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Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that led to a remarkable discovery in basic bioscience. Accounting for such discoveries requires a distributed cognition (DC) analysis, as DC focuses on the roles played by external representations in cognitive processes. However, DC analyses by and large have not examined scientific discovery, and they mostly focus on memory offloading, particularly how the "use" of existing external representations changes the nature of cognitive tasks. In contrast, we study discovery processes and argue that discoveries emerge from the processes of "building" the computational representation. The building process integrates manipulations in imagination and in the representation, creating a "coupled cognitive system" of model and modeler, where the model is "incorporated" into the modeler's imagination. This account extends DC significantly, and we present some of the theoretical and application implications of this extended account.

We hypothesize generic models to be central in conceptual change in science. This hypothesis has its origins in two theoretical sources. The first source, constructive modeling, derives from a philosophical theory that synthesizes analyses of historical conceptual changes in science with investigations of reasoning and representation in cognitive psychology. The theory of constructive modeling posits generic mental models as productive in conceptual change. The second source, adaptive modeling, derives from a computational theory of creative design. The theory of adaptive modeling uses generic mental models to enable analogical transfer. Both theories posit situation independent domain abstractions, i.e. generic models. Using a constructive modeling interpreution of the reasoning exhibited in protocols collected by John Clement (1989) of a problem solving session involving conceptual change, we employ the representational constructs and processing structures of the theory of adaptive modeling to develop a new computational model, ToRQUE . Here we describe a piece of our analysis of the protocol to illustrate how our synthesis of the two theories is being used to develop a system for articulating and testing ToRQUE. The results of our research show how generic modeling plays a central role in conceptual change. They also demonstrate how such an interdisciplinary synthesis can provide significant insights into scientific reasoning.

Thought experiments have played a central role in historical cases of major conceptual change in science. They are important in both constructing new representations of nature and in conveying those representations to others. It is proposed that research into the role of mental modelling in narrative comprehension can illuminate how and why thought experiments work. In constructing and "running" the thought experiment, we make use of inferencing mechanisms, existing representations, and general world knowledge to make realistic transformations from one possible physical state to the next and this process reveals impossibility of applying existing concepts to the world and pinpoints the locus of needed conceptual reform.

We discuss the process of mathematization in science, focusing on uses that theorists make of physical representations that w e refer to as abstracted models. W e review abstracted models constructed by Faraday and Maxwell in the mathematization of electromagnetic phenomena, including Maxwell's use of an analogy between continuum dynamics and electromagnetism. W e discuss ways in which this example requires major modifications of current cognitive theories of analogical reasoning and scientific induction, especially in the need to understand the use of abstracted models containing theoretically meaningful objects that can be manipulated and modified in the development of new concepts and mathematized representations.

As much research has demonstrated, novel scientific concepts do not arise fully formed in the head of a scientist but are created in problem-solving processes, which can extend for considerable periods and even span generations of scientists. To understand concept formation and conceptual change it is important to investigate these processes in the contexts of scientific practice, that is, "in the wild." This article addresses "concept formation in the wild" through examining the relations between concept formation and physical and computational simulation modeling practices in two research laboratories in the bioengineering sciences. It argues that processes of concept formation and of building distributed cognitive systems are deeply entwined. (Contains 5 figures and 4 footnotes.)