Trans-discipline engineering communication characteristics and norms: An exploration of communication behaviours within engineering practice
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Trans-discipline engineering communication
characteristics and norms: An exploration of
communication behaviours within engineering practice*
MK Pilotte†, D Bairaktarova and D Evangelou
Purdue University, USA
ABSTRACT: Industrial firms dependent on their developed engineering knowledge base lament
the loss of years of accumulated capability as Baby Boom generation engineers fade into retirement.
Looking for ways to retain this institutional learning, the notion of knowledge transfer between
engineers of differing generations offers an opportunity to maintain competitive positioning and
innovation momentum. Understanding how communication behaviours and preferences differ
among the engineering disciplines and generations may be a key toward supporting corporate
knowledge transfer. This exploratory study compares communication norms across disciplines of
nearly 400 practicing engineers in America, seeking to identify similarities and differences. The
study examines responses to a communications focused survey instrument using analysis of variance
(ANOVA) statistical methods, offering a glimpse into engineering communication preferences
and behaviours. Findings reveal that statistical differences relating to communication do not
exist between the ten examined engineering disciplines, however, further inquiry and instrument
development is suggested.
KEYWORDS: Generations; communication; engineering discipline; knowledge transfer;
knowledge sharing.
REFERENCE: Pilotte, M. K., Bairaktarova, D. & Evangelou, D. 2013, “Trans-discipline
engineering communication characteristics and norms: An exploration of communication
behaviours within engineering practice”, Australasian Journal of Engineering Education, Vol.
19, No. 2, pp. 87-99, http://dx.doi.org/10.7158/D12-009.2013.19.2.
1 INTRODUCTION of executive comment conducted in 2006 with over
two hundred industrial leaders, cited corporate
Over 10,000 Baby Boomers a day are reportedly knowledge transfer associated with changes in
retiring from the US workforce, a situation that will workforce demographics as one of the most pressing
not end until nearly 20% of the existing workforce issues facing their firms (Lesser, 2006). Improved
is reduced somewhere near the year 2030 (Cohn understanding of engineering knowledge sharing
& Taylor, 2010). With these dramatic retirement and communication norms can assist in identifying
statistics, industrial firms face the reality of lifetimes the magnitude of challenges associated with staving
of “tribal knowledge” and institutional learning off engineering knowledge erosion, and facilitating
departing the organisation, leaving behind great knowledge transfer. This is especially salient with the
voids of understanding. In the field of engineering, intervention and enhanced role of communication
the invaluable “complex understanding” of senior technology in the work place.
engineers is essential for the maintenance of
The issue of knowledge transfer within a firm,
competitive advantages. An informal solicitation
and specifically engineering knowledge transfer,
* Paper D12-009 submitted 23/07/12; accepted for publication
goes beyond the “simple” act of communication.
after review and revision 11/02/13. Knowledge transfer is a complex exchange between
† Corresponding author Mary Pilotte can be contacted at parties, affected by factors such as individual
mpilotte@purdue.edu. motivation, one’s ability to convey complicated
© Institution of Engineers Australia, 2013 Australasian Journal of Engineering Education, Vol 19 No 2
88 “Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou
ideas, access to information and interpersonal bonds correctly”. Some processes in engineering practice
formed within a firm (Reagans & McEvily, 2003). such as design and project management, have
Focusing on the mechanics of how engineers choose been extensively studied (Trevelyan, 2007), while
to communicate tactically preferring one mode to communication dynamics of interdisciplinary
another is essential. An extreme example of the teams are understood to a lesser extent (Smith, 2003;
importance of tactical communication comes from Bracken & Oughton, 2006) . Having greater insight
the United States space program. An official report into the different communication styles exhibited
describing the Columbia space shuttle crash suggests through social interactions within the engineering
the incident was in part related to engineers’ failure disciplines could inform educators inspired to reform
to properly communicate, including “incomplete coursework to more fully meet the profession’s
and misleading information”, poor communication pressing needs. This point is made salient by
flow between departments and levels, and an ongoing reports calling for engineers with greater
overdependence on PowerPoint to convey critical communication skills and developed competencies
information (Columbia Accident Investigation to manage complex technological systems and
Board, 2003). Scholars studying the incident global, multidisciplinary project efforts (Mraz, 2004;
further propose that organisation-based cultural National Academy of Engineering, 2004; Vest, 2005).
conditions influenced the communication norms and To meet such a need, a more detailed systematic
behaviours, which led to mixed messages associated understanding of the social and technical aspects of
with the advance warning of the subsequent communicating engineering work is required.
catastrophic failure (Mason, 2004).
Many factors influence an engineer ’s rationale 3 ENGINEERING COMMUNICATION
for why they communicate what they do. Social
Sheppard et al (2008) argued that engineering
constructionism suggests that a study of routine
knowledge is not simply nor entirely a derivative
communication practices and interactions is a
of science. According to Sheppard et al (2008),
meaningful tool in the scholarly examination of
professional practice (engineering practice) depends
knowledge construction (May & Mumby, 2005) or
on a specialised body of “engineering knowledge”.
what we communicate, and therefore can be used
The knowledge that engineers must bring to their
as a meaningful starting point for examining issues
work includes knowing how to perform tasks,
surrounding knowledge transfer. In this paper, we
knowing facts, and knowing when and how to bring
explore communication norms across engineering
appropriate skills and facts to work on a particular
disciplines, with the aim of providing insights
problem. Vincenti called it “an autonomous body
meaningful to the dialogue surrounding the problem
of knowledge, identifiably different from scientific
of industrial knowledge loss.
knowledge” (Sheppard et al, 2008). Jonassen et
We examine communication perspectives and choices al (2006) added that workplace problems are ill-
inside engineering circles, and across a variety of structured and complex because they possess
engineering disciplines. Our goal in raising this topic “conflicting goals, multiple solution methods, non-
in this way is two-fold. First, engineering educators engineering success standards, non-engineering
may find this information useful in defining specific constraints, unanticipated problems, distributed
objectives for course work within their programs, as knowledge, and collaborative activity that rely on
they seek to bolster multidisciplinary collaboration multiple forms of problem representation”. If these
and communication competencies focused on characteristics of engineering workplace problems
preparing novice engineers for a future wrought are void of any science-based preconditions, then
with complexity (National Academy of Engineering, as engineering educators, we should continue to
2004). Second, results of this study can be useful to expand our descriptions of the engineering practice
industrial firms, as it offers insight into discipline beyond the technical realm, searching for the outer
specific communication behaviours which can limits of what can help define true engineering
affect acceptance of various computer-mediated knowledge as well as unique disciplinary features.
communication tools implemented to address the Rich communication research by Williams (2002)
loss of knowledge capital within their organisation. found that although more creative engineering
communications based content including portfolio
2 REVIEW OF LITERATURE development have been integrated into some
engineering programs, “faculty must ask themselves
Few studies to date have examined differences the question, what constitutes effective engineering
associated with how various engineering disciplines communication within our discipline?” (Williams,
communicate everyday work while interacting 2002). This fundamental question requires us to
socially. Trevelyan (2007) claimed “it is essential assertively consider discipline-based behaviours and
to recognise that most engineering work involves “soft skills” associated with communication in the
highly coordinated work by many people with same fashion that we evaluate and develop critical
different roles and responsibilities and success discipline based technical competencies. This flexible
relies on the ultimate production being performed and expansive view of engineering’s discipline-
Australasian Journal of Engineering Education Vol 19 No 2
“Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou 89
based communication norms is central to progress knowledge transfer is to this point unexplored.
the positive trends in engineering education reform. Generations are typically defined by a grouping of
Further, it is necessary to advance our inquiry and birth years for a span of approximately twenty five
understanding of communication and knowledge years, while cohorts are grouped and associated
transfer issues surrounding the specific engineering with unique, concise “coming of age” periods
disciplines, and pressing industrial organisations. normally for those 17-23 years of age (Schewe et al,
2000). Generational categories are often represented
with titles such as Pre-Baby Boomer, Baby Boomer,
4 COMMUNICATION MODES AND Generation X, and Millennials (Zemke et al, 2000).
ENGINEERING COMMUNICATION BIAS Those generations classified as “Pre-Baby Boomer”
were born in years prior to 1943, “Baby Boomer”
To share accumulated engineering knowledge and are born between 1943 and 1964, “Generation X” are
experience, one must communicate with others in born after 1964 and before 1980, and “Millennials”
a way that can be received, internalised and later are those born from 1980 through 1993 (Zemke
retrieved for use. Court et al (1997) suggested that the et al, 2000). While generational boundaries are
mode of communication one chooses (ie. face-to-face, not typically examined in research related to
email, text, etc.) influences the level of information that knowledge transfer, the significance of this factor
can be transferred. In this age of rapidly developing must be explored, as life experience is one aspect
communication technology, computer mediated known to influence communication exchange
communication (CMC) is a term often used to bundle (Baskin & Aronoff, 1980). Further, the distribution
various communication mode choices. CMCs can of employees in an organisation along demographic
range from internet-based email and the world wide dimensions such as age, tenure, or gender, influence
web to e-file sharing, e-conferencing, and personal communication exchange frequency and produce
handheld communication devices (Sørnes et al, 2004). varied organisational outcomes (Pfeffer, 1981;
Early discipline-specific communication research 1983). Another unique perspective of this study is
revealed that mechanical engineers are known to investigating if the generation an engineer is born
display a preference for face-to-face communication into informs and influences their perception of
based on the desire to trust the source of information engineering communication practices.
(Hertzum & Pejtersen, 2000). Uncovering similar
communication norms including the comfort and
competency to engage CMCs across a wider range 6 STUDY FRAMING AND OBJECTIVE
of engineering disciplines would provide an exciting
avenue for considering the prospects of engineering As the literature suggests, the qualities of an engineer
knowledge transfer on a greater scale. and their discipline can influence how unique
engineering work goals are approached. Through
A study by Wolfe & Powell (2009) went further to this study, we investigate aspects of engineering
consider biases in interpersonal communications communication that might be viewed as either
within specific disciplines of engineering. This work advantageous or threatening to knowledge sharing
indicates that the masculine bias in engineering activities. The primary research question this study
settings influence the manner in which daily, examines is if perceived communication based
mundane, interpersonal interactions are perceived behavioural attributes are homogeneous across
by engineering teams. Personal goals and biases engineering disciplines, and to what extent factors
have been shown to affect both the initiation of such as gender and generation play a role. We will
knowledge sharing, as well as the effectiveness of it test the null hypothesis that statistically significant
(Wittenbaum et al, 2004). Data analysis investigating differences do not exist across engineering disciplines
engineering discipline in the Wolfe & Powell (2009) for communication related behavioural constructs.
study showed that disciplines such as industrial
engineering and bioengineering, known to have a
higher proportion of women than other engineering 7 METHODS
disciplines, are tolerant of female speech compared
to the more male-dominated disciplines such as 7.1 Participants
computer or mechanical engineering. Our research
provides new insight by sharing the extent to which Forty-three firms from a wide range of American
gender influences communication behaviours and industries known for employing large numbers
perceptions within practicing engineering disciplines. of engineers were contacted for participation via
email. The list of firms was generated based on the
first author’s industry experience and background
5 ENGINEERING GENERATIONS knowledge of organisations that are known to
AND KNOWLEDGE TRANSFER employ diverse pools of engineering professionals.
Convenience and snowball sampling methods
Systematic study of the role generational factors (Creswell, 2008; Henry, 1990) were utilised to contact
play in multidisciplinary communication and these difficult to reach prospective participants.
Australasian Journal of Engineering Education Vol 19 No 2
90 “Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou
While working engineer participants are not difficult modes of communication (ie. face-to-face, verses
to garner in terms of their available population, telephone, CMC, etc.), while communication comfort
access to them can be restricted due to email filters on related to an individual participants relative facility
company email systems or human resource policies when facing one communication mode choice over
limiting employees ability to share work related another; and the sub-construct of communication
information. For these reasons, primary contact with benefits asked participants to evaluate perceived
firms was made only through human resource or positive attributes of communication modes (Pilotte
engineering management leadership, not directly & Evangelou, 2012; Spitzberg & Cupach, 1989).
with prospective participants as in traditional Participants were provided with the following
convenience sampling. From the initial company operational definition statements ahead of the sub-
contact onward, the research team was in no way construct elements to guide their response mindset:
aware of or influencing the distribution of the request For the purpose of the following questions, please
for participation, other than to encourage broad accept computer-mediated communication/CMCs
distribution of the participation request within the to include all forms of email as well as computer-
firm, and to send monthly reminders to the primary based networks, instant or text messaging, world-
contact list. The restricted contact with participants wide-web, chat rooms, personal data assistant
and the use of snowball sampling are the main (PDAs), shared electronic bulletin boards, terminal
causes for not reporting a participation response based audio or video telephony, use of all hand held
ratio, as the total number of engineers invited to device/phone applications, etc., for communicating
participate was an uncontrollable and uncollectable engineering issues. Note: CMCs do not include
value. The use of non-probability sampling methods landline phones or documents created on a computer
such as convenience and snowball sampling are not but issued by hand. Additionally, please accept
uncommon where there exists issues of difficult to “engineering issues” to include the broad range
access participants, limited resources and a need to of engineering topics and discussions you would
develop understanding beyond anecdotal evidence normally engage in during your day-to-day work.
(Henry, 1990). Both approaches are found in social
science and education focused studies, and are Survey questions were written to be meaningful to
considered useful when answering hypothesis based the general engineering population, and then were
research questions (Creswell, 2008). assigned to one of the four sub-constructs. This
portion of the survey utilised a five-point Likert
Once the contact at a firm expressed an interest in the scale. Likert structured responses ranged from a
study, they received a formal follow-up email that value of five for strong agreement, to a value of one
included an embedded link to a custom electronic for strong disagreement.
survey instrument hosted on Qualtrics Survey
Software (Qualtrics Labs Inc., 2012). Subsequently,
the survey was available to distribute freely across 8 ANALYSIS
the industrial firm; paper surveys were also made
available with special request, however, none were Descriptive and analysis of variance (ANOVA)
requested. This sampling process resulted in 402 statistics were used to test the null hypothesis of
field-practicing engineers, with a large portion of this study. Prior to performing the analysis, missing
respondents being from the Midwestern region of data was screened from the accumulated responses.
the United States. Descriptive statistics were developed for the three
independent variables: engineering discipline,
7.2 Instrument generation, and gender. The four communication
related sub-constructs were assigned as dependent
An electronic survey made up of two sections and variables (culture, competency, comfort, and
34 questions was presented to participants. The first benefits) by summing the specific individual
section requested details related to demographic question variable identifiers assigned to each sub-
attributes of the participants, while the second construct. The researchers probed for main effects
half posed questions associated with four sub- involving the independent variable engineering
constructs: engineering culture, communication discipline and interaction effects for independent
competency, communication comfort, and perceived variable generations and gender in relation to the
communication interface benefits (Pilotte & dependent variables.
Evangelou, 2012). The instrument was constructed Participants self-assigned into one of ten pre-selected
based on several of the communication sub-constructs engineering discipline categories, choosing one of the
developed by Spitzberg & Cupach (1984). The following as their primary discipline: Aeronautical,
engineering culture sub-construct included questions Biomedical, Chemical, Electrical, Industrial,
tied to group perceptions and behavioural norms; Manufacturing, Mechanical Design, Packaging, or
the communication competency sub-construct was Process engineer. Respondents were allowed to select
a participant self-reflection of perceived skill in “other” and provide an alternative title or “multiple”
successfully communicating when engaging various if their duties were multidisciplinary or if they had
Australasian Journal of Engineering Education Vol 19 No 2“Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou 91
difficulty identifying a single primary engineering The demographic breakdown by gender was 78.5%
association. They were then assigned into one of male and 13.5% female with 8% missing data. Other
four generational categories (pre-baby boomer, baby dominant aspects of the sample include race (76.8%
boomer, generation X, and millennial) by reviewing white, 5% Asian and 4.2% African American); 63.8%
their reported year of birth, and assigning it to the report their primary engineering education came
appropriate generation category. The single “pre- from a college education; and 46.9% of participants
baby boomer” respondent was not shown in the have bachelor’s degrees and another 32.4% earned
descriptive statistics and was withdrawn from the Masters degrees, which may or may not be in the
sample, as this particular generation was not a discipline of engineering.
focus of this study. The single aeronautical engineer
responder (n = 1) is shown in frequency tables, but
was removed prior to analysis to prevent unintended 9 FINDINGS
error related to small population sizes in weighted
calculations. The descriptive statistics for the sample A statistically significant correlation was not detected
population are shown in tables 1 and 2. between engineering discipline and any of the four
sub-constructs of culture, competency, comfort
Table 1: Frequency table for sample by and benefits (Pearson’s correlation coefficient r =
engineering discipline. 0.044, 0.048, 0.038, 0.047, respectively; see table 3).
An ANOVA test of the data looking for differences
Discipline Frequency Percentage between the engineering disciplines, did detect
a statistically significant difference (p = 0.016)
Aeronautical 1 0.3
in responses related to the communication sub-
Biomedical 3 0.8 construct of competency at alpha level p < 0.05, as
Chemical 10 2.7 shown in table 4.
Electrical 108 29.4 Investigating the detailed differences between
subjects did not reveal statistically significant
Industrial 19 5.2 differences between any two engineering disciplines.
Manufacturing 43 11.7 That said, as the ANOVA test concluded there were
Mechanical Design 68 18.5 in fact differences, which while not statistically
significant are discernible under careful review of
Packaging 4 1.1 post-hoc means plots (figure 1). Highlighting the
Process 10 2.7 accumulated means in sub-construct competency
allows us to examine differences found by disciplines
Systems 32 8.7 with a sample size of 30 or more. The largest
Other 44 12.0 difference noted (table 5) is between manufacturing
and systems engineers, with a manufacturing
Multiple 25 6.8
discipline mean difference 1.87, or 0.07% higher,
Total 367 100.0 indicating a slightly more favourable view of
Missing data 34 communication competency overall, than that of
Total 401 systems engineers. While other disciplines such as
electrical, mechanical, or multiple disciplines are
more closely clustered around a mean value of 25.
Table 2: Frequency table for sample by
generational category. Probing further for the level of influence either
generation or gender may play on the difference noted
Generational category Frequency Percentage by discipline for the sub-construct of competency, a
Baby Boom 194 54.3 between-subjects test was run (table 6). No main or
interaction effects related to generation or gender
Generation X 126 35.3 were found to be statistically significant in explaining
Millennial 37 10.4 the variance detected in the communication sub-
construct of competency.
Total 357 100.0
Finally, we examined communication mode
Missing data 44
preferences by discipline. Specifically, participants
Total 401 ranked their preferred mode of communication from
Table 3: Correlation between engineering discipline and survey sub-constructs.
Engineering Sub-construct
discipline Culture Competency Comfort Benefits
Pearson’s correlation coefficient 1 0.044 0.048 0.038 0.047
Australasian Journal of Engineering Education Vol 19 No 292 “Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou
Table 4: ANOVA means test result by communication sub-construct.
Sum of Squares df Mean square F Sig.
Between groups 15.575 10 1.558 0.853 0.578
Sub-construct culture Within groups 622.785 341 1.826
Total 638.361 351
Between groups 181.769 10 18.177 2.225 0.016a
Sub-construct
Within groups 2696.430 330 8.171
competency
Total 2878.199 340
Between groups 76.614 10 7.661 1.419 0.170
Sub-construct comfort Within groups 1797.339 333 5.397
Total 1873.953 343
Between groups 18.907 10 1.891 0.901 0.533
Sub-construct benefits Within groups 692.800 330 2.099
Total 711.707 340
a
Significant at the 0.05 level.
Table 5: Reported means for sub-construct competency by engineering discipline.
Discipline Mean N Discipline Mean N
Aeronautical 27.00 1 Packaging 23.00 4
Biomedical 22.00 3 Process 24.10 10
Chemical 25.20 10 Systems 24.33 30
Electrical 24.58 101 Other 25.27 41
Industrial 26.23 13 Multiple 25.87 23
Manufacturing 26.10 41 Total 25.11 342
Mechanical 25.46 65
Figure 1: Post-hoc means plot comparisons by sub-construct and engineering discipline.
Australasian Journal of Engineering Education Vol 19 No 2“Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou 93
Table 6: Test of between-subjects effects for sub-construct competency.
Sum of squares df Mean square F Sig.
Corrected Model 526.911 52 10.133 1.28 0.107
Intercept 43918.558 1 43918.558 5555.76 0.000
Generation 15.485 2 7.742 0.97 0.377
Gender 0.192 1 0.192 0.024 0.876
ALL_ENGRTYP 169.863 11 15.442 1.95 0.033a
Generation * Gender 6.647 2 3.323 0.42 0.657
Generation * ALL_ENGRTYP 89.585 17 5.270 0.66 0.835
Gender * ALL_ENGRTYP 65.750 9 7.306 0.92 0.504
Generation * Gender * ALL_ENGRTYP 22.238 9 2.471 0.31 0.971
Error 2213.414 280 7.905
Total 211616.000 333
Corrected Total 2740.324 332
a
Significant at the 0.05 level.
one, which represented the most favoured preference perspectives across disciplines is not homogeneous.
to eight indicating the least favoured mode. An Evaluation of discipline-based communication mode
ANOVA test representing communication mode preferences did reveal statistical choice differences
preferences was conducted to check for differences for three of eight presented modes of communication.
between engineering disciplines (table 7), and As expected, for engineering disciplines represented
statistically significant differences for mode choices of by small sample sizes, greater variation is present
face-to-face, instant messaging, and file sharing were and close evaluation is not possible.
detected (p = 0.036, 0.005, 0.025, respectively) at alpha
level p < 0.05. Examination of communication modes In order to verify reliability of these findings,
with statistical differences using a means comparison we completed inter-rater reliability (IRR) asking
table by engineering discipline (table 8) indicates that three coders blind to the purpose of the study to
for face-to-face communication, chemical engineers rate the data. We choose to verify validity of the
have the strongest means preference (1.40) for this findings with more than two raters, as IRR refers
mode choice with packaging engineers expressing to the relative consistency in ratings provided by
the lowest mean preference (2.75). Instant messaging multiple judges of multiple targets. The concept of
was preferred most by biomedical engineers (4.0) and IRR addresses questions concerning whether or not
least by industrial engineers (5.87), while packaging ratings furnished by one judge are ‘‘similar’’ to ratings
engineers represented the highest mean preference furnished by one or more other judges (LeBreton et
(3.5) for file sharing and industrial engineers (5.13) al, 2003). The rating scale the coders used was a 1
the least. Overall, across all engineering disciplines, to 5 Likert scale. The percentage of agreement was
face-to-face communication accumulated the calculated by reporting statistic of Cohen’s Kappa.
strongest mean preference (1.96), and blogs, chats, Reliability was calculated by comparing the number
and electronic information posting boards received of agreements and disagreements of each researcher
the least preferred choice (7.17). with the findings and analysis, and calculating the
average percentage of agreement. Reliability between
The results of the analysis support the null hypothesis
researcher interpretations was found to be 87%, which
that there are no statistically detectable differences
indicates strong agreement. The expert raters were not
in communication sub-constructs across engineering
involved with the study in any role other than rating.
disciplines. Minor discipline-based differences
were detected associated with questions focused
on communication competency, yet a strong causal 10 DISCUSSION
relationship cannot be claimed, nor are the findings
significant. Neither gender nor generation appear to As industrial firms contemplate responses to the
be factors influencing the detected differences and loss of significant engineering expertise, results of
add no explanatory capacity. this study can add value to the discussion. Findings
While differences between engineering disciplines presented here may concur with a standardised
were not detected as statistically significant, the approach towards managing engineering knowledge
means plots indicate that reported communication transfer activities within a firm, but may raise
Australasian Journal of Engineering Education Vol 19 No 294 “Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou
Table 7: ANOVA means test result for communication mode by engineering discipline.
Sum of Mean
df F Sig.
squares square
(Combined) 32.836 12 2.736 1.477 0.131
Between
Linearity 0.112 1 0.112 0.060 0.806
groups
Email Deviation from linearity 32.724 11 2.975 1.605 0.096
Within groups 624.481 337 1.853
Total 657.317 349
(Combined) 20.220 12 1.685 0.737 0.715
Between
Linearity 0.032 1 0.032 0.014 0.907
Phone/voice groups
Deviation from linearity 20.188 11 1.835 0.802 0.638
over IP
Within groups 770.877 337 2.287
Total 791.097 349
(Combined) 36.773 12 3.064 1.875 0.036a
Between
Linearity 0.750 1 0.750 0.459 0.498
groups
Face-to-face Deviation from linearity 36.022 11 3.275 2.004 0.027
Within groups 550.667 337 1.634
Total 587.440 349
(Combined) 17.885 12 1.490 0.783 0.668
Between
Linearity .200 1 0.200 0.105 0.746
PDA/cell phone groups
Deviation from linearity 17.685 11 1.608 0.845 0.595
applets
Within groups 641.329 337 1.903
Total 659.214 349
(Combined) 91.891 12 7.658 2.421 0.005a
Between
Linearity 4.790 1 4.790 1.514 0.219
Instant messaging groups
Deviation from linearity 87.100 11 7.918 2.503 0.005
(IM)/text
Within groups 1065.984 337 3.163
Total 1157.874 349
(Combined) 49.526 12 4.127 1.982 0.025a
Between
File sharing/ Linearity 1.056 1 1.056 0.507 0.477
groups
computer based Deviation from linearity 48.470 11 4.406 2.116 0.019
networks Within groups 701.791 337 2.082
Total 751.317 349
(Combined) 19.959 12 1.663 1.471 0.133
Between
Linearity 1.069 1 1.069 0.945 0.332
Blogs/chat rooms/ groups
Deviation from linearity 18.890 11 1.717 1.519 0.123
e-boards
Within groups 381.095 337 1.131
Total 401.054 349
(Combined) 74.461 12 6.205 1.560 0.102
Between
Linearity .863 1 0.863 0.217 0.642
groups
Video conferencing Deviation from linearity 73.598 11 6.691 1.682 0.076
Within groups 1340.293 337 3.977
Total 1414.754 349
a
Significant at the 0.05 level.
Australasian Journal of Engineering Education Vol 19 No 2“Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou 95
Table 8: Means comparison of communication mode preference by engineering discipline.
File
Phone/ PDA/ Blogs/
Face- Instant sharing/
voice cell chat Video
Engineering discipline Email to- messaging computer
over phone rooms/ conferencing
face (IM)/text based
IP applets e-boards
networks
Mean 2.00 3.00 4.00 6.00 8.00 1.00 5.00 7.00
Aeronautical N 1 1 1 1 1 1 1 1
Std. dev.
Mean 2.33 3.67 2.33 6.00 4.00 3.67 7.33 6.67
Biomedical N 3 3 3 3 3 3 3 3
Std. dev. 2.309 2.082 1.528 2.000 1.000 2.082 0.577 1.528
Mean 2.70 2.90 1.40 6.90 5.50 4.30 7.70 4.60
Chemical N 10 10 10 10 10 10 10 10
Std. dev. 1.252 1.449 0.843 .876 1.179 1.418 0.675 1.265
Mean 1.92 3.55 2.22 6.29 4.49 4.65 7.03 5.85
Electrical N 102 102 102 102 102 102 102 102
Std. dev. 1.114 1.526 1.390 1.287 1.806 1.507 1.246 1.921
Mean 3.13 3.27 1.53 5.47 5.87 5.13 7.27 4.33
Industrial N 15 15 15 15 15 15 15 15
Std. dev. 2.100 1.280 0.834 1.767 1.598 1.767 1.100 1.877
Mean 2.34 3.63 1.76 6.22 5.37 4.24 7.24 5.20
Manufacturing N 41 41 41 41 41 41 41 41
Std. dev. 1.389 1.513 1.319 1.370 1.699 1.300 1.067 2.040
Mean 2.34 3.61 1.87 6.45 5.24 4.12 7.34 5.03
Mechanical N 67 67 67 67 67 67 67 67
Std. dev. 1.309 1.477 1.290 1.374 1.868 1.482 0.808 1.800
Mean 1.50 3.00 2.75 6.50 5.00 3.50 7.50 6.25
Packaging N 4 4 4 4 4 4 4 4
Std. dev. 1.000 0.816 1.500 1.291 2.000 1.291 0.577 1.500
Mean 1.80 3.30 2.60 6.00 5.30 5.00 7.20 4.80
Process N 10 10 10 10 10 10 10 10
Std. dev. 0.919 1.494 1.578 1.764 1.767 1.155 1.033 2.658
Mean 2.41 3.47 1.72 6.22 4.50 4.78 7.38 5.53
Systems N 32 32 32 32 32 32 32 32
Std. dev. 1.624 1.344 0.958 1.362 1.586 1.385 0.707 2.199
Mean 2.29 3.83 2.05 6.22 4.37 4.71 6.83 5.71
Other N 41 41 41 41 41 41 41 41
Std. dev. 1.553 1.745 1.378 1.441 1.907 1.383 1.395 2.089
Mean 2.39 4.09 1.52 6.26 5.04 4.26 7.22 5.22
Multidiscipline N 23 23 23 23 23 23 23 23
Std. dev. 1.234 1.505 0.994 1.389 1.870 1.287 0.671 2.373
Mean 1.00 2.00 4.00 7.00 8.00 3.00 6.00 5.00
Missing N 1 1 1 1 1 1 1 1
Std. dev.
Mean 2.24 3.58 1.96 6.27 4.89 4.48 7.17 5.41
Total N 350 350 350 350 350 350 350 350
Std. dev. 1.372 1.506 1.297 1.374 1.821 1.467 1.072 2.013
Australasian Journal of Engineering Education Vol 19 No 296 “Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou
questions as to what tools might best assist those knowledge transfer. This idea is supported by
activities. While specific engineering disciplines several studies which compared the use of face-to-
do not appear to be closely associated with how face communication with CMC among students
engineers view their communication preferences, (Bordia, 1997). When compared to speaking aloud,
there is indication that engineering disciplines the studies examined by Bordia found that CMC
vary on their view of communication competency. based communication takes longer simply due to
Further, within specific engineering disciplines, there a variety of related CMC activities that interfere
may still exist unique preferences for one mode of with information sharing/transfer (typing, text
communication over another. These finding have formatting, and other electronic interface issues). On
implications for how a firm chooses to approach the surface, it seems as though increased technology
the issue of knowledge transfer across the various use is a rational contemporary response to many
engineering groups within their organisation, and firm’s knowledge transfer issues. However, given
how they choose to spend money on tools promoted Bordia’s and this study’s results, we suggest that
to assist in knowledge sharing and transfer processes. industrial leaders should carefully consider their
Self-perceptions of competency are known to affect plans for an IT-based solution to the long-term
individual behaviours. In particular, negative self- demographic shift of employees that face them.
images of competency completing a given task Finally, for engineering educators, one might
or performing in some social setting are related wonder to what extent first-year engineering
to defensive adaptive behaviours (Rhodewalt students interested in a given discipline, arrive at
& Vohs, 2005). The extent to which a particular university with communication competencies that
engineering discipline “feels” competent in using align with communication attributes associated
one communication mode or approach over another with the same discipline. Alternatively, perhaps
may influence the acceptance of that practice within issues around communication competency are
the engineering culture (ie. CMC based “high tech” attributable to factors that exist within the post-
verses more “traditional” approaches such as face- secondary academic setting and/or are endemic
to-face, or phone). This implies that firms should aspects of the college level engineering education
take into account factors influencing engineering pedagogy. Other possibilities also exist, such as the
communication competency, and be sensitive to number of communication systems and tools that a
how willing their various engineering groups are particular discipline is expected to become familiar
toward utilising both traditional and non-traditional and fluent with. In the discipline specific comparison
means of communication both inside and outside data which suggests systems engineers overall feel
their departments. Depending on the culture less competent using communication technologies
of the engineering discipline, “non-traditional” than their manufacturing counterparts, it could be
communication modes could range from person that this is an artefact of the greater number and
to person interoffice instant messaging, to global complexity of communication tools that the systems
teams engaging in synchronous, virtual, engineering engineers are faced with adopting, when compared
collaboration. Knowledge management initiatives with sometimes lower technology manufacturing
pushing a technology-based knowledge transfer engineering requirements.
solution within an engineering organisation should
be properly vetted to align with existing tool use Still remaining for educators are questions that
competencies and preferences within the engineering revolve around incoming students who belong to the
group. Should new skills be necessary to increase the millennial generation, and their technology-based
technology’s knowledge sharing effectiveness, the communication orientation. What affect might this
company should consider incentives or other forms generation’s communication preferences have on
of motivational enhancements to ensure the target engineering practice in the future? How can post
groups develop the skills and form the mindset to be secondary educators better prepare students for
successful. In addition, where technology is involved, discipline-based communication preferences they
there exists an opportunity for firms to leverage their could face in the workplace? These questions are
young millennial engineering talent and bias toward central to this discussion, since it is believed that
communication technologies (Oblinger, 2003). This oral expression is at the heart of discipline specific
may include allowing lesser-experienced engineers to traditions and socialisation (Dannels, 2002), and
serve as informal trainers for more senior engineering the data collected for this study suggests that face-
colleagues, leading with technologies they feel most to-face communication is still a strong engineering
comfortable using. Informal training arrangements communication preference overall.
may also offer the added benefit of developing into
organic, longer-term professional relationships
11 CONCLUSION
aiding in knowledge sharing between expert and
novice engineers.
While this study was unable to reject the null
Communication preferences and practices hypothesis that communication-based behavioural
within an engineering group affect the speed of attributes are homogeneous across engineering
Australasian Journal of Engineering Education Vol 19 No 2“Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou 97
disciplines, it serves to rekindle research discussions Bordia, P. 1997, “Face-to-Face Versus Computer-
associated with assumptions of homogeneity Mediated Communication: A Synthesis of the
across engineering as a field of practice. Further, it Experimental Literature”, Journal of Business
emphasises the value of face-to-face communication Communication, Vol. 34, pp. 99-118
skills that student learners are developing in and out
of the classroom through pedagogies of engagement, Bracken, L. J. & Oughton, E. A. 2006, “‘What do you
in-context learning and use of team-based projects mean?’ The importance of language in developing
(Gnanapragasam, 2008). interdisciplinary research”, Transactions of the Institute
of British Geographers, Vol. 31, pp. 371-382.
Looking ahead, additional research investigating
discipline-specific engineering communication Cohn, D. V. & Taylor, P. 2010, “Baby Boomers
behaviours and or post-secondary educators’ Approach Age 65 – Glumly; Survey Findings about
current practices and perceptions of the importance America’s Largest Generation”, The Pew Research
of engineering communication may be in order. Center, Washington, DC, http://pewresearch.org/
Studies of interest may include investigating how pubs/1834/baby-boomers-old-age-downbeat-
discipline focused courses are being altered through pessimism, accessed 21 June 2011.
content emphasis and pedagogical approaches,
to align with discipline driven communication Columbia Accident Investigation Board, 2003,
norms. Further, closer examination of how these Columbia Accident Investigation Report, Washington,
preferences may migrate with the exodus of Baby DC.
Boomer engineering talent could offer practical
value to the industrial sector. Finally, we suggest that Court, A., Culley, S. & McMahon, C. 1997, “The
opportunities exist for researchers interested in this influence of information technology in new product
topic to access and engage individual engineering development: observations of an empirical study
participants one-on-one, allowing for qualitative of the access of engineering design information”,
or experimental/observational methods, and the International Journal of Information Management, Vol.
benefit of expanded results. 17, pp. 359-375.
Creswell, J. W. 2008, Educational Research, Pearson,
12 STUDY LIMITATIONS Upper Saddle River, NJ.
One potential weakness of this study involves
Dannels, D. 2002, “Communication Across the
the sampling methodology employed. While
Curriculum and in the Disciplines: Speaking in
participation bias can occur with convenience and
Engineering”, Communication Education, Vol. 51, pp.
snowball sampling, an idealised sample for this study 254-268.
is not materially different from those described by
the basic demographics of the study’s participants. Gnanapragasam, N. 2008, “Industrially Sponsored
Alternatively, those most likely to be inadvertently Senior Capstone Experience: Program Implementation
omitted from the study could include those less and Assessment”, Journal of Professional Issues in
socially engaged and communicative, leaving Engineering Education Practice, Vol. 134, pp. 257-262.
them absent from social formed email lists. While
this situation is conceivable, it is doubtful that this Henry, G. T. 1990, Practical Sampling, Sage Publications,
less social population of engineers are somehow Newbury Park, CA.
excluded from company email distribution lists used
frequently by both engineering and human resource Hertzum, M. & Pejtersen, A. M. 2000, “The
management in sharing this study. In an abundance information-seeking practices of engineers: searching
of caution however, care should be taken when for documents as well as for people”, Information
attempting to generalise the results of this study to Processing & Management, Vol. 36, pp. 761-778.
the greater engineering population. Another area for
ongoing improvement and development would be Jonassen, D., Strobel, J. & Lee, C. B. 2006, “Everyday
the actual survey instrument. Fine tuning questions problem solving in engineering: Lessons for
and their wording may lead to more informed engineering educators”, Journal of Engineering
statistical results. Education, pp. 139-151.
Lebreton, J. M., Burgess, J. R. D., Kaiser, R. B.,
REFERENCES
Atchley, E. K. P. & James, L. R. 2003, “The restriction
of variance hypothesis and interrater reliability and
Baskin, O. W. & Aronoff, C. E. 1980, Interpersonal agreement: Are ratings from multiple sources really
Communication in organizations, Goodyear Publishing dissimilar?”, Organizational Research Methods, Vol. 6,
Company Inc., Santa Monica, Ca pp. 80-128.
Australasian Journal of Engineering Education Vol 19 No 298 “Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou
Lesser, E. 2006, “Closing the Generational Divide: Elliot, A. J. & Dweck, C. S. (editors), Guilford
Shifting workforce demographics and the learning Publications, New York, NY.
function”, Human Capital Management, Services,
I. G. B. (editor), IBM Institute for Business Value, Schewe, C. D. M., Geoffrey, E. & Noble, S. M. 2000,
Sommers, New York. “Defining Moments: Segmenting by Cohorts”,
Marketing Management, Vol. 9, pp. 48-53.
Mason, R. O. 2004, “Lessons in Organizational
Ethics from the Columbia Disaster: Can a Culture Sheppard, S. D., Macangay, K., Colby, A. & Sullivan,
be Lethal?”, Organizational Dynamics, Vol. 33, pp. W. M. 2008, Educating Engineers: Designing for the
128-142. future of the field, Jossey-Bass, San Francisco.
May, S. & Mumby, D. K. (editors), 2005, Engaging Smith, K. A. 2003, Teamwork and Project Management,
Organizational Communication Theory and Research, McGraw-Hill, New York.
Sage Publications, Inc., Thousand Oaks.
Sørnes, J.-O., Stephens, K. K., Sætre, A. S. &
Mraz, S. J. 2004, “At the crossroads: The future of Browning, L. D. 2004, “The Reflexivity between ICTs
engineering education”, Machine Design, Vol. 76, and Business Culture: Applying Hofstede’s Theory to
pp. 42-47. Compare Norway and the United States”, Informing
Science Journal, Vol. 7, pp. 1-30.
National Academy of Engineering, 2004, “The
engineer of 2020 Visions of engineering in the new Spitzberg, B. H. & Cupach, W. R. 1984, Interpersonal
century”, National Academies Press, Washington, communication competence, Sage, Beverly Hills, CA.
DC, http://site.ebrary.com/lib/albertaac/
Doc?id=10057020, accessed 10 October 2009. Spitzberg, B. H. & Cupach, W. R. 1989, Handbook of
interpersonal competence research, Springer-Verlag,
Oblinger, D. 2003, “Boomers, Gen-Xers, and New York.
Millennials: Understanding the ‘New Students’”,
EDUCAUSE Review, Vol. 38, pp. 36-40, 42, 44-45. Trevelyan, J. 2007, “The technical coordination
in engineering practice”, Journal of Engineering
Pfeffer, J. 1981, “Management as symbolic action: Education, pp. 191-201.
The creation and maintenance of organizational
paradigms”, Research in organizational behavior, Staw, Vest, C. M. 2005, “Educating Engineers for 2020 and
B. & Cummings, L. L. (editors), JAI Press, Greenwich, Beyond”, National Academy of Engineering (NAE)
CT. Annual Meeting, 10 October, Washington, DC.
Pfeffer, J. 1983, “Organizational demography”, Williams, J. M. 2002, “The Engineering Portfolio:
Research in organizational behavior, Staw, B. & communication, Reflection, and Student Learning
Cummings, L. L. (editors), JAI Press, Greenwich, CT. Outcomes Assessment”, International Journal of
Engineering Education, Vol. 18, pp. 199-207.
Pilotte, M. & Evangelou, D. 2012, “Building
bridges – identifying generational communication Wittenbaum, G. M., Hollingshead, A. B. & Botero, I.
characteristics to facilitate engineering collaboration C. 2004, “From cooperative to motivated information
and knowledge transfer across field-practicing sharing in groups: Moving beyond the hidden profile
engineers”, Engineering Studies, Vol. 4, pp. 79-99. paradigm”, Communication Monographs, Vol. 71, pp.
286-310.
Qualtrics Labs Inc., 2012, “Qualtrics Survey Software”.
Wolfe, J. & Powell, E. 2009, “Biases in interpersonal
Reagans, R. & McEvily, B. 2003, “Network Structure communication: How engineering students perceive
and Knowledge Transfer: The Effects of Cohesion gender typical speech acts in teamwork”, Journal of
and Range”, Administrative Science Quarterly, Vol. Engineering Education, Vol. 98, p. 5.
48, pp. 240-267.
Zemke, R., Raines, C. & Filipczak, B. 2000, Generations
Rhodewalt, F. & Vohs, K. D. 2005, “Defensive at work: managing the clash of veterans, boomers, xers
Strategies, Motivation, and the Self: A Self-Regulatory and nexters in your workplace, AMA Publications,
Process View”, Handbook of competence and motivation, New York.
Australasian Journal of Engineering Education Vol 19 No 2“Trans-discipline engineering communication ...” – Pilotte, Bairaktarova & Evangelou 99
MARY PILOTTE
Mary K Pilotte is a Doctoral Candidate in the School of Engineering Education at
Purdue University, West Lafayette, Indiana, USA. She holds Bachelor of Science
degree in Organizational Leadership and Supervision from Purdue University,
and an MBA from the Goizueta School of Business, Emory University, Atlanta,
Georgia, USA. Her graduate research focuses on engineering epistemology,
including understanding engineering culture and communication in the
context of industrial practice. Expanded research interests include engineering
entrepreneurship, engineering management, and pedagogies of engagement
including innovative distance learning approaches. Mary has over 20 years of
engineering, manufacturing and operations excellence experience in automotive,
aerospace, airline, and commercial products industries. Her industrial career
includes working for such firms as Trans World Airlines, Ozark Airlines,
McDonnell Douglas Astronautics, Acuity Brands Lighting, and Heartland
Automotive, a company founded by Shigeru Co. Ltd. of Japan. Prior to
undertaking her PhD, Mary served as Managing Director of the Dauch Center
for Management of Manufacturing Enterprise and the Global Supply Chain
Management Initiative for Krannert School of Management at Purdue University.
In this role, Mary guided graduate student research projects, directed global
internship experiences, advised student led professional clubs, and provided
fiscal leadership for this industry facing university outreach centre.
DIANA BAIRAKTAROVA
Diana Bairaktarova is a PhD Candidate in the School of Engineering Education
at Purdue University. She holds BS and MS degrees in Mechanical Engineering
from Technical University in Sofia, Bulgaria, and an MBA degree from the
Hamline School of Business, St Paul, Minnesota. Diana has over a decade of
experience working as a design engineer. Her graduate research is focused on
human learning and engineering, ie. understanding how individual differences
and aptitudes affect interaction with mechanical objects in engineering education
instruction, and how engineering students’ personality traits influence ethical
decision-making process in the engineering design. Diana has contributed to
manuscripts in the European Journal of Engineering Education, Children, Youth,
and Environments, and Contemporary Perspectives on Science and Technology in
Early Childhood Education, and published conference proceedings at American
Society of Engineering Education (ASEE), the European Society of Engineering
Education (SEFI), and Frontier in Education (FIE). She is an Associate member
of Sigma-Xi Science and Engineering Honored Society.
DEMETRA EVANGELOU
Dr Demetra Evangelou is an Assistant Professor in the School of Engineering
Education at Purdue University. She obtained her BA in Psychology from
Northeastern Illinois University, and a MEd and PhD in Education from the
University of Illinois at Urbana-Champaign. Demetra was awarded an NSF
CAREER grant in 2009 and a Presidential Early Career Award for Scientists
and Engineers (PECASE) in 2011. Demetra’s current research focuses on
developmental engineering, early childhood antecedents of engineering
thinking, developmental factors in engineering pedagogy, technological literacy
and human-artefact interactions.
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Copyright of Australasian Journal of Engineering Education is the property of Institution of Engineers Australia, trading as Engineers Australia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.
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