Human Factors: The Journal
of the Human Factors and
Ergonomics Society
http://hfs.sagepub.com/
Training Adaptive Teams
Jamie C. Gorman, Nancy J. Cooke and Polemnia G. Amazeen
Human Factors: The Journal of the Human Factors and Ergonomics Society 2010 52: 295 originally
published online 23 July 2010
DOI: 10.1177/0018720810371689
The online version of this article can be found at:
http://hfs.sagepub.com/content/52/2/295
Published by:
http://www.sagepublications.com
On behalf of:
Human Factors and Ergonomics Society
Additional services and information for Human Factors: The Journal of the Human Factors and Ergonomics
Society can be found at:
Email Alerts: http://hfs.sagepub.com/cgi/alerts
Subscriptions: http://hfs.sagepub.com/subscriptions
Reprints: http://www.sagepub.com/journalsReprints.nav
Permissions: http://www.sagepub.com/journalsPermissions.nav
Citations: http://hfs.sagepub.com/content/52/2/295.refs.html
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
>> Version of Record - Sep 14, 2010
OnlineFirst Version of Record - Jul 23, 2010
What is This?
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
SPECIAL ISSUE
Training Adaptive Teams
Jamie C. Gorman and Nancy J. Cooke, Arizona State University–Polytechnic, Mesa,
Arizona, and Polemnia G. Amazeen, Arizona State University, Tempe, Arizona
Objective: We report an experiment in which three training approaches are compared
with the goal of training adaptive teams. Background: Cross-training is an established
method in which team members are trained with the goal of building shared knowledge.
Perturbation training is a new method in which team interactions are constrained to provide new coordination experiences during task acquisition. These two approaches, and a
more traditional procedural approach, are compared. Method: Assigned to three training
conditions were 26 teams. Teams flew nine simulated uninhabited air vehicle missions;
three were critical tests of the team’s ability to adapt to novel situations. Team performance, response time to novel events, and shared knowledge were measured. Results:
Perturbation-trained teams significantly outperformed teams in the other conditions in
two out of three critical test missions. Cross-training resulted in significant increases in
shared teamwork knowledge and highest mean performance in one critical test.
Procedural training led to the least adaptive teams. Conclusion: Perturbation training
allows teams to match coordination variability during training to demands for coordination variability during posttraining performance. Although cross-training has adaptive
benefits, it is suggested that process-oriented approaches, such as perturbation training,
can lead to more adaptive teams. Application: Perturbation training is amenable to simulation-based training, where perturbations provide interaction experiences that teams
can transfer to novel, real-world situations.
INTRODUCTION
In settings ranging from business and manufacturing to military and medical operations,
there are many tasks that are too cognitively
demanding to be performed by individuals
working alone. An example is a surgical task,
which requires a set of highly trained individuals,
including two surgeons, an anesthesiologist
and two nurses, each of whom brings different
cognitive capabilities to the team. But it is not
enough to bring together a set of highly trained
individuals. To function as a team, individuals
must coordinate their activities. Adaptive teams
have the ability to coordinate their activities not
only under routine conditions but also under
novel conditions for which they have not been
explicitly trained. Adaptation is the altering of
structure in accordance with changes in the
environment. Because they have the ability to
change their interactions to match the changing
demands of the environment, adaptive teams
can perform at a high level under novel task
conditions.
A number of relatively recent tragic system
failures can be at least partially attributed to
poor coordination of a team-level response to
environmental uncertainty. System failures attributable to poor team skills at Three Mile Island
and Chernobyl (Gaddy & Wachtel, 1992), social
pathogens behind the 1986 launch decision of
the space shuttle Challenger (Vaughan, 1996),
and lack of communication in the Operation
Provide Comfort friendly fire incident (Gorman,
Cooke, & Winner, 2006; Snook, 2002) each
implicate, in different ways, deficiencies in interaction and coordination that result in a failure to
adapt to changes in the task environment. These
incidents, and others like them, highlight the
need for training that addresses limitations and
Address correspondence to Jamie C. Gorman, Cognitive Engineering Research Institute, 5810 S. Sossaman Rd.,
Ste. 106, Mesa, AZ 85212; jgorman@cerici.org. HUMAN FACTORS, Vol. 52, No. 2, April 2010, pp. 295–307.
DOI: 10.1177/0018720810371689. Copyright © 2010, Human Factors and Ergonomics Society.
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
296
April 2010 - Human Factors
deficiencies at the team level in responding to
novel patterns of events and threats.
Approaches to Training Adaptive Teams
A challenging problem for training team
cognition (i.e., training teams to decide, plan,
think, and act as an integrated unit; Cooke,
Gorman, & Winner, 2007) is how to balance
training for high performance under routine
task conditions with training to adapt to novel
task demands (Marks, Zaccaro, & Mathieu,
2000; Stachowski, Kaplan, & Waller, 2009).
These training goals can be approached with
varying theoretical motives. In this article, we
report an experiment in which three training
approaches, each with a different underlying
theoretical motive, were investigated with the
goal of training teams that perform at a high
level under novel task conditions. The training
approaches include cross-training, procedural
training, and perturbation training.
Cross-training. In cross-training, team members are trained on each other’s roles and responsibilities (e.g., Blickensderfer, Cannon-Bowers,
& Salas, 1998). Cross-training is theoretically
aligned with the idea that team cognition is the
shared knowledge of the team members and is
found widely in the team training literature (see
Salas et al., 2008, and Salas, Nichols, & Driskell,
2007, for recent meta-analyses). The goal of
cross-training is the development of shared, or
interpositional, knowledge (Cannon-Bowers,
Salas, Blickensderfer, & Bowers, 1998; Cooke
et al., 2003; Volpe, Cannon-Bowers, Salas, &
Spector, 1996). Positional clarification (receiving information on other roles), positional modeling (observing other roles), and positional
rotation (firsthand experience performing different roles) (Blickensderfer et al., 1998), which
are types of cross-training, have been effective
in the development of shared knowledge, ultimately improving coordination and team performance (e.g., Marks, Sabella, Burke, & Zacarro,
2002). Cross-training has a firm empirical
grounding and a record of success in the team
training literature, making it a good point of comparison with the other approaches in this study.
One of the potential benefits of cross-training
for shared knowledge is a high level of team
performance under stress (high workload, time
pressure). Drawing on shared knowledge, team
members anticipate each other’s needs to communicate efficiently, or coordinate implicitly,
under stress (Cannon-Bowers et al., 1998; Entin
& Serfaty, 1999; Stout, Cannon-Bowers, Salas, &
Milanovich, 1999). It is thought that shared
expectations, resulting from the development of
shared knowledge, allow team members to generate predictions for appropriate behavior under
novel conditions, enabling them to quickly adapt
to the changing demands of the task environment (Fiore, Salas, & Cannon-Bowers, 2001). A
possible drawback of a shared set of expectations, however, is the habituation of team member
interaction, which could result in dysfunctional
consequences if the situation is highly novel
(e.g., Gersick & Hackman, 1990; Gorman,
Cooke, & Winner, 2006).
Whereas cross-training is feasible for relatively small, homogeneously skilled teams, it
can become impractical as teams grow in diversity and size. For example, it would be impractical to cross-train the surgeon and nurse positions
of an emergency room team (Cooke et al., 2003;
Marks et al., 2002). Also, cross-training may
negatively impact individual-level performance
due to the demands of training for multiple team
member roles (Cannon-Bowers et al., 1998),
which is problematic as teams grow in size.
Although there are adaptive benefits of crosstraining, there are practical limitations to its
applicability.
Procedural training. Procedural training is a
form of process training in which operators in
complex systems are positively reinforced (through
feedback) to follow a standard sequence of actions
(a procedure) each time a particular stimulus is
encountered. The assumption behind procedural
training is that if the procedure is always followed, then errors resulting from human interaction will be reduced and performance will be
enhanced, particularly under conditions of stress
and high workload (e.g., Hockey, Sauer, &
Wastell, 2007; Sauer, Burkholter, Kluge,
Ritzmann, & Schuler, 2008). Procedural training is widely used in aviation, military, medical,
manufacturing, and business settings, in which
deviations from complicated procedures can be
catastrophic. The prevalence of procedural training for coordination in highly critical team tasks
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Training Adaptive Teams
297
(e.g., emergency response; Ford & Schmidt,
2000; Stachowski et al., 2009) make it a good
point of comparison for the other training methods in this study.
Procedural training is compatible with the
concept of “overlearning”: continuation of practice beyond mastery that leads to automatic
responding. Drilling a standard team interaction
pattern, for a specific class of event, over the
entirety of training can lead to an automatic
response that a team can rely on under stress.
The goal of procedural training, as operationalized in the current study, is to overlearn a team
coordination procedure. Ideally, due to overlearning, procedurally trained teams perform
under stress by automatically (reflexively)
reacting with an a priori coordinated response.
Procedural training does not impose the
practical limitations of cross-training but may
limit a team’s ability to transfer training to novel
situations. Similar to the concept of a “set effect”
(Luchins, 1942), procedural training may set teams
up to coordinate in a routine fashion under a
novel condition. We argue, therefore, that like
habituation (Gersick & Hackman, 1990), rigid
proceedure-following during task acquisition
can lead to poor performance when posttraining
conditions do not match training conditions.
Perturbation training. Perturbation training
is a form of process training introduced in this
study. Adopted from the dynamic systems literature, a perturbation is an extrinsic application
of force that briefly disrupts a dynamic process,
forcing the reacquisition of a new stable trajectory, and is typically used to probe the stability
of that process (Gorman, Amazeen, & Cooke,
in press). The concept of perturbation can be
applied to team training by disrupting standard
coordination procedures multiple times during
task acquisition, forcing teams to coordinate in
novel ways to achieve their objective. Unlike
training in which the situation or objectives are
varied (e.g., training for low- vs. high-frequency
circumstances), in perturbation training, critical
coordination links are disrupted while the team
objective remains constant. The goal of perturbation training is to counteract habituation and
procedural rigidity associated with team interactions—possible outcomes of cross-training and
procedural training, respectively—allowing teams
to acquire flexible interaction processes that
will transfer to novel task conditions.
Perturbation training is theoretically inspired
by findings in the motor- and verbal-learning
literatures that suggest that introducing difficulties for the learner, such as practice condition
variability, facilitates performance under novel
posttraining conditions (Schmidt & Bjork,
1992). Perturbation training thus shares some
features of motor schema theory (Schmidt,
1975) and desirable difficulties (Bjork, 1994)
but for coordination and for teams. According
to motor schema theory, varying the conditions
of practice during motor skill acquisition
enhances the “rules” that relate movements to
external task demands. In verbal learning, desirable difficulties are unpredictable and variable
conditions of practice that cause difficulty for
the learner but ultimately enhance the transfer
of concepts to new contexts. Whereas those
approaches employ equally probable but randomly varying training conditions to introduce
practice condition variability, perturbation
training employs abrupt but focused disruptions
to team coordination.
Bjork (1994) argued that varying practice
conditions exercises more elaborate encoding and
retrieval processes needed in the posttraining
environment. Perturbation training extends this
idea to team process: When coordination is perturbed, all team member interactions (not just
those directly affected by the perturbation) must
readjust to accommodate the perturbation in
such a manner that the team objective is nevertheless met (Turvey, 1990). We suggest that similar to the effects of practice condition variability,
perturbations exercise the team processes needed
to adapt in the posttraining environment.
A major limitation of perturbation training is
that it has not previously been applied and its effectiveness is unknown. An experiment described by
Gorman, Cooke, Pedersen, et al. (2006) provided
some empirical grounding for perturbation
training. Teams were initially trained and performed a repetitive command-and-control task
during a 3-hr experimental session. Participants
returned for a second session after a retention
interval, after which they were either intact
(kept the same team members) or mixed (same
role on the team but different team members).
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
298
April 2010 - Human Factors
As expected, intact teams outperformed mixed
teams under routine conditions, but the effect
was short-lived. Mixed teams, however, performed better on tests of situation awareness,
had higher process ratings (Gorman, Cooke,
Pedersen, et al., 2006), and had more flexible
coordination dynamics (Gorman et al., in press).
Those benefits were not attributable to increased
shared knowledge or procedural rigidity but to
increased variation in interaction experience.
In some sense, mixing up the team members
perturbed rigid coordination patterns, ultimately
leading to a more flexible and adaptive team.
Perturbation training, as operationalized in the
current study, does not involve mixing team
members but was designed have the same effect.
By disrupting standard coordination procedures
during task acquisition, perturbation training
increases interaction experience in intact
command-and-control teams.
The Current Study
We compared the three different training
approaches in an uninhabited air vehicle (UAV)
simulator with the goal of producing teams that
perform at a high level under novel task conditions and that respond rapidly to novel events. In
the UAV task, three team members (navigator,
photographer, and pilot) coordinate to take pictures of stationary ground targets. Three training
protocols were developed for cross-training,
perturbation training, and procedural training of
UAV teams. The following hypotheses are
based on prior results and existing literature.
Hypothesis 1: By focusing on introducing varied interaction experiences during task acquisition, perturbation training will result in performance scores and
response times to novel events that are as good as or
better than cross-training and superior to procedural
training.
Hypothesis 2: Because of its focus on training team
members to know each other’s roles and responsibilities, cross-training will result in higher levels of
shared knowledge compared with both procedural
and perturbation training.
Hypothesis 3: By training teams to rigidly follow a
procedure, procedural training will result in the
least adaptive teams (i.e., poor performance and
slow response to novel events) compared with both
perturbation and cross-training.
METHOD
Participants
We recruited 32 three-person teams (96 participants) for participation from Mesa, Arizona,
and surrounding areas. The team members had
no prior experience working together. Participants
ranged in age from 18 to 54 (M = 28), and
71 were male. The experiment occurred during
two 3- to 4-hr sessions. Because of scheduling
conflicts for Session 2, a total of 26 teams
(78 participants) completed both experimental
sessions. Participants were paid $10 per hour,
and each member of the highest-performing
team received a $100 bonus.
Materials and Apparatus
The experiment was conducted in a UAV
synthetic task environment (UAV-STE) for
teams (Cooke & Shope, 2005). Each of the
three team members was seated at a workstation
in front of three computer monitors with a keyboard and a mouse. To interact, team members
wore aviation-quality headsets and communicated by holding down push-to-talk buttons.
The workstations were located in the same room,
configured in a U shape with team members
backs to each other. With the team members
donning headsets, the UAV-STE did not afford
face-to-face interaction.
The team’s task was to take reconnaissance
photographs of stationary ground targets during
a series of nine 40-min missions divided across
two experimental sessions. There were 11 to
12 targets per mission except for one highworkload mission that had 20 targets. The three
team member roles—navigator, photographer,
and pilot—were each associated with different,
yet interdependent tasks, information resources,
and needs.
Measures
Team performance. Performance was measured for each UAV-STE mission as the weighted
composite of several team-level mission parameters, including number of missed targets, time to
process targets, and time spent with unaddressed
warnings and alarms. Cooke, Gorman, Pedersen,
et al. (2007) report the parameter weights, which
were established in previous experiments to
maximize score sensitivity. Teams started each
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Training Adaptive Teams
299
mission with a performance score of 1,000, and
points were subtracted on the basis of final values
of the mission parameters. This team performance score has been validated against other
measures of team process and performance
(Cooke, Gorman, Duran, & Taylor, 2007; Cooke,
Gorman, Pedersen, et al., 2007).
Response time to novel events. Novel events
were introduced within UAV missions by introducing roadblocks. Roadblocks are novel
changes in the task environment that have to be
jointly recognized by two or more team members
who take action to overcome them (e.g., a new
target is introduced, equipment fails, an enemy
threat appears; Cooke, Gorman, & Rowe, 2009;
Gorman, Cooke, & Winner, 2006). Time to overcome roadblocks, defined as the time from the
initiation of the roadblock to the time that action
is taken that overcomes the roadblock, was the
measure of response time to novel events.
Interpositional taskwork knowledge. This
measure assessed a team’s average knowledge
of the taskwork associated with the other two
roles. To measure taskwork knowledge, relatedness ratings (1 = completely unrelated to 5 =
completely related) were elicited for 55 pairs of
concepts from the UAV task (e.g., airspeed,
altitude). Individual team member ratings
were analyzed using the Pathfinder algorithm
(Schvaneveldt, 1990), which translates relatedness ratings across pairs of concepts into a graphical network representation of conceptual
interrelatedness.
Individual networks were compared with
expert role referent networks. The referents were
derived empirically from the top five individual
performers at each role in previous UAV-STE
experiments (Cooke, Gorman, Pedersen, et al.,
2007). Each team member was scored against the
other two role referents on the basis of the proportion of shared links (0 = no similarity to 1 =
exactly similar). Team-level interpositional taskwork knowledge was taken as the average of
these two scores across each of the three team
members. Scores closer to 1 indicated a higher
level of interpositional taskwork knowledge
across team members.
Interpositional teamwork knowledge. This
measure assessed a team’s average knowledge of
the teamwork associated with the other two roles.
Interpositional teamwork knowledge was elicited
with the use of a questionnaire that consisted of 16
items related to which communications were necessary to achieve a given scenario goal (e.g., “For a
priority target, must the photographer communicate camera settings to the navigator, the pilot, or
both?”). Items that were necessary had to be indicated by individual team members using check
marks. To calculate teamwork knowledge, individual responses were compared with role-specific
answer keys that were generated by experimenters
familiar with the task, and points were awarded
for correct answers (Cooke, Gorman, Pedersen,
et al., 2007).
To measure interpositional teamwork knowledge, each team member was scored on the basis
of the proportion correct relative to the answer
key for each of the other two roles. Interpositional
teamwork knowledge was calculated as the average number of these two scores across the three
team members. Scores closer to 1 indicated a
higher level of interpositional teamwork knowledge across team members.
Procedure
When participants arrived for the first session,
they were randomly assigned to a team member
role and the team was assigned to one of the
three training conditions. Participants received
approximately 1 hr 45 min of training via three
PowerPoint training modules and a hands-on
training mission. The first two PowerPoint
modules were identical for all training conditions and covered the general task and interface.
The third module and the hands-on training mission differed on the basis of training condition.
(Procedures for each training condition are
described in the following section.)
Teams then completed Missions 1 through 5.
Knowledge measures were taken after Mission
1. Missions 2 through 4 were condition-specific
training missions (Table 1). The first roadblock
was introduced during Mission 5, the first posttraining mission. The roadblock consisted of
cutting communication from the navigator to
the pilot for 5 min, during which teams had
to reroute navigator-to-pilot communications
through the photographer to overcome the
roadblock. Mission 5 was the first of three critical missions that tested the teams’ ability to perform under novel conditions. The completion of
Mission 5 concluded the first session.
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
300
April 2010 - Human Factors
TABLE 1: Experimental Procedure
Session 1
Session 2
Initial participant training
Mission 1
Knowledge measures
Mission 2T
Mission 3T
Mission 4T
Mission 5 (first roadblock)C
Refresher training
Mission 6 (retention test and second roadblock)C
Knowledge measures
Mission 7
Mission 8
Mission 9 (high workload and two-part roadblock)C
Debriefing
Note. T = condition-specific training mission; C = critical test mission.
Teams returned after 8 to 10 weeks for the
second session. All participants received refresher
training on the software interfaces, after which
teams completed four additional UAV-STE missions. Roadblocks were introduced during each
mission. Mission 6 was the second critical mission, which tested retention of team skill after
the break and included the second roadblock
(a disguised target was hidden on the navigator
map and photographer target list; teams had to
recognize and photograph the target to overcome the roadblock). Knowledge was measured
for a second time after Mission 6 as a test of
knowledge retention.
Teams then completed their final three missions (Missions 7 through 9). Mission 9 was the
high-workload mission, in which the rate of targets per minute was almost doubled from 0.28
to 0.5 and teams were exposed to a two-part
roadblock (communication channel cut for 5 min
from pilot to navigator and from navigator to
pilot; teams had to reroute their communications through open channels to overcome the
roadblock). Mission 9 was the third of the three
critical test missions.
Training Procedure
Cross-training. For the third PowerPoint training module, team members in the cross-training
condition received training on the other two roles
(positional clarification). Teams then completed a
short training mission followed by approximately
15 min of hands-on experience performing all
team member roles (positional rotation). After
Missions 2 through 4, teams in the cross-training
condition were prompted to discuss how well they
performed and to plan for the next mission.
Procedural training. For the third
PowerPoint training module, teams in the
procedural training condition received training on the standard UAV-STE target photographing procedure: (a) The navigator provides
target information to the pilot, (b) the pilot
and photographer negotiate altitude and airspeed for that target, and (c) the photographer provides feedback on the status of the
target photograph (Figure 1). Teams then
completed a short training mission followed
by approximately 15 min of hands-on training using the target photographing procedure. After Missions 2 through 4, teams in the
procedural condition received experimenter
feedback on deviations from the standard
procedure. During training, team members
in the procedural condition were provided
with a hard copy of the target photographing
procedure.
Perturbation training. Teams in the perturbation training condition received filler
PowerPoint training on the history and current
uses of UAVs. Teams then completed a short
training mission followed by approximately
15 min of communications system testing in
which they identified the source of static in the
UAV-STE communication system (i.e., which
push-to-talk button was emanating static).
This training exercise provided experience on
the use of multiple communication paths.
During Missions 2 through 4, teams in the perturbation condition received perturbations to
the target-photographing procedure (Table 2)
as they attempted to photograph targets.
Perturbations were less general than roadblocks
and forced teams to adjust specific interactions
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Training Adaptive Teams
301
Figure 1. Standard photographing procedure for the uninhabited air vehicle synthetic task environment.
TABLE 2: Perturbations to the Standard Uninhabited Air Vehicle Synthetic Task Environment TargetPhotographing Procedure Used for Perturbation Training During Missions 2 Through 4
Link in the
Procedure
Perturbation
Method of Introducing Perturbation
When Introduced
Information
Photographer must
provide target
information to pilot
Experimenter calls in new target restrictions
to photographer and disables camera until
restrictions are communicated to pilot
Once in Mission 2
Once in Mission 3
Twice in Mission 4
Negotiation
Navigator/pilot
must negotiate
airspeed/altitude
Experimenter calls in new airspeed/altitude
of current target to navigator
Once in Mission 2
Once in Mission 3
Twice in Mission 4
Feedback
Photographer does
not provide feedback
to navigator and pilot
Experimenter calls in status of target photo
to navigator and pilot and cuts all
photographer communications
Once in Mission 2
Twice in Mission 3
Twice in Mission 4
relative to the information-negotiation-feedback
procedure (Figure 1).
RESULTS
Of the 26 teams that completed the experiment, there were 10 teams in the procedural
condition and 8 teams each in the cross-training and perturbation conditions. Previous
experiments in the UAV-STE exhibited low
between-subjects power with a = .05 (M = .11,
SD = .05) on tests of team performance due to
small sample size. To increase statistical
power, a significance level of a = .10 was
used. For planned critical test mission comparisons, two conditions were pooled to form a
comparison against a single condition. These
planned comparisons also served to increase
power.
Team Performance
Team performance results are summarized in
Table 3 and graphed in Figure 2. Team performance was analyzed using a 3 (training) × 9
(mission) mixed ANOVA. The main effect of
mission was significant, F(8, 184) = 22.14, p <
.001, MSE = 3535.25, η2 = .53. No other effects
in the omnibus test were significant. A repeated
contrast on mission revealed that performance
increased significantly during initial performance
acquisition until Mission 4. There was a significant drop in performance at Mission 6, after the
retention interval. Performance then improved
significantly as teams reacquired the task, until
Mission 8. Task reacquisition was followed by a
significant drop in performance at Mission 9, the
high-workload mission. These results reinforce
Missions 5, 6, and 9 as critical missions.
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
302
April 2010 - Human Factors
TABLE 3: Mean Team Performance by Training Condition
Mission
Cross-Trained
Perturbation
Procedural
1
2
3
4
5
6
7
8
9
345.04 (65.80)
383.18 (72.89)
422.58 (74.39)
450.54 (77.71)
446.40 (64.41)
435.99 (54.48)
477.79 (77.32)
513.25 (70.94)
389.13 (76.39)
342.78 (54.23)
409.33 (80.94)
463.39 (80.69)
483.76 (59.83)
500.37 (50.93)*
380.30 (166.10)
471.77 (75.38)
547.06 (47.86)
442.24 (36.83)*
316.92 (78.88)
373.90 (65.65)
439.92 (54.71)
447.83 (54.26)
469.63 (46.92)
383.76 (100.91)
421.38 (86.88)
502.47 (58.60)
372.02 (46.00)
Note. Standard deviations in parentheses.
*p < .10.
Reacquisition
600
Critical Test 1
First Roadblock
Acquisition
Team Performance
550
Critical Test 3
High Workload
Critical Test 2
Retention
500
450
400
Cross-Training
Procedural
350
Perturbation
300
1
2
3
4
5
6
7
8
9
Mission
Figure 2. Team performance for each training condition across missions. Adapted from Gorman et al. (2007).
Planned comparisons were performed for
each of the three critical test missions to address
which training condition resulted in the highest
performance under novel conditions. As shown
in Figure 2, perturbation-trained teams exhibited better mean performance in two of the three
critical test missions (Missions 5 and 9),
whereas cross-trained teams exhibited better
mean performance in one of the critical test
missions (Mission 6). Performance of the
perturbation-trained teams at Mission 5 (M =
500.37, SD = 50.93) was significantly better than
the other two conditions (M = 459.31, SD =
54.91), F(1, 24) = 3.23, p = .085, MSE = 2892.21,
η2 = .12. Performance of perturbation-trained
teams at Mission 9 (M = 442.24, SD = 36.83) was
also significantly better than the other two conditions (M = 379.62, SD = 60.00), F(1, 24) = 7.37,
p = .012, MSE = 2945.49, η2 = .24. The crosstraining performance advantage at Mission 6 was
not significant, F(1, 24) = .76, p = .392, MSE =
8379.75, η2 = .03.
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Time to Overcome Roadblock (seconds)
Training Adaptive Teams
303
Interpositional Knowledge
800
Cross-Trained
Perturbation
Procedural
700
600
500
400
300
200
100
0
5 (First Roadblock)
6 (Retention)
9 (High Workload)
Mission
Figure 3. Time to overcome roadblocks by training
condition across the critical missions (error bars represent 90% confidence intervals).
Response Time to Novel Events
Time to overcome roadblocks was analyzed
with a 3 (training) × 3 (critical mission) mixed
ANOVA. One observation was missing from the
cross-training condition. There was a significant
main effect of mission, F(1.53, 33.59) = 119.82,
p < .001, MSE = 16018.63, η2 = .85 (GreenhouseGeisser correction used). The significant mission
effect was attributed to differences in the difficulty of roadblocks. Therefore, no further analyses were performed to isolate that effect. The
main effect of training was also significant, F(2,
22) = 3.53, p = .047, MSE = 19460.72, η2 = .24
(Figure 3).
The planned comparisons at the critical missions revealed that procedural-trained teams
were significantly slower to overcome roadblocks (M = 218.70, SD = 94.34) than were
teams in the other two conditions (M = 146.67,
SD = 103.52) at Mission 5, F(1, 23) = 3.11, p =
.091, MSE = 10005.89, η2 = .12. Teams with
procedural training were also significantly
slower (M = 656.00, SD = 191.01) than those in
the other two conditions (M = 533.07, SD =
98.35) at Mission 6, F(1, 23) = 4.50, p = .045,
MSE = 20164.71, η2 = .16. The same comparison at Mission 9 was not significant. The
Training × Critical Mission interaction was not
significant. Analysis of the measure for time to
overcome roadblock in the noncritical missions
(i.e., Missions 7 and 8) did not reveal any significant differences.
Interpositional teamwork and taskwork
knowledge results are summarized in Table 4.
Interpositional teamwork and taskwork knowledge were separately analyzed with 3 (training) ×
2 (session) mixed ANOVAs. The taskwork
ANOVA did not reveal any significant differences. There was a significant interaction effect
for interpositional teamwork knowledge,
F(2, 23) = 2.70, p = .089, MSE = .01, η2 = .19
(Figure 4). Pooled comparisons revealed that
cross-training (M = .87, SD = .07) led to significantly higher interpositional teamwork knowledge compared with the other two conditions
(M = .78, SD = .08) at Session 2, F(1, 24) = 7.04,
p = .014, MSE = .01, η2 = .23. The same comparison for Session 1 was not significant. The main
effect of session for interpositional teamwork
knowledge was also significant, F(1, 23) = 6.24,
p = .02, MSE = .01, η2 = .21. Although teams in
all training conditions exhibited some increase in
interpositional teamwork knowledge across sessions, teams in the cross-training condition
exhibited a significantly greater increase.
DISCUSSION
Perturbation-trained teams significantly outperformed teams in the other conditions in two
out of three critical test missions, and their
response times to overcome novel roadblock
events were roughly equivalent to cross-trained
teams. These results lend support to our first
hypothesis that perturbation training leads to
high performance under novel conditions.
The results suggest that something similar to
the effects of practice condition variability
(Schmidt & Bjork, 1992) contributed to transfer
at the team level: Perturbation training allowed
teams to generalize performance to novel conditions by forcing the teams to coordinate in
new ways during task acquisition. However,
whereas practice condition variability provides
a range of task conditions for the individual
learner, perturbation training induced coordination variability across team members during
repetitions of the same task. By training teams
to formulate and test new solutions to the problem of coordinating ground targets during task
acquisition, perturbation training actively engaged
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
304
April 2010 - Human Factors
TABLE 4: Mean Interpositional Teamwork and Taskwork Knowledge by Training Condition
Measure
Teamwork
Session 1
Session 2
Taskwork
Session 1
Session 2
Cross-Trained
Perturbation
Procedural
.73 (.12)
.87 (.07)*
.78 (.12)
.79 (.06)
.74 (.11)
.77 (.09)
.47 (.04)
.47 (.01)
.46 (.05)
.48 (.04)
.48 (.05)
.48 (.03)
Note. Standard deviations in parentheses.
*p < .10.
Interpositional Teamwork Knowledge
1
0.9
Cross-Trained
Perturbation
Procedural
0.8
0.7
0.6
0.5
Session 1
Session 2
Figure 4. Interpositional teamwork knowledge by
training condition across knowledge measurement
sessions (error bars represent 90% confidence intervals).
team processes that are needed to adapt to
novel, but related, coordination problems in the
posttraining environment. Because perturbation
training builds on prior novelty, it may also
have allowed teams to develop within a rich
experiential learning environment (Kolb, 1984).
Our second hypothesis was that cross-training
would result in the highest levels of shared
knowledge but that this would not necessarily
result in the best performance under novel task
conditions or the fastest response times to novel
events. Support for that hypothesis was mixed.
Cross-training resulted in greater shared teamwork knowledge in the second session but not
in the first session. This is not a surprise given
that the majority of condition-specific training
took place after the first knowledge measurement session. However, shared taskwork
knowledge did not change across experimental
sessions, regardless of training condition. This
may suggest a ceiling effect, such that taskrelated concept relatedness (e.g., the association
between airspeed and altitude) does not change
after initial participant training.
Cross-training also resulted in highest mean
performance at one of the critical missions (the
retention test) and faster response times for
overcoming roadblocks, although those differences were not significant. It is possible that
with a larger sample size, or a less variable task
environment, cross-training would have resulted
in significant advantages. Marks et al. (2000) found
that development of a shared mental model predicted performance under novel task conditions
better than under routine task conditions. The
retention and roadblock tests are novel conditions unique to our experiment, however, and
further empirical work is needed to better understand the benefits of cross-training and shared
knowledge under these conditions.
The results support our third hypothesis that
procedural training should result in the least
adaptive teams. Procedural training is arguably
the most prevalent form of training for coordinating highly critical team tasks, but its utility
for training adaptive teams has been increasingly called into question (e.g., Ford & Schmidt,
2000; Grote, Kolbe, Zala-Mezö, Bienefeld-Seall,
& Künzle, 2010; Stachowski et al., 2009).
Procedural training need not be limited to a
single, standardized coordination process; assuming that the space of possible future events is
finite, procedures can be scripted for a variety
of foreseeable contingencies. Nevertheless,
given the current results, we argue that teams
trained to automatically follow a standardized
coordination procedure become rigid and slow
to adapt to novel changes in highly dynamic
task environments. Whereas proceduralization
may be good for unchanging and foreseeable
aspects of a task, in training adaptive teams,
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Training Adaptive Teams
305
there should be a match between interaction
variability and the changing dynamics of the
task environment.
We examined team performance under three
critical situations: adaptation to a novel event
(roadblock), after a retention interval, and under
high workload. This is not an exhaustive list of
possibilities. There are many forms of adaptation
for which a team could be trained (e.g., role structure adaptation; Lepine, 2005). The current results
are intuitively plausible, however, given the nature
of mechanisms of team adaptation currently found
in the adaptive team literature, and extend the
idea of process-based adaptability training. The
building and maintenance of shared mental
models are thought to support team adaptation
(Burke, Stagl, Salas, Pierce, & Kendall, 2006;
Stout et al., 1999; Waller, Gupta, & Giambatista,
2004). Indeed, cross-training was successful in
building shared teamwork knowledge, and crosstrained teams exhibited potential for high performance under novel conditions. Parallel to the
motivation for perturbation training, however,
teams directly adapt via flexible interaction processes (Gorman et al., in press; Manser, Harrison,
Gaba, & Howard, 2009; Stachowski et al.,
2009; Waller, 1999). Kozlowski, Gully, Nason,
and Smith (1999) suggested that teams adapt by
selecting an appropriate form of interaction from
a preexisting repertoire or by creating a new
form. Approaches like perturbation training
have the potential to broaden a team’s interaction repertoire not by prescribing preexisting
forms of coordination but by allowing teams to
exercise bottom-up organization of new coordination links.
What are the practical implications for training adaptive teams, and how can we apply
perturbation training? Simulation-based team
training (Dorsey et al., 2009) would allow for
the design of perturbations that focus on specific
events, times, or interactions (Gorman, Cooke, &
Duran, 2009). Simulation-based training can
emphasize physical (equipment) fidelity or cognitive fidelity (how well the simulation exercises
psychological processes required for that task;
Goettle, Ashworth, & Chaiken, 2007). For perturbation training, cognitive fidelity should be
emphasized in order to exercise the team
interaction processes needed for the real-world
task (Bowers & Jentsch, 2001). Another concern is the specifics of introducing perturbations:
when, how many, what kind, and how often?
Simulation-based training would be the ideal
venue for perturbation training, and although
approaches such as crew resource management
(see Salas, Wilson, Burke, & Wightman, 2006)
may use simulators to train for rare or novel
events, our results suggest that more thought
and research should go into identifying the
types of team interaction experiences needed
and the ideal timing of those experiences.
What are the implications of the varying theoretical training motives—shared knowledge,
proceduralization, flexible interactions—for
team cognition? Prevalent in the team cognition
literature is a distinction between knowledge
and process and which contributes most to team
effectiveness (e.g., Cooke, Gorman, & Winner,
2007). We submit that cross-training most
directly impacts knowledge, that perturbation
training most directly impacts process, and that
procedural training may have little impact on
either. The current study is not an unequivocal
test of knowledge versus process accounts
of team cognition, nor is it an exhaustive sampling of variations on procedural, perturbation,
or cross-training in a variety of contexts.
Nonetheless, the results do suggest that training
focused on process may contribute something
to team effectiveness that a knowledge-focused
approach does not.
CONCLUSION
The details of team adaptation are not specified at the outset of a novel event. The details
accrue gradually, during the process of adaptation, and there lies the problem for training
adaptive teams: They must be able to decide,
plan, think, and act under conditions never experienced. Adaptation is the altering of structure
in accordance with environmental change and,
under many circumstances, is not a purely topdown, knowledge-driven process. Teams should
be provided opportunities to exercise adaptive
competency using not only top-down (knowledgefocused) training but also bottom-up (processoriented) training. Perturbing coordination as
team members interact is one means of eliciting
the bottom-up, process-oriented flexibility that
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
306
April 2010 - Human Factors
teams need in order to adapt. Future research
should continue to explore mechanisms of flexible team interaction and how teams use them to
adapt to the pressures of highly dynamic,
high-stakes work environments.
ACKNOWLEDGMENTs
This research was funded by Air Force Office
of Scientific Research Grant FA9550-04-1-0234
and Air Force Research Laboratory Grant
FA8650-04-6442; additional support came from
National Science Foundation Grant BCS 0447039.
The authors would like to thank the following
individuals who contributed to this research:
Dee Andrews, Christy Caballero, Olena Connor,
Jasmine Duran, Preston Kiekel, Harry Pedersen,
Steven Shope, Amanda Taylor, and Jennifer
Winner. Some team performance results were
previously reported in a technical report (Cooke,
Gorman, Pederson, et al., 2007) and a conference proceeding paper (Gorman et al., 2007).
REFERENCES
Bjork, R. A. (1994). Memory and metamemory considerations in
the training of human beings. In J. Metcalfe & A. Shimamura
(Eds.), Metacognition: Knowing about knowing (pp. 185–205).
Cambridge, MA: MIT Press.
Blickensderfer, E., Cannon-Bowers, J. A., & Salas, E. (1998).
Cross-training and team performance. In J. A. Cannon-Bowers
& E. Salas (Eds.), Making decisions under stress: Implications
for individual and team training (pp. 299–311). Washington, DC:
American Psychological Association.
Bowers, C. A. & Jentsch, F. (2001). Use of commercial, off-theshelf, simulations for team research. In E. Salas (Ed.), Advances
in human performance and cognitive engineering research
(Vol. 1., pp. 293–317). Amsterdam, Netherlands: Elsevier Science.
Burke, C. S., Stagl, K. C., Salas, E., Pierce, L., & Kendall, D.
(2006). Understanding team adaptation: A conceptual analysis
and model. Journal of Applied Psychology, 91, 1189–1207.
Cannon-Bowers, J. A., Salas, E., Blickensderfer, E., & Bowers, C. A.
(1998). The impact of cross-training and workload on team
functioning: A replication and extension of initial findings.
Human Factors, 40, 92–101.
Cannon-Bowers, J. A., Salas, E., & Converse, S. (1993). Shared
mental models in expert team decision making. In N. J. Castellan
(Ed.), Individual and group decision making (pp. 221–246).
Hillsdale, NJ: Erlbaum.
Cooke, N. J., Gorman, J. C., Duran, J. L., & Taylor, A. R. (2007).
Team cognition in experienced command-and-control teams.
Journal of Experimental Psychology: Applied, 13, 146–157.
Cooke, N. J., Gorman, J. C., Pedersen, H. K., Winner, J., Duran, J.,
Taylor, A., Amazeen P. G., Andrews, D., & Rowe, L. (2007).
Acquisition and retention of team coordination in commandand-control (Technical Report for AFOSR Grant FA9550-041-0234 and AFRL Award No. FA8650-04-6442). Washington,
DC: Department of Defense.
Cooke, N. J., Gorman, J. C., & Rowe, L. J. (2009). An ecological
perspective on team cognition. In E. Salas, J. Goodwin, &
C. S. Burke (Eds.), Team effectiveness in complex organizations:
Cross-disciplinary perspectives and approaches (pp. 157–182).
New York, NY: Taylor and Francis.
Cooke, N. J., Gorman, J. C., & Winner, J. L. (2007). Team cognition. In F. Durso, R. Nickerson, S. Dumais, S. Lewandowsky,
& T. Perfect (Eds.), Handbook of applied cognition (2nd ed.,
pp. 239–268). New York, NY: Wiley.
Cooke, N. J., Kiekel, P. A., Salas, E., Stout, R. J., Bowers, C.,
& Cannon-Bowers, J. (2003). Measuring team knowledge:
A window to the cognitive underpinnings of team performance. Group Dynamics: Theory, Research and Practice, 7,
179–199.
Cooke, N. J., & Shope, S. M. (2005). Synthetic task environments
for teams: CERTT’s UAV-STE. In N. Stanton, A. Hedge, K.
Brookhuis, E. Salas & H. Hendrick (Eds.), Handbook of
Human Factors and Ergonomics Methods (pp. 46-41-46-46).
Boca Raton, FL: CRC Press.
Dorsey, D., Russell, S., Keil, C., Campbell, G., Van Buskirk, W., &
Schuck, P. (2009). Measuring teams in action: Automated performance measurement and feedback in simulation-based
training. In E. Salas, G. F. Goodwin, & C. S. Burke (Eds.), Team
effectiveness in complex organizations: Cross-disciplinary
perspectives and approaches (pp. 351–381). New York, NY:
Taylor and Francis.
Entin, E. E. & Serfaty, D. (1999). Adaptive team coordination.
Human Factors, 41, 312-325.
Fiore, S. M., Salas, E., & Cannon-Bowers, J. A. (2001). Group
dynamics and shared mental model development. In M. London
(Ed.), How people evaluate others in organizations (pp. 309–
336). Mahwah, NJ: Erlbaum.
Ford, J. K., & Schmidt, A. M. (2000). Emergency response training:
Strategies for enhancing real-world performance. Journal of
Hazardous Materials, 75, 195–215.
Gaddy, C. D., & Wachtel, J. A. (1992). Team skills training in
nuclear power plant operations. In R. W. Swezey & E. Salas
(Eds.), Teams: Their training and performance (pp. 379–396).
Norwood, NJ: Ablex.
Gersick, C. J. G., & Hackman, J. R. (1990). Habitual routines in
task-performing groups. Organizational Behavior and Human
Decision Processes, 47, 65–97.
Goettle, B. P., Ashworth, A. R. S., III, & Chaiken, S. R.
(2007). Advanced distributed learning for team training in
command and control applications. In S. M. Fiore & E. Salas
(Eds.), Toward a science of distributed learning (pp. 93–117).
Washington, DC: American Psychological Association.
Gorman, J. C., Amazeen, P. G., & Cooke, N. J. (in press). Team
coordination dynamics. In Nonlinear dynamics, psychology
and life sciences.
Gorman, J. C., Cooke, N. J., Amazeen, P. G., Winner, J. L.,
Duran, J. L., Pedersen, H. K., & Taylor, A. R. (2007).
Knowledge training versus process training: The effects of
training protocol on team coordination and performance. In
Proceedings of the Human Factors and Ergonomics Society
50th Annual Meeting (pp. 382–387). Santa Monica, CA:
Human Factors and Ergonomics Society.
Gorman, J. C., Cooke, N. J., & Duran, J. L. (2009). Development
of simulated team environments for measuring team cognition
and performance. In D. Schmorrow, J. Cohen, & D. Nicholson
(Eds.), PSI handbook of virtual environments for training and
education (pp. 347–361). Westport, CT: Praeger Security
International.
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Training Adaptive Teams
307
Gorman, J. C., Cooke, N. J., Pedersen, H. K., Winner, J. L.,
Andrews, D., & Amazeen, P. G. (2006). Changes in team composition after a break: Building adaptive command-and-control
teams. In Proceedings of the Human Factors and Ergonomics
Society 49th Annual Meeting (pp. 487–491). Santa Monica,
CA: Human Factors and Ergonomics Society.
Gorman, J. C., Cooke, N. J., & Winner, J. L. (2006). Measuring
team situation awareness in decentralized command and control environments. Ergonomics, 49, 1312–1325.
Grote, G., Kolbe, M., Zala-Mezö, E., Bienefeld-Seall, N., &
Künzle, B. (2010). Adaptive coordination and heedfulness
make better cockpit crews. Ergonomics, 53, 211–228.
Hockey, G. R. J., Sauer, J., & Wastell, D. G. (2007). Adaptability of
training in simulated process control: Knowledge- versus rulebased guidance under task changes and environmental stress.
Human Factors, 49, 158–174.
Kolb, D. A. (1984). Experiential learning: Experience as the
source of learning and development. Englewood Cliffs, NJ:
Prentice Hall.
Kozlowski, S. W. J., Gully, S. M., Nason, E. R., & Smith, E. M.
(1999). Developing adaptive teams: A theory of compilation
and performance across levels and time. In D. R. Ilgen &
E. D. Pulakos (Eds.), The changing nature of work and performance: Implications for staffing, personnel actions, and development (pp. 240–292). San Francisco, CA: Jossey-Bass.
Lepine, J. A. (2005). Adaptation of teams in response to unforeseen
change: Effects of goal difficulty and team composition in
terms of cognitive ability and goal orientation. Journal of
Applied Psychology, 90, 1153–1167.
Luchins, A. S. (1942). Mechanization in problem solving.
Psychological Monographs, 54(248).
Manser, T., Harrison, T. K., Gaba, D. M., & Howard, S. K. (2009).
Coordination patterns related to high clinical performance in a
simulated anesthetic crisis. International Anesthesia Research
Society, 108, 1606–1615.
Marks, M. A., Sabella, M. J., Burke, C. S., & Zaccaro, S. J. (2002).
The impact of cross-training on team effectiveness. Journal of
Applied Psychology, 87, 3–13.
Marks, M. A., Zaccaro, S. J., & Mathieu, J. E. (2000). Performance
implications of leader briefings and team-interaction training
for team adaptation to novel environments. Journal of Applied
Psychology, 85, 971–986.
Sauer, J., Burkolter, D., Kluge, A., Ritzmann, S., & Schuler, K.
(2008). The effects of heuristic rule training on operator
performance in a simulated process control environment.
Ergonomics, 51, 953–967.
Salas, E., DiazGranados, D., Klein, C., Burke, C. S., Stagl, K. C.,
Goodwin, G. F., & Halpin, S. M. (2008). Does team training
improve team performance? A meta-analysis. Human Factors,
50, 903–933.
Salas, E., Nichols, D., & Driskell, J. E. (2007). Testing three team
training strategies in intact teams: A meta-analysis. Small
Group Research, 38, 471–488.
Salas, E., Wilson, K. A., Burke, C. S., & Wightman, D. C. (2006).
Does crew resource management training work? An update, an
extension, and some critical needs. Human Factors, 48,
392–412.
Schmidt, R. A. (1975). A schema theory of discrete motor skill
learning. Psychological Review, 82, 225–260.
Schmidt, R. A., & Bjork, R. A. (1992). New conceptualizations of
practice: Common principles in three paradigms suggest new
concepts for training. Psychological Science, 3, 207–217.
Schvaneveldt, R. W. (1990). Pathfinder associative networks:
Studies in knowledge organization. Norwood, NJ: Ablex.
Snook, S. A. (2002). Friendly fire: The accidental shootdown of
U.S. black hawks over northern Iraq. Princeton, NJ: Princeton
University Press.
Stachowski, A. A., Kaplan, S. A., & Waller, M. J. (2009). The benefits of flexible team interaction during crises. Journal of
Applied Psychology, 94, 1536–1543.
Stout, R. J., Cannon-Bowers, J. A., Salas, E., & Milanovich, D. M.
(1999). Planning, shared mental models, and coordinated performance: An empirical link is established. Human Factors,
41, 61–71.
Turvey, M. T. (1990). Coordination. American Psychologist, 45,
938–953.
Vaughan, D. (1996). The Challenger launch decision: Risky technology, culture, and deviance at NASA. Chicago, IL: University
of Chicago Press.
Volpe, C. E., Cannon-Bowers, J. A., Salas, E., & Spector, P. E.
(1996). The impact of cross-training on team functioning: An
empirical investigation. Human Factors, 38, 87-100.
Waller, M. J. (1999). The timing of adaptive group responses to
nonroutine events. Academy of Management Journal, 42,
127–137.
Waller, M. J., Gupta, N., & Giambatista, R. C. (2004). Effects of
adaptive behaviors and shared mental models on control crew
performance. Management Science, 50, 1534–1544.
Jamie C. Gorman received his PhD in cognitive
psychology from New Mexico State University,
Las Cruces, in 2006 and is a postdoctoral research
associate at Arizona State University–Polytechnic
and the Cognitive Engineering Research Institute in
Mesa, Arizona. Beginning August 2010, he will be
an assistant professor in the Human Factors Program
at Texas Tech University.
Nancy J. Cooke received her PhD in cognitive
psychology from New Mexico State University,
Las Cruces, in 1987 and is a professor in applied
psychology at Arizona State University–Polytechnic
and science director of the Cognitive Engineering
Research Institute in Mesa, Arizona.
Polemnia G. Amazeen received her PhD in experimental psychology from the University of Connecticut,
Storrs, in 1996 and is an associate professor in psychology at Arizona State University, Tempe, and a faculty research associate at the Cognitive Engineering
Research Institute in Mesa, Arizona.
Date received: May 13, 2009
Date accepted: March 29, 2010
Downloaded from hfs.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Small http://sgr.sagepub.com/
Group Research
Does Team Building Work?
Cameron Klein, Deborah DiazGranados, Eduardo Salas, Huy Le, C. Shawn
Burke, Rebecca Lyons and Gerald F. Goodwin
Small Group Research 2009 40: 181 originally published online 6 January 2009
DOI: 10.1177/1046496408328821
The online version of this article can be found at:
http://sgr.sagepub.com/content/40/2/181
Published by:
http://www.sagepublications.com
Additional services and information for Small Group Research can be found at:
Email Alerts: http://sgr.sagepub.com/cgi/alerts
Subscriptions: http://sgr.sagepub.com/subscriptions
Reprints: http://www.sagepub.com/journalsReprints.nav
Permissions: http://www.sagepub.com/journalsPermissions.nav
Citations: http://sgr.sagepub.com/content/40/2/181.refs.html
>> Version of Record - Mar 10, 2009
OnlineFirst Version of Record - Jan 6, 2009
What is This?
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Does Team Building Work?
Cameron Klein
Deborah DiazGranados
Eduardo Salas
Huy Le
C. Shawn Burke
Rebecca Lyons
Small Group Research
Volume 40 Number 2
April 2009 181-222
© 2009 SAGE Publications
10.1177/1046496408328821
http://sgr.sagepub.com
hosted at
http://online.sagepub.com
University of Central Florida
Gerald F. Goodwin
Army Research Institute
This research reports the results of a comprehensive investigation into the
effectiveness of team building. The article serves to update and extend Salas,
Rozell, Mullen, and Driskell’s (1999) team-building meta-analysis by assessing a larger database and examining a broader set of outcomes. Our study
considers the impact of four specific team-building components (goal setting,
interpersonal relations, problem solving, and role clarification) on cognitive,
affective, process, and performance outcomes. Results (based on 60 correlations) suggest that team building has a positive moderate effect across all
team outcomes. In terms of specific outcomes, team building was most
strongly related to affective and process outcomes. Results are also presented
on the differential effectiveness of team building based upon the team size.
Keywords:
team building; team performance; team development
Teams of people working together for a common cause touch all our lives.
From everyday activities like air travel, fire fighting, and running the United
Way drive to amazing feats of human accomplishment like climbing Mt.
Everest and reaching for the stars, teams are at the center of how work gets
done in modern life.
Kozlowski & Ilgen, 2006, p. 78
This quote, from a recent review of work-team effectiveness, exemplifies
the central role that teams play in our lives. Although many labels have
been applied to team-based forms of organizing (i.e., crews, teams, groups,
and collectives), these entities are essential to the accomplishment of organizational goals. Indeed, there is ample support in the literature for the
181
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
182
Small Group Research
contention that team-based forms of organizing are beneficial both to
organizations and to individuals. For example, Applebaum and Batt (1994)
reviewed 12 large-scale surveys and 185 case studies of managerial practices and concluded that team-based work leads to improvements in organizational performance on measures of both efficiency and quality. They
argued that team-based systems benefit workers because of the higher likelihood of job enhancement, autonomy, and skill development associated
with these systems. However, the simple existence of a team-based organizing structure is not enough to ensure that positive outcomes will result.
Teams must be nurtured, supported, and developed.
The Motivation for Understanding the
Efficacy of Team Building
There are three motivations for understanding the efficacy of teambuilding interventions in organizations. First, team building is one of the
most commonly applied group development interventions in organizations
today. It is widely used and comes in many forms, including outdoor experiential activities and indoor group process discussions. However, no one is
quite sure how and why these interventions work, or if they even work at
all. Considering the vast sum of money directed toward the development of
teams in organizations, it is important that practitioners (and researchers)
gain a better understanding of the effectiveness and boundary conditions of
team building.
Second, as there are many options available to organizations in the
pursuit of improved teamwork, it is important to determine whether team
building is a worthy choice. Some of these interventions are organizational
Authors’ Note: This work was partially supported by funding from the U.S. Army Research
Institute for the Behavioral and Social Sciences (Contract W74V8H-04-C-0025) and grant
SES0527675 from the National Science Foundation, awarded to Glenn Harrison, Stephen M.
Fiore, Charlie Hughes, and Eduardo Salas. All opinions expressed in this article are those of
the authors and do not necessarily reflect the official opinion or position of the University of
Central Florida, the Department of the Army, the Department of Defense, or the National
Science Foundation. Portions of the article were presented at the 2nd Annual Conference of
the Interdisciplinary Network for Group Research (INGRoup) held at Michigan State
University, in Lansing, Michigan. Correspondence concerning this article should be addressed
to: Dr. Eduardo Salas, Institute for Simulation & Training, University of Central Florida, 3100
Technology Parkway, Suite 132, Orlando, FL 32826, USA. Tel: (407) 882-1325; fax: (407)
882-1550; e-mail: esalas@ist.ucf.edu.
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
183
or structural in nature and do not specifically target team member interactions (e.g., job redesign, selection systems, and group incentive and
performance management programs). In contrast, team-development interventions—those whose quest is to directly impact the functioning and
effectiveness of work teams—provide the focus for the current research
integration. These interventions, when properly conducted, can have a
positive impact on organizations. Consider a research study conducted by
Macy and Izumi (1993), who analyzed 131 studies of organizational
change. They found that interventions with the largest effects upon financial measures of organizational performance were team-development
interventions. That is, of all organizational interventions, those that focus
on team development had the largest effect on measures of financial
performance.
Third, beyond financial performance, it is widely understood that team
developmental interventions are key mechanisms that may be used to facilitate team effectiveness (Noe, 2002). Therefore, it is important to understand how these interventions are most effective. At a general level,
team-development interventions may include some form of team-training
or team-building activities. Although both types of team-development interventions are designed to improve team functioning and effectiveness (especially when the science of individual and team training is utilized; Salas &
Cannon-Bowers, 1997), team training and team building differ in important
ways (Tannenbaum, Beard, & Salas, 1992). Team training is skill-focused
(i.e., it is focused on gaining specific competencies), typically includes a
practice component, and is done in context. It is generally formal and
systematic. Team building, on the other hand, does not target skill-based
competencies, is not systematic in nature, and is typically done in settings
that do not approximate the actual performance environment. For our purposes, we define team building as a class of formal and informal team-level
interventions that focus on improving social relations and clarifying roles,
as well as solving task and interpersonal problems that affect team functioning. Team building works by assisting individuals and groups to examine, diagnose, and act upon their behavior and interpersonal relationships
(Schein, 1969, 1999).
In light of the above, this article investigates the efficacy of team building.
We begin with a brief review of conceptual issues and methodological issues
in team building. Next, the hypotheses for this research are presented.
Finally, the results of several meta-analytic integrations are discussed. First,
however, is the rationale for the present research.
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
184
Small Group Research
Understanding the Need for an Update
It is an unfortunate indictment of the literature and practice in this area
that we are still searching for answers to questions posed by Beer (1976)
and Salas, Rozell, Mullen, and Driskell (1999). Namely, does team building result in positive outcomes? Why? Under what conditions? Upon a
careful review of the extent literature, it is clear that these questions need to
be examined more closely to clarify our understanding of the effectiveness
and boundary conditions of team building. Thus, this article reports the
findings from a series of meta-analytic investigations of research on the
efficacy of team-building interventions to update and extend the current
state of knowledge in the team-building domain. In total, this research will
examine three moderator variables in addition to making an overall assessment of the efficacy of team-building interventions. The current replication
is meant to be systematic, rather than direct in nature (e.g., Aronson,
Ellsworth, Carlsmith, & Gonzales, 1990). That is, rather than replicating
the exact analyses from the study by Salas and colleagues, the current
research will replicate and extend the earlier study in an effort to resolve
ambiguities and provide new insights for organizational stakeholders and
academicians alike concerning the effectiveness of team building.
Although the empirical evidence on team-building interventions is limited, a critical investigation of the available literature is warranted for several reasons. First, since the 1990s there has been an increasing incursion
of team-building interventions in organizations. Some of the most recent
trends in team building have taken these interventions into the kitchen and
even the wilderness. Second, many practitioners feel that these interventions are useful. However, a more careful exploration of the utilities and
strengths of these interventions would benefit practitioners now and would
benefit the development of these interventions in the long run. Finally, there
are enough data available to form estimates regarding some of the variables
that may moderate the impact a team-building intervention may have on
team outcomes.
There is a general consensus for the idea that the science of team training can be applied to enhance team functioning across organizations (e.g.,
Kozlowski & Ilgen, 2006; Salas & Cannon-Bowers, 1997). At the same
time, reviews of team effectiveness have noted the inconsistent findings for
the effectiveness of team-building interventions. Despite these inconsistent
findings, researchers such as Kozlowski and Ilgen have acknowledged the
potential that these interventions may have on shaping team development
and on improving team effectiveness. Given the increasing frequency of
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
185
team-building interventions, if researchers do not catch up and start doing
this research, an important window might be missed to constructively shape
the important practice in this area. Thus, examining team building further—
a topic that has not received recent sufficient attention in the literature—is
critical. In the next section, a number of conceptual and methodological
issues in team building are discussed.
Team Building
Conceptual Issues in Team Building
Originally designed as a group process intervention (e.g., Schein, 1969,
1999) for improving interpersonal relations and social interactions, team
building has evolved to also include a concern for achieving results, meeting goals, and accomplishing tasks (Payne, 2001). In the late 1990s, Salas
and colleagues (1999) described team-building interventions as extremely
popular and common. According to Beer (1976), there are four basic
approaches to team building, including: (a) a goal-setting, problem-solving
model; (b) an interpersonal model; (c) a role model; and (d) the Managerial
Grid (Blake & Mouton, 1964) model. However, this initial conceptualization has since been reconsidered.
Refinements to this four-pronged system began with the Managerial Grid
model being dropped as a distinct team-building approach. In addition to
dropping the Managerial Grid model, modern conceptualizations have separated the goal-setting and problem-solving approaches, using Buller’s
(1986) problem-solving component as a distinct approach. As discussed by
Buller, team-building models rarely exist in pure form. That is, the interventions reported in the literature usually involve elements from several or all of
the models. As a result, he proposed a general problem-solving model that
follows Dyer’s (1977) problem-solving framework. This model incorporates
a focus on task or interpersonal issues, goal setting, and role clarification,
depending on the nature of the specific problems identified for the group
under investigation. Moreover, the problem-solving approach to team building is said to subsume each of Beer’s (1976) components, and, as perhaps
evident by its title, emphasizes the identification of major problems in the
team. All told, these modifications have added clarity to the investigation
and implementation of team building. Unfortunately, this newfound conceptual clarity may not have come soon enough for many investigators who had
previously sought to assess the efficacy of team building.
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
186
Small Group Research
Perhaps because of the conceptual confusion that existed in this area,
many reviews of team building did not include the same articles. For example
two noteworthy reviews (DeMeuse & Liebowitz, 1981; Woodman &
Sherwood, 1980) had only 14 studies in common out of a total of 66 studies
reviewed. A subsequent review by Buller (1986) included only 9 studies, 3 in
common with Woodman and Sherwood (1980) and 6 in common with
DeMeuse and Liebowitz. One reason for the apparent lack of consistency in
the articles chosen for reviews is that team building has been an ill-defined
concept (Buller, 1986). At the time of these early reviews there was no
agreed-upon operational definition of the intervention. Taken together, there
is now a consensus position that there exist four distinct models of team
building. Although combinations of these approaches are common, the
models include goal-setting, developing interpersonal relations, clarifying
roles, and creating additional capacity for problem solving (Beer, 1976;
Buller, 1986; Dyer, 1987; Salas et al., 1999). Table 1 describes each of the
four models or components of team building in more detail.
Despite the recently established consensus on team-building components, there have been other problematic issues that have persisted for
researchers and practitioners of this topic. Specifically, many early efforts
were plagued by a number of methodological issues. A few of these are discussed in the next section.
Methodological Issues in Team Building
Early reviews of team building described both a lack of extensive research
on the issue and trepidation concerning the methodological rigor of published
studies (Buller, 1986; DeMeuse & Liebowitz, 1981; Tannenbaum et al.,
1992; Woodman & Sherwood, 1980). That is, even if one could get beyond
the disagreement concerning operational definitions of team building,
much of the previous team-building research is characterized by methodological flaws (i.e., study design and measurement issues). For example,
Buller (1982) found that more than half of the reported team-building studies
employed pre-experimental designs—designs that do not allow for causal
inferences. Also problematic, there was often no attempt to disentangle the
effects of team building from other interventions that may be in process
within an organization. Although this can be a common problem for field
research in general, it has been particularly problematic in the team-building
domain.
Tannenbaum and colleagues (1992) highlighted another methodological
flaw in the team-building research. Specifically, they pointed out that there
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
187
Table 1
Models/Components of Team Building
Component
Goal setting
Salas, Rozell, Mullen,
& Driskell, 1999
Salas, Priest, &
DeRouin, 2005
Emphasis: Setting objectives
and development of
individual and team goals.
Team members: Become involved
in action planning to identify
ways to achieve goals.
Designed to strengthen team member
motivation to achieve team goals
and objectives.
By identifying specific outcome
levels, teams can determine what
future resources are needed.
Individual characteristics (e.g., team
member motivation) can also be
altered by use of this intervention.
Interpersonal Emphasis: Increasing teamwork
Based on the assumption that teams
relations
skills (i.e., mutual supportiveness,
with fewer interpersonal conflicts
communication, and sharing
function more effectively than
of feelings).
teams with greater numbers of
Team members: Develop trust in
interpersonal conflicts.
one another and confidence
Requires the use of a facilitator to
in the team.
develop mutual trust and open
communication between team
members.
As team members achieve higher
levels of trust, cooperation, and
cohesiveness, team characteristics
can be changed as well.
Role
Emphasis: Increasing communication Defines the team as comprising a set
clarification
among team members regarding
of overlapping roles.
their respective roles within
These overlapping roles are
the team.
characterized as the behaviors that
Team members: Improve
are expected of each individual
understanding of their own and
team member.
others’ respective roles and duties Can be used to improve team and
within the team.
individual characteristics (i.e., by
reducing role ambiguity) and work
structure by negotiating, defining,
and adjusting team member roles.
Problem
Emphasis: Identifying
Buller’s (1986) problem-solving
solving
major task-related problems
component subsumes aspects from
within the team.
all of the components described by
Team members: Become involved
Beer (1976).
in action planning, implement
Team members practice setting goals,
solutions to identify problems
develop interpersonal relations,
clarify team roles, and work to
(continued)
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
188
Small Group Research
Table 1 (continued)
Component
Salas, Rozell, Mullen,
& Driskell, 1999
and to evaluate those
solutions.
Salas, Priest, &
DeRouin, 2005
improve organizational
characteristics through
problem-solving tasks.
Can have the added benefit of
enhancing critical-thinking skills.
has been a reliance on measuring the effectiveness of team-building interventions with process measures. Although implicitly appealing, improvements in processes can not always be linked to improvements in team
performance (e.g., Porras & Wilkens, 1980). For example, team performance is typically fashioned by additional environmental and/or organizational characteristics and contingencies that are out of the volitional control
of team members. Stated differently, team members are active participants
in the enactment of team processes, but must also interact within the larger
system to produce more distal performance outputs. Team processes may
also be impacted by the larger organizational environment, but not likely to
the same degree as team performance outputs.
As a final methodological concern with previous team-building
research, there has been an overreliance on subjective indicators of group
or organizational performance criteria as dependent measures (Tannenbaum
et al., 1992). Though this type of information may be interesting and relevant to measuring participant satisfaction and other affective outcomes that
may be impacted by team-building interventions, it is often not concrete
enough to allow for accurate predictions of the performance outcomes of
team building.
A Recent Advancement in Team-Building Research
Despite the conceptual and methodological issues associated with evaluations of team building, one recent effort has represented advancement
over previous reviews by empirically investigating the effectiveness of
these interventions. Specifically, Salas and colleagues (1999) responded to
a call by Buller (1986) to use the primary focus of the intervention
(i.e., goal setting, interpersonal relations, role clarification, and problem
solving) as a potential moderating variable. The results of their study failed
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
189
to indicate a relationship between the combined set of team-building interventions and team performance (r = .01, k = 16 effect sizes). Moreover, of
the four components of team building, only role clarification proved to be
effective, as judged by both objective (r = .71) and subjective (r = .75)
accounts of performance. Interestingly, for objective and subjective measures there was a nonsignificant effect of goal setting (r = −.06 and −.11,
respectively), interpersonal relations (r = −.38 and −.04, respectively), and
problem solving (r = −.31 and .09, respectively). Also examined in this
study were the potential moderating influences of the source of the criterion
measurement of performance (i.e., objective vs. subjective), team size, and
training duration. For objective measures of performance, there was no evidence of a relationship between team building and performance (r = −.04,
k = 8); for subjective measures, there was a small positive relationship
between team building and performance (r = .14, k = 8). Concerning team
size, the results of their study suggested that the effects of team building on
performance decreased as a function of the size of the team (r = −.34).
Finally, there was a slight tendency for the effects of team building to
decrease as a function of the duration of the intervention (r = −.20).
Taken together, this study enhanced our understanding of the efficacy of
team building. However, there were a number of limitations associated with
it—limitations that now necessitate the need for additional inquiry. For
example, the amount of data analyzed in this study was relatively modest.
Specifically, the research findings presented were based on only 16 effect
sizes, and thus, it is difficult to discern, with any degree of confidence, the
actual effectiveness of these interventions. Moreover, the findings derived
from the Salas and colleagues’ (1999) study did not necessarily reflect the
findings from existing narrative reviews. Finally, their study left many
questions unanswered regarding the potential moderating impact of other
relevant variables. As an organizing tool provided to summarize the literature in this area, Table 2 provides a summary of five previous investigations
into the efficacy of team building, and includes the number of articles
reviewed, the years spanned, and other noteworthy features.
In summary the current research was initiated to provide an updated
meta-analysis of the team-building literature. Phrased in the form of questions, an examination of these issues will help clarify our understanding of
the effectiveness of team building and lead to hypothesized relationships
involving the effectiveness of team building, including an investigation of
specific moderators. A model that serves to graphically illustrate these
hypotheses is presented in Figure 1.
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
190
Small Group Research
Table 2
Summary of Previous Team-Building Reviews
Review
Study
Details
Woodman & 30 articles
Sherwood
(1980)
Qualitative
data
Summary of
Findings
TB elicits positive affective
reactions.
The linkage between TB and
work group performance
remains largely unsubstantiated.
Years spanned: TB is more commonly
1964–1978
conducted with management
teams than groups lower
in organizational hierarchies.
TB is more commonly conducted
with intact and established
work teams than new groups.
Affective reactions as dependent
measures are used more often
than objective performance data.
DeMeuse & 36 articles
TB is described as having great
Liebowitz
promise for improving employee
(1981)
Qualitative
attitudes, perceptions, behaviors,
data
and organizational effectiveness.
Eighty-seven percent of the 68
Years spanned:
evaluations indicated positive results.a
1962–1980 Due to the lack of rigorous research
designs, firm conclusions
concerning the effectiveness of these
interventions could not be made.
Buller
9 articles
TB must be more carefully defined.
(1986)
More rigorous experimental
Qualitative
designs should be used.
data
There are numerous methodological
flaws in previous TB studies.
Years spanned: Therefore a clear assessment of the
1964–1981
TB and task performance
relationship had yet to emerge.
Noteworthy
Features
Distinguished between team
development and T-group
or sensitivity training.
Made subjective assessments
of the internal validity
of the studies reviewed.
Coded studies according to
research design, sample size,
multiple dependent variables,
and duration of the TB
intervention.
Presented and described a
general problem solving
approachto TB that added to
Beer’s (1976)
four-component model.
Argued that Beer’s
classification is difficult to
use in practice because TB
programs usually involve
elements from each of the
models.
Tannenbaum, 17 articles
The quantity of TB research decreased; Presented a comprehensive
Beard, &
however, the quality had improved.
model of team effectiveness
Salas
Qualitative
Most studies used multiple components
that continues to influence
(1992)
data
in their TB interventions.
research and theorizing
More researchers began using
in this field.
Years spanned:
behavioral and objective measures.
1980–1988 Presented evidence to cast doubt the
connection between process and
performance; TB is effective, but
for only perceptions and attitudes.
(continued)
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
191
Table 2 (continued)
Review
Study
Details
Summary of
Findings
Noteworthy
Features
Post-intervention strategies may be a
key mechanism to ensure the
long-term effectiveness of these
interventions.
Salas, Rozell, 11 articles
No significant effect of TB on
First known attempt to
Mullen, &
performance.
empirically summarize the
Driskell
Quantitative
A nonsignificant tendency for TB to
effectiveness of TB.
(1999)
data
result in lower performance when
Assessed a number of
measured objectively, but increase
moderators, including team
Years spanned:
performance when subjective
building component, team
1965–1990
measures were used.
size, training duration, and
The role clarification component was
type of performance measure
used (i.e., objective
more likely to increase performance.b
The effects of TB decreased as the size
versus subjective).
of the team increased.
The effects of TB decreased as the
duration of the intervention increased.
Note: TB = team building.
a. Many of the 36 studies reported evaluations of multiple dependent variables.
b. This result should be interpreted with caution as it was based on a small number of effect sizes (it’s difficult to determine, but likely only three or four effect sizes were used in this calculation).
Hypotheses
Is Team Building Effective?
We agree with Salas and colleagues (1999) that previous narrative
reviews have frequently expressed the benefits that can result from team
building (e.g., Buller, 1986; DeMeuse & Liebowitz, 1981; Sundstrom,
DeMeuse, & Futrell, 1990, Tannenbaum et al., 1992; Woodman &
Sherwood, 1980); however, there has been a lack of definitive, compelling
evidence concerning the positive effects of team building on team performance.
Specifically, previous qualitative reviews of the team-building domain have
concluded that evidence of an effect of team building on performance was
“inconclusive” (Buller, 1986), “unsubstantiated” (Woodman & Sherwood,
1980), “equivocal” (Tannenbaum et al., 1992), and “mixed” (Sundstrom
et al., 1990). Meta-analytic results from one study have suggested there is
no overall effect of team building on team performance (Salas et al., 1999).
However, there was support for the role-clarification component of team
building. Theoretically, one would assume that an intervention focused on
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
192
Small Group Research
Figure 1
Theoretical Model Depicting Study Hypotheses
improving team functioning would result in positive (as opposed to negative) outcomes. In addition, the moderate support suggested by several
narrative reviews (e.g., Tannenbaum et al.) leads us to predict a positive
overall effect of team building on team functioning. Thus, we present our
first hypothesis:
Hypothesis 1: Team building interventions will result in enhanced team outcomes.
The result from testing this hypothesis will provide for a baseline judgment concerning the efficacy of this particular form of team-development
intervention. The omnibus test will therefore allow for an overall assessment of the efficacy of team building, with all independent outcomes from
primary studies combined for this analysis.
Is Team Building More Effective for Some
Outcomes Than Others?
This framing question asks whether the combined set of team-building
interventions is shown to be more useful for improving certain team outcomes
than others. Specifically, does team building work better for cognitive
outcomes (e.g., declarative knowledge of teamwork competencies), team
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
193
member affective outcomes (e.g., trust, team potency), team processes
(e.g., coordination, communication), or team performance outcomes (e.g.,
volume of sales, productivity measures)? This division of team-building
outcomes is similar to the commonly discussed cognitive, affective, and
skill-based breakdown of general training outcomes (e.g., Kraiger, Ford, &
Salas, 1993). However, for the current research, skill-based outcomes are
further divided into two additional categories—team processes and more
performance-related or productivity-related outcomes.
The division and examination of team-building effectiveness based on
specific outcomes is intended to help clarify the often disparate results
seen in the literature on these interventions. For example, Woodman and
Sherwood’s (1980) qualitative review of team building concluded that it
was only useful for facilitating affective outcomes, not team performance.
Equally pejorative to the position that team building results in improved
team performance was the conclusion provided by Buller (1986), who upon
reviewing team-building studies conducted through 1980, suggested that
the relationship between team building and performance was inconclusive.
In yet another review that added to the opaque nature of the efficacy of team
building, DeMeuse and Liebowitz (1981) accurately noted that most of the
early research on team building relied almost exclusively on perceptual
ratings of the dependent variables being studied.
More recent reviewers of the efficacy of team building have reported
somewhat different (i.e., more positive) conclusions. For example, the integration of team-building research reported by Salas and colleagues (1999)
has served, in many ways, as the focal point for the current research. And,
although there was no significant overall effect of team building in their
research, there was a small, yet significant, tendency for team building to
increase performance when criteria were assessed with subjective measures.
In another investigation into the efficacy of team building, Tannenbaum and
colleagues (1992) reviewed team-building research conducted in the 1980s
and found support for these interventions, especially when the outcome of
interest was limited to team member perceptions or attitudes. Finally,
Svyantek, Goodman, Benz, and Gard (1999) found that team building positively impacted work-group productivity. Specifically, the largest impact of
team building was on productivity measures of cost-effectiveness, with a
smaller influence on quantity and quality measures.
In general, previous research that has investigated the effectiveness of
team building for improving specific outcomes has been equivocal at best,
especially considering performance or productivity measures. At the same
time, there has been perhaps the greatest support for the efficacy of team
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
194
Small Group Research
building for improving affective or attitudinal outcomes. Finally, to our
knowledge there have been no reviews citing the correlation between teambuilding interventions and improvements in cognitive outcomes.
The mixed results found in the literature concerning the effect of teambuilding interventions on team outcomes lead us to believe that moderators
may exist. Therefore, team building impacts certain outcomes more than
others. Based on the general characteristics of team building, (e.g., that
team building develops interpersonal relations, mutual trust, and open communication between team members), it is likely that team building will
have a greater effect on affective outcomes than any on other type of outcomes. As a process intervention, it makes theoretical sense that team
building would result in enhanced team member affective outcomes.
Finally, although the findings of more distal reviews of team building were
taken into consideration, a decision was made to place more credence on
recent research, which more often reported positive findings. These findings, along with a complete consideration of the expected benefits of team
building, led us to Hypotheses 2a and 2b:
Hypothesis 2a: Team building interventions will result in improved outcomes
across each of the four outcome types.
Hypothesis 2b: Team building will be most effective for improving affective
outcomes.
Does the Focus of Team Building Moderate Its Effectiveness?
It is certainly important to be able to identify whether team building
results in enhanced team functioning, but it is perhaps more informative to
know which forms or components of team building are most effective.
Advancements in theory in the last quarter century (e.g., Buller, 1986; Salas
et al., 1999; Salas, Priest, & DeRouin, 2005) have allowed for the parceling of team-building interventions into four distinct foci (see Table 1).
Unfortunately, the single existing empirical integration on the relative efficacy of different components of team building (i.e., Salas et al.) did not
provide encouraging results. Combining subjective and objective estimates,
there was a slight (nonsignificant) tendency for goal-setting (r = −.16),
interpersonal relations (r = −.06), and problem-solving (r = −.05) models
of team building to result in decreased performance. It was only the
role-clarification component that appeared to be effective for improving
performance (r = .76). However, upon examination of their data set, it
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
195
appears this positive finding for role clarification was supported by the
results from only three studies and three effect sizes. Thus, caution and further
investigation are warranted before concluding that the role-clarification
component of team building is superior to the other forms.
Nonetheless, because the role-clarification component of team building
is designed to relieve role stress as created by role ambiguity or role conflict, it is reasonable to anticipate that a significant improvement in team
functioning should result. In addition, the role-clarification component of
team building emphasizes communication among team members, and
thus it is likely that an increase in the level and quality of communication
between team members will impact their effectiveness. Unlike the other
forms of team building, improvements in role clarity and communication
are expected to produce more lasting benefits in terms of team functioning (as assessed through an analysis of the combined set of team outcomes).
Combining this theoretical rationale with the preliminary findings of
Salas and colleagues (1999) concerning the role-clarification component
of team building, it is our belief that a team-building intervention that
utilizes a role-clarification focus will provide the most benefit to team
functioning. At the same time, it is our view that any carefully thought out
team-building intervention should have at least some positive impact on
team members. Thus, we also expect that team building that focuses on
interpersonal relations, goal setting, or problem solving will also prove
useful, at least for the short-term benefits that are typically assessed.
Taking these dual considerations into perspective, we present our next set
of hypotheses:
Hypothesis 3a: Each of the four components of team building will demonstrate a moderate level of effectiveness for improving team functioning.
Hypothesis 3b: The role clarification component of team building will be
most effective for improving team functioning.
Is the Effectiveness of Team Building
Moderated by Team Size?
This research will also investigate whether the effectiveness of team
building is moderated by the size of the team. At a basic level, “the resources
available on a team result from how many people are on it” (Hambrick &
D’Aveni, 1992, p. 1449). Sundstrom, McIntyre, Halfhill, and Richards’s
(2000) review of 83 field studies and experiments conducted with work
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
196
Small Group Research
groups suggested that the average group size was 11 members. Moreover,
Halebian and Finkelstein (1993) have suggested that team size is synonymous with cognitive capability. Providing support for this assertion, Bantel
and Jackson (1989) found that larger teams generally have a greater reservoir
of cognitive resources than smaller teams. There is little doubt that there are
benefits to having medium- to large-sized teams available to perform work
tasks rather than smaller teams. However, research has also found that larger
teams can facilitate the enactment of other, less desirable, group phenomenon, including the participation leadership effect, the in-group bias effect, the
cohesiveness performance effect, and the well-known groupthink effect (cf.
Mullen, Anthony, Salas, & Driskell, 1994; Mullen, Brown, & Smith, 1992;
Mullen & Copper, 1994; Mullen, Salas, & Driskell, 1989).
From other research, we know that information pooling is critical to teambased decision making. That is, the size of a team may impact the effectiveness
with which a team pools common and unique information. For example, Stasser,
Vaughan, and Stewart (2000) discussed the tendency for group members to discuss shared information rather than the unique information that is held by team
members—an issue that becomes more problematic as teams increase in size.
This lack of attention to unique information held by individual team members
can lead to mal-informed decisions and occasionally even detrimental results.
Salas and colleagues (1999) presented the only existing research integration
that has assessed the relative efficacy of team building for teams of different
sizes. They found that the effects of team building on performance decreased
as a function of the size of the team, both in objective measures and in subjective measures of performance. These authors concluded that any positive effect
of team building is most likely to prevail only in small teams. Similarly, others
have argued that as group size increases, members’ liking for the group (Indik,
1965) and performance (Mullen, 1987) tend to decrease. Taking these findings
into consideration, the current research examined team size as a moderator of
the effectiveness of team-building efforts on team performance. In this study,
we seek to replicate Salas and colleagues’ findings. However, rather than simply correlating the database of effect sizes with their associated team sizes, the
current research will examine the efficacy of team building for three distinct
subgroup classifications of team size: small teams (i.e., less than 5 members);
medium-sized teams (i.e., 5 to 10 members); and large teams (i.e., greater than
10 members). In addition, although there is some reason to expect that larger
teams have an increased cognitive capacity with which to perform tasks (e.g.,
Bantel & Jackson, 1989), the other negative issues often associated with
increased group size are expected to be the overwhelming influences on the
performance of teams. Therefore, it is reasonable to suggest that larger teams
Downloaded from sgr.sagepub.com at LIBERTY UNIV LIBRARY on August 17, 2012
Klein et al. / Team Building
197
are already performing at a lower level than medium or small teams, and would
therefore exhibit enhanced benefits from team-building interventions. Stated
differently, as teams increase in size, it is more likely they will show substantial benefits from team building. This expectation, although supported by
theory, is in direct contradiction to the findings reported by Salas and colleagues. The following hypothesis is proposed to investigate this assertion.
Hypothesis 4: Large teams will show greater benefits from team building
than small- or medium-sized teams.
Method
Literature Search
A comprehensive literature review was conducted to identify published
and unpublished studies relevant to the effects of team building on the four
team outcomes. As a starting point for our literature review, we conducted
an online search of the Defense Technical Information Center (DTIC),
Google Scholar ©, and the most common academic search databases
(e.g., PsycINFO). The particular keywords that were used included, but were
not limited to, the following terms: team building, team development, team
goal setting, interpersonal relations, problem solving, role clarification, group
building, and group development. In addition to these search techniques, key
articles relevant to team building were inspected by hand for additional,
potentially useful primary studies (e.g., Buller, 1986; DeMeuse & Liebowitz,
1981; Salas et al., 1999; Tannenbaum et al., 1992; Woodman & Sherwood,
1980). This ancestry approach was later extended to each of the articles that
were included in the database in an effort to ensure that no fugitive studies
had been overlooked. In the end, the literature search process resulted in 103
articles being identified for potential inclusion in the database.
Criteria for inclusion. Specific limits were placed on the search to include
articles published from 1950 to 2007. This date range was selected because
previous reviews had not uncovered any published or unpublished teambuilding evaluations prior to 1950. Moreover, studies were include...
Purchase answer to see full
attachment