpretation of data tables and graphs. Design is a form of problem solving in which thinking, tool manipulation, and materials are reflected in the construction of an artifact (Bucciarelli, 1994; Roth, 1996; Simon, 1981). In turn, artifacts become objects that facilitate the sharing of knowledge. Moreover, because many design problems are, at least initially, inherently unspecified, the problem solver must often first define the problem and then explicitly state and justify the relation between the problem and the proposed solution. This promotes a view of knowledge as purposeful, fluid, and conditional (Lehrer, 1993). In this study, we used a design context for developing childrens understanding of the natural world via the designing, building, testing, and evaluation of models. We chose a design focus because the process of design affords the potential for children to construct, apply, debate, and evaluate models, rather than to simply


Journal of Research in Science Teaching | 1998

Reasoning about Structure and Function: Children's Conceptions of Gears

Richard Lehrer; Leona Schauble

Twenty-three second graders and 20 fifth graders were interviewed about how gears move on a gearboard and work in commonplace machines. Questions focused on transmission of motion; direc- tion, plane, and speed of turning; and mechanical advantage. Several children believed that meshed gears turn in the same direction and at the same speed. Many second graders provided very incomplete expla- nations of transmission of motion. Most children confused mechanical advantage with speed. Yet as the interview proceeded, several fifth graders generalized conceptions about transmission of motion into a rule about turning direction. They increasingly justified their ideas about gear speed by referring to ratio. Chil- drens reasoning became more general, formal, and mathematical as problem complexity increased, sug- gesting that mathematical forms of reasoning may develop when they provide a clear advantage over sim- ple causal generalizations.


Journal of Applied Developmental Psychology | 2000

Developing Model-Based Reasoning in Mathematics and Science

Richard Lehrer; Leona Schauble

Abstract It is essential to base instruction on a foundation of understanding of childrens thinking, but it is equally important to adopt the longer-term view that is needed to stretch these early competencies into forms of thinking that are complex, multifaceted, and subject to development over years, rather than weeks or months. We pursue this topic through our studies of model-based reasoning. We have identified four forms of models and related modeling practices that show promise for developing model-based reasoning. Models have the fortuitous feature of making forms of student reasoning public and inspectable—not only among the community of modelers, but also to teachers. Modeling provides feedback about student thinking that can guide teaching decisions, an important dividend for improving professional practice.


International Journal of Computers for Mathematical Learning | 2007

Supporting the Development of Conceptions of Statistics by Engaging Students in Measuring and Modeling Variability

Richard Lehrer; Min-Joung Kim; Leona Schauble

New capabilities in TinkerPlots 2.0 supported the conceptual development of fifth- and sixth-grade students as they pursued several weeks of instruction that emphasized data modeling. The instruction highlighted links between data analysis, chance, and modeling in the context of describing and explaining the distributions of measures that result from repeatedly measuring multiple objects (i.e., the height of the school’s flagpole, a teacher’s head circumference, the arm-span of a peer). We describe the variety of data representations, statistics, and models that students invented and how these inscriptions were grounded both in their personal experience as measurers and in the affordances of TinkerPlots, which assisted them in quantifying what they could readily display with the computer tool. By inventing statistics, students explored the relation between qualities of distribution and methods for expressing these qualities as a quantity. Attention to different aspects of distribution resulted in the invention of different statistics. Variable invention invited attention to the qualities of “good” measures (statistics), thus meshing conceptual and procedural knowledge. Students used chance simulations, built into TinkerPlots, to generate models that explained variability in a sample of measurements as a composition of true value and chance error. Error was, in turn, decomposed into a variety of sources and associated magnitudes—a form of analysis of variance for children. The dynamic notations of TinkerPlots altered the conceptual landscape of modeling, placing simulation and world on more equal footing, as first suggested by Kaput (Journal of Mathematical Behavior, 17(2), 265–281, 1998).


Science Education | 1997

Constructing a Science Gallery for Children and Families: The Role of Research in an Innovative Design Process.

Leona Schauble; Karol Bartlett

We describe the role of research in designing ScienceWorks, an innovative gallery at The Childrens Museum of Indianapolis. The gallery, intended for 6–10-year-old children and their families, was constructed on the basis of existing and new research concerning how children think and learn about science. The gallery is atypical in several respects, but perhaps most fundamentally in its overarching agenda, to foster childrens understanding. Each major component in the gallery contains a broad array of activities to support learning for casual visitors, but also includes opportunities for successively deeper levels of learning and engagement. Existing research on science learning was reviewed to develop the theoretical framework that guided the design process. Moreover, research informed the development of each of the major gallery components and its associated learning activities. Current ongoing research focuses on identifying effective forms of mediation in the gallery, which is more accurately conceived as a collection of tools for supporting childrens learning at various levels of engagement, than as a series of stand-alone “exhibits.”


Archive | 2010

What Kind of Explanation is a Model

Richard Lehrer; Leona Schauble

We describe modeling as a form of explanation that is particular to science and, based on a research program conducted over the last 15 years, identify the conceptual resources and practices that must be developed for school students to become initiated into this kind of reasoning. We point out that modeling is difficult for novices to grasp but is treated by school science as self-evident, which may account for the fact that it is widely misunderstood by learners and educators alike. We close by considering components of instruction, especially classroom norms and tasks, that best support the long-term development of modeling.


Interactive Learning Environments | 1994

Developing Model‐Based Reasoning

Richard Lehrer; Jeffrey Horvath; Leona Schauble

Key elements of the structure and function of models in mathematics and science are identified. These elements are used as a basis for discussing the development of model‐based reasoning. A microgenetic study examines the beginnings of model‐based reasoning in a pair of fourth‐ and fifth‐grade children who solved several problems about chance and probability. Results are reported in the form of a cognitive model of childrens problem‐solving performance. The cognitive model explains a transition in childrens reasoning from tacit reliance on empirical regularity to a form of model‐based reasoning. Several factors fostering change in childrens thinking are identified, including the role of notations, peer interaction, and teacher assistance. We suggest that model‐based reasoning is a slowly‐developing capability that emerges only with proper contextual and social support and that future study should be carried out in classrooms, where these forms of assistance can also be part of the object of study. Mode...

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Rich Lehrer

University of Wisconsin-Madison

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Robert Glaser

University of Pittsburgh

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Anthony J. Petrosino

University of Texas at Austin

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David E. Penner

University of Wisconsin-Madison

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Nancy D. Giles

University of Wisconsin-Madison

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Sharon J. Derry

University of Wisconsin-Madison

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