1、18THE ENACTMENT-EXTERNALIZATION DIALECTIC:RATIONALIZATION AND THE PERSISTENCE OFCOUNTERPRODUCTIVE TECHNOLOGY DESIGN PRACTICESIN STUDENT ENGINEERINGPAUL M. LEONARDINorthwestern UniversityMICHELE H. JACKSONAMER DIWANUniversity of ColoradoThis article explores why engineering students are committed to
2、counterproductivepractices. Student informants work practices appeared to coincide with lay stereo-types about what “good engineers” do, and they sought to justify those practices asrational. This externalization encouraged them to perform these practices more fre-quently. We characterize the relati
3、onship between the enactment of norms and theexternalization of work practices as a dialectical process that helps explain why thestudents could not conceive of changing their practices. We draw implications fortheory on occupational socialization and for the management of engineering workfrom our f
4、indings.Socialization processes are normally aimed athelping newcomers to learn the norms of a partic-ular culture. For this reason, most research on or-ganizational and occupational socialization dis-cusses those tactics that managers, leaders,colleagues, teachers, and others use to teach new-comer
5、s what sorts of practices are “natural” (VanMaanen Brown, 1985; Cable,Aiman-Smith, Mulvey, Jones,1986; Kim, Cable, Morrison, 2002;Van Maanen, 1978). In other cases, socialization isnecessary because people come to an occupation ororganization with strong, inaccurate ideas aboutwhat it means to be a
6、member. In superb ethno-graphic detail, Becker and his colleagues (Becker,Geer, Hughes, Turrow, 1989;Wright, Huston, Truglio, Fitch, Smith, Holtz, 2007; Ma-chura McIlwee Yurtseven, 2002). As pervasive assuch stereotypes may be, practicing engineers reg-ularly claim that popular images of this occupa
7、-tional culture are out of line with the ways engi-neers actually work (Bucciarelli, 2003; Darling Schoeneman, 2006).Students who are training to become engineers,lawyers, and doctors, like all individuals who arebeing socialized into a culture, constantly lookaround themselves for clues about how t
8、o act. Earlysymbolic interactionist researchers such as Mead(1934) and Goffman (1959) recognized that whenindividuals are being socialized into a new socialsetting, they discern the degree to which they be-long by assessing the fit between their own identityand the idealized identity of other group
9、members.The socialization period is ripe for identity forma-tion because during this time people seek reinforce-ment, information from others that tells them theyare acting appropriately (Brown, 1985; Morrison,2002; Wanberg Nkomo Feld-man, 1976; Ondrack, 1975; Wanberg Lovgren Chris-2009 401Leonardi,
10、 Jackson, and Diwantiansen, 2002; Waite, Jackson, Diwan, Berger thus, several informants were recruitedby the snowball method. Instructors were not toldwho was interviewed or how many people hadparticipated, and participation in the study did notaffect students grades. Informants education lev-els r
11、anged from one through five years of universitystudy. All informants had completed at least twointroductory courses in software and computer en-gineering, and the average number of engineeringcourses completed was five.The primary data collection procedure used inthis study was the semistructured in
12、terview. Semi-structured interviews are an effective way to under-stand “behaviors that derive from the cultural andideological identities of the speaker” (Lindlof,1995: 165166). Thus, following the symbolic in-teractionist framework, we used interviewing pro-cedures to obtain informants “vocabulari
13、es of mo-tive” (Mills, 1940). Adopting the view thatmotivation for action does not reside solely in in-dividuals, but is constructed in the situations inwhich people find themselves, we sought to un-cover the ways in which informants perceived theirown actions and the reasons they gave for theircont
14、inued performance of such actions.Interviews were conducted in the final third ofeach 15-week semester. All interviews used a semi-structured protocol; the Appendix presents anabridged version of this protocol. We asked infor-mants a series of open-ended questions within fourgeneral areas: (1) educa
15、tion and work experience,(2) experience working in groups in engineeringcourses, (3) studying and preparation practices forengineering courses, and (4) opinions about theassignments and teaching style of the course inwhich an informant was currently enrolled. Infor-mants were also asked to estimate
16、the grade theyexpected to receive in the course. All interviews,which averaged approximately 50 minutes, wererecorded and transcribed. Over the course of thisstudy, 643 students were enrolled in the eightclasses included in our data. Every one of thesestudents received an invitation to participate i
17、n thestudy. In total, we conducted in-depth interviewswith 128 engineering students (104 men and 24women),3achieving an overall participation rate of20 percent.We collected additional data by observing stu-dents completing engineering homework and extra-curricular assignments. We asked each of the 1
18、28students we interviewed if he/she would also bewilling to allow one of the researchers to “shadow”his or her normal work for a two- to three-hourperiod so we could observe how informants con-ducted tasks. Fifty-four students (42 percent of theinterviewees) were observed working alone andwith other
19、s in class, in labs, and in groups on daysbefore large assignments were due. In total, weobserved over 140 hours of activity.Throughout the period of data collection, mem-bers of the research team from the Department ofCommunication, the Department of Computer Sci-ence, and the Department of Electri
20、cal and Com-puter Engineering met weekly to discuss data col-lection procedures and emerging themes. Periodicanalysis throughout data collection helps tosharpen questions, focus interviews and observa-tions, and ground evolving theory (Miles Margo-lis Hughes,1958; Reichers, 1987). With this assumpti
21、on as ourguide, the goal of this axial coding process was tohelp us to explain the types of practices informantsengaged in or believed they should engage in to beconsidered good engineers. Several informantswho expressed interest in our study agreed to becontacted again if we had any further questio
22、ns,and by comparing our findings with those of otherstudies of engineering students, we modified ourcategorization scheme to reflect two main catego-ries that best represented informants perceptionsof their occupational cultures norms (see the Find-ings section).Next, we returned to the raw intervie
23、w and ob-servational data and used open coding to find in-stances in which informants referenced either orboth of the norms we identified. Within each ofthese coded segments, we looked for explicit justi-fications informants gave for those norms. Afteridentifying these justifications, we again used
24、axialcoding to group similar reasons into a common set ofjustifications. We refer to these collective justifica-tions as “rationalization practices.” Two ration-alization practices surfaced: justifying from perceivedtask demands and justifying from occupational ex-pectations. These rationalization p
25、ractices repre-sented an aggregate of all the justifications informantsmade about why they performed work as they did.Through our qualitative analysis procedures, wenoticed that a greater number of each of the eightwork practices appeared in the interviews and ob-servations of long-tenured informant
26、s (upperclass-men) than those of the relative newcomers (under-classmen). To determine whether this observationcould be empirically verified, we used chi-squaretests to measure the differences between these twogroups in the number of each of the eight workpractices that appeared in their respective
27、inter-view transcripts and field notes. We also combinedthe frequencies for each work practice into onecontinuous variable and submitted the data to ananalysis of variance test. Similar methods wereused to determine if any difference existed betweenthe frequency with which upperclassmen and un-dercl
28、assmen performed the two rationalizationpractices we uncovered in our qualitative analysis.Finally, our qualitative coding suggested that thepractice of justifying from perceived task demandsexternalized work practices that enacted one occu-pational norm and the practice of justifying fromoccupation
29、al expectations externalized work prac-tices that enacted another. To verify this interpre-tation, we regressed the frequency with which eachof these two norms was enacted against the fre-quency of the two externalization practices. Each ofthese tests was used to corroborate our qualitativefindings
30、and to verify whether our interpretationsof the patterns in the data could be substantiated bydifferent analysis techniques.FINDINGSOur presentation of the findings is divided intothree sections. First, we provide illustrations ofeight work practices informants routinely engagedin as they were learn
31、ing to become software andcomputer engineers. The performance of thesework practices enacted two occupational normsthat informants believed were characteristic of en-gineering culture. Next, we discuss the two ration-alization practices informants used to justify thosenorms. Finally, we present our
32、quantitative analy-ses, which suggest that by rationalizing their normsover time, informants eventually began to external-ize their work practicesthat is, they began to viewthem as natural, normal, and proper and to performthem more frequently.Occupational Work PracticesInformants carried out eight
33、distinct work prac-tices. Each work practice certainly affected howstudents engaged tasks and assignments, but whenperformed with other similar practices, they alsoenacted occupational norms. Informants perfor-mance of these eight work practices enacted twodistinct occupational norms. In this sectio
34、n, wefirst describe the eight work practices and thenpresent the norms those practices enact.Work practice 1: Delaying the start of a task. Acommon work practice was to delay starting aproject. Although waiting until the last possiblemoment to begin a project might be seen as a sign oflaziness or of
35、 lack of good judgment, informants inthis study framed this practice as a sign of technicalcompetence and expertise. Informants describedintentionally calculating backward from the dead-line to determine the last feasible moment to beginwork. For example, one informant described histime management a
36、s follows:404 AprilAcademy of Management JournalI dont. Im bad at it, I admit it. I procrastinate. Iwatch TV, I surf the internet. Ill go to my computerand sit down, start reading over the assignment, andjust be like, well, I have three more days until itsdue, so I figure I can surf the internet or
37、play acouple of video games or something. Then I eventu-ally get down to the due day and, like, damn. Andthatsits a big time crunch sometimes. I just puttogether half-ass work and send it in or, you know,really try hard and nail it. I end up doing it all in onebig block. I try to, and end up having
38、it in the lasteight hours of possible time. (2nd-year male, antic-ipated course grade, B)Another informant not only shared this strategy,but also described how he gauged the difficulty of atask on the basis of his expectations that otherstudents would procrastinate as well:So basically what I do is
39、I would wait until Mondaynight for an assignment due on Tuesday and Iwould go into the lab and I would see how manypeople were there. If there was no one there, then Iknew that it was easy. If there were a lot of peoplethere, then I knew that Im going to stay up all night.So basically Monday night I
40、 would plan on stayingup, you know, until five the next day working onthis thing, if I could. Which means, you know, skip-ping his the instructors class and all sorts of stuff.(5th-year male, anticipated grade, A)Note in both of these examples the acceptance ofengaging in a practice that effectively
41、 increased thedifficulty of completing the assignment. One infor-mant recounted an experience with a group projectin which she wanted to complete and test pieces ofthe assigned program and other students wanted towait until the end and write the program all atonce. To reconcile their differences of
42、opinion, thestudents took a vote. The informant who proposedthe “outrageous” idea of starting early was out-voted, because the others felt that not waiting todelay the start of the project would be a sign thatthey hadnt mastered the concepts and that theyneeded extra time to work on the project. Thu
43、s, theentire group stayed up the night before the assign-ment was due to debug the program.Certainly, students in disciplines outside of en-gineering procrastinate when it comes to complet-ing routine assignments. The important point hereis that for the informants in this study, waitinguntil the las
44、t minute to begin a project was not asign of laziness or disinterest in the subject matter.Rather, beginning an assignment late made the suc-cessful completion of the task more difficult and,thus, was a sign of their expertise and mastery oftechnical skill. In the laboratories on days beforelarge pr
45、ojects were due, informants regularly dis-cussed the status of their projects with one another,comparing how much they had completed. Simi-larly, on days projects were due, student engineerstypically asked one another, When did you start?and When did you finish? Higher status wasawarded to those who
46、 waited the longest and stillcompleted the project successfully. As one infor-mant exclaimed after hearing that another startedhad his project only four hours before it was due:“Geez, you must really know your shit. Theres noway I could write that in FORTRAN in such a shorttime. Thats impressive” (1
47、st-year male, antici-pated course grade, B).Work practice 2: Ignoring instructions. Thoseperforming professional engineering work typicallyfollow some structured procedure to arrive at de-sired solutions (Brooks, 1982; Bucciarelli, 2003).These structured procedures, instructions, or “bestpractices”
48、are taught from one generation of engi-neers to the next because they have proven theirability to direct engineers toward the “right an-swers” (Vincenti, 1990). Oftentimes, student engi-neers are taught to first conceptualize the problemand then draw on their training to select and followone such be
49、st practice to reach the correct answer.However, because assignments are commonlygraded solely on output (e.g., Does the solutionfunction as it is supposed to?), it may not be nec-essary for students to follow best practices to re-ceive high marks on assignments. This situationintroduces an opportunity for students to increasethe challenge of an assignment by ignoring thepractices that they have been told will make thetask easier. When asked how they generally ap-proached assignments for an engineering course,informants normally responded that while theywere supposed t
