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The concept of roles is ubiquitous in the social sciences, and a number of scholars have examined the operation of roles in task teams. In fact, this research has resulted in a seemingly unlimited number of roles that have been described as relevant to team performance. In this study, we attempt to integrate this research by deriving a model that describes three primary behavioral dimensions that underlie team role behavior: (a) dominance, (b) sociability, and (c) task orientation. Based on this model, we conduct a cluster analysis of the 154 team roles described in previous research. We identify 13 primary team role clusters, and discuss the implications of this approach for gaining further insight into team role structure and performance. We believe this is one step toward speaking a common language in discussing team roles.
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Team Roles 1
Team Roles: A Review and Integration
The concept of roles is ubiquitous in the social sciences, and a number of scholars have
examined the operation of roles in task teams. In fact, this research has resulted in a seemingly
unlimited number of roles that have been described as relevant to team performance. In this
study, we attempt to integrate this research by deriving a model that describes three primary
behavioral dimensions that underlie team role behavior: (a) dominance, (b) sociability, and (c)
task orientation. Based on this model, we conduct a cluster analysis of the 154 team roles
described in previous research. We identify 13 primary team role clusters, and discuss the
implications of this approach for gaining further insight into team role structure and
performance. We believe this is one step towards speaking a common language in discussing
team roles.
Team Roles 2
Team Roles: A Review and Integration
All the world's a stage. And all the men and women merely players: They have their exits and
their entrances; And one man in his time plays many parts....” (Shakespeare, As You Like It, Act
II, Scene vii)
The term “role” comes from the French le, which originally referred to the rolls of paper
on which actors parts were written (and often read to the actors if they forgot their lines). Thus,
the theatrical analogy is quite aptthe term role came to refer to the theatrical part enacted by an
actor in a play. However, in the theater, an actor adopts and sheds roles easily, whereas in real-
world teams, a role is a more internalized, enduring set of behaviors. Accordingly, Stewart,
Fulmer, and Barrick (2005) define a role as a set of behaviors that are repetitive activities
characteristic of a person in a particular setting. Roles are important in teams because they
represent patterns of behavior that are interrelated with the activities of other team members in
pursuit of the overall team goal.
Sports teams often provide a clear illustration of how roles structure team interaction. In a
basketball team, for example, the five primary roles include a point guard, a shooting guard, a
center, a small forward, and a power forward. Although these roles may vary within any
particular team, it is generally accepted that some variation of this basic structure underlies the
nature of basketball team performance. Unfortunately, there is less consensus on the nature of
the basic role structure of task teams. For example, some team role taxonomies have described
primary task team roles in as few as two role dimensions (Bales & Slater, 1955) to as many as 27
(Benne & Sheats, 1948). Moreover, Gregory, Shimono, Burke, and Salas (2015) reviewed 23
existing team role taxonomies and identified a total of 164 different roles described by these
taxonomies. This would lead one to conclude that there are a seemingly infinite number of team
roles, or that different researchers are using different terms for similar role dimensions. We
believe it is the latter.
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In this article, we attempt to integrate existing team role taxonomies to derive a primary or
core set of team roles. We do this by presenting a model that describes three primary behavioral
dimensions that underlie team role behavior: (a) dominance, (b) sociability, and (c) task
orientation. We conduct a cluster analysis of team roles identified in existing team role
taxonomies to identify primary role “clusters” or dimensions. We describe the results of this
analysis and the implications of this approach for further research.
Early Theoretical and Empirical Work
As Biddle (1986), Moxnes (1999), and others have noted, the concept of role is one of the
most central in social science. Yet, it has no single scientific origin, nor a single core definition.
Early proponents of the role concept include Ralph Linton (an anthropologist), George Herbert
Mead (a social theorist), and Jacob Moreno (a psychologist), each with a different perspective on
roles. In the audaciously-titled book, “The Study of Man”, Linton (1936) described how the
functioning of a group depends on the patterns of reciprocal behavior between individuals.
Linton noted that when a person puts a given set of rights and responsibilities (which he terms a
status or position, such as “father” or “leader”) into effect, he or she is performing a role. Thus,
Linton described a role as a set of patterned behaviors that are “inseparable” from a position.
Roles have been defined as institutionalized sets of expectations, relationships, and behaviors
that ensure stable and predictable social interactions (Stryker & Statham, 1985). Kreps and
Bosworth (1993) note that:
In any situation where people interact there is a tendency for their behaviors, sentiments,
and motives to become differentiated into discrete entities called roles (Turner 1980, p.
126). Once roles have become differentiated, the behavior, sentiments, and motives that
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appear subsequently in similar situations will tend to become patterned (i.e., they will be
performed conventionally). (p. 436)
However, roles are not simply static sets of expectations and behaviors, but instead they
change and adapt in response to role demands. In fact, two overarching goals of research on roles
within teams are to account for both role stability and role change.
During the same time period as Linton, George Herbert Mead (1934) examined how social
structure is organized and maintained, and emphasized the concept of role taking as a key to
social control. In the process of role taking, the individual takes the perspective of a significant
other and is able to view his or herself from that standpoint, and it is this reciprocal role taking
that makes social activity possible (Heimer & Matsueda, 1994). Another contemporary, Jacob
Moreno (1934), viewed role playing as a mechanism of role change, and emphasized the value
of playing or practicing a role in a simulated psychodrama setting in order to gain a deeper or
more in-depth understanding of the role. This work, couched within the psychodrama context,
was influential but perhaps less impactful on mainstream group research.
The influential early work of Mead, Linton, and others lead to a proliferation of research on
various aspects of group roles. This included work on role conflict (Kahn, Wolfe, Quinn, Snoek,
& Rosenthal, 1964), role ambiguity (Rizzo, House, & Lirtzman, 1970), role strain (Beehr, 1976),
role transitions (Nicholson, 1984), role overload (Kahn et al., 1964), role change (Turner, 1990),
role efficacy (Beauchamp, Bray, Eys, & Carron, 2002), and person-role fit (DeRue & Morgeson,
Early research efforts were also devoted to determining the basic role dimensions that define
group interaction (see Hare, 1972). Stated simply, if we define roles broadly as coherent sets of
expectations and behaviors, then what are the core roles that we observe in task teams? This
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fundamental question has been posed by various researchers in various guises: “What are the
characteristics which can be evaluated by observing people interacting?” (Carter, 1954, p. 477);
What are the “functional role behaviors” that emerge in small groups? (Mudrack & Farrell,
1995, p. 542); What are the roles members play in executing critical team functions
(Mumford, Iddekinge, Morgeson, & Campion, 2008, p. 250). In the following, we discuss
attempts to develop a classification of team roles.
Team Role Taxonomies
Although Stewart et al. (2005) state that “A universally accepted taxonomy of team member
roles does not exist” (p. 346), this is not necessarily the case. The fact is that, whereas there is no
one way of characterizing team roles that is used to the exclusion of others, there are a number of
different types of role taxonomies. A broad or higher-order characterization of team roles may
adopt a simple two-factor model, distinguishing roles as either primarily task-oriented or
primarily socioemotionally oriented (see Bales, 1950; Bales & Slater, 1955). More detailed team
role taxonomies include Belbin (1993), who described 9 team roles based on observations of
management teams, and Benne & Sheats (1948), who defined team roles in terms of 27 discrete
dimensions, including those of (a) initiator, (b) information giver, (c) coordinator, (d)
harmonizer, (e) encourager, and so on.
There are several problems with these and other role taxonomies. First, there is a
considerable divergence in terms of the “team” contexts examined. For example, Belbin’s
classification was based on observations of managerial personnel who performed a one-week
computerized business game as part of a general management course (Dulewicz, 1995). One of
the most heavily cited role taxonomies, proposed by Benne and Sheats (1948), was based on
observations of sensitivity training groups, or t-groups, that were popular in the human potential
Team Roles 6
movement of the 1960s, and whose primary purpose was interpersonal growth. In fact, Benne
noted that these observations were never meant to apply to work groups, noting that it was a
“mistake to think that a group that was specifically created for learning...about self…could
become the prototype of a work group” (quoted in Freedman, 1996, p. 336). Thus, while Benne
and Sheats’ (1948) work is often described as “the earliest and perhaps most pervasive” attempt
at role classification (Mumford et al., 2008, p. 251), it is prudent to conclude that no one
taxonomy constitutes a single gold standard.
Second, within the existing team role taxonomies, there is also considerable divergence in
terms of the roles described. For example, Gregory et al. (2015) conducted a comprehensive
inventory of existing team role taxonomies. To generate a list of task role taxonomies, Gregory
et al. conducted a search of multiple databases (including PsycNET, Sociological Abstracts,
EBSCOhost, Web of Science, and ProQuest) using the following search terms: team roles, group
roles, social roles, and emotional roles paired with the term taxonomy. A series of additional
searches were conducted using the keywords role sets, role strain, role transition, role
differentiation, and role conflict paired with the terms teams, groups, and crew. Finally, a third
search was conducted using the keywords using the terms team [group] role measurement, team
[group] role assessment, team [group] role questionnaire, and related terms. Based on this
search, 187 articles were deemed to be potentially relevant, from which a final set off 139
articles were selected, which produced 23 unique team role taxonomies (including Bales, 1950;
Belbin, 1981; Benne & Sheats, 1948; Mathieu, Tannenbaum, Kukenberger, Donsbach, &
Alliger, 2015; Stempfle, Hübner, & Badke-Schaub, 2001; Mumford, Campion, & Morgeson,
2006; and seventeen others). Cumulatively, these 23 team role taxonomies rendered 164 role
descriptors. Some roles were similar across some of the taxonomies. For example, William,
Team Roles 7
Morgan, and Cameron (2011), Beck, Eng, and Brusa (1989) and Belbin (1993) identified leader,
task leader, and chairman roles, respectively. However, many roles were unique to specific
taxonomies. For example, the procedural technician role was only identified by Benne and
Sheats (1948), the shaper role was only identified by Belbin (1993), and the contractor role was
only identified by Mumford et al. (2006). As Neiman and Hughes (1951) observed some 60
years ago, “In surveying the literature, one is confronted with…a hopeless mass of different
definitions, usages, and implications” (p. 142). It seems that little has changed.
The Nature and Structure of Team Roles
One question that group researchers have attempted to answer is what is the basic structure of
roles in task teams? In other words, is there a primary set of role dimensions that are descriptive
of role performance in task teams, and can we use this model of the nature and structure of team
roles to better understand how role performance relates to team functioning and performance?
Given that group roles can be viewed as patterns of behavior (Mumford, et al., 2008), Carter
(1954; 1962) was one of the first researchers to attempt to account for the regularities of behavior
that are observed in task groups. Couch and Carter (1952) observed small groups performing
discussion, reasoning, and mechanical assembly tasks. They asked observers to rate their
behavior on a number of variables, including aggressiveness, cooperativeness, leadership, task
orientation, talkativeness, and other characteristics. A series of factor analyses found that, across
differences in team tasks and group sizes, three primary factors emerged. They labeled these
dimensions (a) Individual Prominence (behaviors associated with leadership, striving for
recognition, and aggressiveness), (b) Sociability (behaviors related to positive social interaction,
sociability, and maintenance of group relations), and (c) Group Goal Facilitation (behaviors
related to achieving the group goal, cooperation, and attainment of the task.) Carter (1954)
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concluded that "It seems apparent that the interaction behavior of individuals involved in small
group situations can be adequately described by three factors" (p. 284). Couch (1960) replicated
this research with a more comprehensive coding scheme incorporating 55 team behavior
measures and found a similar factor structure, which he labeled (a) Interpersonal Dominance
(prominence, activity, initiative), (b) Interpersonal Affect (positive affect towards others), and (c)
Task Serious vs. Social Expressivity (seriousness of purpose in working on the group task).
Similar results were found by Mann (1961) and Borgatta (1963). Mudrack and Farrell (1995)
also found that three primary factors emerged in examining behavior in small problem solving
groups, which they labeled (a) individual roles (e.g, asserts authority), (b) maintenance roles
(e.g., praises and encourages others) and (c) task roles (e.g., coordinates task activities, suggests
task solutions).
Drawing on the previous work of Parsons, Bales, and Shils (1953) as well as Carter and
Couch (1952), Bales (2001) posed the question of what are the basic problems that must be
addressed in all task groups (e.g., directing the group’s progress, motivating group members,
problem-solving), and what discrete roles develop to solve these problems? Bales described
three “functional problems” that are faced by all groups:
(a) “activity” or managing dominance or the exercise of power (i.e., some people dominate group
activity to the exclusion of others).
(b) “likeability” or managing the maintenance of positive relations (i.e., positive relations must
be maintained to support the continuance of the group), and
(c) “task ability” or managing efforts to facilitate goal achievement (i.e., efforts must be
marshalled to pursue the solution of group goals).
Team Roles 9
Thus, at a broad level, Bales argued that these “problems” (dominance, sociability, and task
orientation) are essential to the effective functioning of all groups. Accordingly, Bales (see
Bales, 1970; Bales & Cohen, 1979) proposed three primary dimensions to describe group
behavior: Upward/Downward (dominance or submissiveness), Negative/Positive (friendly or
unfriendly), and a third dimension labeled Forward/Backward that was defined as instrumentally
controlled or task oriented vs. emotionally expressive. Thus, Bales argued that regularities of
group behavior emerge along these three primary dimensions.
Finally, Fiske, Cuddy, and Glick (2008) have described what they term as “universal
dimensions” of social cognition. That is, when people attempt to interpret behavior or form
impressions of others, they do so in terms of the basic dimensions of competence (industrious,
intelligent, skillful) and warmth (sociable, good-natured). Fiske et al. also note a third
dimension, Bales’ activity or dominance dimension, which they note is likely more relevant to
actual interaction than to perceptions.
Following Carter (1954; 1962), Bales (2001) et al., we believe that role behavior in groups
can be described in terms of the three broad dimensions of (1) individual prominence, or
Dominance, (2) Sociability, and (3) group goal facilitation, or Task Orientation. The Dominance
dimension captures the distinction between behavior that is dominant vs. submissive, active vs.
passive, or seeking control vs. deference. The Sociability dimension captures the distinction
between behavior that is sociable, friendly, and agreeable vs. behavior that is withdrawn,
unfriendly, and aloof. The Task Orientation dimension captures the distinction between
behavior that is oriented towards the solution of task problems vs. behavior that shirks or evades
task responsibilities. Table 1 presents behavioral descriptors for these dimensions.
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We present a three-dimension model (termed TRIAD; Tracking Roles In and Across
Domains) that is comprised of the dimensions of Dominance (high dominance vs. low
dominance); Sociability (high sociability vs. low sociability), and Task Orientation (high task
orientation vs. low task orientation). Figure 1 presents a three-dimensional representation of the
TRIAD model. The horizontal (left to right) axis represents low vs. high Task Orientation; the
vertical (down to up) axis represents low vs. high Sociability, and the third axis coming out from
back to front represents low vs. high Dominance. The assumption is that any role can be mapped
onto this three-dimensional space. For example, we may expect that the Team Leader role
would occupy a high Dominance, moderate Sociability, high Task Orientation space.
The Current Study
We believe that this model can be useful in several ways. First, it represents a seeming
consensus on three primary behavioral dimensions that underlie team task behavior. Second, it
provides a means by which to map team roles in order to determine “core” roles that occupy a
similar conceptual space. In pursuit of this second goal, we developed a rating scale designed to
tap each of the three dimensions of the TRIAD model. We utilized this scale to rate each of the
154 role descriptors identified by Gregory et al. (2015).
Cluster analysis is then used to
determine the extent to which certain roles cluster in adjacent spaces in order to identify primary
or core role categories.
Cluster analysis is logically appropriate for suggesting underlying structures in data. We can
take as an operating hypothesis that among the 154 distinct roles that have been drawn from the
research literature, there are some roles that are similar to one another and which form a distinct
We eliminated 10 roles from the original list of 164 roles aggregated by Gregory et al. (2015) because they
were viewed as irrelevant (i.e., programmer).
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sub-set, and that there are other roles that group together to form a sub-set unique from the first,
and so on. That is, we assume that there is an underlying structure within the data that may be
informative in terms of understanding the data. In the present case, the 154 roles can be sorted
by similarity on the TRIAD dimensions of Dominance, Sociability, and Task Orientation. In
performing a cluster analysis, the purpose is to join together objects into successively larger
clusters according to their similarity, such that the clusters have maximum internal homogeneity
and maximum between-cluster heterogeneity (Bortz, 2005). Or, as described by Bailey (1975),
cluster analysis attempts to divide a set of objects into a smaller number of relatively
homogeneous groups on the basis of their similarity over N variables. That is, cluster analysis is
a means to draw boundaries in multidimensional space such that objects are grouped by their
similarity on all variables considered simultaneously. Once significant clusters have been
identified, this emergent structure may suggest an entirely new way of approaching the data.
This approach has been applied in a variety of domains, including medical research (e.g., Moore
et al., 2010), marketing research (Punj & Stewart, 1983), and psychological research (e.g.,
Kivlighan & Tibbits, 2012). For example, Meyer and Glenz (2013) describe a cluster analysis-
based faultline measure to quantify the subgroup structure of work teams.
Two raters (Ph.D.-level researchers) independently rated each of the 154 role descriptions on
the dimensions of dominance, sociability, and task orientation. The rating scale included three
items describing each of these three dimensions. These items were chosen based on concurrence
with Bales (2001), Couch (1960), and Couch and Carter (1952). Specifically, dominance was
assessed by the following bipolar items: takes a leading roletakes a supporting role; directs
activitiesfollows direction; and dominant behaviorpassive behavior. Sociability was assessed
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by the following bipolar items: friendlyunfriendly; warmcold; and interested in othersaloof.
Finally, task orientation was assessed by the following bipolar items: hard-workingwork-shy;
focused on taskunfocused; and conscientiouscareless. Each of the 154 role descriptions, from
Gregory et al. (2015), was derived from the original source documents, similar to the following:
Encourager. Praises, agrees with and accepts the contribution of others. He
indicates warmth and solidarity in his attitude toward other group members, offers
commendation and praise and in various ways indicates understanding and
acceptance of other points of view, ideas and suggestions. (Benne & Sheats,1948)
Ratings were completed on a 7-point Likert scale. After scoring was completed, the scale was
transformed from a range of 1-7 to a range of (-3) to (+3). This was done so that, for each item
(such as dominance, for example), zero would then represent the midpoint of the scale, +3 would
represent high dominance, and -3 would represent low dominance. This also allows scores to be
more easily represented in a 3-dimensional plane.
Interrater agreement was assessed by ICC(2) scores. Overall agreement was high with all
items scoring over .85. Subsequently, the ratings of the two-raters were averaged in order to
compute a single score for the nine total items. In order to obtain a single score for each facet,
the three items representing each facet were averaged, thus creating an overall score for
dominance, sociability, and task orientation. Cronbach’s alpha was used as justification for data
aggregation. Alphas for dominance, sociability, and task orientation were .99, .99, and .99,
First, we performed a hierarchical cluster analysis on the 154 roles extracted from the
literature. Overall ratings for dominance, sociability, and task orientation were used as input
Team Roles 13
variables in the analysis. The analysis using Ward’s method produced 13 clusters. The resultant
dendrogram is represented in tabular form in Table 2. Table 3 shows the 13 clusters and the
specific roles (that is, the titles of the roles from the original sources) that comprise each cluster.
Table 4 provides a summary description of each of the 13 role clusters.
The hierarchical cluster analysis was supplemented by a two-step cluster analysis. Analogous
to the hierarchical analysis, a 13-cluster solution provided the best fit for the data. The output
from this analysis is provided in Table 3. Table 3 shows the rated levels of task orientation,
sociability, and dominance for each cluster. These data points provide the necessary coordinates
to map each cluster in a 3-dimentional plane (see Figure 2). In this three-dimensional space, the
midpoint of each dimension is zero, and the high end of the dimension is represented as +3, with
the low end represented as -3. Thus, as shown in Figure 2, Cluster 5 is situated at the low end of
the Task Orientation dimension (-2.46), and at the approximate mid-points of the Social
dimension (0.00) and the Dominance dimension (0.50). For purposes of interpretation, we have
chosen 2 to 3 to represent high scores on the scale, 0.75 to 1.9 to represent moderately high
scores, 0.74 to -0.74 to represent average scores, -0.75 to -1.9 to represent moderately low
scores, and -2 to -3 to represent low scores.
The naming or labeling of clusters is a subjective process, similar to naming a factor in a
factor analysis (see Kivlighan & Arseneau, 2009). However representative names were selected
for each cluster based on (a) the original labeling of the roles that comprise each cluster and (b)
consideration of the themes and behavioral descriptors that described the original roles. The 13
derived role clusters include the following.
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Cluster 1: Team Leader
Cluster 1 is characterized by high task orientation (2.58), average sociability (0.04), and high
dominance (2.35). We define Cluster 1 as comprising the Team Leader role. This cluster is
primarily defined by roles identified as Leader, Chairman, Task Leader, and Organizing
Leadership. Descriptive behaviors (drawn from the role descriptions in the original team task
role taxonomies) that define this role cluster include: guiding and controlling, facilitates
activities, brings order, convenes the group and acts as guide to task accomplishment, structures
the task, organizes and coordinates, and commands.
Cluster 2: Task Motivator
Cluster 2 is characterized by average task orientation (0.64), average sociability (-0.04), and
moderately high dominance (1.96). We define Cluster 2 as comprising the Task Motivator role.
This cluster is defined by roles identified as Energizer, Challenger, Motivator, and
Manipulative/Persuasive. We view this cluster as representing a “2nd in command” or task
manager role that supports the team leader. Descriptive behaviors that define this role cluster
include: prods the group to action, stimulates the group to keep going, encourages the team, and
energizes the team.
Cluster 3: Power Seeker
Cluster 3 is characterized by average task orientation (-0.43), low sociability (-2.43), and
high dominance (2.13). We define Cluster 3 as comprising the Power Seeker role. This cluster
is defined by roles identified as Dominator, Aggressor, and Defiant Leader. We view this cluster
as representing a domineering or autocratic role that may have negative consequences for the
team. Descriptive behaviors that define this role cluster include: asserts authority or superiority,
Team Roles 15
interrupts the contributions of others, belittles team members, attempts to seize control, opposes
the leader, and is aggressive towards others.
Cluster 4: Critic
Cluster 4 is characterized by moderately low task orientation (-0.92), moderately low
sociability (-1.31), and average dominance (-0.30). We define Cluster 4 as comprising the Critic
role. This cluster is defined by roles identified as Disagrees, Shows Antagonism, Flaw-Finder,
and Blocker. We view this cluster as representing a critical, fault-finding, or devil’s advocate
type of role. Descriptive behaviors that define this role cluster include: negativistic and
stubborn, disagrees and opposes, shows cynicism, judges others, tends to go against the rest of
the group, and may make others defensive. Note that the devil’s advocate role can be useful in
decision-making, but tends to be a negatively-evaluated role.
Cluster 5: Attention Seeker
Cluster 5 is characterized by low task orientation (-2.46), average sociability (0.00), and
average dominance (0.50). We define Cluster 5 as comprising the Attention Seeker role. This
cluster is defined by roles identified as Spoiler, Coat-Tails, Concealer, and Wannabe. We view
this cluster as representing a primarily negative role in which the incumbent seeks attention from
the group but shirks actual task work. Descriptive behaviors that define this role cluster include:
uses team to express personal views, seeks attention without responsibility, seeks attention and
sympathy from group, expects others to do work, withholds information until it is personally
advantageous, and leaves serious thinking to others.
Cluster 6: Negative
Cluster 6 is characterized by low task orientation (-2.75), low sociability (-2.22), and low
dominance (-2.22). We define Cluster 6 as comprising the Negative role. This cluster is defined
Team Roles 16
by roles identified as Shows Tension, Pessimist, Bored One, and Silent One. We view this
cluster as representing negative affective behavior. Descriptive behaviors that define this role
cluster include: shows tension, withdraws, has nothing to contribute, possesses a “can’t do”
attitude, gripes and complains, erodes team spirit, views effort as a waste of time.
Cluster 7: Social
Cluster 7 is characterized by average task orientation (-0.03), high sociability (2.84), and
average dominance (-0.45). We define Cluster 7 as comprising the Social role. This cluster is
defined by roles identified as Harmonizer, Helper of Others, Emotional Leader, People
Supporter, and Encourager. We view this cluster as representing positive social behavior, or
behavior that contributes to group harmony and maintenance of socio-emotional relations.
Descriptive behaviors that define this role cluster include: relieves tension and jokes, mediates
disagreements, praises others, shows warmth and solidarity, promotes group cohesiveness,
supportive of others, and maintains morale.
Cluster 8: Coordinator
Cluster 8 is characterized by moderately high task orientation (1.69), high sociability (2.15),
and average dominance (0.56). We define Cluster 8 as comprising the Coordinator role. This
cluster is defined by roles identified as Coordinator, Team Worker, Conciliator, Gate-Keeper,
and Consul. We view this cluster as representing coordinating task activities within the team and
with those outside of the team. Descriptive behaviors that define this role cluster include:
facilities team functions, coordinates activities of team members of sub-groups, clarifies task
relationships, keeps communication channels open, facilitates participation of others, and
promotes ideas to others inside and outside the team.
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Cluster 9: Follower
Cluster 9 is characterized by average task orientation (0.56), moderately high sociability
(1.24), and low dominance (-2.39). We define Cluster 9 as comprising the Follower role. This
cluster is defined by roles identified as Follower, Cooperator, Agrees, Listener, and
Communicator. We view this cluster as primarily comprised of taskwork behaviors of listening,
agreeing, and cooperating. The Follower role is generally viewed as reciprocal to the Leader
role. Descriptive behaviors that define this role cluster include: participates in group discussion
and decisions, builds on others’ ideas, effective listener and facilitator, conforms to assignments,
seeks cooperation, and avoids disagreements.
Cluster 10: Teamwork Support
Cluster 10 is characterized by high task orientation (2.24), average sociability (0.11), and low
dominance (-2.15). We define Cluster 10 as comprising the Teamwork Support role. This
cluster is defined by roles identified as Supportive Worker, Summarizer, Recorder, Process
Observer, Company Worker, and Completer. We view this cluster as comprising behaviors that
support team task accomplishment. Descriptive behaviors that define this role cluster include:
implements plans, does things for the group, makes records of group processes and output, takes
initiative to ensure group’s success, puts information together, prepares for team meetings, sums
up and clarifies, and pitches in to achieve team goals.
Cluster 11: Evaluator
Cluster 11 is characterized by high task orientation (2.30), low sociability (-2.23), and
average dominance (-0.10). We define Cluster 11 as comprising the Evaluator role. This
cluster is defined by roles identified as Monitor-Evaluator, Controller-Inspector, and Evaluator.
We view this cluster as comprising behaviors related to inspection and evaluation. Descriptive
Team Roles 18
behaviors that define this role cluster include: analyzes and evaluates proposals, is careful and
meticulous, and focused on facts and figures of the task.
Cluster 12: Problem Solver
Cluster 12 is characterized by moderately high task orientation (1.28), average sociability
(0.02), and average dominance (-0.25). We define Cluster 12 as comprising the Problem Solver
role. This cluster is defined by roles identified as Opinion Seeker, Opinion Giver, Clarifier, Idea
Creator, Information Seeker, Information Giver, and Critical Tester. We view this cluster as
comprised of behaviors related to idea production and evaluation, problem-solving, and decision
making. Descriptive behaviors that define this role cluster include: orients the group to the task;
asks for opinion; asks for information; asks for clarification; offers facts, information, and
opinions; points out inconsistencies and clarifies them; synthesizes new ideas and comes up with
solutions; and repeats, clarifies, and confirms.
Cluster 13: Task Completer
Cluster 13 is characterized by high task orientation (2.64), average sociability (-0.08), and
average dominance (-0.56). We define Cluster 13 as comprising the Task Completer role. This
cluster is defined by roles identified as Completer-Finisher, Proceduralist, Logical/Precision, and
Production. We view this cluster as representing detail-oriented, routine behaviors oriented to
completion of the task. Descriptive behaviors that define this role cluster include: focused on
details and deadlines, conscientious and orderly, adheres to responsibilities, focused on
procedures, and performs explicit and routine tasks.
This analysis integrates previous taxonomies within the team roles literature, provides further
insight into the nature and structure of team roles, and provides some new directions for role
Team Roles 19
research. Moreover, the role clusters identified resonate to the original roles literature.
Consistent with the early work of Bales and colleagues (Bales, 1950; Bales & Slater, 1955), we
capture the two primary roles of task leader (Team Leader role) and socio-emotional leader
(Social role). Consistent with Benne and Sheats (1948), we capture the roles of energizer (Task
Motivator role) and coordinator (Coordinator role). Consistent with Belbin (1981; 1993), we
capture the roles of completer-finisher (Task Completer role) and opinion-giver (Problem Solver
role). Furthermore, this classification captures both positive team roles as well as potentially
negative team roles (Power Seeker, Critic, Attention Seeker, and Negative roles).
It is useful to discuss the relationship between team roles and team composition models.
From both perspectives, the overall goal is to optimize team composition and, subsequently,
team effectiveness. Mathieu, Tannenbaum, Donsbach, and Alliger (2014) have presented an
overview of four types of team composition models. The first is a traditional personnel-position
fit model that emphasizes the particular set of individual knowledge, skills, abilities and other
characteristics (KSAOs) that contribute to successful performance in a specific position or role.
The second type is a personnel model with teamwork considerations model that emphasizes
team-generic competencies such as collective orientation (Driskell, Salas, & Hughes, 2010). The
third type is a team profile model that considers team member's KSAOs collectively in terms of
how they are distributed in the team. The fourth type of team composition model is a relative
contribution model that examines the relative or disproportional impact that some characteristics
may have on team effectiveness, such as a negative or overly critical team member (Felps,
Mitchell, & Byington, 2006).
Furthermore, Mathieu et al. (2014) propose that team composition can be more
comprehensively examined by integrating these different team composition approaches. They
Team Roles 20
provide the example in the context of replacing a team member. In this case, the examination of
position-specific KSAOs would be consistent with a traditional person-fit model. The further
examination of teamwork-oriented KSAOs would be consistent with a personnel with teamwork
considerations model. The impact of the KSAOs of the team member replacement in terms of
the distribution of KSAOs across the team would be consistent with a team profile model.
Finally, the relative impact of the specific KSAOs subtracted and added to the team and the
interrelationship with specific team roles would be consistent with a relative contribution model.
Moreover, this organizing framework suggests that we can examine the impact of team roles
on team effectiveness in a similar manner. From a person-position fit perspective, we would
focus on the individual team member and how he or she would fill specific roles to support team
effectiveness. For example, we have proposed that the Team Leader role is comprised of
behaviors related to high task orientation, average sociability, and high dominance. KSAOs
related to this role may include comprehensive knowledge of the task, skills such as organizing
and directing team members, as well as other characteristics such as initiative. Generally, a
person who possesses these characteristics should be more adept at meeting Team Leader role
Adopting a personnel model with teamwork considerations perspective, we would further
examine the contributions of team competencies such as performance monitoring (Cannon-
Bowers, Tannenbaum, Salas, & Volpe, 1995) or teamwork knowledge (Stevens & Campion,
1994). Although these types of team-generic skills are viewed as valuable for any team setting,
we would propose that some team roles such as the Social role may place a higher value on a
competency such as interpersonal relations; whereas another team role such as Coordinator
would place a higher value on a competency such as coordination.
Team Roles 21
A team-profile perspective leads us to examine how team member's characteristics
collectively fit team requirements. For example, we would propose that effective teams require a
balance within the 3-dimensional space shown in Figure 2. That is, too much activity located in
the leftmost dimension of the 3-dimensional model reflects a team that is not task-oriented;
whereas too little activity in the uppermost dimension of the model suggests that team
maintenance functions may be compromised. (Although it is difficult to represent on the printed
page, the 3-D scattergram illustrated in Figure 2 can be rotated for visualization on each of its
three axes.) An optimal team profile would involve team members enacting role activity that
spreads over the high task-orientation, high dominance, and high sociability spaces.
On the other hand, we may consider that a team profile in which multiple team members
attempt to perform the same role may impair team effectiveness. Too many people performing a
single role may be not only redundant but lead to inefficiencies and conflict. Dynes (1986) noted
that, under emergency conditions, you may have more people trying to assume relevant roles
than there are relevant roles to fill. Further, in an examination of group performance in polar
winter-overs , Johnson, Boster, and Palinkas (2003) found that role collision may occur when
multiple individuals in a group attempt to perform roles which overlap.
Finally, a relative contribution perspective allows us to examine whether some roles may be
more influential than others. For example, Mann (1961) and others have suggested that for teams
performing a task that is primarily social, interpersonal, or emotionally nuanced, team
maintenance activities may be more relevant; whereas for teams performing a primarily
instrumental task, task-oriented activities may be more relevant. Or, we may examine the
interplay among roles. For example, the Social role may be disproportionally important in a
situation in which the Task Leader is especially dominant. Team roles that are negatively-
Team Roles 22
valenced (in the leftmost space in Figure 2) such as the Critic, Attention Seeker, or Negative
roles may disproportionally impact team effectiveness in that negative emotionality can be
contagious and spread throughout the team (Barsade, 2002).
Research Implications
There are several implications for further research that can be drawn from the current study.
Foremost, research is needed to empirically test and instantiate the model presented. First, can
an independent set of raters obtain similar results to that of the expert raters in the current study?
Second, can observers use the model presented in sutu to distinguish among role behaviors in
real-world groups? Third, we offer suggestions for the use of this model for examining
personality-role fit, the impact of contextual factors such time or temporal dynamics, and effects
of the type of task on team role requirements.
Early in the past century, Linton (1936, p. 476) observed that “It is vitally necessary for the
functioning of society that the personalities of its members be at least superficially adapted to
their statuses” (or roles). Research on personality-role fit is still sparse (DeRue & Morgeson,
2007). Personality-role fit refers to the compatibility between a team member’s personality
characteristics and his or her role within the team. In terms of personality/role fit, we can
imagine that those role clusters that are located in the high Social space in Figure 2 (Cluster 7,
Social; Cluster 8, Coordinator; Cluster 9, Follower; and Cluster 10, Teamwork Support) would
all have a strong link to the Big Five Extraversion or Sociability personality dimensions. That is,
a person scoring low on trait Sociabilty is probably ill-suited to roles that fall within the upper
zone of this three-dimensional space.
In fact, we may hypothesize linkages between personality and each of the broad TRIAD
dimensions (see Driskell, Goodwin, Salas, & O’Shea, 2006 ; Stewart, Fulmer, & Barrick, 2005).
Team Roles 23
For example, Dominance may be predicted by the Big Five factor of Extraversion (particularly
the sub-facets of Dominance and Ambition). Sociability may be predicted by the factors of
Agreeableness and low Neuroticism, and cognate sub-facets of Sociability, Warmth, and
Expressiveness. Task Orientation may be predicted by the factor of Conscientiousness and
cognate sub-facets of Achievement-Orientation and Dependability. Empirical research is needed
to examine these relationships.
Further research can utilize this model to examine role performance under various contexts
or conditions. Note that there are no preferential spaces per se in the three-dimensional model
that is, a role that enacts low task orientation, low sociability, and high dominance (i.e., the
Power Seeker role) may not be highly functional or supportive of team effectiveness under
normal task conditions, but may perhaps be more functional under emergency conditions when
authority needs to be asserted. Furthermore, a specific role, such as Completer, may be more or
less functional over time, such that the role may be prominent at Time A, but less so at Time B.
In brief, teams and team roles are dynamicteam performance conditions may change over
time, team members may change over time, and the task itself may require different types of
activities as it evolves over time. In fact, the importance of examining how some roles become
more relevant or less relevant over time has been noted by Mann (1961) and others but remains
an under-researched area of group dynamics.
As Driskell & Salas (2013) have noted: “It is important to note that almost any overall
statement regarding teams must be qualified by factors such as the type of task” (p. 745).
Holland (1966) has presented a RIASEC classification of task environments based on the
activities that describe each category, including Realistic, Investigative, Artistic, Social,
Enterprising, and Conventional tasks (see also Driskell, Hogan, & Salas, 1987). The
Team Roles 24
visualization of role dimensions in the TRIAD model presented in Figure 2 suggests potential
linkages between roles and types of task environments. For example, Realistic tasks are
production tasks that typically involve little interaction with others but may require the
production and completion of activities. Realistic tasks may be most dependent on effective role
enactment in the low Dominance, low Sociability, high Task Orientation space (i.e., Problem
Solver, Completer). Social tasks require personal interaction with others and may involve
assisting or supporting other team members and behaviors related to maintaining team harmony.
Social tasks may be most dependent on effective role enactment in the low Dominance, high
Sociability, average Task Orientation space (i.e., Social, Coordinator). Further research is
needed to elaborate and test these assumptions.
Applied Implications
The examination of team role is relevant to various types of applied organizational activities,
including the selection of team members, the removal of team members, and the replacement of
team members (see Mathieu et al., 2014). In selecting team members, one should be cognizant
of the type of team, the type of task, the type of roles to be filled, and the characteristics
(KSAOs) of those who may potentially fill those roles. In general, the optimal strategy is to
select the individuals that have the optical KSAOs to match specific team roles, although there
are certainly elaborations on this rule. For example, for a small team (2-3 members) it may be
advantageous to select generalists (that have moderate levels of task orientation, dominance, and
sociability) who would be able to fulfill an idealized "team" role. Larger teams would provide
the affordance to select more "specialists," that is, persons who could fill separate Task Leader,
Social, Problem Solver and other roles. Caution should be exercised in selecting too many high
dominance task leaders or too many highly sociable members. At least one person fulfilling these
Team Roles 25
roles may be ideal, but there may be diminishing returns with multiple team members attempting
to lead or multiple team members engaging in social activity.
Our model suggests that the removal of some negative team roles may be beneficial to the
team. For example, the Power Seeker role is characterized by very high dominant behavior and
very low social behavior, which may represent an overbearing team member with little concern
for others. The Attention Seeker and Negative roles are characterized by very low task
orientation, which suggests that persons fulfilling these roles contribute little to overall team
In replacing team members because of turnover or attrition, the TRIAD model provides a
means to examine role balance in the team. The 3-D representation of the 13 role clusters within
the TRIAD conceptual space (Figure 2) provides insight into the topography of role
performance. For example, the examination of Figure 2 reveals that some role clusters are
relatively “close” in distance. Thus, we see that Cluster 10 (Teamwork Support) and Cluster 12
(Problem Solver) are close and thus somewhat related (suggesting, for example, that these roles
could perhaps be performed by a single person). Figure 2 also provides insight on what role
clusters are dissimilar and spatially distant. Thus, Cluster 7 (Social) and Cluster 11 (Evaluator)
are spatially separated (and suggests that these two roles are more disparate and would be more
difficult to perform by a single person). Further, in terms of role shifts or role replacement, this
model also provides potentially useful insight on how to replace or change a specific role
incumbent (e.g., ideally, with the role incumbent that is spatially nearest to that location or
Team training interventions may also serve to support effective role performance. For
example, cross-training of team members may enhance team member’s understanding of their
Team Roles 26
own and other team members roles (Cannon-Bowers & Salas, 1998; Marks, Sabella, Burke, &
Zaccaro, 2002). Ellis, Bell, Ployhart, Hollenbeck, and Ilgen (2005) found that generic teamwork
skills training enhanced overall team performance, and that this training was more valuable for
some roles than others. Other team training interventions that may support effective role
performance include team building interventions (Salas, Rozell, Mullen, & Driskell, 1999) and
facilitating knowledge building across team members (Rentsch, Delise, Salas, & Letsky, 2010).
One further applied research task is to identify the competencies, or KSAOs that underlie
effective role performance for a given task. For example, the Leader role requires both task-
specific taskwork skills as well as role-relevant teamwork skills. That is, an effective leader
possesses skills that are relevant to the specific task at hand (taskwork skills) as well as skills that
are required to support effective teamwork (teamwork skills) (Morgan, Glickman,Woodard,
Blaiwes, & Salas, 1986; Stevens & Campion, 1994). In the model presented, we have tended to
emphasize teamwork skills that are relevant across tasks. For example, Leader role activities
include organizing, explaining, giving information, and leadership behaviors (Figure 2). These
types of teamwork behaviors can be trained generically. However, taskwork competencies (such
as knowledge of the task requirements) are tied to the specific task. In an applied setting, it is
necessary to define both the taskwork competencies as well as the teamwork competencies that
are required to perform a given role.
The present research is an attempt to integrate a large and disparate number of team role
descriptions within the research literature and derive a smaller, core set of team roles, using a
cluster analytic approach. To accomplish this task, we first proposed a model that describes three
primary behavioral dimensions that underlie team role behavior: (a) dominance, (b) sociability,
Team Roles 27
and (c) task orientation. We use this three-dimensional model to map team roles in order to
determine “core” roles that occupy a similar conceptual space. We believe that the value of this
approach is two-fold. First, we have attempted to reduce as complex dataset into a smaller,
homogenous set of categories that represent a theoretically-based and quantitatively-derived set
of 13 core team roles. We believe the resultant team role classification provides a reasonable
approximation of the nature and structure of team roles. Second, the TRIAD roles model
presented suggests a number of potentially valuable, yet untested, avenues to examine the
linkage between role performance and different types of team tasks, team member personality,
and team performance over time. Although, at this point, these links are only speculative, we
believe that further research will yield greater insight into team role structure and performance.
Team Roles 28
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Team Roles 37
Table 1
Behavioral descriptors for Dominance, Sociability, and Task Orientation
dominate, control, direct, influence, assert,
take charge, lead, command, active
defer, comply, follow, compliant, submissive,
support, take orders, passive
friendly, interested in others, cordial, warm,
gregarious, supportive
withdrawn, aloof, avoids contact with others,
prefers working alone, solitary
achievement-oriented, organized, reliable,
dependable, conscientious, planful,
responsible, serious
careless, irresponsible, disordered, impulsive,
spontaneous, untrustworthy, inactive, work-
Team Roles 38
Table 2
Two-step cluster analysis results
Team Roles 39
Table 3
Role Clusters and Corresponding Role Descriptors
Team Roles 40
Table 4
Summary Role Clusters
Team Leader
Task Motivator
Power Seeker
organizes, and
leads the team
towards task
Acts as a second
in command or
task manager to
stimulate the
group to action
Seeks power and
Adopts a critical,
fault-finding, or
devil’s advocate
Seeks attention
and resources
but does little
Moderately Low
Moderately Low
Moderately High
Guides, brings
order, convenes
the group,
structures the
task, commands
and organizes
Prods the group
to action,
stimulates the
group, energizes
the group
Asserts authority
or superiority,
interrupts and
belittles others,
seeks power
Disagrees, shows
cynicism, judges
Seeks attention
seeks sympathy,
personal views
Shows tension,
Team Roles 41
Table 4, Continued
Problem Solver
Task Completer
Contributes to
group harmony
and maintenance
of interpersonal
Coordinates task
activities within
the team and with
those outside the
activities of
listening, agreeing,
and cooperating
Supports team task
Inspects and
evaluates team
Involved in
generation of ideas,
problem solving.
Performs detail-
oriented, routine
activities related to
completing the task
Moderately High
Moderately High
Moderately High
Relieves tension,
praises others,
shows warmth
Facilitates team
Participates in
discussions, listens
to others’ ideas,
conforms to tasks,
seeks cooperation.
Pitches in to
achieve team
goals, implements
plans, sums up and
clarifies, records
team activities
Analyses and
evaluates proposals,
focuses on facts and
Asks for
information, offers
facts and opinion,
offers solutions
Adheres to
procedures and
deadlines, detail-
oriented and orderly
Team Roles 42
Figure 1: The TRIAD model
Team Roles 43
Figure 2. Three dimensional scatterplot of the 13 role clusters
Cluster12 Cluster13
TRIAD 3D Scatterplot
... For more meaningful and productive participation in different areas of society, individuals must learn how to act in meaningful roles when interacting and collaborating with others. Although studied extensively in other fields such as organisational sciences (Driskell et al., 2017;Lehmann-Willenbrock et al., 2016), there exists surprisingly little research on roles and their significance in collaborative learning. Furthermore, the existing research in this context has mainly focused on studying the impact of roles that are prescribed for learners prior to a collaborative activity, even though the practical reality in reallife classrooms is that collaborative activities are typically organised without any predefined individual responsibilities or roles (Kirschner & Erkens, 2013). ...
... To clarify the focus of this thesis further, I note that while the term 'role' originated as a dramaturgical analogy to paper rolls on which actors' lines were written, the term has become ubiquitous and taken on multiple different meanings (Driskell et al., 2017). Although the early phases of research that employed a dramaturgical approach to roles (e.g., Goffman, 1959), where 'parts' and 'scripts' played by the actors were believed to structure real-life social drama like in a theatre, were perhaps the most influential, soon, a number of competing theories emerged (Biddle, 1986). ...
... While the main focus of this early research was on society-based roles, today, roles are studied from multiple perspectives within different disciplines (Hare, 1994;Stets & Thai, 2010). Although roles can be broadly defined as a set of behaviour characteristics of an individual in a particular context, there exists no single universally agreed upon conceptualisation of what constitutes a role (Biddle, 1979;Driskell et al., 2017;Turner, 2002). ...
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Research on roles in collaborative learning has concentrated mainly on roles that are prescribed for students while only limited attention has been devoted to roles that emerge naturally during collaboration. To address this gap, this thesis adopted a situative approach to study the functional participatory roles that emerge spontaneously and are self-enacted by students during collaborative learning and examined the significance of such roles in collaborative learning. Three datasets on students collaborating on inquiry-based science activities in small groups made up the data for the thesis. The role analyses were based on systematic video observations, including a detailed analysis of emergent roles from videotaped group activities and a subsequent hierarchical cluster analysis to identify student role profiles. These analyses were consolidated further with an in-depth qualitative approach. The thesis consists of three studies. Study I investigated the emergence of functional participatory roles in a computer-supported science inquiry and developed an analytical coding scheme for their analysis. Fine-grained analysis of the video data identified 17 distinct functional participatory roles self-enacted by the students and provided empirical support for the spontaneous, interactive, and dynamically evolving nature of roles in collaborative learning. Study II developed a scalable framework for analysing these emergent roles across a range of collaborative science learning environments. This flexible framework distinguishes between the core roles that resemble each other across different science learning settings and activity-specific roles that are unique to a particular context. Finally, Study III examined the relationships between group achievement and within-group configurations of role profiles. The results revealed striking differences in role configuration between higher- and lower-achieving groups. Taken together, this thesis extend existing understanding of spontaneously self-enacted roles and their significance in collaborative science learning and consolidate methodology in this area. KEYWORDS: Roles, collaborative learning, role analysis, video observation
... Three aspects were captured using SNA: the participation dimension of CSCL (Weinberger & Fischer, 2006), the social dimension (Kreijns et al., 2013), and the diffusion and uptake of ideas (Saqr & López-Pernas, 2021b). The centrality measures were also based on the frameworks proposed by Strijbos and De Laat (2010) to capture the high and low effort dimensions, and by Driskell et al. (2017) to capture the sociality, dominance and task engagement dimensions. Therefore, three types of centralities were selected: (1) degree centrality reflecting students participation (e.g., Chen & Chang, 2014;Kim & Ketenci, 2019;Marcos-García et al., 2015), (2) closeness, betweenness and eigenvector centralities reflecting social positioning, influence, and involvement in the discussions (Marcos-García et al., 2015;Ouyang & Chang, 2019;Temdee et al., 2006), and (3) diffusion and cross clique centralities reflecting the diffusion, uptake, and reply-worthiness of posts (Saqr & López-Pernas, 2021b). ...
... Higher density reflects diverse collaborations, inclusion of collaborators, and group cohesion (Vignery, 2022). Similarly, we computed the centralization degree which reflects the dominance of collaborators (Driskell et al., 2017). Higher values of centralization reflect the presence of few central collaborators and lack of inclusion or participation of group members (Marcos-García et al., 2015). ...
... Our first research question aimed at discovering the types of roles that can be identified using LPA from a full program data. The identified roles were principally aligned with the theoretical frameworks proposed by Strijbos and De Laat (2010) and Driskell et al. (2017), especially at either side of the spectrum (high vs. low effort), task engagement, and dominance. We identified a leader role with high effort, influence, and strong social connections, in line with most prior research (e.g., Jimoyiannis et al., 2013;Marcos-García et al., 2015;Medina et al., 2016;Saqr et al., 2018;Xie et al., 2018). ...
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A prevailing trend in CSCL literature has been to study of students' participatory roles. The majority of existing studies examine a single collaborative task or, at most, a complete course. This study aims to investigate the presence-or the lack thereof-of a more enduring disposition that drives student participation patterns across courses. Based on data from a 4-year program where 329 students used CSCL to collaborate in 10 successive courses (amounting up to 84,597 interactions), we identify the emerging roles using centrality measures and latent profile analysis and trace the unfolding of roles over the entire duration of the program. Thereafter, we use Mixture Hidden Markov Models (MHMM)-methods that are particularly useful in detecting "latent traits" in longitudinal data-to identify how students' roles, transition, persist or evolve over time. Relevant covariates were also examined to explain students' membership of different trajectories. We identified three different roles (leader, mediator, isolate) at the course level. At the program level, we found three distinct trajectories: an intense trajectory with mostly leaders, a fluctuating trajectory with mostly mediators, and a wallowing-in-the-mire trajectory with mostly isolates. Our results show that roles re-emerge consistently regardless of the task or the course over extended periods of time and in a predictable manner. For instance, isolates "assumed" such a role in almost all of their courses over four years.
... In various studies, expressed in somewhat varying terminologies, the consensus emerges that three behavioral patterns contribute to influence team performance: dominance or individual prominence; sociability or interpersonal affect, which includes agreeableness; and task orientation or group goal facilitation (Driskell, Driskell, Burke & Salas, 2017). Driskell et al. (2017) identify 13 role model clusters, of which one is that of contributing a foremost "social role" within and to the team. ...
... In various studies, expressed in somewhat varying terminologies, the consensus emerges that three behavioral patterns contribute to influence team performance: dominance or individual prominence; sociability or interpersonal affect, which includes agreeableness; and task orientation or group goal facilitation (Driskell, Driskell, Burke & Salas, 2017). Driskell et al. (2017) identify 13 role model clusters, of which one is that of contributing a foremost "social role" within and to the team. This "social role" harmonizes, aids, supports, and reassures others by appeasing, resolving disputes, commending others, expressing warmth, emotion and solidarity, enhancing cohesiveness, and assisting morale. ...
... This "social role" harmonizes, aids, supports, and reassures others by appeasing, resolving disputes, commending others, expressing warmth, emotion and solidarity, enhancing cohesiveness, and assisting morale. Furthermore, while the "social role" is instrumental to a team, if too many team members take on that role it may lead to redundancy and disharmony (Driskell et al., 2017). Team members with unique complementary qualifications are not just beneficial to the team, but the benefits of this complementarity may grow over time (Neffke, 2019). ...
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Male homosexual preference (MHP) is present in many human societies, making up a small but significant cohort. Because homosexual mate preferences are associated with lower fecundity, many evolutionary explanations have been advanced to account for the persistence of this trait. After reviewing a number of these hypotheses and finding room for additional explanations, we propose a new hypothesis that depends on the observed greater empathy and reduced hostility of men who express MHP. This gives them a central role in the performance of groups or teams (all male and mixed) where cooperation and intra-team coherence are at a premium. In this view, teams that contain men with MHP will outcompete teams without such men, other variables being similar. The links between personality traits and team performance do not require homosexual activity within the group. The hypothesis is supported by observations of the personality traits associated with MHP, such as increased agreeableness, which is linked to the literature on team cohesion and performance in sports and other kinds of teams and groups. This novel hypothesis could be examined through direct study of team performance. The proposed hypothesis may also have relevance to better performance among the diverse teams whose efficient performance is so important in modern society.
... In other words, we will not only be able to implement our deep learning models as a black box, but we will also be able to describe the distinctive features found in the sensor data which are specific for team flow. Another potential challenge is the situation that people could be too diverse in terms of individual differences or team roles (Driskell et al., 2017) -for one single machine learning approach analyzing their cognitive state and the interaction with their colleagues. It might come out that there are some different types (clusters) of people in the virtual teams having similar properties so that one machine learning configuration works better for one cluster, another for another. ...
... Another important domain that affects team processes relates to formal and informal social roles and relationships within the team (Belbin, 1981;Driskell et al., 2017). Teams mostly consist of a team manager and team members, with certain individual characteristics as well as formal and informal roles (Belbin, 1981). ...
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More and more teams are collaborating virtually across the globe, and the COVID-19 pandemic has further encouraged the dissemination of virtual teamwork. However, there are challenges for virtual teams – such as reduced informal communication – with implications for team effectiveness. Team flow is a concept with high potential for promoting team effectiveness, however its measurement and promotion are challenging. Traditional team flow measurements rely on self-report questionnaires that require interrupting the team process. Approaches in artificial intelligence, i.e., machine learning, offer methods to identify an algorithm based on behavioral and sensor data that is able to identify team flow and its dynamics over time without interrupting the process. Thus, in this article we present an approach to identify team flow in virtual teams, using machine learning methods. First of all, based on a literature review, we provide a model of team flow characteristics, composed of characteristics that are shared with individual flow and characteristics that are unique for team flow. It is argued that those characteristics that are unique for team flow are represented by the concept of collective communication. Based on that, we present physiological and behavioral correlates of team flow which are suitable – but not limited to – being assessed in virtual teams and which can be used as input data for a machine learning system to assess team flow in real time. Finally, we suggest interventions to support team flow that can be implemented in real time, in virtual environments and controlled by artificial intelligence. This article thus contributes to finding indicators and dynamics of team flow in virtual teams, to stimulate future research and to promote team effectiveness.
... Different ways of forming teamwork have been studied over years of research (Garrido and Garine, 2014). Concretely, a widely used team-forming method to develop this skill is based on classification by students' roles (Aritzeta et al., 2007;Driskell et al., 2017;Manning et al., 2006;Rahmani et al., 2021), and the Belbin role theory is the most accepted worldwide (Aranzabal et al., 2022;Belbin, 2011;Fekry et al., 2019;Meslec and Curşeu, 2015;Storch de Gracia et al., 2017). Belbin proposed the categorisation of individual behaviour within the team into nine roles: Plant, Monitor Evaluator and Specialist (roles oriented to thinking and solving problems); Coordinator, Teamworker and Resource Investigator (people-oriented roles); Shaper, Implementer, Completer and Finisher (action-oriented roles) (Aranzabal et al., 2022). ...
... For example, the focal article discusses the importance of the team charter in setting expectations and establishing procedures (Mathieu & Rapp, 2009). Likewise, an understanding of stages of group development (Tuckman & Jensen, 1977), the punctuated-equilibrium model (Chang et al., 2003), or the importance of individual roles within a team (Driskell et al., 2017) would help any student properly prepare for and plan for a team project whether in class or at work. Moreover, many students are likely to find themselves leading a team at some point in their future, whether it be managing a project implementation team at work, or collating efforts for social justice movements. ...
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The focal article by Kath and colleagues (2020) presents a clear and laudable argument for why and how I-O instructors should be demonstrating best practices of teaching in the classroom. Though they mention the importance of having non-I-O students benefit from I-O classes, implicit in their body of helpful resources and advice is the as-sumption that instructors will be focused on teach-ing I-O students (or at least, psychology majors). In our response, we extend the I-O content described in the focal article beyond simply that of informing our teaching practices; instead, the content of what is taught in an I-O course can and should be pre-sented in a way that is applicable to students from all fields and educational backgrounds. Taken a step further, we daresay that an “Introduction to I-O Psychology” course should be a foundational general studies course for all undergraduate stu-dents regardless of major. Too often, I-O instructors seem to be stuck in the idea that they’re teaching future I-O graduate students, researchers, consultants, or HR profes-sionals (Weathington et al., 2014; Ones et al., 2017). As a result, I-O content tends to be present-ed with such an audience in mind: diversity and inclusion is taught from the perspective of test bias and predictive validity in selection, leadership is taught from the perspective of training leaders within organizations, and teamwork is taught from the perspective of managing teams or assessing team performance. However, the reality is that the field of I-O has much to offer to students who are planning to become professional musicians, medi-cal doctors, restaurant managers, or even have no clue what they want to do post-graduation. The popularization of an I-O course for non-psychology students falls in line with SIOP’s stra-tegic goals in advancing public knowledge of our field, and we argue is a worthy goal of any I-O in-structor. Kath and colleagues (2020) acknowledge this in their focal article, but their recommenda-tions remain focused on how each of the four con-tent areas (training and development, diversity and inclusion, groups and teams, and leadership) in-form best practices in teaching. Following their four-part structure, we demonstrate how each of these content areas not only inform best practices in teaching, but can also themselves be taught as content applicable to any undergraduate student who steps foot in our classroom.
... Extreme conditions need properly trained staff. According to research, the extreme environment includes task contexts that are atypical in terms of demands, type of demands and contexts etc. Extreme condition is defined as settings in which there are significant task, social and environmental demands that entail high risk and increase consequences like COVID-19 situation (Driskell, 2017). Team building is explained in two different approaches (Ciasullo et al., 2017) i. e. traditional approach and the hybrid bottom-up approach. ...
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The exploratory study examined the role of teamwork quality on team effectiveness and individual team member's success. There is another variable interpersonal skill is identified as affecting teamwork quality. A total of 21 items are clustered into 4 basic competencies by using Exploratory Factor Analysis (EFA) in SPSS: Interpersonal skill (IPS), Teamwork Quality (TWQ), Team effectiveness (TEF), Individual team member's success (IMS). Nurses are invited to participate and 200 data was collected successfully manually and also in Google doc. from five multispecialty hospitals of Bhubaneswar and Cuttack, Odisha. Regression analyses found support for the hypotheses that team effectiveness and individual member's success depends upon teamwork quality and there are some effects of interpersonal skills on teamwork quality, team effectiveness and individual team member's success. This study examined the relationship between different variables by utilizing the Teamwork Quality Model (TWQ Model) and other various conceptual theories of teamwork and team effectiveness with the primary data analysis. It analyses how interpersonal skills impact team effectiveness along with the mediating effect of teamwork quality, in efforts to develop a more elaborated and theoretical ground to understand the Teamwork Quality Processes.
Purpose As the risks and uncertainties faced by construction projects increase, the study of organizational resilience becomes more and more important for construction project management. Therefore, this study aims to deepen the understanding of the micro-mechanisms of organizational resilience in construction projects and explore the impact of employee resilience on organizational resilience. Design/methodology/approach By combining the conservation of resources, this study constructs the mechanism of employee resilience on organizational resilience in construction projects and considers the mediating role of task types. A partial least squares structural equation model (SEM) was used to test hypotheses based on data collected from 224 respondents. Findings The results show that employees' work resilience has a direct positive impact on the organizational resilience in construction projects and is also mediated by inter-team tasks. However, the psychological resilience of employees will have a direct adverse effect on the organizational resilience in construction projects and will be mediated by inter-team tasks and intra-team tasks. Originality/value This study verifies the impact mechanism of employee resilience on organizational resilience, including direct effects and indirect effects through different types of team tasks, and reveals the micro-mechanisms of using employee resources to build organizational resilience. This article sheds light on how project managers and employees can develop resilience to deal with the uncertainty and complexity of construction projects.
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Se presentan tres intervenciones para favorecer la labor de los equipos en las organizaciones: Desarrollo de Equipo, Construcción de Equipo, y Entrenamiento de Equipo. Motiva este trabajo la necesidad de precisar las diferencias entre dichas intervenciones. Está orientado a ser útil principalmente a estudiantes de la carrera de psicología. El documento incluye aspectos básicos desde una perspectiva práctica, y espera servir de estímulo para continuar aprendiendo sobre el tema, que actualmente presenta un extraordinario desarrollo. Three interventions are presented to promote teamwork in organizations: Team Development, Team Building, and Team Training. This study is motivated by the need to specify the differences between these interventions. It is aimed mainly at Psychology tudents. The document includes essential aspects from a practical perspective and intends to encourage students to continue learning on the subject, which is currently experiencing extraordinary development.
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This article reports on the evolution of network structure as it relates to formal and informal social roles in well-bounded, isolated groups. Research was conducted at the Amundsen-Scott South Pole Station. Data were collected on crewmembers' networks of social interaction over each of three winter-over periods, when the station is completely isolated. In addition, data were collectedon the informal roles played by crewmembers (e.g., instrumental leadership, expressive leadership). The study found that globally coherent networks in winter-over groups were associated with group consensus on the presence of critically important informal social roles (e.g., expressive leadership)where global coherence is the extent to which a network forms a single group composed of a unitary core and periphery as opposed to being factionalized into two or more subgroups. Conversely, the evolution of multiple subgroups was associated with the absence of consensus on critical informal social roles, above all the critically important role of instrumental leader.
Applications of cluster analysis to marketing problems are reviewed. Alternative methods of cluster analysis are presented and evaluated in terms of recent empirical work on their performance characteristics. A two-stage cluster analysis methodology is recommended: preliminary identification of clusters via Ward's minimum variance method or simple average linkage, followed by cluster refinement by an iterative partitioning procedure. Issues and problems related to the use and validation of cluster analytic methods are discussed.
Prüfungsrelevanz und ein durchdachtes didaktisches Konzept zeichnen auch die fünfte Auflage des mittlerweile zum Standardwerk gewordenen Lehrbuchs der Statistik aus. Die Neuauflage wurde durch eine Formelsammlung erweitert und ermöglicht somit ein schnelles Auffinden der zentralen Formeln der Statistik. Das ebenfalls neue Glossar enthält die wichtigsten Begriffs-Definitionen in Kürze. Um die Lösungen der Übungsaufgaben garantiert verständlich und nachvollziebar darzustellen, wurden sie unter Mitarbeit von Studenten nochmals vollständig überarbeitet. Interpretationshilfen, Anleitungen für die Auswertung mit dem PC und Hinweise zur Bestimmung optimaler Stichprobenumfänge für die wichtigsten Verfahren und ein gut strukturiertes Layout gewährleisten nach wie vor ein effektives Arbeiten und Lernen.