July 2009 Journal of Engineering Education 273

Measuring Leadership in Self-ManagedTeams Using the Competing Values Framework

CARMEN R. ZAFFT

Department of Agricultural, Leadership, Education, and CommunicationUniversity of Nebraska-Lincoln

STEPHANIE G. ADAMS

Department of Mechanical EngineeringVirginia Commonwealth University

GINA S. MATKIN

Department of Agricultural, Leadership, Education, and CommunicationUniversity of Nebraska-Lincoln

ABSTRACT

This study demonstrates how the application of the CompetingValues Framework (CVF) to self-managed teams (SMTs) assistengineering educators to understand how to measure leadershipwithin this context and facilitate an increased awareness of thestudents in a team, which will consequently increase effective-ness. Specifically, we analyzed data from the ManagerialBehavior Instrument, completed by 81 engineering students whoparticipated in self-managed teams for one semester. The instru-ment measured the use of the four leadership profiles of theCompeting Values Framework which then allowed theresearcher to determine the presence of high or low behavioralcomplexity. Behavioral complexity determines the team’s abilityto utilize multiple leadership roles and subsequent effectiveness.The findings indicate that behavioral complexity does have a sig-nificant effect on performance but does not have a significanteffect on the attitudes of team members. Overall, teams withhigh behavioral complexity earned a higher grade on their finalteam project than teams with low behavioral complexity. Thisstudy is significant for engineering education because it providesa theory and framework for understanding leadership in teams.By exploring the relationship between leadership in SMTs andeffectiveness, educators and industry can better understand thetype of leadership roles necessary for achieving a highly effectiveteam. As a result, instructors can design their teamwork curriculaand teamwork training based on the leadership strengths andskills of students which will then prepare students for industryupon graduation.

Keywords: leadership, teams, team effectiveness

I. INTRODUCTION

Teamwork and communication skills are two attributes most

desired by engineering employers (Bahner, 1996; Natishan et al.,

2000). In addition to the industry, engineering educators have empha-

sized the need for the development of teaming skills. Yet, studies show

that students are lacking these skills (Adams, 2003; Bahner, 1996;

Gardner, 2001; Natishan et al., 2000). ABET states in the criteria for

accrediting engineering programs that institutions must demonstrate

that their graduates have the ability to function on multi-disciplinary

teams and communicate effectively. But, many engineering programs

have struggled in incorporating effective teaming curricula into the

classroom. As a result, there is a need to better prepare students at

the collegiate level to successfully work in teams (Lewis et al., 1998;

Natishan, Schmidt, and Mead, 2000; Susman, 1976).

We propose that identifying students’ leadership skills and mea-

suring their impact on team effectiveness will assist in preparing

students to work effectively in teams upon graduation. We hypothe-

sized that teams with high behavioral complexity will perform better

than teams with low behavioral complexity. Low behavioral complexityis the use of one or two (or even zero) of the leadership profiles of the

Competing Values Framework. High behavioral complexity is the use

of three or four leadership profiles. For the purposes of this study,

team effectiveness is characterized by attitude and performance.

Attitude is defined as the commitment the members have to the

team creating positive experiences. Performance is defined by the

final project grade received by the team. Although there are other

indicators of effectiveness and performance for teams such as,

interdependency, learning, potency, goal setting (Imbrie, Maller, and

Immekus, 2005; Moore, Diefes-Dux, and Imbrie, 2006) and task

work competencies, teamwork competencies and integrated team-

level action (Salas et al., 2007), the decision was made to use grades

because grades were the most appropriate and readily available indica-

tor as to how the teams performed. Our research questions addressed:

RQ1: How does the Relating to People leadership profile

relate to team effectiveness, as indicated by performance and

attitude ratings?

RQ2: How does the Producing Results leadership profile

relate to team effectiveness, as indicated by performance and

attitude ratings?

RQ3: How does the Managing Process leadership profile

relate to team effectiveness, as indicated by performance and

attitude ratings?

RQ4: How does the Leading Change leadership profile

relate to team effectiveness, as indicated by performance and

attitude ratings?

Because certain terms carry different meanings, or because the

terms might be unfamiliar, we provide brief descriptions of four key

terms used throughout this article. The definitions for teams and

leadership are derived predominately from the management, lead-

ership, teaming, and human relations literature.

First, a self-managed team (SMT) is made up of individuals

who are self-regulated and responsible for a number of operations

and responsibilities such as planning, scheduling, evaluating, and

continual improvement. In the context of this study, students of

SMTs are given the autonomy to lead, share responsibility and

goals, manage resources, and create meeting schedules for the

development of their class project. Second, shared leadership is

distributed among all individuals within the team. The diversity of

ideas and abilities of each team member allows them to carry out a

variety of leadership roles throughout the team experience (Pearce

and Conger, 2003). Third, the Competing Values Framework(CVF) is designed to reflect the complex and paradoxical roles

demonstrated by leaders and the framework used to measure

shared leadership (Quinn, 1988). In this article, at times we inter-

changeably use the terms leadership profiles and leadership quad-rants. The profiles/quadrants make up the CVF and reflect the

leadership roles performed by the team member. Lastly, Behav-ioral Complexity (BC) is the theoretical framework of the CVF

and accounts for the competing demands experienced by leaders in

teams (Lawrence et al., 2003).

For this article, we are primarily interested in the use of shared

leadership in self-managed teams. Using the CVF to measure

shared leadership in teams is an exploratory investigation. The CVF

has not been used as a way of identifying leadership skills within en-

gineering education teams; instead the framework has been used in

business contexts. While Bealsen (1997) and Barry (1991) both

proposed the idea of applying the framework to SMTs, they did not

test it. This study will test this application. We also take the stance

that engineering students have unique leadership skills and when

used within a team, the effectiveness of the team will ultimately be

enhanced. Through our investigation, this has not been widely re-

searched. In the next section we will provide a brief review of the

literature involving self-managed teams and the Competing Values

Framework. We will then discuss the methods of the study, results,

limitations that surfaced, and lastly, recommendations for

engineering educators who desire to replicate this study in the

engineering classroom.

II. LITERATURE REVIEW

Research on leadership in SMTs has typically focused on the

emergent or external leader of the team. However, the research has

evolved over the years. Once concentrating on the emergent and ex-

ternal leader, researchers such as Manz, Sims, and Pearce have

identified a different type of leadership in SMT that is mutually

shared and focuses on the various roles of team members. This form

of leadership is called, shared leadership.

Research in the area of self-managed teams and shared leader-

ship is minimal and still developing. Even in its infancy, shared

leadership is an important condition in SMTs that can determine

effectiveness. In its simplest form, shared leadership as defined by

Cox, Pearce, and Perry (2003) as a condition in which teams collec-

tively exert influence, and leadership is distributed among all team

members depending on their skills, abilities, and the task. Although

useful, the shared leadership theory is difficult to measure. In re-

sponse to this issue, Belasen (1997) proposed the application of the

Competing Values Framework to provide explanation to shared

leadership within SMTs.

A. Theoretical FrameworkThe CVF clarifies leadership roles and expectations. This clarifi-

cation minimizes ambiguity and avoids interpersonal conflicts

within teams. The competing values approach accounts for the

complexities inherent in SMTs. It provides an understanding of

how a team is effective through the use of different roles and skills

and adopts the need for a balanced approach to leadership. Behav-

ioral complexity (BC) is the theoretical foundation for this frame-

work. For a leader to be effective in a team, it is essential that the

leader engage in a wide range of behaviors. A leader who is deemed

to behave in this way is a leader with high behavioral complexity. A

leader operating in low behavioral complexity does not have the

ability to engage in a wide range of behaviors and as a result, will be

less effective (Zaccaro, 2001). Figure 1 provides an illustration of

the framework.

Each continuum of the CVF highlights a value that is opposite

from the value at the other end of the range, i.e., flexibility vs. con-

trol and internal vs. external (Cameron and Quinn, 1999). The

horizontal axis demonstrates the level of organizational focus; ei-

ther internal or external. The vertical axis demonstrates the level

of adaptability; either flexible or controlled (Lawrence et al., 2003;

Quinn, 1988; Quinn et al., 1996). These axes readily demonstrate

the competing values experienced in organizations. Each quad-

rant has a competing opposite. For instance, the Relating to Peoplequadrant emphasizes a flexible structure and an internal focus. Its

exact opposite is the Producing Results quadrant that emphasizes a

stable structure and an external focus. This example demonstrates

the complexity that occurs for leaders. Leaders should value

relationships within the organization and make certain that the

organization is flexible to support these relationships. In contrast,

results are an important element of any organization and

maintaining a stable structure is a significant factor in producing

results (Quinn, 1988). For further review, Table 1 provides a de-

scription of each quadrant and a description of its accompanying

leadership role.

While a number of studies have focused on teams and the use-

fulness of them in a classroom setting, the specific hypotheses this

study proposes offer some insights into the needs of engineering

students and perhaps students in general in regards to both the

usefulness of teams and the effectiveness of outcomes. The

hypotheses are:

H1a. Teams with high behavioral complexity will have a

higher academic grade than teams with low behavioral

complexity.

H1b. Teams with high behavioral complexity will have

higher attitude scores than teams with low behavioral

complexity.

274 Journal of Engineering Education July 2009

III. METHODS

A. ParticipantsThe study was conducted at a large Midwestern university. The

subjects were undergraduate students enrolled in a required junior

and senior level construction management and architecture course

in the College of Engineering. Of the 101 students, 81 participated

in the study for an 80 percent participation rate. The population

was highly homogenous with 81 percent of the students being

males; 87.7 percent were Caucasian; and 64.2 percent were engi-

neering majors. Nineteen percent of the participants were female

(the percentage of females for the entire college is 12 percent).

B. Team DesignAt the beginning of the semester, students were assigned to

seventeen self-managed teams. The teams were designed by the

July 2009 Journal of Engineering Education 275

Figure 1. Leadership roles and profiles of the Competing Values Framework. Source: Quinn et al., 1996.

Table 1. Leadership quadrants and role descriptions.

instructor to ensure an evenly distributed number of construction

management and architecture students. At least two female stu-

dents were assigned to each team to ensure diversity among the

teams. Students were also assigned to the teams based on their

grade point average, with each team having a combination of high

performing and lower performing students. The mean team size

was six members, ranging from five to seven members per team.

Teams worked together throughout the entire fall semester to

develop a written Request for Proposal (RFP) to renovate the

mechanical systems for the local State Fair Grandstand. The teams

were required to identify, analyze, and implement mechanical sys-

tem renovations in an existing building (i.e., Grandstand) to comply

with the Green Building Rating System Criteria as established by

the Leadership in Energy and Environmental Design (LEED).

The class and project were designed so that the students would

experience a tangible renovation project for the betterment of their

community in addition to gaining valuable experience working in a

multi-disciplinary team (i.e., engineering, construction manage-

ment, and architecture students).

C. MeasurementsThree types of measurements were used in determining the im-

pact of leadership on team effectiveness. Grades received by the team

from the final project were used to measure performance, and two

types of surveys were administered to measure the leadership profiles

and attitude. Both surveys were administered at the conclusion of

each team’s experience at the end of the fall semester.

A discussion of the measures is significant in understanding the

exploratory nature of the study. It was previously mentioned that

the Competing Values Framework was adapted to fit student teams

and as a result, the Managerial Behavior Instrument (MBI) was

modified to meet the needs of the study. The issues pertaining to

this new instrument will be discussed further.

The MBI, developed by Lawrence, Quinn, and Lenk (2003), is

a 360� survey that measures behavioral complexity in teams. It iden-

tifies the previously described leadership profiles of the Competing

Values Framework exhibited by team members which then enables

the investigator to determine the level of behavioral complexity each

team is operating in. It contains two surveys: the self-evaluation and

the team member evaluation. The self-evaluation includes items

relating to teamwork training and demographic items. Both surveys

contain 36 items measuring the leadership profiles of the CVF for

each individual. Participants were asked to evaluate their own lead-

ership profiles and the leadership profiles of each member of their

team. As a reminder, the profiles are: (1) Relating to People (RP),

(2) Producing Results (PR), (3) Leading Change (LC), and (4)

Managing Processes (MP).

Permission and assistance was given by Katherine Lawrence, co-

author of the instrument, to modify the MBI. The foundation of

the items from the original MBI was not altered. Instead, attention

was given to modifying the language of the survey to accommodate

an educational team setting in addition to developing a new scoring

system to fit the needs of the study. We created a cut-off score for

both low behavioral complexity and high behavioral complexity.

Our decision was based on the work of Hart and Quinn. Hart and

Quinn (1993) defined low behavioral complexity as leaders who

comprise two or fewer of the leadership profiles, whereas those who

comprise three or four leadership profiles maintain high behavioral

complexity. It was determined that the mean score needed to be set

at a high level (4.0) so that each skill was distinctively set apart from

others. If any one person in the team had a leadership profile above a

mean score of 4.0 (agree), then the leadership profile was consid-

ered to be present. If three or four of these leadership profiles were

present in the team, then the rater was considered to have high BC;

two or less was considered to be low. Once assessed, each team was

then coded as either having high or low behavioral complexity, and

then further data analysis was performed.

Reliability was measured for both the self-evaluations (alone)

and all surveys (both self and raters). The Cronbach’s alpha pro-

duced an r-value of 0.89 for the self-evaluations and produced an

r-value of 0.93 for both the self and peer surveys.

Attitude was measured by seven items from the Team Effective-

ness Questionnaire (TEQ) (Adams, Vena, and Ulloa, 2002). The

TEQ measures the effectiveness of student teams in addition to

students’ attitudes concerning teams. The items from the TEQ

were included on the self-evaluation only because the items were

not designed to accommodate multi-raters. The participants rated

their attitudes towards teams using a five-point Likert scale with

1 � strongly disagree to 5 � strongly agree.

IV. RESULTS

A. Behavioral Complexity and Team EffectivenessThe independent measures t-test yielded a significant difference

when comparing the team’s level of behavioral complexity and

grades. Table 2 provides the results for the relationship between

behavioral complexity and team effectiveness. The teams with high

behavioral complexity averaged a score of M � 90.9 with SD �2.70. They out-performed teams with low behavioral complexity

who averaged a score of M � 88.9 with SD � 1.51. Teams with

high behavioral complexity scored higher than teams with low

behavioral complexity, t(69.7) � �4.113, p � 0.001, d � 0.93.

Reported values are for equal variances not assumed as Levene’s test

for homogeneity showed there to be a significant difference between

the variance of the two groups. The t-statistic was significant at the

0.05 level (two-tailed test).

The statistical analysis did not yield a significant overall differ-

ence for the effect of behavioral complexity on team members’ atti-

tudes towards their teaming experience. High behaviorally complex

teams averaged M � 3.85 with SD � 0.696 while low behaviorally

complex teams averaged M � 3.57 with SD � 0.618. Behavioral

complexity did not have a significant effect on attitude, t(79) ��1.701, p � 0.093, d � 0.43. Reported values are for equal vari-

ances assumed as Levene’s test for homogeneity showed no signifi-

cant difference between the variance of the two groups. The

t-statistic was significant at the 0.05 level (two-tailed test).

B. Leadership Profiles and PerformanceWe extended our analysis to determine if any one of the leader-

ship profiles had more of an effect on the final grade than the other

profiles. Table 3 shows the results for the relationship between each

leadership profile and project grades. Teams with a low Relating to

People score averaged M � 89.46, SD � 2.73 on their project while

teams with a high Relating to People score averaged M � 89.78, SD �0.877. The independent measures t-test did not yield a significant re-

lationship between Relating to People and grades, t(40.6) � �0.738,

p � 0.465, d � 0.17. Therefore, the leadership profile, Relating to

276 Journal of Engineering Education July 2009

People, had very little effect on performance. A significant relation-

ship was revealed for Producing Results and project grades, t(79) ��6.341, p � 0.05, d � 1.6. Teams with a low Producing Results score

averaged M � 86.7, SD � 2.35 on their project while teams with a

high Producing Results score averaged M � 90.2, SD � 2.03. Teams

with a low Managing Processes score averaged M � 87.2, SD �2.52 on their project whereas teams with a high Managing Processes

score averaged M � 90.1, SD 2.20. The analysis revealed a signifi-

cant relationship between Managing Processes and grade, t(79) ��4.861, p � 0.0001, d � 1.25. Lastly, teams with a low Leading

Change score averaged M � 88.9, SD 2.63 and teams with a high

Leading Change score averaged M � 90.9, SD 1.74 rendering a sig-

nificant relationship between the Leading Change leadership profile

and project grade, t(53.2) � �3.84, p � 0.05, d � 0.89.

C. Performance EffectsThe first issue addressed was whether the observed mean differ-

ences of the project grades and attitude scores were significantly

significant. To conduct the analysis, the teams were further segre-

gated by level of behavioral complexity into three different groups:

(1) low behavioral complexity—teams with zero to one leadership

profiles, (2) medium behavioral complexity—teams with two

leadership profiles, and (3) high behavioral complexity—teams

with three or four leadership profiles. Tables 4 and 5 provide results

of the one-way ANOVAs that compared behavioral complexity to

grades and attitude. The analysis also addressed if the original be-

havioral complexity cut-off score, as originally proposed, has merit.

The analysis of variance revealed a significant difference among

the three group means in relation to the final grade, F � 24.69, p �0.001. To determine which pairs of groups were significantly differ-

ent, we ran a Tukey’s post hoc test. The strongest difference was

between the mean scores of the low behavioral complexity teams

and high behavioral complexity teams (MD � 4.204), and very lit-

tle difference between medium and high behavioral complexity

teams, (MD � 0.860). This indicates that the actual empirical

difference between the scores is between the low and medium be-

havioral complexity levels. The post hoc analysis does not support

the original behavioral complexity cut-off score. Instead, the results

indicate that the cut-off for low behavioral complexity should be at

one leadership profile and high behavioral complexity is indicated

by the use of two, three or four of the leadership profiles.

The analysis of variance did not reveal significance among the

three group means in relation to attitude, F � 1.719, p � 0.186.

Consequently, no post hoc analysis was justified.

July 2009 Journal of Engineering Education 277

Table 2. Independent measures t-tests.

Table 3. Independent measures t-tests.

V. DISCUSSION

The results of the hypotheses demonstrate that behavioral com-

plexity has a significant effect on one aspect of performance:

grades. High behaviorally complex teams scored higher on their

final project than low behaviorally complex teams. These results

propose that teams who use three or four of the leadership profiles

of the CVF will perform better (in terms of grades) than teams

who use two or less throughout the teaming experience. This con-

firms the initial hypothesis on the importance of shared leadership

within SMTs, i.e., leadership is distributed among all individuals

within the team instead of being held by one individual. However,

it is recommended that once a sound scoring system is in place for

the MBI, it may be possible for the issue of shared leadership to be

addressed further. The identification of high and low behavioral

complexity does not necessarily explain if the leadership profiles

were broadly distributed or shared. These findings are in agree-

ment with Shamir and Lapidot (2003) who posit that shared lead-

ership is still not clearly defined and needs to be further researched.

In this study, shared leadership was difficult to measure since the

survey was taken at the end of the teaming experience. Shared

leadership could be further investigated by identifying specific

points throughout the life cycle of the team and measuring which

leadership profiles were utilized and by whom. Previous research

suggests that shared leadership is used through different stages of

the team (Pearce and Conger, 2003). Identifying these stages

would be essential to measure shared leadership.

The results of the Tukey post hoc test suggest that the actual

cut-off score for high behavioral complexity is at two instead of the

proposed three leadership profiles. Teams that operate with only

two leadership profiles will perform at a greater level than teams

who perform with zero or one. This contradicts the cut-off score

originally proposed and minimizes the necessity of various leader-

ship roles in teams. The lower cut-off score may be the result of

researching student led teams. These students did not receive previ-

ous teamwork training and can be categorized as “novices” to

teamwork.

It was also found that behavioral complexity did not have a sig-

nificant effect on the attitudes (another aspect of team effectiveness)

of team members. The findings demonstrate that the attitude of the

team members was somewhat indifferent toward their teaming

experience. The responses from the team members fell between

either agree/disagree (3.0) and agree (4.0) for their overall commit-

ment and positive experience. Although the t-test results did not

show a significant effect, the results are still promising since the

mean scores did not fall below 3.0 (neither agree/disagree). This is

supported by the participants’ response to this question on the self-

evaluation, “I would like to continue to work in teams in the future.”

278 Journal of Engineering Education July 2009

Table 4. One-way ANOVA.

Table 5. One-way ANOVA.

Forty-three percent of the population agreed with this statement

while 17.3 percent strongly agreed. Although the t-test did not

reflect a significant relationship between attitude and behavioral

complexity, the results suggest that team members believe that

teams are a viable option in solving problems.

Research questions in this study revealed which of the four

leadership profiles had the greatest effect on performance. The

results can support educators who design teams in the classroom.

Knowing which leadership skills are most important in an educa-

tional team could potentially improve the team experience and

outcome. Of the four leadership profiles, teams who scored high

in Leading Change, Producing Results, and Managing Processes

had the three highest mean grades. These results reflect the point

in time at which the MBI was administered. Because the surveys

were completed towards the end of the semester and near the pro-

ject deadline, it is reasonable to consider that the participants’

responses reflected “results driven” reactions. The Producing

Results leadership profile focuses on areas such as overall produc-

tion, goal accomplishment, direction, planning, structure, and

competition. The Managing Processes leadership profile focuses

on areas such as controlling projects, ensuring accurate work, clar-

ifying policies, developing measures, maintaining order, overall

coordination, and enforcing. Both profiles fall on the “control”

end of the CVF. It can be assumed that towards the end of pro-

jects, teams are more focused on accomplishing tasks than con-

centrating on skills that allow for more flexibility, such as Relating

to People. While the participants were asked to respond to the

survey by assessing their entire teaming experience, it is possible

that their recollections of more flexible processes could have been

overwhelmed by the pressures to complete the final project. This

might suggest why Relating to People was not significantly

related to grades.

This rationale does not explain the significance of the Leading

Change profile. Teams who scored high in Leading Change had

the highest mean grade of all four profiles. Initially, this did not

appear to be illogical as Leading Change is a flexible process on the

CVF diagram. However, its characteristics do represent skills that

might be beneficial not only towards the end but throughout the

entire teaming experience. Characteristics such as: adaptability,

responsiveness to the external environment (i.e., stakeholders), an-

ticipating customer needs, experimentation, creative problem solv-

ing, searching for improvements, and acquiring needed resources.

The project assigned to the teams focused on changing the current

heating and cooling structure of the building facility. The founda-

tion of the project was rooted in change and the instructor graded

the teams based on their ability to meet the needs of the customer

and their use of creativity and imagination in designing the project.

It is realistic to propose that producing a final product was impor-

tant to the teams, but their creative abilities were just as significant.

A. LimitationsDue to the exploratory nature of this study, certain factors and

conditions had an effect on the results. There are natural limitations

to applying a theoretical framework to teams that has traditionally

been applied to organizations and managers (Belasen, 1997).

Furthermore, the MBI underwent modifications from its initial

publication. The original instrument was extensively used, but the

authors (Lawrence, Quinn and Lenk, 2003) have been working on

a more reliable and valid instrument. The instrument used for this

study has been tested for reliability and validity, but has not yet been

published. In addition, because the tool is in development, a set

criterion cut-off score was not yet determined. As a result, the cut-

off score was set by the current researchers and needs to be further

evaluated and tested. Due to the scoring concerns, the development

of the scoring system may not be an absolute measure of leadership.

Empirically sound decisions were difficult to make in determining

the score, but the decisions were deemed reasonable for the purposes

of this study.

There are also limitations in using a 360� survey. Raters might

not be equipped to fully interpret behaviors of their peers or even

themselves. In addition, their responses are based on memory and

might not be an adequate representation of the leadership profile

that was exhibited. Raters also can inherently feel threatened by

taking the surveys. Although confidentiality was ensured, partici-

pants might not wholly trust the process; therefore, they may not

respond in a truthful way (Hurley, 1998). The 360� process is also

time consuming and survey fatigue can set in. Raters can become

tired and restless when completing the surveys which could result in

inaccurate answers as well (Garavan et al., 1997).

Some could view the lack of widely distributed grades as a limi-

tation of the study. The final project grades for the teams ranged

from 83.7 (B) to 93.0 (A). First, grades can be very subjective. It is

understandable to be wary when using this type of outcome to

identify performance. However, the instructor developed mea-

sures to aid in eliminating some of the biases that do exist when

grading students. The scoring matrix includes input from the stu-

dents’ peers in the form of a peer review evaluation. In addition,

the instructor used seven different components in determining the

grade. These include:

1. Clear expectation of thought

2. Depth of coverage (covers all aspects of RFP)

3. LEED Energy Rating analysis and heating and cooling loads

4. Reasonableness of cost/benefit ratio

5. Meets the needs of the owner

6. Creativity and imagination

7. Grammar, neatness, and professionalism

The relatively high scores of the teams support Fisher’s (1993)

theory that when autonomy is given to teams to make decisions, it

enhances their competitive advantage. Also, the Producing Results

leadership profile focuses on competition, and this was a significant

leadership profile among the teams.

Finally, because of the overarching culture of which the stu-

dents are a part, there are limitations that might restrict their atti-

tudes about teamwork. The United States is an individualist

culture. Between 1967 and 1973, Hofstede (2001) conducted an

extensive study of employees at IBM. Of the 72 countries studies,

it was found that the United States rated first in individualism.

Individualist societies focus on the individual over the interests of

the group. And, in education, the purpose is to allow the student

to be independent. Because education is focused on indepen-

dence, it is possible that the participants of this study could have

had a negative perception of teams. Their perceptions could affect

how they conduct themselves throughout the teaming experience.

The collectivist nature of teams (group before self ) may be in con-

tradiction with the individualist culture which these students have

become accustomed. Hence, the individualistic culture might

affect their attitudes towards working in teams which would then

affect their responses for this study.

July 2009 Journal of Engineering Education 279

B. Recommendations for Further ResearchTaking into consideration the results of the study and the limita-

tions, four recommendations are presented to consider when

replicating this study in the engineering classroom.

1) Population: The researcher should participate in the design

and implementation of the SMTs before collecting data. If imple-

menting this study in the classroom, a collaborative effort should be

made between the investigator and the instructor to create an envi-

ronment that allows for data collection and training throughout the

entire team experience. It should also be determined whether the

findings would be replicated in a class that has a diverse set of engi-

neering disciplines. In this study, the population was vastly similar.

While the results from an analogous population are useful, it would

be worthwhile to discern how team members interact and employ

their leadership skills when placed in teams with individuals from

different disciplines.

2) Measures: It would be valuable to consider additional methods

to further measure attitude and performance. Qualitative data in the

form of interviews or journals might be useful. Further investigation

into the attitudes of team members would determine if teams are

a viable tool in solving classroom and industry problems/projects.

In terms of performance, evaluating the customer on the perfor-

mance of the team would be advantageous. The customer/

stakeholders are essential in the overall success of the team’s produc-

tion (see Figure 2).

3) Survey Design and Data Collection: A firm scoring system

should be implemented for the MBI. Due to the results from the

one-way ANOVA, the cut-off score should be further investigated

to determine who possesses which leadership profile(s) and to re-

solve the point at which low and high behavioral complexity is

determined. It is essential that a scoring system is created that trans-

lates into a clear and easily interpreted score for the investigator and

users. These scores should also be available to the users immediately

so that they can see which leadership profiles they possess. Lastly,

steps should be made to implement the survey online. Doing so will

eliminate some survey fatigue and will lessen the paper load for the

investigator.

The completion of the surveys should be implemented through-

out the entire teaming experience (See Figure 3). Collecting data

throughout the teaming experience will help to reconcile the issues

previously presented and if shared leadership can be accurately

measured.

280 Journal of Engineering Education July 2009

Figure 2. Measures.

Figure 3. Survey design and data collection.

First, the self-evaluation should be applied at the beginning of

the team experience and the results can be used to identify the lead-

ership profiles of individuals prior to their team assignments. Once

the individual is aware of his or her leadership profile score, training

can take place. Training is a critical component of this process

(Barry, 1991) and training will help students understand the leader-

ship skills they possess and how the skills can best be used in a

SMT. The results of the survey may not be effective if team mem-

bers do not comprehend what it means to “Lead Change” or how to

work alongside someone who has a dominant score in “Relating to

People.” Training will allow students to become aware of their own

profiles and the profiles of others within their team. The students

will be able to understand how each profile is significant to the ef-

fectiveness of the team and how to best work with a team member

who has a leadership profile different from their own. This aware-

ness will ideally decrease power struggles, role ambiguity, and

miscommunications that often occur in teams (Zaccaro, 2001).

Overall, this process contributes to the skill development of engi-

neering students which better prepares them for future employers.

Training will not only contribute to the success of the team, it

will also provide more adequate feedback for subsequent surveys.

Once the team members understand the breadth of the profiles,

they can then accurately evaluate themselves and their peers. After

the completion of the self-evaluation and training, the instructor

can then design the teams accordingly so that there are diverse skill

sets within the team.

VI. CONCLUSION

In this article we proposed that applying the Competing Values

Framework to self-managed teams will help engineering educators

understand how to measure leadership within this context. We be-

lieve that it is through the identification and understanding of these

four leadership profiles that engineering students will have an

increased awareness of their role within a team and will consequent-

ly increase effectiveness. This study brings to the forefront the

importance of leadership in engineering teams and how to begin

measuring the effectiveness of leadership within those teams. Data

from this study indicates that leadership roles do matter and should

be considered when designing a team.

Researchers of SMTs and shared leadership have called for fur-

ther research in this area and in response we have taken the charge

in attempting to identify how to best measure leadership in this

context. This study has proposed an instrument that can be used to

identify four key leadership roles to be used in teams; developed the

first phase of a scoring system for the instrument; has provided a

framework and recommendations for measuring leadership in

teams within the classroom; and has addressed many of the confines

associated with this research.

ACKNOWLEDGMENTS

This work was supported by the Engineering Education and

Centers Division of the National Science Foundation (EEC-

0237135). The authors would like to thank the numerous students

who took time to complete the surveys and colleagues who provided

editorial support.

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AUTHORS’ BIOGRAPHIES

Carmen R. Zafft is a Ph.D. student in Human Sciences with a

specialization in Leadership Studies at the University of Nebraska-

Lincoln. She obtained a Master of Science in Leadership Educa-

tion from the University of Nebraska-Lincoln in 2007 and a

Bachelor of Science in Criminal Justice from the University of

Nebraska-Lincoln in 1999. She has also served in various manage-

ment and program development roles for non-profit and

educational agencies both in Pennsylvania and Nebraska.

Address: University of Nebraska-Lincoln, 114 Othmer

Hall/820 N 16th St., P.O. Box 880642, Lincoln, NE 68588-0642;

telephone: (�1) 402.472.4940; e-mail: czafft2@unl.edu.

Stephanie G. Adams is the associate dean of Undergraduate

Studies and an associate professor of Mechanical Engineering at

Virginia Commonwealth University. She previously spent ten

years as a professor of Industrial and Management Systems Engi-

neering at the University of Nebraska-Lincoln. She received her

Ph.D. in Interdisciplinary Engineering from Texas A&M University

in August of 1998. Dr. Adams is an honor graduate of North

Carolina Agricultural and Technical State University where she

earned her B.S. in Mechanical Engineering in 1988. In 1991 she

was awarded the Master of Engineering degree in Systems Engi-

neering from the University of Virginia. Her areas of concentration

were Industrial Engineering and Management. Her research in-

terests include Team Effectiveness, Collaborative and Active

Learning, Engineering Education and Pedagogy, and Quality

Control and Management.

Address: Virginia Commonwealth University, 601 West Main

Street, P.O. Box 843068, Richmond, VA 23284-3068; telephone:

(�1) 804.828.3925; e-mail: sgadams2@vcu.edu.

Gina S. Matkin is an assistant professor of Human Sciences/

Leadership Studies at the University of Nebraska-Lincoln. She

received her Ph.D. in Human Sciences with a specialization in

Leadership Studies at the University of Nebraska-Lincoln in

August of 2005. She graduated Magna cum Laude from Southeast

Missouri State with a B.S. in Biology Education in 1982. In 1989

she was awarded a Master of Science in General Graduate Studies

with emphases in Sociology, Adult Education, and Women’s

Studies. Her research interests include outcomes of intercultural

sensitivity in organizations and communities, diversity and leader-

ship, helping leaders/teachers develop critical thinking in them-

selves and others, and outcomes of using and developing teams in

the classroom.

Address: University of Nebraska-Lincoln, Department of Agri-

cultural Leadership Education and Communication, 300 Ag Hall,

Lincoln, NE 68583-0709; telephone: (�1) 402.472.4454; e-mail:

gmatkin1@unl.edu.

282 Journal of Engineering Education July 2009