Abstract
Designing, building, and experimenting with physical simulation models are central problem-solving practices in the engineering sciences. Model-based simulation is an epistemic activity that includes exploration, generation and testing of hypotheses, explanation, and inference. This paper argues that to interpret and understand how these simulation models function in creating knowledge and technologies requires construing problem solving as accomplished by a researcher-artifact system. It draws on and further develops the framework of "distributed cognition" to interpret data collected in ethnographic and cognitive-historical studies of two biomedical engineering research laboratories, and articulates the notion of distributed model-based cognition to answer the question posed in the title.
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