research laboratories as evolving distributed cognitive...

Nersessian, N. J., Kurz-Milcke, E., Newstetter, W. C., & Davies, J. (2003). Research laboratories as evolving distributed cognitive systems.In R. Alterman & D. Kirsh (Eds.) Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society.

Research Laboratories as Evolving Distributed Cognitive Systems

Nancy J. Nersessian ([email protected])College of Computing, Program in Cognitive Science, Georgia Institute of Technology

Atlanta, GA 30332-0280 USA

Elke Kurz-Milcke ([email protected])College of Computing, Georgia Institute of Technology


Wendy C. Newstetter ([email protected])Department of Biomedical Engineering, Georgia Institute of Technology


Jim Davies ([email protected])College of Computing, Georgia Institute of Technology


Abstract

We are carrying out a research project aimed at understandingreasoning and representational practices employed in problemsolving in biomedical engineering (BME) laboratories. Theselaboratories are best construed as evolving distributedcognitive systems: the laboratory is not simply a physicalspace, but a problem space, the components of which changeover time; cognition is distributed among people and artifacts;and the cognitive partnerships between the technologicalartifacts and the researchers in the system evolve. Toinvestigate this evolving cognitive system we use bothethnography and cognitive-historical analysis. Understandingpractices in innovative research laboratories requires in-depthobservation of the lab as it presently exists, as well as researchinto the histories of the experimental devices used in it. Weare aiming here for relational accounts (‘biographies’) of thedistributed cognitive systems within the lab as they change intime. In this we find that one cannot divorce research fromlearning in the context of the laboratory, where learninginvolves building relationships with artifacts.

1. IntroductionScience and engineering research laboratories are primelocations for studying the role of environment in cognition.Clearly laboratory practices are located in mico and macrosocial, cultural, and material environments. So too, thesepractices employ cognitive representations and processes indeveloping and using knowledge to solve researchproblems. We are carrying out a research project aimed atunderstanding reasoning and representational practicesemployed in problem solving in biomedical engineering(BME) laboratories. We have begun working in multiplesites, but here report on our research on a specific tissueengineering laboratory, ‘Lab A’, that has as its ultimateobjective the eventual development of artificial bloodvessels. The daily research is directed towards solvingproblems that are smaller pieces of that grand objective. Theproblem solving in these laboratories is best characterized as

situated and distributed. These activities are situated in thatthey lie in localized interactions among humans, and amonghumans and technological artifacts. They are distributed inthat they take place across systems of humans and artifacts.

BME is an interdiscipline in which the melding ofknowledge and practices from more than one discipline is soextensive that significantly new ways of thinking andworking are emerging. Significantly, innovation intechnology and lab practices occurs continually, as doeslearning, development, and change in lab researchers. Thus,we characterize the labs as “evolving distributed cognitivesystems”. Investigating and interpreting these kinds ofsystems requires innovation on the part of cognitive scienceresearchers studying them as well. As an interdisciplinaryteam of researchers, ourselves, we struggle with myriadmethodological and conceptual issues. Two issues we willdiscuss in this paper are (1) to capture the “evolving”dimension of the labs we have developed a “mixed-method”approach, integrating ethnography and cognitive-historicalanalysis and (2) to develop the “distributed cognitivesystem” analysis of the labs we are recasting some usefultraditional interpretive notions employed in cognitivescience, especially as they relate to the customaryinternal/external distinction; in particular, ‘problem space’and ‘mental model’.

2. Integrating Methods to Investigate EvolvingCognitive Systems

In carrying out this case study we have been conductingboth cognitive-historical analyses of the problems, objects,and models employed in the research and ethnographicanalyses of the day-to-day practices in the lab. Cognitive-historical analysis uses the customary range of historicalrecords to recover how the representational, methodological,and reasoning practices have been developed and used bypractitioners in a domain. The practices are examined overtime spans of varying length, ranging from shorter spans


defined by the activity itself to spans of decades or more.Cognitive-historical analysis aims to interpret and explainthe generativity of these practices in light of salientcognitive science investigations and results (Nersessian1992, 1995). Saliency is determined by the nature of thepractices under scrutiny. Cognitive-historical analyses arenot historical narratives. Rather, the objective is to enrichunderstanding of cognition through examining thedevelopment of cognitive practices in science andengineering domains.1 Existing studies have tended to focuson historical individuals, including Faraday, Maxwell, andBell, and on developing explanatory accounts of conceptformation, concept use, and conceptual change (Gooding1990, Gorman & Carlson, 1994, Nersessian 1992, 1999,Tweney 1985). In our study of BME practices thus far, thecognitive-historical analyses are focused on thetechnological artifacts that push BME research activity andare shaped and re-shaped by that activity. These artifactsbecome and remain part of the lab’s history. How themembers of the lab appropriate the history and employ theartifacts in their daily research is subject to ethnographicanalysis.

Ethnographic analysis seeks to uncover the situatedactivities, tools, and interpretive frameworks utilized in anenvironment that support the work and the on-goingmeaning-making of a community. Ethnography of scienceand engineering practices aims to describe and interpret therelations between observed practices and the social, cultural,and material contexts in which they occur. Ethnographicstudies of science and engineering practices abound (See,e.g, Bucciarelli 1994, Latour & Woolgar, 1986, Lynch,1985). However, studies that focus on situated cognitivepractices in these areas are few in number. And, existingobservational (Dunbar 1995) and ethnographic studies (See,e.g., Goodwin 1995, Hall et al., in press, Ochs & Jacoby1997) of cognition lack attention to the historical dimensionthat we find important to our case study.

We find the ‘mixed methodology’ approach essential todeveloping an integrated understanding of the reasoning andrepresentational practices in the cognitive systems of theBME lab. Ethnographic analysis allows us to develop tracesof transient arrangements of the components of thecognitive system, such as evidenced in laboratory routines,the organization of the workspace, the cultural artifacts inuse, and the social organization of the lab at a time, as theseunfold in the daily research activities and ground thoseactivities. Cognitive-historical analysis enables us to followtrajectories of the human and technological components ofthe cognitive system on multiple levels, including theirphysical shaping and re-shaping in response to problems,their changing contributions to the models that aredeveloped in the lab, and the nature of the concepts that areat play in the research activity at any particular time.

1 For a comparison of cognitive-historical analysis to othermethodologies – laboratory studies, observation, computationalmodeling – employed in research on scientific discovery, see Klahr& Simon, 1999.

None of the conceptions of distributed cognition in thecurrent literature account for systems the components ofwhich are evolving in time. In studies of distributedcognition in work environments, for instance the cockpit oron board a ship, the problem solving situations change intime. The problems faced, for example, by the pilot changeas she is in the process of landing the plane or bringing aship into the harbor. However, the nature of the technologyand the knowledge the pilot and crew bring to bear in thoseprocesses is relatively stable. Even though the artifacts havea history within the field, such as Hutchins documents forthe instruments aboard a ship, they do not evolve in the day-to-day problem solving processes on board. Thus, thecognitive system is dynamic but largely synchronic. Thecognitive systems of the BME research laboratory aredynamic and diachronic in that, although there loci ofstability, during problem solving processes they undergodevelopment and change over time. The technology and theresearchers have evolving, relational trajectories that mustbe factored into the understanding of the cognition at anypoint in time. It is the cognitive-historical analysesperformed on these trajectories that we refer to asbiographies. BME researchers, assistants, and students havebiographies that, in part, become a piece of the lab history;as do the multiple and diverse objects that are manipulatedand transformed in the lab. The researchers, for instance,include Post-docs, Ph.D. students, and undergraduates, all ofwhom have learning trajectories. These trajectories, in turn,intersect with the developmental trajectories of thetechnological resources within the lab. In this case, the userof the artifacts also re-designs some of them. In order tobegin research, a new participant must first master therelevant aspects of the biography of an artifact necessary tothe research and then figure ways to alter it to carry out herresearch project as the new research problems demand.

For example, one highly significant artifact in Lab A isthe flow loop, a device that emulates the shear stressesexperienced by cells within blood vessels. A Ph.D. studentwe interviewed discussed how the researcher prior to her

Figure 1: Diagram and photograph of a flow loop

had modified the block to solve some technical problemsassociated with bacterial contamination - a constant problemin this line of research. The flow loop, as inherited by thenew student had previously been used on smooth muscle


cells. The new student was planning to use the flow loop toexperiment with vascular constructs of endothelial cells thatare thicker than the muscle cells, and not flat. To begin thatresearch, she, together with another new student, had to re-engineer the flow loop by changing the width of the flowslit that holds the spacers. Because the vascular constructsare not flat, spacers need to be used between the block andthe glass slides in order to improve the flow pattern aroundthe boundary to bring the in vitro model more in accord withthe in vivo model.

Making sense of the day to day cognitive practices in aBME laboratory and bringing biographies of scientificobjects to life are prime facie separate tasks. We experience,however, that the research process in this distributedcognitive system evolves at a fast pace, which necessitatesgoing back and forth between the two endeavors. Theethnographic study of the development, understanding, anduse of particular devices by various lab members, as well asethnographic interviews have allowed us to conjoin thecognitive-historical study of biographies of lab members,lab objects, and the lab itself with an eye on the perceptionof these entities by the lab members themselves. We areusing the notion 'biography’, in distinction to 'history', toemphasize that at this point we are most interested in thedeveloping relationship between the researchers and theirartifacts. We are aiming here for an account of the livedrelation of the researchers with specific artifacts, rather thanfor an account of the developing knowledge about theseartifacts per se.

Setting 'biography' and 'history' apart in this fashion,however, does not suffice for the relational account ofdistributed cognitive systems that we are attempting toarticulate. In fact, the mixed-method approach that we havebeen utilizing entails the distinction between the twocategories as well as recognition of the need for theirorchestration in the meaning-making processes occurringaround the artifacts in the laboratory. On this account,relating to an artifact entails an appropriation of its history,which chronicles the development of the problem situationincluding what is known about the artifacts in question. In away then biography comes to include history.

3. The BME Lab as an Evolving DistributedCognitive System

3.1. The Lab as Problem SpaceThe laboratory, as we construe it, is not simply a physicalspace existing in the present, but rather a problem space,constrained by the research program of the lab director, thatis reconfiguring itself almost continually as the researchprogram moves along and takes new directions in responseto what occurs both in the lab and in the wider communityof which the research is a part. Researchers and artifactsmove back and forth between the wider community and thephysical space of the lab. Thus the problem space haspermeable boundaries.

For instance, among the most notable and recent artifacts(initiated in 1996) in Lab A are the tubular-shaped, bio-engineered cell-seeded vascular grafts, locally called‘constructs’. These are models of native blood vessels thelab hopes to engineer, eventually, as viable implants for thehuman vascular system. The endothelial cells the lab uses inseeding constructs are obtained by researchers going to adistant medical school and bringing them back into theproblem space of the lab. Occasionally, the constructs orsubstrates of constructs travel with lab members to placesoutside of the lab. For instance, one of the graduate studentstakes substrates of constructs to a laboratory at a nearbymedical school that has the elaborate instrumentation toperform certain kinds of genetic analysis (microarrays). Thisline of research is dependent on resources that are currentlyonly available outside Lab A, here in the literal, spatialsense. The information produced in this locale is broughtback into the problem space of the lab by the researcher.

At any point in time the lab-as-problem-space containsresources for problem solving which comprise people,technology, techniques, knowledge resources (e.g. articles,books, the internet), problems, and relationships. Construedin this way, the notion of ‘problem space’ takes on anexpanded meaning from that customarily employed by thetraditional cognitive science characterization of problemsolving as search through an internally represented problemspace. Most importantly, in our characterization, theproblem space comprises models and artifacts together witha repertoire of activities in which simulative model-basedreasoning assumes a central place (Nersessian 1999).

Following Hutchins (1995), we analyze the cognitiveprocesses implicated in a problem-solving episode asresiding in the cognitive systems comprising both one ormore researcher and the cognitive artifacts involved in theepisode. In line with his analysis, ‘cognitive systems’ areunderstood to be socio-technical in nature and ‘cognitiveartifacts’ are material media possessing the cognitiveproperties of generating, manipulating, or propagatingrepresentations. In contrast to the systems he as studied,though, ours are communities focused on innovation.

Determining the cognitive artifacts within any cognitivesystem involves issues of agency and intention that arepressing questions for cognitive science research, both in thedevelopment of the theoretical foundations of distributedcognition and in relation to a specific case study. To betterunderstand such issues we have been focusing on thetechnology employed in experimentation. During a researchmeeting with the lab members, including the PI, we askedthem to sort the material artifacts in the lab according tocategories of their own devising and rank the importance ofthe various pieces to their research. Their classification isrepresented below (Table 1).

Additional ethnographic observations have led us toformulate working definitions of the categories employedby Lab A’s researchers. ‘Devices’ are engineered facsimiles


that serve as in vitro models and sites of simulation.2

‘Instruments’ generate measured output in visual,quantitative, or graphical form. ‘Equipment’ assists withmanual or mental labor. Much to the surprise of the PI, the

Table 1: Sorting of lab artifacts by the lab members

newer Ph.D. students initially wanted to rank some of theequipment, such as the pipette, as the most important totheir research; whereas for him the devices the lab engineersfor simulation purposes are the most important.

The cognitive artifacts in the distributed systems in thelab cut across these distinctions, though most are devices orinstruments. Analysis of the ethnographic data has focusedour attention on the devices, all of which we classify ascognitive artifacts. Devices serve as sites of experimentationwith cells and constructs under conditions simulating thosefound in the vascular systems of organisms. It is in relationto the researcher(s)’s intent of performing a simulation withthe device in order to create new situations that parallelpotential real-world situations, and the activity of the devicein so doing, that qualify a device as a cognitive artifactwithin the system that employs it. For example, as a device,the flow loop represents blood flow in the artery. In theprocess of simulating, it manipulates constructs which arerepresentations of blood vessel walls. After beingmanipulated, the constructs are then removed and examinedwith the aid of instruments, such as the confocalmicroscope, which generates images for many colorchannels, at multiple locations, magnifications, and gains.Thus, the manipulated representation of the flow loop ispropagated within the cognitive system.

2 We are using the term ‘device’ because this is how theresearchers in the lab categorized the in vitro simulationtechnology. This notion differs from the notion of “inscriptiondevices” that Latour & Woolgar (1987, p. 51) introduced and thathas been discussed widely in the science studies literature. Thelatter are devices for literally creating figures or diagrams ofphenomena. The former are sites of in vitro simulation, and furtherprocessing with instruments is necessary to transform theinformation provided by these devices into visual representationsor quantitative measures.

3.2 Distributed Mental Modeling3

An in vivo/in vitro division is a significant component of thecognitive framework guiding practice in Lab A. Because thetest bed environment for developing artificial blood vesselscannot be the human body in which they will ultimately beimplanted, the BME researchers have to design facsimiles ofthe in vivo environment where the experiments can occur.These devices provide locally constructed sites ofexperimentation where in vitro models are used to screenand control specific aspects of the in vivo phenomena theywant to examine. The researchers in the lab call the processof constructing and manipulating these in vitro sites “puttinga thought into the bench top and seeing whether it works ornot.” These instantiated “thoughts” allow researchers toperform controlled simulations of an in vivo context, forexample, of the local forces at work in the artery. The“bench top”, as one researcher explained, is not the flat tablesurface but comprises all the locales where experimentationtakes place.

Devices perform as models instantiating currentunderstanding of properties and behaviors of biologicalsystems. For example, the flow loop is constructed so thatthe behavior of the fluid is such as to create the kinds ofmechanical stresses in the vascular system. But devices aresystems themselves, possessing engineering constraints thatoften require simplification and idealization in instantiatingthe biological system they are modeling. For example, thebioreactor, as used in Lab A, was designed for “mimickingthe wall motions of the natural artery.” It is used to exposethe constructs to mechanical loads in order to improve theiroverall mechanical properties. The researchers call thisprocess “mechanical conditioning” or as one researcher putit “exercising the cells.” Preferably, this is done at an earlystage of the formation of the construct, shortly after seedingthe cells onto a prepared tubular silicon sleeve. In vivo,arterial wall motion is conditioned upon pulsatile bloodflow. With the bioreactor, though, which consists of arectangular reservoir containing a fluid medium (blood-mimicking fluid) in which the tubular constructs areimmersed and connected to inlet and outlet ports off thewalls of the reservoir, “fluid doesn’t actually move,” as one

Figure 2: Photograph of a bioreactor

3 Of course, we use the term ‘mental’ metaphorically here, as arhetorical move to connect our discussion with aspects of thetraditional notion of mental modeling and extend the notion for usein the distributed cognition framework.

ONTOLOGY OF ARTIFACTS

DEVICES INSTRUMENTS EQUIPMENT

flow loop confocal pipettebioreactor flow cytometer flaskbi-axial strain coulter counter refrigeratorconstruct “beauty and beast” sterile hood mechanical tester water bath

LM5 (program) camera

computer


lab member put it, “which is somewhat different from theactual, uh, you know, real life situation that flows.” Thebioreactor is a functional model of pulsatile blood flow.The sleeves are inflated with pressurized culture medium,under pneumatic control (produced by an air pump). Themedium functions as an incompressible fluid, similar toblood. By pressurizing the medium within the sleeves, thediameter of the silicon sleeve is changed, producing strainon the cells, similar to that experienced in vivo.

Many instances of model-based reasoning in science andengineering employ ‘external’ representations that areconstructed during the reasoning process, such as diagrams,sketches, and physical models. These can be viewed asproviding constraints and affordances essential to problemsolving that augment those available in whatever ‘internal’representations are used by the reasoner during the process.A device is a kind of physical model employed in theproblem solving in Lab A. Within the cognitive systems inthe lab, devices instantiate part of the current model of thephenomena and allow simulation and manipulation. Theintent of the simulation is to create new situations in vitrothat parallel potential in vivo situations.

In previous research Nersessian (2002) characterized thereasoning involved in simulative model-based reasoning asa form of dynamic mental modeling employing iconicrepresentations. That analysis used the traditional notion ofmental modeling as an internal thought process. Here weexpand the notion of simulation of a mental model tocomprise both what are customarily held to be the internalthought processes of the human agent and the processing ofthe external device. Simulative model-based reasoninginvolves a process of co-constructing the ‘internal’researcher models of the phenomena and of the device andthe ‘external’ model that is the device, each incomplete.Understood in this way, simulating the mental model wouldconsist of processing information both in memory and in theenvironment (See Greeno 1989 for a similar view). That is,the mental modeling process is distributed in the cognitivesystem.

3.3 Evolving Cognitive PartnershipsDevices, such as the construct, the flow loop, and thebioreactor are constructed and modified in the course ofresearch with respect to problems encountered and changesin understanding. These devices have a history within theresearch of the lab. For example, the flow loop was firstcreated in this particular lab to simulate “known fluidmechanically imposed wall sheer stress,” in other words toperform as a model of hemodynamics. We have tracedaspects of its development since 1985. The constructs werefirst devised in 1996 as an important step in the overallobjective of creating implantable vascular substitutes. Theyafford experimentation not only on cells, but on structuresmore closely related to the in vivo model. The bioreactor,though having a longer and more varied history outside thelab, first made its appearance in this lab in conjunction with

the tubular constructs and was not used anywhere before forthat purpose.

Newcomers to the lab, who are seeking to find their placein the evolving system, initially encounter these devices asmaterially circumscribed objects. As they begin to interactwith these devices, the newcomers, almost as a rule,experience them as fraught with intricacies that withstandtheir easy handling: Tubes leak, sutures don’t keep,reservoirs overflow, pumps malfunction, the availablespacers don’t fit, and, as if this were not enough, cells “gobad.” On the other hand, newcomers find themselves in anenvironment in which everybody else, including the mostexperienced old-timer, is constantly struggling to get thingsto work—a serious fact about laboratory life (not alwayshandled with dead seriousness in this environment).

Growing cognitive membership in the lab involves agradual process of coming to understand these objects asdevices - as objects with evolving trajectories, constructedand employed to respond to problems, to help answerquestions, and to generate new ones. Thus, we find that onecannot divorce research from learning in the context of thelaboratory, and learning involves building relationships withartifacts. We characterize the relationships between thetechnological artifacts in the cognitive system and theresearchers as cognitive partnerships. Over timeunderstandings are constructed, revised, enhanced, andtransformed through partnerships with the artifacts in thecommunity. As relationships change, so too do knowledgeand participation. It is because these lived relationships playout in time that we have dubbed our analyses of them‘biographies’.

Learning is central in the partnering process. One newundergraduate research scholar from mechanicalengineering, who was about to use the mechanical tester – adevice used to test the strength of the constructs –responded:

A2: ….I know that we are pulling little slices of the construct –they are round, we are just pulling them. It’s the machine that isright there before the computer in the lab. The one that has thebig “DO NOT TOUCH” on it.I: Is it the axial strain (mechanical tester)?A2: I know it has a hook in it and pulls

That the novice researcher describes the mechanical tester atthis point in time as nothing more than parts suggests thatshe has yet to partner with the device. In contrast, a seniorPh.D. researcher, at that point in time considered the“resident expert” on the bioreactor, was able easily todiscuss the artifact and some of its history:

I: Do you sometimes go back and make modifications? Doesthat mean you have some generations of this?A 12: Uh yes I do. The first generation and the secondgeneration or an offshoot I guess of the first generation. Wellthe first one I made was to do mechanical loading and perfusion.And then we realized that perfusion was a much more intricateproblem than we had - or interesting thing to look at - than wehad guessed. And so we decided okay we will make abioreactor that just does perfusion on a smaller scale, doesn’ttake up much space, can be used more easily, can have a largernumber of replicates, and so I came up with this idea.


He continued by pulling down previous versions ofbioreactor (made by earlier researchers as well) andexplaining the modifications and problems for which designchanges were made. His account suggests a developedpartnership.

The cognitive partnerships transform both researcher andartifact. A researcher who some months earlier was anewcomer and who saw the artifacts as just many kinds ofmachines and objects piled on shelves and on the bench top,now can see a device as an in vitro site for “putting athought [his thought] into the bench top and seeing whetherit works or not.” During the problem-solving processesinvolved in instantiating a thought and seeing if it works,devices are re-engineered as exemplified with the flow loopin Section 2. And, potential device transformations can beenvisioned, as with one undergraduate research scholar weinterviewed about the bioreactor:

A16: ..I wish we could accomplish - would be to actually suturethe actual construct in there somehow. To find a way not to usethe silicon sleeve….That would really be neat. Um, simplybecause the silicon sleeves add the next level of doubt. They’re– they are a variable thing that we use, they’re not always 100%consistent. Um the construct itself is not actually seeing thepressure that the sleeve does. And because of that you know, itdoesn’t actually see a – a pressure. It feels the distention but itdoesn’t really feel the pressure. It doesn’t have to withstand thepressure. That’s the whole idea of the sleeve. And so, um, Ithink that it would provide a little bit more realism to it. And uh,because that also, a surgeon would actually want to suture theconstruct into a patient. And um, because of that you’re alsomimicking the patient as well - if you actually have the constructin the path. I think another thing is to actually have the flowbecause um, so this flow wouldn’t be important with just thesleeve in there. But if you had the construct in contact with the –with the liquid that’s on the inside, you could actually start toflow media through there.

In this case an undergraduate student has been transformedover the course of several semesters to a BME researcher,contributing to immediate research goals; who transformsartifacts in his immediate research; who understands theoutstanding problems and objectives; and who can envisionhow a device might change from a functional model to amodel more closely paralleling the in vivo situation to pushthe research along. At this point in evolution, thinking istaking place through the cognitive partnering of theresearcher and device. The partnership provides the meansfor generating, manipulating, and propagating representa-tions within the distributed cognitive systems of thisresearch laboratory.

4. ConclusionsA relational account of distributed cognitive systemscharacterizes cognition in terms of the lived relationshipsbetween the “players” in these systems, people and artifacts.In the research laboratories that we have been studying,these relationships evolve in significant ways for theindividual lab members and for the community as a whole.In their established form, relationships with artifacts entail

cognitive partnerships that live in interlocking modelsperforming internally, as well as externally.

AcknowledgmentsWe thank Kareen Malone and Eteinne Pelaprat for theircontributions to the research on this project. We thank ourresearch subjects for allowing us into their work environment andgranting us numerous interviews. We gratefully acknowledge thesupport of the National Science Foundation ROLE GrantREC0106773.

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