Nancy J. Nersessian

Model-Based Reasoning in Conceptual Change

This paper addresses how specific modeling practices employed by scientists are productive methods of conceptual change in science. Within philosophy, where the identification of reasoning with argument and logic is deeply ingrained, these practices have not traditionally been considered significant forms of scientific reasoning. Embracing these modeling practices as “methods” of conceptual change in science requires expanding philosophical notions of scientific reasoning to encompass forms of creative reasoning. I focus on three forms of model-based reasoning demonstrated in my previous work as generative of conceptual change in science: analogical modeling, visual modeling, and thought experimenting. The models are intended as interpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. In the modeling process, various forms of abstraction, such as limiting case, idealization, generalization, generic modeling, are utilized. Evaluation and adaptation take place in light of structural, causal, and/or functional constraint satisfaction. Simulation can be used to produce new states and enable evaluation of behaviors, constraint satisfaction, and other factors.

Conceptual change in science and in science education

There is substantial evidence that traditional instructional methods have not been successful in helping students to ‘restructure’ their commonsense conceptions and learn the conceptual structures of scientific theories. This paper argues that the nature of the changes and the kinds of reasoning required in a major conceptual restructuring of a representation of a domain are fundamentally the same in the discovery and in the learning processes. Understanding conceptual change as it occurs in science and in learning science will require the development of a common cognitive model of conceptual change. The historical construction of an inertial representation of motion is examined and the potential instructional implications of the case are explored.

Distributed Cognition as a Theoretical Framework for Information Visualization

Even though information visualization (InfoVis) research has matured in recent years, it is generally acknowledged that the field still lacks supporting, encompassing theories. In this paper, we argue that the distributed cognition framework can be used to substantiate the theoretical foundation of InfoVis. We highlight fundamental assumptions and theoretical constructs of the distributed cognition approach, based on the cognitive science literature and a real life scenario. We then discuss how the distributed cognition framework can have an impact on the research directions and methodologies we take as InfoVis researchers. Our contributions are as follows. First, we highlight the view that cognition is more an emergent property of interaction than a property of the human mind. Second, we argue that a reductionist approach to study the abstract properties of isolated human minds may not be useful in informing InfoVis design. Finally we propose to make cognition an explicit research agenda, and discuss the implications on how we perform evaluation and theory building.

In the Theoretician's Laboratory: Thought Experimenting as Mental Modeling

Thought experiments have played a prominent role in numerous cases of conceptual change in science. I propose that research in cognitive psychology into the role of mental modeling in narrative comprehension can illuminate how and why thought experiments work. In thought experimenting a scientist constructs and manipulates a mental simulation of the experimental situation. During this process, she makes use of inferencing mechanisms, existing representations, and general world knowledge to make realistic transformations from one possible physical state to the next. The simulation reveals the impossibility of integrating multiple constraints drawn from existing representations and the world and pinpoints the locus of the required conceptual reform.

The Cognitive-Cultural Systems of the Research Laboratory

A central challenge for science studies researchers in developing accounts of knowledge construction in science and engineering is to integrate the cognitive, social, cultural, and material dimensions of practice. Within science studies there is a perceived divide between cognitive practices, on the one hand, and cultural practices, on the other. Any such divide, though at times analytically useful, is artificial. Producing scientific knowledge requires the kind of sophisticated cognition that only rich social, cultural, and material environments can enable. This paper aims to move in the direction of an integrative account of these dimensions of practice. It discusses model-based reasoning practices in biomedical engineering research laboratories construed as ‘evolving cognitive-cultural systems’.

Should physicists preach what they practice

Does one need to think like a scientist to learn science? To what extent can examining the cognitive activities of scientists provide insights for developing effective pedagogical practices? The cognition and instruction literature has focused on providing a model of expert knowledge structures. To answer these questions, what is needed is a model of expert reasoning practices. This analysis is a step in that direction. It focuses on a tacit dimension of the thinking practices of expert physicists, “constructive modeling”. Drawing on studies of historical cases and protocol accounts of expert reasoning in scientific problem solving, it is argued that having expertise in physics requires facility with the practice of “constructive modeling” that includes the ability to reason with models viewed generically. Issues pertaining to why and how this practice of experts might be incorporated into teaching are explored.

Hybrid analogies in conceptual innovation in science

Analogies are ubiquitous in science, both in theory and experiments. Based on an ethnographic study of a research lab in neural engineering, we focus on a case of conceptual innovation where the cross-breeding of two types of analogies led to a breakthrough. In vivo phenomena were recreated in two analogical forms: one, as an in vitro physical model, and the other, as a computational model of the first physical model. The computational model also embodied constraints drawn from the neuroscience and engineering literature. Cross connections and linkages were then made between these two analogical models, over time, to solve problems. We describe how the development of the intermediary, hybrid computational model led to a conceptual innovation, and subsequent engineering innovations. Using this case study, we highlight some of the peculiar features of such hybrid analogies that are now used widely in the sciences and engineering sciences, and the significant questions they raise for current theories of analogy.

Engineering Concepts: The Interplay between Concept Formation and Modeling Practices in Bioengineering Sciences

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.

A computational model of visual analogies in design

We present an analysis of the work of human participants in addressing design problems by analogy. We describe a computer program, called Galatea, that simulates the visual input and output of four experimental participants. Since Galatea is an operational computer program, it makes specific commitments about the visual representations and reasoning it uses for analogical transfer. In particular, Galatea provides a computational model of how human designers might be generating new designs by incremental transfer of the problem-solving procedure used in previous design cases.

A Cognitive-Historical Approach to Meaning in Scientific Theories

The creation of concepts through which to comprehend, structure, and communicate about physical phenomena constitutes much of the scientific enterprise. Concepts play a central role in the construction and testing of the laws and principles of a theory. The introduction of new concepts and/or the alteration of existing ones is a crucial step in most changes of theory. And, in many scientific controversies what is at issue is disagreement over the interpretation of fundamental concepts. In short, articulating concepts is a central aspect of scientific research. Thus, our understanding of science is seriously deficient if we fail to examine the question of how scientific concepts emerge and are subsequently altered. Yet, such examinations have played little role in the philosophy of science. This is especially surprising in view of the fact that problems of conceptual change in science, in the form of the problems of ‘meaning variance’ and ‘incommensurability’, have dominated so much of post-positivistic philosophy of science. Most responses to these problems have centered on discussion of the alleged nature and necessities of language per se; the presumption being that the results of such analysis can simply be transferred to the scientific case. Thus, actual linguistic practices in science, and in particular the processes of concept formation and change, have gone largely unexamined. The result of this neglect has been that philosophical accounts of ‘meaning’ and ‘meaning-change’ for scientific theories and scientific practices concerning meaning continue to be at odds with one another.