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Unformatted text preview: TEIF. JUURNJ‘LI . t r|-' | HI-. LEARNENE‘. St Tl-INt'I-H. mm. .I-II'I FIJI Clilflj'l'iylil 31 .‘IIJT. Lawmnt‘e lirlbaum rum-claws. III-t' Fish Swim, Rocks Sit, and Lungs Breathe: Expert—Novice Understanding of Complex Systems Cindy E. l-ltnetu—Silver, Sarahhi Marathe, anti Lei Liu Department tn" Ethtt‘urr'tmm' Psyehrii'om' Rutgers Unirersify Undcrxlauding cumplex antenna is fuluhtmenral tn understanding suit-nee. The mnplesity ni' such system makes them very tliifit'ull. In undetslarld because they are CDmFH‘IfiIBd nI' multiple interrelated leveha that interact in dynamic ways. The gaa! al' this study was to understand lam experts and ntwiees diiTem-d in liteir understanding al' aw eemptes systems. Ihe liamaa tespiralnry system and an aquarium eeusystem. In panieular. we examined hem a remesentatitut nl'emnp1ex systems. Simt-Iure—Behaviar—thelitm Ihent'y {SBFL ming aeenunl In: these diI— Features. SBF is liatlicuiarly retevflllt in uIthm-‘lnnding ilittittgical systems because an illlptu1a|1l dtittluin principle is IJ1I: telulitu! between rum]. funL'linn. .'|I1tl mecha- niNIEIEL Our testllls demunermetl that there were minimal differences |1e1ween 1ht: expert and "twice gnmps HI'I slmttutes. but that Ii1e Incas "F the tlifl'etence was on understanding causal hehavinrs and Functitilts. Ihe leasl salien1 elements nf [11c sys~ tents. Meatal mtuiel analysis provided largely eulwcrgem; restarts. We altar i'nund difl'etences Mtween the END tl'tlfercnl kinds af espens in each tltamtin. These re- salts suggest lJ'ut1 SBF dues capture espen- nmiee Jiffeaeuees and nut}- lttn-e impli- mliuns fur inslnleliun. This research was funded by Nalitmal Science Fitmndaliun CAREER Lintrtt LlIIJthJ-i It: Cindy E. HrneJn-Eils'et. [‘unelusiuns nr remrnnaendntiuns expressed in this material nu- ma nwn antldn nnl nee- essarily teflet'l 1hr.- views ui'1hc Naliunal Suit-me iiuuntlaliun. 1M: lhank Vent Tacharlsky fnr her assis- lam‘e wuh mulling Iltt: than and Relwct'il Janina rm unwiLling feullmck nu an enriiet draft. We thank i-‘aul Feltm-it-II and Wm illlmlerII-um mkiewurx I'nrlllclr lepilll Eaetllmck. F'leitnlxnflhis test'lueh haw: been lu'esemetl al. Hie :II‘IIILIaI Ineeling 11" IIIt‘: Eumpual't Assmiation [m R¢§¢ilflih tln Lemming and In- stmetimt tum}. the annual mat-eutim nd'the Amerieau stehrdagieal Asstmialiun [RM-IL and Inn-r. Italinnal Cnnfet'enue nl'tlie Learning Sciences {ZEN}. Currenpmulenee shnuld be addressed In {‘iruly F.. Hmeln-Silt-‘er. Rutgers University. I11 Seminal;- Place. New Brunswick. NJ HEWJ-l HS}. lid-mail: t'l'intelvttlii?l rci.rutgers.edu SUE! amt-i i: sit .'le|t. startartue. |.l't| t.‘nntplex systems are a fundamental aspect of many different scientific domains. This is especially trtie of the biological sciences. For example. the processes that take place within an organism {physiology}. the interaction between organism and environment [environmental biology}. and interactions among different organisms witltitt and acre-a.- species {ecology} are all best described itt terms of complex sys- tems. t'jomplcx systems an: clnn-ntrterised by multilevel organisation. interconnec- tions. heterogeneous colttptme nts. and invisible dynamic processes {Ferrari o'e {'iiti. I993; Hlnclt‘I-SllvflT at; neevcdo. Elmo; IIr'r'ilcnsky d: Resnick. Hill‘s). The relation- ships across tlitt‘crent levels of such systems are not intuitively obvious {Duncan Er Raiser. ztlttfi], These characteristics present cognitive barriers tltat tnake complex systems difficult In tmderstand [Feltovicih {Toltlsom ti Spiro. 200”. For cxalttple. in learning ahout ecological systems. one tteeds to ettvision how gent-s. individuals. populations. and ctnntnunilies intel'relate. In an aquarium eeo- system. tltc altilttals provide carbon dioxide needed by the plums for photosynthe- sis. and the ptants provide oxygen needed by Iislt to utilise energy. In human biol- ogy. phenomena occur at the anatomical. biochemical. and physiological levels. For example. respiration occurs at a cellular level as well as at the organ system level. There are intricate relationships among tltc structtlrcs {the parts of a system i. the behaviors tthe “how“ or mechanisms of a system}. and the functions {the “why” of a systch. These. levels are interdependent. A distttrbance at one level or component of the system can easily atTect others. When cells need oxygen. not only does a person breathe more deeply than usual. but also the heart may heat faster to deliver more oxygcrt to the tissues. Moreover. roost biological systems need to remain at a dynamic equilibrium. This is possible only through tlte use of self-correcting feedback Icmps. The interactions among different levels are dy— namic as the system constantly rccalihrates itself to remain at equilibrium. This makes the interactions between components of tire system difiieult to understand. Because complex systems are important in pottplc's intefiwtietts with the world. understanding these systetns is an important part of being scie ntiiically literatecit- irens {Sahelli Edtlo}. Many different conceptual representatives Itan be used to understand complex systems. Cine prineiple that cuts across many systems is emergence. In an emer— gent system. tlte outcomes are not predetermined. The behavior of the system arises as a function of spatial and tentporal interactions between its components. Any change in the components can result in nonintuitivc changes in tlte way the system functions. Matty biological systems like ecosystems have multiple. nested. and interacting levels and are emergent in nature. Moreover. understanding the mechanisms [i.e.. behaviors} that relate structure to function is a fundamental as- pect ul‘ explanation in biological systems {Bechtel t’i‘t Abrahamson. Ztlt'lfi]. Struc- ture and function in biological systems are causally related through behavioral mechanisms. The structures can be microscopic {like cells} or macroscopic {like organs}. These different levels of structures and their behaviors also interact with L'UMPIJEK svs‘t‘trnts 309 one another. fits a resultI ettrltplnx biological syslnrlts are composed of itttcn'elntml structural. behavioral. and functional Icvcls. Given this. structure-beltavior lune-- tiott {Fill-IF} theory provides a representation tltat can account for how pcople think about etattplex syslettts {Gocl cl al.. Ili‘Jol. The Sfl-Frepreseatatiun allows one to reason effectively about the functional and causal roles executed by the structures in a syslnrtt lit-.rrattse this I‘cllt'flfifirllflllflll accounts for a syslortt's parts. their purpose in the systent. and the mechanisms that enable their functions. In this article. we examine how well this representation accounts for expert—novice diflintences across two complex biological systems: the iiurltatt respiratory systetn and an aquarium ecosystem. We tltelt consider the implications of otlr results l't tr design- ing instruction. Consistent with other research on expertise. novice understanding nt'comples systclns focuses on visible structures tCieIlerl. lilo}. Hmelo. Holttat. Rt Kolotlncr. Etltl-tj: l'vlintaes. 'I'Iowhridge. Arnaurlin. lit Wandersee. l‘J'Ell ; Worst-Robinson. t995]. Mtllticomponent phenomena that are invisible. dynamic. and interdepen- dent are particularly difficult to understand {Feltoviclt et al.. EtJtit: l-‘elttwich. Coulson. Spiro. Sc Dawson-Saunders. Iii‘lfl}. One reason for this is excessive working tttentory demand. One ntust tirst process all of the simultanetms events and interactions. This requires mental simulation and rule-based inl'erenecs to cott- struct a complete mental model {Gracssen [999: Narayanan 3c l-lcgarty. 151%]. Also. making connections among ditfet'ent levels ofa cotnplex system increases the working memory load. This is especially true because tnany systems are epito- mized by indirect and complex causality {Perkins 3t Grotxcr. Elltltll. Finally. com- plex systerns may have emergent properties tltat are not completely predictable from the behavior ofindividual parts {Wiiensky d: Resniek. lililil'i. Prior experience often impedes learners' understanding of complex systems {Feltovieit. Spiro. dc Coul‘ton. [939}. For example. based on their experiences. most people prefer explanations that assulnc central control and single catlsality {Rcsnick s 1I"t"ilenslty. Iliilill. In an expert—novice comparison. Jacobson tZElUI} interviewed undergraduate students and complex systems experts attd indeed found that students t'avtaerl simple causality, central control. and predictahility. Expert explanations showed decentralized thinking. multiple causes. and the use ot‘stocltastic and equilibration processes. This kittd of novice reasoning is robust across a range of research. A review by Perkins and Groteer {Ziltlll'l demon— strated that when reasoning about a range of contplcx systems. students tend to- ward very simple causal explanntions. When students reason about effects. they miss the connectedness within tltc system and the eolttplcx causal rclatioltships. displaying a reductive bias {Feltoyiclt et al.. lli'blil—llie tendency to erroneously reduce the complexity of a phenomenon. One possible explanation for this is that learners tend to focus on the structure of systems ratlter tltan on the underly— ing function. 1ti'v'hen Chi, DeLecuw. IC‘hiu. anti La‘v'anchcr “994) risked students to read a passage ahout tlte circulatory system. they found that most of the func- 31f] Elltllil.tt-.‘il|.l-"iil<.MnRr‘tlttli.t.:|l! titntal aspects of the circulatory system were implicit attd difficult for students to infer. Tltere ntay he addititntal cognitive ban'iers for novices in understanding com- plex systems. Ctti {Ell-Iii] provided another perspective on why people fail to un- derstand cenain types of pr: messes. According to lChi {2W5}. causal structures on- tlerlying processes can be divided into different ontological categories. Processes can be direct or tunergent. in a direct process. the cause and effect are obvious and follow each other unambiguously. However. emergent processes ale otttologicaliy distinct. insofar as the cause—effect relationship is not obvittus. Novices fail to cor- rectly recognise the ontological category to which a process belongs. 'l'liey emitte- ously apply their schema for understanding a direct process while trying to make sense of emergent processes. This results in incorrect conceptions and partial un- derstanding of' the process. Understanding emergent phenomena requires one to recognise that a system can have mttltiple causal factors tilat occur at l'lotJt micro- and macmlevels. 'l'he nriemier-ef refers to the level of individual elements of a sys- tem. whereas ntrrcm refers to tile aggregate level. For exaIupIE. at the macroleve]. diffusion can appear to he an orderly flow of gas. However. at the El'tlti'l'ttlE‘t't-‘El, there is random movement of indivitlual ntoleculcs tChi. 2000]. Students have dilliculty connecting phenomena across levels tPenner. fltlftl ,1. Making of complex systents requires a representation of concepts and principles that eon-espond to key phenomena and the relationships acmss different levels of a system. whether it is micro to macro. or structure to behavior to fIJItc' tion. This is hard because it requires abstract thinking and often conflicts with ex— isting conceptions fFEllt‘WlCl'l ct al.. lass}. Misconceptions at one level can affect onc‘s understanding at other levels {Folto‘r'icb ct Eli-1 ml.” i- DEEF" PRINCIPLES FOR UNDERSTANDING CUM FLEX SYSTEMS Despite the challenging nature of complex systems. there are deep principles that explain behavior in such systems. account for the relationships across levels. and may support understanding. Deep principles are the core ideas that underlie a given domain tl-Iranst'ord. Brown. a; Cooking, Ellflth. Emergence is one example of a deep principle for understanding complex systems; the principle that form fol- lows function is another. lGoldstone and Sakantoto (2003} provided a nuntber of other exatnplcs as tltey showed that people can transfer complex systems princi- ples across domain s. Thus. an important question is how some ofthese deep prin- ciples map onto people‘s existing understanding and whether they can he spring- boards for future learning. There are several altemative ways of making sense of such systems [Collins 3t Ferguson. lililii). Complex systems can be viewed from t'ostrltcx Hrs-riots 311 the perspective of aggregate or emergent behavior. a systems dynautics motlcl. or an SBF analysis. The tendency of learners to focus on observable structures attd simple explanations suggests that the SH f" representation may provide a deep prin- ciple that is useful for thinking and learning about L‘olttples systems. REF theory describes a complex system‘s rnnltiple interrelated levels and its dyltatrtic nature. This representation was developed in artificial intelligence to support reasoning shout designed systems such as electrical circuits and heat es Changers tl'iocl cl Ell.. 1996-. Weld. 1933] but only recently has been applied to natural systems {i llllelo et al.. Qtltlt'l: Hntelo-Silver 3t Pfefler. EUEHJ. Although the emergent processes vienr tChi. Elliifii provides insight into onto- ltigieally different categories ol'oausal structures. it does rtot explicitly address the functional and structural aspects ofthe system performing the powess. S Ill: Ilteol'y provides conceptual representation that considers the ttaturc oftbe processes. why these processes occur. and what structures are involved in performing the process. For example. although the circulatory system has been characterised by direct pro- cesses. the system itselfean he described as complex because tlte direct processes act at different levels and interact with olte nttother. This classification of the siren- latory system as a direct process. is flawed and ntost liker occurs because the be havior of the system as a whole is predictable and. as sttch. does not seetlt either emergent or complex_ However. this overall predictable behavior ofa complex sys- tem can he explained by what Strcvens (RUDE—Ii called strum pmlmfu'fr'tt' analyst's. Eaton refers to parts of a system. These parts interact strongly but function rela- tively independently. In certain ltinds of Complex systems. the hcl'lavior of each part follows a lnohahility distribution. Therefore. individuals can utilize predictions about how and in what way these parts will interact with one another. According to Stievens. this “probability analysis provides an understanding of macrolcvel dy- namics in terms of a probabilistieally characterized microievel dynamics“ to. 535.1. SElF AS A CUNCEFTUhL HEPRESENTATEDN Understanding the causal relations hetweett form and function is very important for deep conceptual understanding of biological phenomena. The Slit" representaa tion describes form fi.o.. structures] and function. as well as explains how they are causally related through actions ti.e.. behaviors}. Moreover. because biological systems are composed of multiple nestetl subsystems. the SBF represent atinn also catt provide a means to tease ottt how different levels of structures. bebaviorfi. and functions intemot with one another and how the aggregate working ol' the system emerges as a result of it. SBF is a fruitful representation because it focuses on causal understandings of the relationships among dill'erent aspects of the system. 'litis is consistent with research on expertise that has demonstrated that experts in domains such as physics. medicine. and history organize their knowledge around 312 Its-Hits]slls-‘lili.l-tnttn'lllliJjII deep tlotnaitt principles tE.'lti. Feltovit'h. iii-t Glaser. liiiil'. [.arltin. iv'ieDenuott. Si- tnon. 3t: Simon. t‘Jt-tti'. Norman. 't'i'ott. Brooks. & Smith. “394: 1ii'r'iuelsorg. IQ'JIJ. Storefront re fer to elerlteltts ol'a system te.g.. filters and air pumps are elements of aquarium ecosystems}. Hiologieat systeuts are very tliverse in nature. therefore structures can vary itt sine and organisation. Structures cart be visible and tIt-‘tero- seopie. stleh as lungs or Iish. They can also he microscopic. like red blootl cells or bacteria. They can also he Iticraufltically organith like in the respiratory system where tlte cells Ittalte up the tissttcs. which in turn ntalte up the systeltt. However. in a dim: rent it lrltl ol' systeirt te.g.. ecosystems]. these may he seruiautmtomoos but in- teracting parts of tire systent. such as fish and bactena. .fi‘e'frrrtv'rna' refer to mechanisms of how the structures of a systent achieve their outcome or function. Both the macroscopic and microscopic structures have cer- tain heltaviors associated with them. Behaviors can also he nested {the behavior of an organ is. ill part. tlte result of the various types of [issues it is mat-mam of}. or they can he interacting [the behaviors of different genes interact to give rise to overall. visible behavior of tire organismi. II: We rospirattu‘y system. the he|tavior of the ribs. namely ntoving outward. results iii an expansion of the volume of the chest. causing a decrease in pressure. Air flows into the lungs from the higher pres sure in the atnhient air to the lower pressure in the lungs. Here the movetnent of tlte ribs is the system behavior. and the underlying reason for this behavior {to allow inhalation} is the function. Finally. Jame-tinny.- refer to the role of an element in a system te.g.. the alveoli are where gas exchange occurs}. Many diflerent structttres at various levels oforgani- nation can behave in an interacting manner to fulfill the function. For example. central to understanding the respiratory system is knowing tltat a main function is to supply oxygen to provide energy and that the behaviors. such as cellular pro— cesses. eriahle that function. lls structures. such as the lungs. perform these behav- iors. Indeed. different organisttts havedil'l'erettt structures that esltihit fl 'r'flt'lfiiii' ni- behavinrs to fullill identical functions. in earlier research. Hmelo et al. {2000} showed that the SBFrept-esentation was a useful frameon it for examining how childrett understand the respiratory system. The authors accomplished this iii the contest ofhaving middle school students de- sign artificial lungs. The design activities stressed the function of lungs. Students had to achieve at least a partial functional understandittg ofthe respiratory system in order to design a working lung model. Also. the mode! did not have to be struc— turain identical to actna] tongs. This allowed students to focus on why lungs are needed and bow lungs worlt as opposed to what lungs look like. The design activi- ties. with an emphasis on fttnetion. heiped students construct an improved fune- tiottal understanding ofthe respiratory sy stent and become more likely To consider behaviors] mechanisms. Ilowever. their understanding of behaviors was as likely to he incorrect as correct. This occurred because the SEF representation was not made cpriCil. and there was no opportunity for the students to test their models t‘thiPILt-tsvslrsts 313 antl obtain I'eetllstclt. We extend this work by csarniiting how well the REF repre- sentation captures the differences hetween expert anti novice understanding of truth the aquarium and the human respinunry systems attd therefore captures a deep principle that may transfer across different systems {Goldslnne 3s Hakaluoto. Ettttfii. We have previously reported dilfcrenees in expert novice understanding of aquarium ecosystems ttlmelo-Silvcr 3t Pt'effer. Zttttsl}. 'fhal article used a small suhset of the data from the current stlltly. The results of ottr preliminary worlt {littlelo-Hilvet' is I'TEffEI'. HRH] slto‘n'etl that experts and |'tI'_1‘.'it'.'t;.|i dil'l'ei- witit respect to their knowledge organization of a single coirtples system. The SBF knowledge representation is a fruitqu way of de- lineating these ditl'erences. in order to promote a better understanding of ex- pert—novice differences in a complex system. this article reports results froln an in- creased sample. sire with additional analyses ofparticipanls' mental models. We also wanted to determine if the ditiierences reported in Hntelo-Silver and Pl'el'l'er were characteristic of the aquarium domain or whether they Could he generalized to other complex system s. In order to study the generaliaabitity ofSEi-li rein-eseina— tion. we conducted additional ex pert—novice comparisons iii the dtnnain of the hu- man respiratory systein. Accordingly. this aniele reports results float an additional complex system and extends the results manned on the aquarium system by Hmelo~Silver and Pl'etl'er. METHOD Participants For the atiuariunt system interviews. the participants were 21] seventh-grade stu- dents from a suburban public middle school. 26 preservice teachers from a large puh]ic university. and If] experts. The experts Itatl heen involved in aquatic systems either professionally or recreationaiiy for ID to 3!} years. The former group t“the biu]ogists“] included 5 established academic researchers who held advanced tie- grccs in biology. The latter group t“thc hobtiyists"] consisted of S ittdiviti uals wlto hart maintained nu merous aquariums for more than it] years and mate active melo- bcrs of a local aquarium society. Only | piratieipant in eaeh of the middle school student and prescrvicc teacher groups reporteti having alt atttnlrinm at hottte. and 3 from each group reported that they had studied about aquariums. For the human respiratory system interviews. the participants were 2 t middle school children from a suburban public middle SCI'Iool. 2ft orcst'Tvicc teachers from a large public university. and |'.i experts. The experts included ti tespiratory thera- pists and 5 pulmonary physicians. For both systems. tlte prescrviee teachers re- ceived course credit for participating in the study. and the experts were paid for their participation. 314 unit-tostrvr-rt.Matt-vt'irrLrJiI Mthough we did not collect data about the preservice teachers‘ majors for tltis research. the aggregate statistics for teachers graduating dtrring that titrte period. attd our data from other studies using tlte educational psychology subject pttttl. are Fairly consistent. These data show Iliai only 5% to ltl'ii- of prescrvicc leaclters had becrt planning to be science teachers tineluding pltysieal attd biological sciencesi. The nest of tire pr'eservit-e teachers had planned on being either elerturntary school teachers or teachers irt other secondary seltooi subject areas. The teachers rtot seek- irtg sciertce certification needed only two science courses to graduate. and these could be irt arty scientific dotttairr tbiulogy. physics. chemistry. geology. astron- ortty. etc}. Procedure Wecorrdttcted ittdividual interviews that ranged front Zitto tit‘i min. All interviews were tape-recorded and transcribed. For the squadron systetrr. the interviewer pre— sealer! participants witlt a piece of [JE||'|L'I' tltat httd a three-sided reclangularsltape irepresenting an aquarium t. as described irt l-imeln-Silver and i‘feffer {HIM}. For Ihc litlliitltt respin’rtory systelrt. participants were provided with a piece of paper with art otrtiitte of a lrtrttran body. The participants were provided with colored Ittarlters and were asked. while thinking aloud. to dnrw a picture of"any1hing you think is itt art anttariurtt” or “the pttrts of your body involved in breathing." If needed. the interviewer asked the participants for funher clarifications of their drawings. I{since participants had cor'rrplctetl their drawings. the interviewer began askirtg questions. 'I'he interviews included opeIi—etltied questions and problems to eiicit partici- pants‘ knowledge about either the aquarium or respiratory system. Some questions asked about a system's structure {e.g.. 1titfhat is in a fish tattk‘t. 1It‘t'hat ntakcs up the respiratory sysiern'E'}. other questions elicited functiottal knowledge fe.g.. What do fisi't do itt art aquariunt'i. 1titi'hat do the luttgs dad}. and others asked abttut the bed havioral ttiecitanislits fe.g.. What happens when a filter l'ncaks'i'. llo'tt-I do you breathe'.’]. The participants were also given a list of itents and asked how these re- lated tn an aquarium te.g.. air stone. heater. gravel} or the human respiratory sys- tem fc.g.. ottygen. alveoli. ribs}. In addition. several problems were posed. In these problems. participants were asked what would happen if the system were per— turbed. For example. iii the aquarium domain. one question asked. "What do you think would happen if you decided to add if! ttew fish to the JE guppies already ett- istirrg in a 2i} gallon tank'.’" For the respiratory system. the following problem was presented [adapted front Rea-Ramirez. Hut-i}: 1't'tru antl your friend plan to goon a lung itike.'l'br: weather is moderate. not too hot or ten cold. its usual. your friend is late when you arrive to piclt ltimi'lter up. You hear his-'her art-titer retttind hint-titer to be sure tireat a good breakfast. But your Friend says t'ottr-rrassvstrsis 315 hei'sln: Ia-‘iil cat later. Later. lrefshe is having too march fun to strip amt car mmm |1;.|f. way up the second till]. your friend gets dizzy and feels faint. Hisi'her heart is heating very ihfit. itl'lti Itctslte is trying to hrerrtlrr: In big gulps of air. I‘he students were asked to pnrvrde an esplanatrort for tire physiological effects that tict'uITcd. ltI tlil parts ofllre interview. participants were always prompted to provide as complete an esplanation as possible. Coding and Analysis l'articiparits‘ interviews were transcribed and coded according to an Biff-Ii coding scheme for the presence or absence of a target concept. For both syslerrts- the cod- ing scheme identified a target list of structures and a list afoot-responding [train-1v- iors artd functions. The transcripts were coded for evidence of SIIF concepts We defined structure its :I mention of art clerttent ot" the system. either alone or in ena- tteclit'rn with its behavior and function. For exatttple. any mention of plants t“l attt dressing some fake plants“; or organs of respiration (“Those are the lungs." "Now I’m drawing rihs“} were coded as structure. Discussion of bacterial processes (“Eat'let'ia changes the ammonia into nitrite and tltert nitrite into nitrate hack into clean wateriil was coded as a behavittr because it referred to a mectrtririsrrr fin ltow a function {e.g.. the cleaning of water; was accotttplr'stred. Similarly. we coded physiological mee hanisnts such as "The ribs move upwards and outwards" as a he- htlvior. because it provided evidence of understanding of how lurtg capacity in- creases. Behaviors described how a structure 1nitrorked to perform one or more func- tions. Function described why the pttrtieular structure was present or radial its role was in the system. For a statement to be coded as behavior it had to show evidence of understand- ing of the H'IEE‘ilEllliEitli of action. If a person mentioned "Filter cleans water.“ it was coded as function. If'. however. the participant referred trr how the tiller cleaned Wider ic.g.. "The activated carbon traps particles of waste"t. it was coded as behav- ior. Sirttilarly. for the respiratory systent “Movement of ribs allows breathing to in;- cur" was coded as function. Whereas “Ribs rnove tart-roofs rind rinrnvrrti's“ was coded as li-Eiutvior. Likewise. the statement “Blood carries oxygen and earhorr di- uside" is a statement of function: firm-ever. if the strident saitl. “Blood has some- thing that attaches to oxygen attd earbort dioxide.“ it was coded as behavior. AI- tl'tough the second statement did not completely describe what the “stuttetlting” was. we still ended it as behavior because it showed art overall understanding of how blood carried out its function of transporting oxygen turd carbon dioxide. We defined function as referring to a structure‘s role in the system or its outcome. Statements that mentioned filters re moving byproducts [HA litter filters out tlte or- ganic waste") or the brain controlling respiration (“The brain tells you In tiiearhe“} 316 ttttttztttsttytan.stasmrtmttt were ended as t'unctinn beeause they llttlltftttt‘tl that tlte participant was “linking. abnut why the structures exhibited certain hehayinrs. Each identified structure. hcltay'itrt'. tJI‘ f'ttltc'lirm was t'tttl_'g.r ceded nnee. Multiple Irtentinns nl' tlte same structure tnr beltayiur ur l'nnctiurt} were net cntIrtIEd senil- rately. We did this Iteeause same Intt'ticipants were tnut'e yet'buse titan uthers. Mttieuver. we wanted tn ascertain the cxtettt cf the pattieiuants‘ kltnwiectge base and nut I.t'hat aspects nt'the system they l'neused en. set we only ended i'ur presence ur absence ul'each structure. behavint‘. er functiun and nut 1hr frequency. Due pri- maryI researcher cnnducted the majnt'ity hi the ending and a seeetnd independent rater eutch EU'iri- at tile transcripts. Tile interrater agreettteut was 94% fer Ihe aquarium system and 95% fur the respit'atnt'y system. Mental ntudel analyses were cuntluctetl tu capture the ltuiislic Character of par- ticipants' rept'esentatinns. centplentcnting the fine-grained SBF ceding. Five unal- ugtttls muddy were: identified liar reach sysleltt. The mndels are described ltt Tables I and 2 far the aquarium and respiratnry systems. respectively. In bull: systettts. the tun-dcls pntgruss. I'rnut simple and structure-lstseri tn mare elabnrate. intereun- nected mndels that increasingly eunsider behaviors anti I'urtcliuns. The [it'figtltatic and hierarchical tnndels are bntlt expert mndels with a sophisticated and thereugh understanding nt'thc interactinth within the cctrtplex system. I'lnwet-‘er. lhe knew]- edge structures are nt'ganized differently. as we discuss in detail in the Results sec— tirm. The suitltisticatinn hi the mental tna-del was ended hnlistieally. Tu measure inten'ater reliability. urte primary researcher eunductetl the majm'ity 0f the ending. TAELLE 1 Aquarium Mental Maude-la .t'l-‘irtrmtl Mrtrl'et' De'tt'nym'ml Egucentrie Channeled-ted by a li|||'i[t,'\d:l1l-tlerttlilrltl1flg at the srtucttnes ins-ntued. The pcrxuu thinks |I15|| structure's exisl [err their hcaury and visual appeal. llltd. [u enhance the ettjeymem at the viewer. simple 1 testing; Fist; The: innltrtsc at an aqtctritua is In itcep the fish healthy. The needs et'the hair are held at be central. and there is early a limited urnlerstanding LII uther structures like filters and plants. finttd Tank tinrlersratnling is centered up the aquarium its il Witcle. Then! is .sm'tle understanding of the I'uttctiunal umt beltavierill intercept-anemic: and interactions between tliflemtt stnlcturea. Pragmatic fitn expert View with elubumte systcutic shticttJI’C. htthfit'inl. nflt'l filtfliunal cumtectimts. .fl. wphisricated malignant-tiling nl'titc interrelations between 1I|c 'u-Elriltll'llfi. t'lttt'trtttrttenla elf title :trltlarilltlfl exists. Tilt: fish. are central. and the rrllher kltwletlglt taslialH mttward littl't't IhE‘l'lI. fill. catwrl view with eiahmate Isystemic structure. hehayinr. and l'unetiutnal cttnnuctinns. The aquarium is seen as an ec‘nsystent. The central aspect ul this an Itch is Ihe transl'er ut' energy acrnss Lhe yttrirtus cumpunents ed the Missy-stem. Hierarchical f'tlhll'lJEl'Z S‘r'S'l'liMS 31? TABLE 2 Human Ftespuatury System Mantel Medals Neutral .I'tfrtrl'rt' Um‘rt't'tjrtirttl ligucctttric f'lctramerired by a limited understanthrls: Hi the sltllcltlres itt'rttlx'ed. These armature: un- ||puught It: t-sist irulcltcttdcutly. and their cnnnccttuns are nut understand. The pemtn slsn thinks ttl'ltis nr her (M11 lungs us central. Simple Healthy Lung Lungs are, wgaulcd as central. but the persun alsu has i| limited understanding nfnthcr structures like heart. diaphragm. ilml ri|x\. 'i'lmugh tlta persen understands that the rIthernrt-zints influence int-tn. the I'unt-timtal mlatinnships are net understand. Utah-"landing cctttetterl art the respitautry system as it winds. Then“: is same atrubetstatnling ut' the functiunul and lt-ehiurimal itltcttlcpclhchI-ec and interacriuns between different slruclulcs. Pragmatic An e: pct-t view with elattunne systemic structure. heliut'inr. and I'uttctiunal mnnet'tiuns. The lungs are central. and the ether knew-ledge radiates mtlward. [mutt tltEt'tt. An expert view I.Itirh clahnrate systemic structure. bellitwur. and t'urtctinnttl tstttneeriens. There is an understanding ut the neulmlily Ill mltrlttllins! mechanisms te.g._ rcgtflulimt by thi- itraunju in: the. pattth I'unc'tintting at the respirattrry system. Healthy Hudy T-lieratehicat and a seeunrl independent research assistant ceded 21.1% nl‘the transcripts. Tire reli- ability was 92% agreement Fer the aquarium system artd 'EJI‘ii- fur the respiratnt'y system. The SBF cedan was analysed with a 3 tierel el'expcrtise} X Li {level {if SBF} mixed analysts at t-‘arianee. Planned contrasts enmpared the twu nnyice grnups with the experts and enmpared the middle seltnnl studean willt. the preseryiee teachers. In additien. we did within-an bjects eumparisuns el'strlleltll'es. heltayinl's. and [Lint-.tiuns. 't‘lte mental metch ending was analysed witlt. maximum Iilrelihttu-tl chi-squares (G2). RESULTS SEtF Analysis We expected differences bciwtltjl't experts and nnyices. particularly in hettayiets and l'unetiuns. but it was not clear whether there wnultt the differences bet ween the twu greups et' nut-ices. Overall. experts and unyiees exhibited dill'ering patterns cf SBF knuwledge as strewn in Tables 3 and 4. In general. tteltayinrs were the wurst understetest aspect of the respiratery system, H I , 5 l] = 3] 1.52. p «c .tltJl . but this interacted with level ut'cxpertise, Fit. 5|} = 192.49.}: e .tl‘tll. Fer the I'Efil'tll'itttll'y 313 IIMFtlttSill-Wilt.MAIL-KTHEJJLI TABLE 3 Descriptive Statistics for Situetute-Eiehaviur—Funelinn in the Respiratory System —__,—.__—. (mm;- It stint-rim:- Ht'illrll'flrt P'rult'rl'mr Experts I'l Ill'I‘i' I'ljt'n l‘l I5 (3.941 It]. I5 [2.9.1] li‘rewrviee tent-Inlet: 2“ -II. I” t I .43] Fffl I: I .[WI 5.7!] I: I .49] Middle st'llrrnl sllltlenls 2 I I5? [ I .39] I I” 'i I - III-l 9-!” I: I Hf] —._.—..———-—-- TABLE 4 Deseripttva Statistics In: Strueture—Behavier—Funuliuu in the equarium System _._..._._—_.—————— (jump u .‘jrrmvmtr Relatives Flmr'nrlvr Experts ilt l2.9l] ttlJ-lt I439 $.35] IH.-1[lt3.i'ifti| Presets-ire teachers as Ill 5 use} [9'5 [1.9m 15%| [2.343 Middle sch:st stutlt'nls 2“ I13” {LIT} first] [1.51] TfiU [3.31 :I system. the experts differed I'rtnn tlte two groups nf nnviees in identifying mare stntetures. Ffl . 5 I} = 44.39. p e .IIHIH: behaviurs. Ff l . 5 ii = {$6.54. p s: .09]; and funetinns. F[ I. 5 I i = 53.?3.;: a: .titil , than the neviee Jgrnnps. There 1arere nn differ- enees between the preserviee teaehers and the middle sehuul ehiidren fur strue- ttn'es. behaviurs. er ftlneliens. A similar pattern was observed fur the aquarium system as shnwn in Table 4. Behaviors were generally the least eumprehensihle aspect of aquarium sysleitts. Ft; | . 53} = hath“; e: _D{] I. Again, this interacted with level of experti5e. Ff I , 53} .= 58H]. p e .Dfll. The experts did not differ from the nnviees an the number at struc- tures that they mentiened. Ffl. 53} = 1.31;}? .it'}. but the}.r did identify mere be- haviurs. PH. .53] = 31.9841 e .tiiill . and functions. Ff l , 53} = 92.93.;1' s: .[Jtli . than the nnviees There were nu significant differences between the middle seheul ehil- dren and the preserviee teaehers. Mental Model Analysis As shnwn in Tables 5 and e. the mental model analysis previtted a converging snuree ui'evidenee that neviees had simple. strnetnraity based models. whereas the experLs were able to fueus more an the underlying funetien and behavior fer built the respirstury system. filth} = rid-.Bfi. p e .UUI , and aquarium. (33(8) = fill-i1...” e .tJtti. Preserviee teachers tended tn held more suphisfiented medels than middle sehuul students. Because the mere sephistieated models euneeptnaiieed the sys- tems {buth respiratury and aquarium eeusysletns} ns innl'e interdependent. it sug— t.'t1t.tt‘l.t_=s sv sit-net 31 Q TABLE 5 Respiratory System Mental Medals Jinn-alts Ht'rtftn'ty .l’r'npnntrit' Hit'l'nlt'frr'i tr! fins-n: n Egan mini:- fi'rtn'tiir Limp flint}- Hum? little" Middle st'hunl dudents '3! It] f1 5 l] “I Pleservit'e teachers 2‘” .1 9 1!- t] It Experts | '- ti t] it ii- 5 TABLE 6 Aquarium Eyslern Mental Medals Sister's f’trtgnnnit' l'fr'r'rvtrt'ttiitn' Gimp .Ir Egan-unit Hearth}.- Fish thirst 'l'h'ut fit]!th fauna? Middle suhtinl students Zl] ] | E 3 U U f’reservite teachers 2111 9 5 I”! U U Experts It] it [t [l 5 5 gests that althnngh the preserviet' teaehers did nut have :I highly deveiupm under- standing nl' helmvitn-s and function. titey did have seine understanding Hi the interdependeneies in the systems. Expert—Expert Differences The mental tnndei analysis previded evidence that all experts were uni equal. linr bath systems. there were qualitative distinetinns between the twn types el' experts we studied. We first discuss the differences between the biuiugists and hultltyisls in the aquarium dun-lain. We funeral this with a eensideratien ef the differences be- tween the respiratory therapists and ptlirltennry physicians. The hinlugists and the hnhhyists both had rieh represenltttiens. but they stressed different aspeets of the sq uarjum system. '['he bielegists fneused en the abstrttet bi- nlngienl princesses anti Ineehanies ef the fish lanlt as at system. wheteas the hubby- ists focused on ennerete aspeets relating tn maintaining the health ed' tile 17le. Fur esantple. in discussing hnw the filter is related In aquarium systems. hintnpists prnvided a men: til-istntet. seientifie espianatinn ed the impnrtanee ul' liltel's and bacterial aetien. as this hielegisl neted: Se the filters are set then: tn pennit nitri tying er denitrifying bacteria 1n build up an the attached tn the chateau! anaehed tn the stnne in the lilter :Ind relnuve these 11i- meejmus wastes. an1|1eu1herlhing the filter dues is el'eeurse clean the. water l'rttm particles mganie panieles. when an animal dies tJr bits tint" tissue uf the ttliiliittl tliCS 320 ||r-.|l-It.tt sits-ten. M-tlm't'mi. |.I't| and is telettsct] into the aquarium Iltcsc go tlnough tht‘ filter system Emil they 'dIL‘ ub- stn'bed to [he elta roonl because these have charges on them datum-id w tab-ureml was . .. This explanation focused on the role oI' bacteria in colwerting fish waste Io less httnni'nl stiltslnrtees but lacked pragmatic concerns such Its the specific types of lil- tors or how these filters work. The hobbyists. in contrast. talked about theseprag- I _ 3 malic etnteei us. as itt this example: ‘I I — l There‘s rliIIete-nt types of filters timln. they all do basically tin:- same type ot'1l1il1g. you could do the mechanical liitl'tllitlrt. ant! tEhEI'ItiCLtl filln‘tliurt. there is h lJT-i'll'llii of filters they have a patent on il with hit'l wheels. it's ihtfit’: lltllc wheels lhttl M3116 ills: clean water. the lilrererl water spills on it] the wheel and it turn '1'. =|I1ti tlll the good bite- tcria, the atittohactcrnnd the nitrostuntuias grow tn! that so as soon as water hi1}: i1. lite ammonia is converted it: nitritc.1|1en to “limit. llllftl il Slltllfi hack in“: Tl'lC aquarium. the otnnpnny got the technology tioIn water sewage tresltnent plants hunt the 5th: and fills. 'causc they still Ilse them. urn. that's about it1l1en. Like the biologist, the hobbyist made references to how bacteria are important i for biological filtration. Howeverr the hobbyist also talked about the specific ltinds of bacteria and when: the filtration technology originated. The description l was situated in a reference to a specific brand of filters [the tillers with the bio I l wheels}. Iitlrtbernuu'e. biologists were more lilter to focus on global. dynamic ielation- ships in the system than htnihyists Hobbyists produced more focused. Focal ex pla- natiorts ol‘ the relationships among structures attd their associates! functions and behaviors. For example, in response to the question "What do we mean when we talk about an aquarium as a system?" the hinlogisls focused on the components 0ft: generic system and: then related it to an LtELritlrnS to show that they functioned as sys- tems. 'l'bey were also very concerned with the regulation of the system. which is essential to keep it at equilibrium tshown in Figure 1‘). as well as emphasised how energy drives the system. The hobbyists talked about the specifics of maintaining a __ the aquarium [Figure 2]. hllhough hobbyists also discussed how the system was y" maintained at equilibrium. they tlid it by using concrete csampies and without \ mentioning global characteristics of system regulation. They discussed practical i... y; concerns, such as moving a sufficient volume of water and checking the tetnpera- ' E 3 g ] g L__ .: . : IF \\ a E . —,'\t—,It_ a'l'ntt-«ev HNIW near-cw Tum-:Iu-gli tnre. The hobbyists were more likely to discuss the specific behaviors that allowed the system to I'unetitnt. For example, hobbyists. whose mental model is shown in 3 Figure 2, were able to explain the mechanics of how the nitrogen cycle worked and g~ why it was important. The biologists. whose mental model is shown in Figure 1. \ talltetl more globally and gave l'ew concrete examples. However. the biologists de- scribed and explained the underlying scientific basis of new the system worked in [or greater detail than the hobbyists. .I'" Biologist martini inc-rm ot' aquarium us a system. FIGURE 1 322 NW- mite-I lien—m wfilfl' i k. \. “.15 is mun» rennin-mud he I. temp-end to W“ .' mm m f unrdImOIIrHt-ls *‘thhfllu K. "a... -2“ 'Ilrwlxlcll'll THtH-i-fi vale. teeth-ma W ." —-. _H__H Lem “"- _ _p' ml : Film I '~-.__.-“' .-I-" M_. H J" nude-m was Mglmd MWM III-tllddfi- term-e .- K-fil’ _— "-"“' ‘——____._ ‘wtenclntht ..—o-""" iniqmitm-ml a I'Dt'l'fl'fl'lq f can ..—o-""" _? t'Ttth’l .rzs M's-rims 323 We ehserved similar patterns Iwhen eernparing truth Itinds et'esperts in tlte re- spiratery drrntain. filtheugh tlte respiratnry therapists Iwere limriaily etltlt'nled. their training was geared ltJWlIJ‘tl preteiiec. must in either a 2- er 4-year undergradu- ate program. The pullnelnu'y physicians had an undergraduate degree. 4 yeais ul' tltetliL‘itl selltntlI and 4 years "I'll residency in internal medicine. and truly lhcn did they undertake several years el'a I'ellnwship iIt pullnttnnry medicine. The differ- enees in heth training and geals fer the 1th grnnps nl'esperls slinnld have led In differences iIt liUW they represented their ltttewledge. Mueh as energy was the driving faetnr in the :IL] uarittln I'ur hinlegisls. the central Her-mus system drum-e respirmiml I'm' the pullnenttry pliysieians. as Figtlle 3 slttiws. The eentral nervous system eentrels the aetitm ef the lung and respiratery rnnscles lltt‘uuglt Ctilttples I'EEtlltilclt tulips. 'l‘he lllttgs are 1! central [1:LL’I til' lhi: rnudel. and eellular respiratien is eiah-urately detailed. Matty linking hehayiers are included in the rich representalinat. The L‘nltcepl Iltilp that Itpl'esents a respinttery therapist‘s mental Inedel is shewn in Figure 4. In this model. tlte lungs are elearly the central aspect et‘lhe therapist’s Thinking. 1When asked, “What wuuld happen In a Iltll'llflrl iF he er she were deprived tii' esygen‘l” tine respiratory therapist answered in terms (if a clinical cycle nt' events: Basically what happens it yeu‘ne deprin et' esygen. it‘s a state called anusia and. tilt. the first thing that s'r'tiuld prehalfly happen is. tItII. yw wnuld begin In have car- 'lllil'L'-ll.|':|'l!}'l.l"tl'l'|l-illl1 uni. leading ltJ cardiac aI'J est. um. and sulmequently l1rniudilt11ape. I mean. immediately what wuuld Impperl Mltlld Is: L'yutnrsis. ytal‘d turn blue llte hluing [tr lips and thee and wluttnttl. hut that weuld rapidly lead te eurtline nrnest. This indireetly referred tr.- eellular disruptlnn. hut the resplnilmy therapist tie- seribed the cycle ei' events in tennis ul'eliltieal resultsthe heart rhythm wuuld gt] astray. the Jack at esygen in the bleed weuld lead tt: :1 hluish eeler iii the lips {cyanusis}. and the heart weuld step. fine pulmenary physician Liealt with this as well. as he said the fullerwing: Well. death weultl he the ultimate cause and effect. But. then ytJu‘re stripping nsida- 1i'.'e prouesses From going on, and lit'iIl'll: eells nu hanger have the exygen tr: run the try- eles to make theirenergy. sneh as the Krebs eyele. er switeh ever If! an anaemttie per lien el' ntetab-ehsm. but that weutdn't be enough to sustain life and yen thtlld eventually die. He then went err te discuss issues in prtWidiitg energy I'Ltr Itietabelislri {ritut‘h lilte the hielegists in the aquarium domain). This explaJtatien unpacked the eause and ell'tbet black bus in terms el prm'itlirlg energy fer cellular Etteh‘lbelistn via the Krebs eyele. Per the pragmatie experts, the respiratory therapists. senie it!" these Ineeha- nisms remained unanieulated as they Feeused en issues they related tn their [JI'iIC- 324 imam sum-n. MAIL-altqu |.t|.| _\ . ._." I . -._ _..r . Mi I | an... l ._,._... mm “nu-"I - _ ..1... n-v-r-r- _ K I, 1 I an... . . ln-‘F'lflllr . IIII' .-_,...,.. Hug-man mm... .- - ...........i..-.' I..." I - - I' ._..q_m..,.. manna-1.1.. - -"' ' nun-«wu- hum—Hm a...“ 1. '- ._ "I..qu FIGURE '3 t'ulamnstjr physician mental nmdel. CNS = Central Nermus System; h'I'P I adeflmille triphnsphate: RFIC = red liltle Dell. lice. 'l'he expert—expert analyses demonstrated that there was fitnelinn and behav— iur included in bath tyres: ul' es pen understanding. All ex perLs went lacy:in a purely structural ultderslaitding—snmethiltg that we did nnt eta-serve in either lit" the net-tee gmups. The seie nl'nic esperls Excusch on interactions within the system am] not an any target naictane 03.3.. maintaining the aq LtElIltlll'l as an optimum ent'i- ronment far Iish to live in. In ensuring that the blend n: ygen [EVE] rem-11' us at a de- sired level}. They also talked mere about the theoretically imp-urtant principles underlying their damain. In ccntrast. tile pragmatic experts were grounded in [trite- tiee. 'I‘Iicy Imd clear nulcnmes in mind. This has implications for instructinn. A]- thnugh it is a desirable gnal efinstruetinn tu enable students In l'nCIJtt DI‘I deep [trin- t't 1M FLEX S YETI EM H Vt anew . “It _ [ Hm:- umhm r— x ,a L Dirt-munixh r“ .J a Jill Elllmfilwl . uwmrL‘hl mlnm'flfi "Nd-Hutu: ""5" “"1" d if r H" ,r[ Inn-I ] -—- -. . mummies - if}. rhmmmifxff "M'W'Mu —- IJJ'Ntts -"' w.5i""i.iim|\ lull-it: l _ _r“"-"-u|um _ __ \ Hm“ I L " "——" “hurt. I Inmlmker K _ . \ Wklmnmnm \{E‘m'fl'vj wlrltlnurlhn' "I". _ _ NI \ Dtmt't --_ m I ‘- ' _ _.ImWIlf1-Iutfil1fl __ __I “well t——--’ “mm m - J mm: at .--"" .-' .a-t‘" .-"' ___.--"' naith um lulu ..-" ___.-"' mm mm in Hui-"MK . mm ll I‘m a r r—— — 1...". lI'IIIIuII [tn-anad- i "H:— rfl. ] i can J . __,I ‘- .. _ _ FIG DRE 4 Resplratary therapist mental mmlrl. Rm; I rod blind call. 325 eiples all the dninain. it is not easy. The cnnerele grmmding ur' the pragmatic experts. Whirl! keeps it clear cum-me in sight and wnrks inward it. might is: easier t'nr students to achieve. Achieving better understanding or concrete pun-cusses and aulcumcs might act as a scaffold far achieving mun: abs-1mm understanding nt‘a system. This suggests that pragmatic expertise might be an apprnprinlc target Inuch far instrnelittn. Instruction that i'nregmnnds i'unctiun and ins-ulcer; learners in nlmtel-liuitding experiences might heip meme them Inward a pragmatic caper: [eve] at understanding. It remains an empirical questinn lu dctennjne whether this made! might help term a bridge In :1 nture hicrarelrieai expert nmdei. DISCUSSION The msuils {if this stud).r show that structures are easier in cnmprehend than func- tinns nr behaviors. particularly for nnviees, As the must tangible aspect {if a cum- ples system, structures are mere easily represented than behaviors and t'nncljuns. 326 unit-:Ln-sIIs-‘rn.Msmlnlmt- I-'or1hc experts. the iu:h:1vioral and functional understanding ot'the system sei'vxts as :1 deep principle to tnganise their knowledge of the system.‘ Understanding the belittvitn's :uul fillielious of a system intlicates :I more elaborate network of ideas representing key phenomena and their iutcnelationships. Tile respiratory system esperls Iueuti ued functions. hehat-iors. and structure with roughly equal proba- hility. wilelxtas tor the aquarium syslt‘tl'tI experts I'ttenliorlml tittltclltrltul L'lettlc‘t‘lls more than behavioral and structural concepts. as multiple behaviors and structures tl'tay nutrition 1:: IK'I'l-ltl'lt'l various Iimeliorls. In addition. functional aspects of the system deal Iarith outcomes. hut I'nehavioral mcchauisJus deal with processes that are dynamic. invisible. :tnd therel'orc hard In understand. t hir results suggest that complex systems expertise is dich rent from other terms ttl' experliso Imcatlse stlclt experts need In tlutlel'sltll'ttl lite retationships anumg {lir- l'erenl levels old system. understand how cmcrgcnt properties :trisc. and be able to use this knowledge to Ihink about the pmpcrlies oil a lit-hole system. Such expertise goes beyond undcrstmuling deep principles ol' the dolnain tthough this is inlpor— Iantll. Cornp1es systems experts understand causality that results from multiple in- teracting and ol'len indirect l'actors {see also .Iax'obson. 200k Perkins :5: Grower. erase. We found qualitative dil'l'erenees in how dil'l'erent kitlds ut‘ Experts represent ctuultlex systems. Iiiologists thought in global ecosystems terms. whereas hobby- is1s thoughl in Itlnre Ittcul. concrete lttrtl'ts :iltotll what it takes to rnaiulaiu :1 healthy aquarium. In the samc rn:u1uer.tbe respiratory therapists focused on concrete. clin- ical consequences. whereas the pulmonary physicians included discussions of cause and el'l'ect that included more abstract mechanisms. These differences are eonsisteal will: the results or other studies that have investigated dill'erences be- tween various kinds of experts in :t dotnaiu. Previous research has shrwu'lt that dif- l'eient experts organise theircoutent knowledge differentiy. and this knowledge or- ganisation is goal ditectcd. In this vein. the gratis I'ur the hobbyists and resph'attn'y ttleiapists were very practical, whereas the biologists‘ and pttlmonary physiciaus' goals were brtstder. :‘ts other examples. majority culture and Native Nautical: listl- enuan differ in how they organize their {equally well-differentiated} knowledge ahoul fish {Medin el al., EtJtJm. Similar differences were observed between genetic counselors' and molecular biologists' knowledge structures (Smith. IWII} about classical genetics. Ulher studies have also shown expert—expert dilt'erenees. in knowledge organisation in dil'l'erent kinds ol' tree experts [Lyrtcth Holey. 5r. Media, 2mm; Media, Lynch. fir. Coley. IUFJTJ. The SHF framework is one way to account for ex pen ululerstantliug. but other goal-related principles can cause expert—expert dill'erences as well. 'Ihese resuhs demonstrate that expertise is eotuptex and can 'There ale other deep principles that might be innuutnnl For knruvlcdgcorguniralion as wellnthls is particularly impottnnl in hullugical sciences. lirnetgt'uce is another possible orgauiring lralnewuric. 1-: sun .r-‘x svs I'I-ZMS 32? take I'uuuy I'urms even within the salue Liorlmin. and that there are multiple paths to expertise. :‘ts in previous research. our results show that expertise is practice related [Patel u‘t'. Gwen. liI'IJI '. Fichunn IS: Anderson. IW‘J: Serihaer. HEM; Winehtug, tWSi, Ete- causc the aquarium llohhyisls had extensive pmctice maintaining aquariums and the biologists studied marine ecosystems. they focused on tlilt'erent things. a]. though scictltilic understanding is necessary I'orunderstandiug eensysletns. it will be much more pruduelive to talk to a hobbyist it'a person needs to liutl out why fish in an aquarium :tre dying and how to titt the problem .u’tn advantage tir'pragmatie understanding. estmcially when it comes to instruction, is that it has a clear goal and a specific outcome in view. It may thcrcl'ore be easier for students to under- stand than general principles te.e.. principles governing the new of energy ther- uugh ecttsy‘ilt‘ll'lt'll. As such. pragmatic understanding has the lunenlial to he a springboard for teaching and leaming about complex systems. The Eli-F Framework appears to he a deep principle that maps onto expert ways of knowing about ctuul'rlex systems in two dil'l'ercnt biological dtuaains. as well as being a canonical Fun" of explanation in biology. Utlr plogran: of research is at:- tively exploring how to capitalise on the SBF representation as all esamplt- af a. conceptual representation to support learning about ctrrupies systems. 511E? may provide a schema that can be used to understand a number of ctuuplex systems_ Thinking about complex systems in SBF terms should help learners understand the relationships among the different levels of a complex system. IMPLIDATIUNS FUR DESIGNING INSTRUCTION The general instructional pattern I'ollowed by teachers and teslhtmlts alike is to Ire a: biology as it collection of objects. definitions. and cycles to be memorized {Anteri- ean Association l'orlhe Advancement tiI'Seie nee, all), This inatntetiunm “mthndm- ogy promotes :t structure-centered approach to understanding and. in him, may cause students to miss 1he connectedness that characterizes systems. However, the essence of Lutderstartdinga system isthe dynamic Itrticessesut'lhe system radial-than the static structures. Functionaeentered instruction should help students to euaeep- tual'lze systc ms at :lwchol'intcrrelated behaviors thatallonsI slrucltues1t1aet-ampljsh particular I'urlctious and should promote more coherent understanding. Complex systems are recognized as a key idea in national seieuee standards {National Research Council. 19%). Urgauiaiug lean:ng around deep principles such as SBF should enable students to understand new comptes sys1ems they en- counter {Collins :5: Ferguson. I993: Goldstoue it: Sukarnoto. 2MB}. ‘I'lte Slil7|11p- reserttation ol'I'ers a way For learners to look behind the scenes at pttentuuena that are not maulin available to unaided perception. The goal of our research program is to understand different ways ilt which conceptual representations such as SB F' can he used to suppru't deep learnng about complex systems. 323 ||h1l-.t.U-Fill!.‘-.-'l-.l{. h-lIth‘t'l'lll-IJJU IJesignlng iristruetinn tn stipptn-I euntptes systetns understanding requires prn- eiding learners Inith opportunities to interact 1With these systeltts tJacultseIt flit Wilenstty. Etitlnr. But interacting with real systems alone may not he sufficient— many aspects nf'cnlnples systems are not easily accessible to unaided inscription. E‘utnpularional lttltl'i such as agent-hased modeling tools and simulations ol'l'er pnnnise to help main: the invisihle yisihle and highlight otherwise nonsalient as- pects ul'a system. In addition. conceptual n‘piescrttalinlts. stICh as 53F. need 1n he nrade explicit. i‘t telling t'estrlt nf'tnrr study was tlte fact that. althnllglt the prescl'yiec teachers had slightly more sophisticated mental models than the middle school students. their tttttdels were otherwise identical to those of the s1ltdents. Must prcsurviee teachers had tint participated in arty significant science instntctien since ltigh school. so it is not surprising that they pcrl'urntrsJ no better than middle school stu- dents. Their more sephisticatcd rrtclthtl nattlels might he the result rrFeollEgt: edu- cation in general. and tlttl science cdtrcation in particular. Although scientific literacy is [stunning increasineg inriispeusaltte thrthriying in the wnriti. teachers often have tirnited understandings of complex systems cott- cepts. Unless teachers understand tlte natttre of cornplcs systems. it 1will be d'tl'li- cult l'ur them to preside appropriate learrtirrg experiences. Although it is tenrpting to say that teachers should take I'rttit'E science courses. this approach may not be re- alistic given the range rit'suhjeet matter tttal etententary and middle school Ieae bets are responsible for teaching. Conceptual tools tlra1 prepare teachers to learn alt-nut enattples drnnaitts may instead he an important aspect ul' teacher pmfessional de- velopment and methods courses. .ltrst as students need opportunities to ertgage Willi ettlnples: systems. so do their teachers. The SEF conceptual representation might be a gnarl target for pml'cssional development beeattse it cuts across many systems arid may prepare. teachers to hctter learn about new systems they encoun— terantl subsequently organise appropriate learrtirtg experiences for their stud: an. lll our ongoing research pmgratn. we have been conducting studies in the labo- ratory that suggest that Foregroundittg Function in hypennedia produces deeper learning than t'nregrtnirttling structure (Lin. Harem-Silver. 3r. Marathe. 2W5}. In our classroom sttrdics. we are using sets of integrated hands-on and computer- hased activity to help students ask the what—huw—why questions that SiiF theory suggests :tte imponant. These. activities incorporate multiple utodels at dill'crent system levels. tart researchers need to hetler understand how to sea t'f'clrl learners in making connections aeniss the different levels tI-lineIn-Silyer Sc Acevedo. Etitlfi]. CON CLU SiDN The goal of our research program is to understand dill'erenr ways in which cuneep- tuat representations such as SBF can he used tn su ppntt deep learning about com- plex systems. SBF is an appropriate representation because it is consistent with corn PI res SYSTEMS 329 both the structure ut— the domain ti.c.. biology} as well as how cspcns understand complex systems. These analyses of expert understanding provide suggestions for representational tools to support learning and instruction as I.t-ell as pmeide pussi- hle target models I'or instruction. The espert—espcrt rlil'l'crcnccs raise sortrc inter- estirtg questions abottt what might he an appropriate target model. Further re seam-Ii shttulrl examine whether tJI'lI: tn“ the ttlhtrr :ritigl'rl he I'ilttl‘ft'. appropriate and whether one model cart be a bridge to the other. We have list-Ed this representation to design hypermedia For both tltc human rc- spiratpry system and aquarium ecosystems. Future work will explore I'IUW siinuta- tiort tttudels can he used as man-ert'ul tools that matte. l'urlctions arid behaviors 1."rsi hle aspects of systems and open for exploration and discussion. This approach has the potential to help students understand complex. systems not as a set of structures [tltat have certain behaviors and Functions associated with them}. but rather as :i rnul1i|eeeled weh. Fl EFEFI ENC ES American .I'tssuciatien For the aid Irsnrrernrurrt nl'eiciertce. tn.d.:l. its-121.5 tantra-r 2am hitting-.- turnouts ewrlrmtr'a-Ir. Return-ed Not-errth 21‘. ZLHJT. fren- hllpa'ilwwmwnyethtlt‘ll LIrgtpuhlitsrtiensn'tesrhtmir! lashit'u'rewurfde l:rtlll.l!r|r‘rt Bechtel. W. d'e AhrahaJnsnn. A. r2tltifi]. Explanation: .5. ineehunisr alternative. .'i'tur.liir'.r m the Hr's'rrirj' arm! Fni'tnsrsntry radiological and Fimnedi'cm' .i't'r'ences. 36. 421—14 t. Brnnsl’rud. 1. L1. Brown. A. L.. a r(inciting. R. tlelJUi. Hmt'pteple learn. 1r‘t'thlringtrm. DC: Natinrud Academy Press. Chi.l'-1.'l'. it. tlflUU. t’tprilt. Mr'.‘-'amferstrmrfing t'inevuwrrjutlr'cssnr at entrant. Paper presented at thean- ntral rnt'relirlg rrltlre Amer-berm Fairictrliurlal Research hssrrcintinrr'r. New Urlertrts. l.."'t Chi. M. T. H. ['lthlS}. {Thinnutrtsense conceptions ofcmergent practises: Itit-'hy some rnisciuiu-priiiiu are rnhusr. errrirut' rgrrJ'M Lem-nine Jim-rm eta. tr'tr. ital—Wu. Chi. M. 'T. H.. DeLeeuw. N.. EIhiu. & La‘v'aneher. L'. tlU‘Hi. lilieiling sell-explanations ilnpnm-s understanding. Cognitive .Ei-r'emv. Ht. flit—4T1 Chi. l'ul.T.H..l"cltL11'ich.I-‘..et Glaser. R. t |‘il§.t_‘ategmitutionand argumentation tIt physics pn-hlerns by team-nit and uranium. ['tt-Il‘erJ'Il-1T.‘.t'r'J-r.lricr_ 5. Hi l."i l. Cullins. _-"I..._ (it. Fergmstrt. W. |' W93]. Epislel'r‘r'u: limits and epistemic-games: fitl’rlcltrles :Ir'rri shale-Ewe In guide: ilrrlllil'y. Edm‘rmrmml' Phpt'lllrJtl-UXETI'. EH. 25-41. Iltrntct'rrt. R. G... St Raiser. B.J.['21'.|l'.l§._ Aprill]. Dr'sr'girr'itg'fiii't'rHJrlrt-t't'.t’.‘ll_‘|'.tt'rrrl termini-.t'irirlrfJHg r'.I.I .rilir' .l'ri'gIr mFmi-a' .Wrflrxgj' ei'nssrrmat. Paper presented at the annual meeting otthe National Itmsciatitm I'nr Re- search in Science Teaching. Dallas. TX l"ellnrtlich. P. J.. Ctmlson. R. L.. if: Spinal. H. J. thl l. lei-Irlurs' t"1i‘t_|tllllilllrh|itlltlrl'lg nl irlrpnrtanl and dillieultcmrrarpls. Ill K. D. thlhll!& P. J. FedIr:I-.-ircl‘r{Fain._|i.Erarrrrt'ririrt'liirirrxm rglrrrymrlrr: .t'.'|.;' 1'I’hll.’f.lf_t? rc't'rii'urr'mr an erhrt'riimrrri." rrr'Irimt'Hm' [Eli's 349—335}. Menln Ptrl'ii. Cali: il'ifitftli'l'u'lli'l" Press FeIrm-ielr. F. J.. Cnulsnn. R. l....-'i'piro. Tvt. J..& Dammit-Saunders. B. K. Il'ildl]. Knowledge :tpplitsaimi and transth inr eornptear tasirs in ill-structured domains: implications iiir instruction and testing in hinmedieine. In D. Evans Er V. L. Patel [Eds.:r. Adr'rinreu' Hamlet's in'crrgniriunfiar medir-ni imitating rainI Famine tpp. 2 | 3—7“). Berlin: Swinger-Whig. Feltntrieh. l’. J.. Spiro. R- at Hudson. R. L. tlllt'tllt. The. nature rrl L'Itrrt'eptuul underrsurndiup ir1 biernedicine:'lhe deep structure at complies Ideas and line rlets'lurllrlunl nl'rrtirs'rnrctqiliuns. in I). lir- 33E} FlMl-Ii.U-Sl|."r'iil~‘.. himmrnla. |.ILI um 31 ‘v'. l’alcl (ELL-L]. C'ufi'flfrl'l'l.‘ .n'in'irn' in .Iurclir'r'nr' flirmmhrwi r-Irrieh‘n'r'fly: 1H1. “3-l 1'2]. L'illl'l- bridge. Mfr: MI'I' i’nrm. Jim-ran. M. em“. M.'I'_ ll. 1 :Ulmj. '|'|w "alum ui uni-n: lennalinns ul' natural princlipn. Jriirnrafl'rwwn' fimmnl'uffi'r'r'fln'r l'irl'nr'nrr'alr. 2”. l2.“ lififi. GellnL IE. I: M121 {'hilrlTuuls ulna-[mun urlhz sum-um: and [u MliUlfl rrfllx' hrlnlrln burly. L'r'wrrrr'r PAT ('hrlfriyu Mmmgnqlhr. r’rfi. I93- -41|_"1. Lira-I. A. K... fillllll'p’. llL' SHIV" Gill'ril. .u'l... “HIE. N.. Murdm'k. J. W.. Hacker. M- M-. 3L fil’fl'rlll'ilflmj‘. T. “HUM. 'limanlxrhxiglling Itmuiug clwirrmmcnts: I. ExpEunnglm'drvlwx wmk. [I1 lefiflll. Cr. Smith-in. {E .-'i.. LA'nglrl rI-‘dm. hwmxmr rurrmrn.I .‘ll_‘|'.'|'fl’|:'|.i.' .chrrur 1mm in r'rJrJIerIe'rn'im'Ir-‘r [pp- JUJ—EIJI}. New Ymk: Springer. Liuldsrunc. H. i,__ S: Sukmnurn. Y. |E[1i_i-].Tllclr:ln51'cr nl' ubfilruc‘l principles gun-fining WI'IIpch adap- livn.‘ swarms. f'aguirirr' I’.r_l.'r'.f|rdrn.l_r. dl’r. 4||1 4%. Gratin-r. A. L'. [I‘M]. .I‘rprili. Lier drawn-In: rrmrprrhmrd rim rilsrlmirin'mr rgFe'iiemfiny r.’r'1'r'rr-r? Thu: I'Il'rmmiirms rulci fJR'rJlu'u'hI-I'IF .tr'r'nrnfrrr. '1“le pmmulmfl :1.| Ill: annuai rnrcting rrl'th: Amman Edu- culirmu] chcnrch chintinn. Munlrr'ul. le'lm'. Cilllilllfi. HIM]:LC.E..H1JII1)|1. LL 5.- Knlndm-r. J‘. L. (EFH'KIIJ. Dcsigningm Icun: ulxrm turnpinx syslcnm. .I'wmml nfriir er'm'irg Sc'r'mrrs. 5'. 24T—2‘J’H. HII'lCIU-Silm_ C. |_-'.. at man-tin. |{. A. 12mm]. lhnflcrstnnding L'prnpltx Hyfilums: Sunni: Linn: L‘lml- ltngcs. Jrrmncrl' IEFHH‘ Imnrin: Sr'imrrw. 1'5. .‘rl—fil. Hindu—5ile Li IS: Plinth-L M. {1. 12mm. Cmnparing Expert and nLWite untlmlinldillg trl'a mm- plcx gym-m I'mm |||c In'rulwclivu ul' xlulcrumg. behaviors. and funcliuns. Cngm'rr'w 3rér'arr'r. EH. IZT—Efil'l. Juanita-rm. M. 1.12m” ]. thlcm mlvii-5.1.:uguilinnmnrl mninth syslcrns: Diil'rcrmi-rus between flip-HIS and rip-rites. E'wrljdg'xr'rjr. 1‘1[2:I. l—':l J'ufulxm1. M. J_. S: wilunskp LI. 12mm. Cnmplcx 555nm“ ll'l. cducalinn: Scmlrlil'ir; and Educatinnal impurlnnw and impliuulim'm [cur llm lcamiug minutes. Jana-mi 0f J'J'rr' Emma'er .‘u'rsr'mcfl. 1'5. ll-- 34. Lmkin. J. H.. ML-llulnmrr. 1.. Sinmn. I). P.. 5.: Simun. I! h. [Fran]. RIPE” and “twin: pcrl'urmantc in sulving Flux-31:5 riml1lt‘rl'l'm. Crmrlirr'w .fi'e'iwnre. F2. lUl—lm'l. Liu. 1.... Hmelu-SiIL-cr. C. F... Jr. Maratth M. {2035. April]. F-imr-n'rm biz-fine firm].- An :n're'murr'b'r ap- pnwi: In framing"me mmurkx .ryiremr. Puprr prcmllml ul mhlllul1l1tflingnflhl.‘ Amaritnn LidLI- uariuuul Research Aafincinlinn. MHIIUL‘HI. Quebec. Canada. Lynch. F.. Ii... (Inlay. J. |J_. a. Medin. D. L. mum}. Tull is uliicul: Ecrural tendency. id¢nl dililcnsillnfi and graded mmgury structure nmrlng trot upon-s mid luavicfl. Menu»? and CrIgEIIi-‘iln. EH. 41—54]. Marlin. U. l...l._'.-|k.'|1. E. H.. a Culcy. l. D. (WWII. Culngwizilliml and FCILWIIing anmngll'cl: “parts: DU ii" mmlfi litml Lu Hume? fingriin'lae P.r_l.'r.|'mir1g_v. 32. 49--9EI. Marlin. I}. 1... Russ. H.. Alrun. 5.. L'rsx. LL Coir-LL Fluff—Ill. 1- 5.. fit BJ— [flll'lfi]. l‘filk biulugy Dr [9355!- 'A'il1tr fish. Cngm'iimi. 99. 25—233. Misuzcs. .i. .l.. Trnwhridgc. l. .I'lrrrumdi'u. M. W.. & WMMIEME. J. H. [1991]. Ul'l'lldl'tll'h l'lifllflflh'l Slurlicu m1 mnmplunl dm'cldplncnt in tin: lil'r: mieIIL'Efi. lflS. M. Glynn. R. H. Ycanjr'. Ii E5. K- Brillflll {Elm}. Hui pru-Inrhagi-«J'meiirg .rcirm'r lpp. 11'? 4‘02}. Hillfitlalt. NI: Eflbuuln. Nnmyanuu. N. H.. at llngarly. M. I: I‘jljs}. [in designing :nmprchcusiblc intmtiw Il}}#nll¢tliil manu- als. hrrrmcrrirmul' J'rmmn! rJh‘mnmI-t'ananrrr SIIrJI'M. 4H. HIT—3U]. N:|Ii|.‘r|1:ll chcarch Council.1IUUfiEI..I'I'ari'mrm'ar'rr'ur'rrr‘dm'alinrl.fffllmm'fi. 'I-Wlu'l'l'll'lglul'l. DC: Nflliflflfll Amrlmny Prcfis. Nnrman.fi. R..1'rntl. A. |J_. Bnmks. L.. H.. J; Smilll. F.. K. [ |W4i.£‘ngnilivc ditfcrcnccs illulinical r23- mning minted m pnslgruduulc lraining. deliux ram-i Fran-11M}: r'fl thifi'fm. '5'. ll‘T—JEU. Pilltf. ‘v'. i... 3-. firm. LLJ. [ [WIL'J'hu genemlnmlsmcifi: nnlurc ni'mdirnlurmnise: Acriliflfil Infik. In K. A. Er'msnn .9: J. Smilh llidsJ. 'rauwnrx :1- .wmrmi I’M-ml rJ_r' mlmirr: Pmspn'rs and limit. Nim- ‘r'nllc: Cambridge Uni-ricrsil}I Prm. *4 L'DMPIJJX .‘i‘r'Fi'l'I-IMS 331 Pcnnncr. D. l-;. [Elli L Cnmplcnily. enmgcm-c. :mcl. synlimic "with in science {'rlurillinn. In K. L'anluyl {7. [:I. Sflmnm at T. Ukudn [film]. fh‘migfllifllfl 1hr .rcr'rncr (pp. 1'” 1m“. Mullwnll. NJ: Erlhaum. Perkin; D. N_. .5: UMZEI’. T. A. :mr. April]. Maid: nrm' rJrrJL'rx: Fl'Jr'Im'er rm :I'J'mr’rllhillffl u} :‘rJan.’ nmrpfamj' frJ m'l'rr'n'r prrr .':r.'I'4'ilhil'J-r.' Hildé‘rjrmrfilr'rrg harm prcscnrcd ill thL‘ :1n rlllill meeting 11! llw. Ammicm: I-‘duwalimml RcscurL'Ii Amu‘intinu. NEW Ul'ltilflt'n [adu— Hfl.g.-lr.1im;-. u ,‘t “0!er erfrls (Jr-wrg-minrri' Iniri'flljrcrmfirm in irrimcnr mud-warn»? rJrIrJ'nrera'JrI'e'l far imirrm'him]. Unpublifihtd rim-rink :Iissnrlnrinn. Llnivc'rxity11EMuwwlmxullh. Ran-nick. H.. E: 'lenusky. Li. [IQQREL I'Ji'p'illg inln :nmplcnily: [Jr- wlnping I‘lmhnhilifilic :kucnrrellirc'd Ihin'king thus-ugh [file—plilfi'lllg :bcrivi1ics. .Jrirm'iri.r a} Hit LMI'JrI'Jrg Fri-“an v.1: 5'. lfiJ—lTZ. E:LI:-clEi. N. H. (with). Culnluiexily. Icclumlngy. scicnn; 21ml1-drmflliml..rl'rwli'mri'rfl'hrlé‘ harming Srr'nlr'r'n. Li. 5—”. Suhunu. L‘. [1. at Andaman-1.]. R. 119%]. The gnmrulilfismrfifwiry nrcxmnisc in witII1ifiL'rurIumlirIg. Cnpm'iiw Sriwrcr. 2‘3. 337-33“. Scrihmr. 5. I: [11134]. Sluulyinp marking inIEIJigtncn. III [1. RLmtJIT-i 1— Law: EEI-lfi.].fflr'¢"_‘lfl'm' rwrm'Ir'rr-Ir: fr: dg'p'ffulmnmrl'r11.wk'idnre'rfllh'l'f'lpp. 9—4fii. Ehllllhiidgc. lid-"t? HLLWIIHl Universin PM“. Smim. M. LI. {WWI}. Kuuwlrdgc. sum-urns and Ihr: nalurc nl' carp-tnth in tlrlss'lwi gltlmtiufi. Eng-rlirima :rrm' hrxl'rm'n'r'lm. .7. ZEN—1'3. Slit-mm. M. [ZIIE]. er an: the: mimlcfl nl'umnplcx Fffilfil‘lfi Mullah? Plu'i'urupiu' of Sc'r'wic'r. .72. 5'] l—Sfin. Wcld. D. 5. {151333. Erpiar'm'ng :‘rJrerl'i‘I engine'er ri'r'uir'r-x. Rheum: Hnl1 Btrunck IInd NLW-h'n'lilil. Wiicmky. Li. a: Refillidr. M. HEW]. Thinking in levels: A :lynmnic sysrrms nppwur'h Lu rhulringrawmn nrlhc world. Jaunmi gramme Ednmn'ml and 'Fi'r'l'rmn'ng}; H. J—I‘J. ancburg.5. “993,1. Rmding Abrahurn Linculll: An Exmflnrtxpcllfludy in UK' Inlurplulntlun«ifhifimri- cu] Luau. Cngm'n've Science. 22. Zl-I'J- 346. Winelmrgfifi. [1991]. Hislnnnii pmlalem mining: A study u11llr. mgnilii-r: hummer: usnd in In»: {Will- uatinn nj'dmumenmq and illiL‘tl'lrifll mridan-n J'mrnmf rnf {Brim-animal Fjj'c'mlllflfj'. H3. 3'3. 3‘1. Wmd-Rnbinm. C. [W95]. E'lliler‘rL's binlngirill idunfi! Klinwlcdgc DENIM Ironing}: iulwriianuc. :Illtl :mlulium In S. M. Glynn & R. Duit {5:15.}. Lmrm'ug mining in Hie .rr'llrw-I'r" Fir-Wail: iril'mwmrx me-ri'cr [pp | | t--lfi I). Malia-uh. NJ: LithIIIIIII. ...
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