How Do Engineering Scientists Think? Model‐Based Simulation in Biomedical Engineering Research Laboratories

Abstract

Designing, building, and experimenting with physical simulation models are central problemsolving 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.

An engineering paradigm in the biomedical sciences: Knowledge as epistemic tool

“…Nersessian (2009), for instance, counts designing, building, and experimenting with physical simulation models as typical of engineering approaches. Additionally, philosophers have studied these practices, and indicated typical engineering strategies of using combinations of methods that mutually support each other in investigating and modelling complex systems.…”

“…Technological production and manipulation of (artificial) biological phenomena and functions by means of interlocking modelling techniques (using experimental, theoretical, mathematical and computer models, e.g. Nersessian 2009). …”

“…Instead of scientific knowledge firstly being a representation of how the world is independent of humans, they propose to characterize knowledge as epistemic tools (Nersessian 2009, Boon and Knuuttila 2009, Feest 2010, Knuuttila and Boon 2011, Boon 2012a, Green 2013. 3 Here, it is suggested that 'knowledge as representation' (in a correspondence sense) is deeply embedded in the physics paradigm whereas 'knowledge as epistemic tool' is central to the engineering paradigm.…”

“…Nersessian (2009), for instance, has used detailed history of science studies to argue that novel scientific concepts arise from attempts to solve specific problems, where scientists utilize conceptual ideas (such as analogies), and analytical and material resources. Feest (2010), Chang (2004 and Boon (2012a) add that in many cases the initial conceptual content of a scientific concept is determined by the 'paradigmatic experiment' in which its purported phenomenon manifests and is investigated.…”

Constructive Research and Info-computational Knowledge Generation

“…They are representations and thus play a role in model-based reasoning and problem-solving; they are central artifacts around which social practices form; they are sites of learning; they connect one generation of researchers to another; they perform as cultural ratchets (..) in an epistemic community (..), enabling researchers to build upon the results of the previous generations, and thus move the problem solving forward. Nercessian [8] In a similar way as physical reality presents fundamental constraints for knowledge construction, a community of practice (epistemic community) puts additional constraints through the process of interaction. Indeed, scientific work is in many ways defined by the interactions between members of a research community, but its role is often misunderstood by postmodern critics.…”