During the past decade there has been an immense growth on research within teams
(e.g. Cohen and Bailey, 1997; Johnson and Johnson, 2003). Within this field of research the
interest for the recently emerged concept ‘team learning’ has increased rapidly (Yorks and
Sauquet, 2003). Senge pointed out the importance of team learning for organisations in his
book about organisational learning (Senge, 1990). He states that team learning is the key to
organisational learning and innovation necessary in our rapidly changing society. In addition,
research has shown that the occurrence of team learning within a team has a positive effect on
team performance (Van den Bossche, Gijselaers, Segers, and Kirschner, 2006).
The main focus of this article is to test the Team Learning Beliefs and Behaviours
model (TLB&B model) as proposed by Van den Bossche et al. (2006) in the, for team
learning relatively unexplored context of police and firemen teams. This model has been
tested in very different settings, e.g. military teams (Veestraeten, Kyndt and Dochy,
submitted); student teams (Van den Bossche et al, 2006), sport teams (Decuyper, Dochy, Van
den Bossche and De Bosscher, 2010). Validating the TLB&B model in response teams will
give the opportunity to make a comparison over different contexts. In addition, the effect of
self-efficacy on team learning and team performance will be examined in this study. Selfefficacy is a person’s belief in his or her ability to be successful in a course of action to meet
given situational demands (Bandura, 1993). Self-efficacy is predictive for individual
performance (Bandura, 1993) and individual learning (Van Dinther, Dochy and Segers, 2010)
and it influences a person’s motivation (Schunk, 2003). It can be argued that the extent to
which members of a team exhibit self-efficacy concerning the team task can influence the
learning of the team and team performance, because individual learning is an important
condition for team learning (Decuyper et al., 2010). Finally, this study will also focus on one
of the different input variables that influence the process of team learning and team
functioning, namely frequency of team meetings during a certain period (Van den Bossche et
al., 2006).
A ‘team’ defined.
Although teamwork is the subject of a vast body of empirical research, authors cannot
seem to agree on the definition of ‘a team’ (Delarue, Van Hootegem, Procter, and Burridge,
2008). To define the concept ‘team’ in this article a combination of the definitions of Cohen
and Bailey (1997) and Salas, Burke and Cannon-Bowles (2000) is adopted. Cohen and Bailey
(1997) describe a team as a group of individuals who depend on each other in their task, who
share responsibility for the team outcome and who consider themselves and are considered by
others as a social entity. A last criterion mentioned by these authors is that members
“…manage their relationships across organisational boundaries.” (Cohen and Bailey, 1997,
p.241). This criterion corresponds to what Kasl, Marsick and Dechant (1997) call boundary
crossing, which is seeking and giving information, views and ideas by interacting with other
individuals, units or teams. Salas, Burke and Cannon-Bowers (2000) add two more crucial
characteristics of a team to the definition of Cohen and Bailey, namely team interaction and
the development of a shared vision. By combining these two definitions, five key
characteristics of a team can be distinguished: interdependence, shared responsibility, the
ability to draw the boundaries of the team (determining the difference between the team and
the rest of the world), boundary crossing and the development of a shared mental model
(Cohen and Bailey, 1997; Salas et al., 2000).
In this study, the focus will specifically be on police and fireman teams. According to
the typology of Devine (2002) they can both be classified under ‘response teams’. These
teams are characterised by their collective team task which often requires them to scan an
unknown situation in a real-time setting, decide upon an appropriate action and perform the
action coordinated and quickly. They have to act in ambiguous high-risk environments where
their physical health is at stake and time-pressure is severe. Due to this team-pressure the
team members have to trust on their common sense and reason for a response. Coordination
between team members is important in this type of teams. Since prior research has shown that
the type of team has an influence on the observed team learning processes (Edmondson, 1999)
it is expected that certain processes and variables in the TLB&B model of Van den Bossche et
al. (2006) will have a different influence on team effectiveness compared to these variables
and processes in other team types. According to the model of Hollenbeck, Beersma and
Schouten (2012) however, police and firemen teams can be distinguished from each other in
their temporal stability. And this is also the case in this study: while most police teams are
fixed teams, who work together for a certain period, firemen teams tend to be less invariable.
The firemen teams that were investigated are composed from larger pools. Working in shifts,
firemen teams are assembled per intervention: every short-lived intervention team is thus part
of a larger pool, and team composition may vary from time to time. Firemen teams can thus
be considered to be less stable over time than police teams, although members work together
for a long time (in the larger pool). Therefore, differences between police teams and firemen
teams in the influence of the variables and processes in the TLB&B model of Van den
Bossche et al. (2006) on team effectiveness will also be investigated. Different input factors
could also have an influence on the occurrence and strength of team learning processes and
variables (Decuyper et al., 2010). Up until now most of these input variables have not been
investigated. In this study, the focus will be on the amount of gatherings of a team throughout
a certain period. This meeting frequency increases the teams’ communication opportunities
and stimulates members to disagree and think critically (Hofner, 1996). Because
communication and critical thinking are important processes in team learning (Van den
Bossche et al., 2006), this study will focus on the effect of the frequency of the meetings
teams have on team learning processes and variables.
Team learning
The review study of Decuyper et al. (2010) illustrates that numerous definitions of
team learning exist. Decuyper et al. (2010) identified no less than 30 different definitions of
team learning. In addition to the differences in conceptualisation, literature shows different
views on (the position of) team learning. Some authors consider team learning as a team
performance outcome of building shared knowledge and communication (Savelsbergh, van
der Heijden, and Poell, 2009) in addition to outcomes such as productivity or quality (Burke,
Stagl, Klein, Goodwin, Salas, and Halpin, 2006). Other authors consider team learning as a
process of adapting to change, enhancing understanding, or improving performance
(Edmondson, 1999). In this study, the definition of team learning by Van den Bossche et al.
(2006) is used: “building and maintaining of mutually shared cognition, leading to increased
perceived team performance” (p. 490), but team learning is also considered as an element of
team effectiveness. Thus the focus in this article will be on team learning as a process as well
as an outcome.
A Team Learning Beliefs and Behaviours model.
Van den Bossche et al. (2006) developed the TLB&B model (see Figure 1). This
model distinguishes four different categories of variables on the team level. The model
suggests that the social context of the team, referred to as beliefs about the interpersonal
context, has a direct influence on the team learning behaviours. These team learning
behaviours contribute to the development of mutually shared cognition and mutually shared
condition directly relates to team effectiveness. Subsequently, the different variables of the
team learning beliefs and behaviours model (Van den Bossche et al., 2006) will be discussed.
[insert figure 1]
Beliefs about the interpersonal context
A collection of different individuals is not a sufficient condition to learn as a team. In order to
be able to learn, certain aspects should be present in the interpersonal context (Roschelle and
Teasley, 1995). The most important aspects are included in the TLB&B model of Van den
Bossche et al. (2006). In the following paragraphs, the variables interdependence, social and
task cohesion, group potency and psychological safety are discussed. These variables belong
to the social perspective on team learning and are a part of the interpersonal context of the
team. The social perspective on team learning stresses the social factors that contribute to
successful team performance. Next to the social perspective there is also a cognitive
perspective on team learning that stresses the influence of group work on cognitive processes
and the cognitive processes that arise from working in group (Olivera and Strauss, 2004). This
perspective will be discussed later.
Interdependence. One of the key characteristics of a team is that team members work
interdependently (Kozlowski and Bell, 2003). Two forms of interdependence can be
distinguished namely task and outcome interdependence (Wageman, 1995). Task
interdependence is defined as the degree to which team members need each other and have to
rely on one another to successfully accomplish the team task (Burke et al., 2006). Outcome
interdependence can be defined as the extent to which successfully reaching the team goal
influences the outcome for each of the team members separately (De Dreu, 2007). Both types
can either be ‘positive’, ‘negative’ or ‘absent’ (Johnson, Johnson, and Smith, 2007). Positive
interdependence between team members exists when they feel that they can only reach their
goal when the other team members do so too. Negative interdependence is found when
individuals feel that they can only reach their goals when the other team members fail to do
so. Absence of interdependence is found when individuals feel that they can reach their goals
regardless of whether others reach their goals (Johnson et al., 2007).
Studies have shown that positive task interdependence enhances cooperation and
learning in teams (Cohen and Bailey, 1997) because an increasing level of task
interdependence heightens the need for coordination to achieve a positive outcome (Burke et
al., 2006). Outcome interdependence on the other hand contributes to team member’s effort to
achieve consensus and solutions (Wageman, 1995; Johnson et al., 2007). Moreover,
Wageman (1995) finds that total interdependence (a combination of task and outcome
interdependence) positively affects the degree to which members learn from each other. In her
qualitative research Edmondson (2002) also found a positive relationship between team
interdependence and team learning. As a consequence, when testing the model of Van den
Bossche et al. (2006) in police- and firemen teams positive relationship between the two
forms of interdependence and team learning is expected.
Hypothesis 1 (H1): (Task and outcome) Interdependence is positively related to the team
learning behaviours.
Cohesion. Cohesion is a frequently discussed concept in teamwork literature (Decuyper et al.,
2010). Most authors follow the definition of Festinger (1950) who defines cohesion as “the
resultant of all forces acting on all the members to remain in the group” (Festinger, 1950, p.
274). Cohesion can thus be seen as the force that keeps the team together (Mullen and
Copper, 1994). Beal, Cohen, Burke and McLendon (2003) found that the stronger cohesion,
the higher the team performance. Two underlying concepts can be distinguished namely task
cohesion and social cohesion (Mullen and Copper, 1994). Task cohesion concerns the
members’ attraction to the group because of a shared commitment to a shared task (Van
Vianen and De Dreu, 2001). Social cohesion can be described as team members’ attraction to
the group because of positive interpersonal relationships with other team members. Overall,
researchers agree that the influence of task cohesion on team learning behaviour and team
performance is stronger than the influence of social cohesion (Mullen and Copper, 1994).
Most researchers agree on the positive relation between task cohesion and team performance
(Mathieu et al., 2008). Moreover, Van den Bossche et al. (2006) found a positive influence of
task cohesion on team learning. But there is disagreement about the relation between social
cohesion and team performance (Beal et al., 2003). Mathieu et al. (2000) state that a certain
amount of social cohesion can attribute to a team’s learning and performance; a team cannot
function properly when team members refuse to work with each other (Mathieu et al., 2000).
However, social cohesion can become a problem when the relationships between different
team members distract them from their work. Van den Bossche et al. (2006) conclude
however that the influence of social cohesion on team learning behaviour is too small to be
significant.
Hypothesis 2a (H2a): Social cohesion is not related to the team learning behaviours.
Hypothesis 2b (H2b): Task cohesion is positively related to the team learning behaviours.
Psychological safety. Edmondson (1999) conceptualises psychological safety as “a shared
belief that the team is safe for interpersonal risk taking (…), a sense of confidence that the
team will not embarrass, reject, or punish someone for speaking up. This confidence stems
from mutual respect and trust among team members.” (p. 354). Edmondson investigates the
influence of psychological safety on team learning. She found that psychological safety
stimulates team learning behaviours such as seeking feedback, asking questions and
discussing decisions since team members worry less about possible embarrassment or
rejection due to speaking up when psychological safety is present (Edmondson, 1999).
Accordingly, Kayes et al. (2005) state that when psychological safety is low teams tend to
communicate less effectively and encounter conflict more often, which can counter the
occurrence of team learning. Some authors found that team psychological safety is a key
factor for team learning (e.g. Decuyper et al., 2010; Edmondson, 1999; Van den Bossche et
al., 2006).
Hypothesis 3 (H3): Team psychological safety is positively related to the team learning
behaviours.
Group potency. Group potency can be defined as the collective belief of team members that
their team has the ability to be successful (Mathieu et al., 2008). It is often confused with
team efficacy. Team efficacy refers to the collective belief that the team can be successful on
a certain task. Group potency on the other hand concerns various tasks in diverse contexts
(Mathieu et al., 2008). Group potency is a predictor for team performance (Cohen and Bailey,
1997; Mathieu et al., 2008). Edmondson (1999) and Van den Bossche et al. (2006) found a
positive influence of group potency on team learning behaviour even when controlling for
other variables such as team psychological safety, cohesion and interdependence (Decuyper et
al., 2010).
Hypothesis 4 (H4): Group potency is positively related to the team learning behaviours.
Team learning behaviours.
Team learning behaviours are considered as a part of the cognitive perspective on team
learning (Van den Bossche et al., 2006). The cognitive perspective on team learning stresses
the influence of group work on cognitive processes and the cognitive processes that arise from
working in a group. This perspective receives a lot of attention in educational research
(Olivera and Strauss, 2004).
Van den Bossche et al. (2006) define team learning behaviour as “the social process of
building mutually shared cognition” (p. 495) and they formulate three team learning
behaviours: construction, co-construction and constructive conflict. Although not all
researchers (e.g. Van Hoffenbeek and Koopman, 1996) agree on which behaviours can be
seen as team learning behaviours, these three behaviours are the most important team learning
behaviours. Thus the focus in this study will be on the three team learning behaviours Van
den Bossche et al. (2006) described in their model: construction, co-construction and
constructive conflict.
Construction and co-construction. The process of construction occurs when one (or more)
team member shares their opinion with the other team members and the other team members
listen and try to understand what is said (or not said) (Webb and Palinscar, 1996). This
concept is closely related to the action of ‘sharing’ as described by de Vries, van den Hooff,
and de Ridder (2006, p.116):
“Knowledge sharing is the process where individuals mutually exchange their (tacit
and explicit) knowledge and jointly create new knowledge. This definition implies that
every knowledge-sharing behaviour consists of both bringing (or donating) knowledge
and getting (or collecting) knowledge.”
Edmondson (1999) states that ‘sharing information’ as an important team learning behaviour.
Salas et al. (2000) consider the exchange of information and resources as a characteristic that
distinguishes a real ‘team’ from just ‘a group of people’ and Tjosvold et al. (2005) state that
the coordination and successful applying of individual resources can make a team effective.
This sharing of personal knowledge (tacit or explicit) can initiate a process of co-construction
in which team members not only donate or collect knowledge and experiences but
collaboratively improve, build on, negotiate and discuss the newly obtained information
(Baker, 1994). Through these processes of construction and co-construction information is not
only shared and obtained but new insights, experiences or expertise may be created (Wilson,
Goodman and Cronin, 2007).
Constructive conflict. Although agreement is a crucial notion for developing a body of
mutually shared knowledge, it is not unusual that team members encounter disagreement or
controversy while expressing their opinions and interacting with each other (Tjosvold and Yu,
2007). Tjosvold et al. (2005) found that cooperative conflict positively relates to team
performance, whereas competitive conflict negatively relates to team performance. This
distinction clarifies that when team members encounter disagreement or controversy there is
always a risk for the emergence of an ‘un-constructive’ conflict. A relevant question in this
context is what makes a conflict constructive? A constructive conflict can be described as
“expressing opposing views openly and respectfully, seeking mutually acceptable agreements,
listening and understanding each other, and combining ideas” (Tjosvold and Yu, 2007, p.
658). A mutual understanding of meanings is not sufficient but the actual acceptance and
integration of certain information is necessary for the information to become a part of the
common ground (Van den Bossche et al., 2006). Van den Bossche et al. (2006) also mention
that a key factor in constructive conflict is ‘communication’. When a team does not react to
conflict or controversy with ‘communication’, escalation of the problem can negatively affect
the team’s productivity (Van den Bossche et al., 2006). But when a team does communicate
about the matter by elaboration, negotiation and discussion, mutually shared cognition can
occur (Van den Bossche et al., 2006).
Hypothesis 5 (H5): The amount of (co-)construction and constructive conflict in a team is
positively related to the construction of mutually shared cognition in this team.
Hypothesis 6 (H6): The amount of (co-)construction and constructive conflict in a team is
positively related to team effectiveness.
Mutually shared cognition.
A key factor in the team learning model as proposed by Van den Bossche et al. (2006)
is mutually shared cognition which is seen as the primary outcome of the team learning
process and is positively related to team performance. Decuyper et al. (2010) stated that
through the sharing and storage of knowledge a team can build a shared mental model: “team
member’s shared, organised understandings and mental representations of knowledge about
the key elements of the team’s task environment” (Decuyper et al., 2010, p.121). The question
that rises is what exactly is ‘shared’ in mutually shared cognition? Cannon-Bowers and Salas
(2001) state that ‘what is shared’ can be divided in four broad categories, all of which can
have a different function in teamwork. The first two categories concern the team task. The
first category, task-specific knowledge, allows team members to perform tasks in an
organised way without necessarily having to plan or discuss the action. Team members that
share task-related knowledge – the second task-specific category that Cannon-Bowers and
Salas distinguish – have an agreement about what the task-related processes are in the team.
They have a shared idea about what teamwork is, how it proceeds within the team and how
important it is for the team and the team performance. This kind of shared cognition enhances
the team’s ability to successfully complete a task. The other two categories concern the team
itself as a group of people. The third category is the team member’s knowledge of each other.
Team members need to know each other’s preferences, strengths and weaknesses in order to
maximise the team performance. With this kind of knowledge they can adjust their actions to
what they expect from their teammates. The fourth category is the shared attitudes and beliefs
among those team members. When team members share attitudes and beliefs they will have
compatible ideas about tasks and work. The decisions and actions they take will be more
effective. Both categories are not task-specific but very team-specific (Cannon-Bowers and
Salas, 2001). The four categories of shared cognition lead to better performance both direct
and indirect. Shared cognition directly leads to better fulfilling a task. Indirectly it leads to
better team processes, which in turn leads to better performance (Cannon-Bowers and Salas,
2001). Klimoski and Mohammed (1994) confirm this role of mutually shared cognition on
team efficiency and performance but they notify the risk of over-reliability on this shared
information and groupthink.
Hypothesis 7 (H7): A more developed body of mutually shared cognition is positively related
to team effectiveness.
Team effectiveness.
Several authors have shown the positive influence of team learning on team
effectiveness (Edmondson, 1999; Van der Vegt and Bunderson, 2005). In line with
researchers such as Van den Bossche et al. (2006) and Edmondson (1999) team effectiveness
is defined in a broad sense. Team effectiveness does not only incorporate team performance
but also team viability and team learning (Van den Bossche et al., 2006). Team performance
concerns both the process and the product of the team’s work, whereas team viability
concerns the willingness of team members to remain a team in the future (Balkundi, Barsness,
and Michael, 2009). Van den Bossche et al. (2006) incorporated team learning in their team
effectiveness scale indicating that they not only consider team learning as a process that
influences team effectiveness but also as a product of team effectiveness.
Self-efficacy
Cohen and Bailey (1997) concluded their comprehensive review on team functioning
with the remark that future research could further explore the key areas of group potency and
collective self-efficacy. Considering the key role of self-efficacy in explaining individual
performance (Bandura, 1993) and individual learning (Schunk, 2003; Van Dinther, Dochy
and Segers, 2011) it seems useful to examine the role that self-efficacy of the different team
members could play in team learning. According to Bandura’s self-efficacy theory, a person’s
self-efficacy can be described as the belief an individual has in his/her own capabilities to
successfully accomplish a certain task (Bandura, 1997). “Efficacy beliefs influence how
people feel, think, motivate themselves and behave.” (Bandura, 1993, p.118).
In this study, self-efficacy of team members concerning the team task will be
measured and based on those measurements the average amount of self-efficacy that is
present in the team will be determined. The influence of this variable on team learning
behaviours and team performance will be determined. Since self-efficacy affects a person’s
learning behaviour (Schunk, 2003) and influences how people act and behave (Bandura,
1993) (e.g. in teams), it could be hypothesised that a positive relationship between individual
team member self-efficacy of a team and team learning behaviour (H8a), and team
effectiveness can be found (H8b).
Police and firemen teams.
Different teams have different task structures, different memberships, different time
durations, and different health risks associated with their task (Devine, 2002). These
differences influence the team processes and can partly explain the differences in results in
team research (Cohen and Bailey, 1997; Edmondson, 1999; Devine, 2002). E.g. Veestraeten,
Kyndt, Decuyper and Dochy (2012) found that social cohesion has an important influence on
team learning behaviours in military teams, which is contrary to the finding of Van den
Bossche et al. (2006) that social cohesion has no influence on team learning behaviours in
temporary student teams. In the context of this study, it will be investigated to which extent
different variables of the team learning model are present in police and firemen teams and if
there is a difference between police teams and firemen teams. Although both teams can be
considered as response teams (Devine, 2002), there are several aspects in which these teams
differ from each other (e.g. health risk during intervention, type of task, team tenure).
Another distinction that can be made between different teams is how often teams come
together: some teams meet every week or even very day; other teams meet once a month.
Drach-Zahavy and Somech (2001) found that the meeting frequency of teams positively
influences the success of a team. The more teams come together, the higher their motivation
and commitment to the team goal, which contributes to the team’s performance (Brewer and
Kramer, 1986) and effectiveness (Lizzio and Wilson, 2006). It could be hypothesised that the
meeting frequency influences the different variables and processes in the TLB&B model of
Van den Bossche et al. (2006) (where a higher amount of meetings results in higher scores on
the other variables) (H9), because the more teams meet, the more communication
opportunities are created and the more team members are stimulated to disagree and think
criticaly (Hofner, 1996). Communication and critical thinking are important processes in team
learning (Van den Bossche et al, 2006).
Method
The present study is a quantitative empirical study that investigates team learning in
police and firemen teams. To test the formulated hypotheses data were collected from a
number of operational police- and firemen teams by means of a survey.
Participants
The criteria for inclusion for respondents are determined based on the definition of a
team mentioned above: a group of people that consists of two or more members (between 18
and 65 years old), that operates around professional activities, with a clear goal or task can be
seen as a team when members and non-members see this group of people as a social entity.
All included teams are active intervention and operational field teams of Belgian police and
firemen departments. Ad hoc teams, that only work together and form a team for several
hours, were also admitted in our research if the members of this team were part of a larger
team or pool and thus already knew each other and had regularly worked together. Data were
collected from 39 police departments and 16 firemen departments in Belgium. In total, 771
individuals divided over 216 work teams completed the questionnaire. The teams of which
more than one third of the members did not fill out the questionnaire were excluded from the
analysis. After this exclusion 126 teams remained. The average number of members per team
is 6.48 members (SD = 3.31; min. = 2; max. = 21). More than half of the teams had two or
more team meetings a week (52.4%, N = 77).
Instruments
The questionnaire in this studies consisted of three different parts. The first part is the
Team Learning Beliefs and Behaviours Questionnaire (Van den Bossche et al., 2006). This
questionnaire comprises eight scales and measures all variables in this study except selfefficacy. The second part of the questionnaire consists of a scale developed to measure selfefficacy. The scale is based on items measuring self-efficacy within the research of Keijzer,
Oomens and Hazelzet (2009) and the items of the scale used by Van den Bossche et al. (2006)
to measure group potency at the individual level. In total seven items measuring self-efficacy
were included. All the items were scored with a 7-point Likert scale that ranged from
‘strongly disagree’ (1) over ‘neutral’ (4), to ‘strongly agree’ (7). The final part of the
questionnaire consisted of ten questions pertaining to the demographic information of the
participants.
Analyses
All analyses for this study were conducted with the R software (R Development Core Team,
2012), using the packages ‘psych’ (Revelle, 2012), ‘lavaan’ (Rosseel, 2012), ‘car’ (Fox
2002), ‘nlme’ (Pinheiro, Bates, DebRoy, Sarkar and the R Development Core Team,
2012),‘reshape’ (Wickham, 2007), and ‘Hmisc’ (Harrell, 2012).
Confirmatory factor analysis. Because a validated questionnaire is used for this research,
three confirmatory factor analyses (CFA) are conducted to test whether the structure of the
original questionnaire fitted the data of this study. One CFA tested the adequacy of the scales
measuring the beliefs of the interpersonal context. A second CFA analysed the fit of the TLB
and MSC scales. The adequacy of the team effectiveness scale was tested in a third CFA.
Based on the modification indices, respectively four and three covariates were added to the
first and second CFA to enhance the model fit, in the last CFA two covariates were inserted.
All covariates were between items belonging to the same scale. CFI values of respectively
.918, .972 and 1.00; and TLI values equal to .900, .966 and 1.00 reflect an adequate fit of the
model to the data (Schumacker and Lomax, 1996). Furthermore, the SRMR of all three CFAs
has a value smaller than .09 (SRMR = .048, .032 and .000) and the RMSEA respectively
equals .064, .049 and .002. These indicate an acceptable model fit (Byrne, 1998; Brown and
Cudeck, 1993). Of the 40 original items 38 loaded significantly on the construct they were
predicted to load on. One item of the interdependence scale was deleted since it loaded
significantly on two factors. One item of the mutually shared cognition scale was deleted due
to a non-significant loading. Task cohesion and interdependence have an internal
inconsistency below .60 and are therefore excluded from further analyses (see table 1).
Exploratory factor analysis. An exploratory factor analysis (maximum likelihood estimation
and varimax rotation ) was conducted on the items measuring self-efficacy. All items except
one had high loadings (between .579 and .756) on one factor. The internal consistency of the
scale equals .82. A second exploratory factor analysis was conducted, to check whether group
potency and self-efficacy are two distinct constructs. Therefore, the six items of the group
potency-scale were analysed together with the six self-efficacy items. Results show that group
potency and self-efficacy should be seen as two different constructs: all included items loaded
high on only one of both constructs.
Within-group agreement as second-level predictor. Although data were collected from
different individuals, it should be recognised that these individuals are nested in team.
Therefore an analysis of the within-group agreement per team and per scale was performed
using the multiple-item estimator rwg (James, Demaree, and Wolf, 1984). Analysis of the rwg
per team per variable showed an average rwg higher than the cut-off score of .70 for all
constructs (George and Bettenhausen, 1990). A mean of the rwg over the different team
constructs was calculated, which resembles the within-group agreement of a team, and is
included in the analyses to answer the research questions.
Method of analysis. The hypotheses are tested in three steps. First, the relation between the
beliefs about the interpersonal context and team learning behaviour are examined by means of
a multilevel analysis. In addition, the variable self-efficacy is added. Secondly, the relation
between team learning behaviours, mutually shared cognition and team effectiveness is
investigated. Finally, the mediation of mutually shared cognition on the relation between team
learning behaviour and team effectiveness is tested by means of a Sobel’s test. Next to these
analyses ANOVA-analyses were conducted to test the research question: ‘Do the measures of
the observed constructs differ significantly among teams?’ Distinctions are made between
police and firemen teams, and based on the frequency of meeting of these teams. For
example, some teams meet once a week and others meet once a month. It will be investigated
how this influences the different variables cited in this study.
Results
Descriptive statistics, correlations and internal consistencies of the investigated factors can be
found in Table 1.
[Insert table 1]
The relation between beliefs about the interpersonal context and team learning behaviour.
To test hypotheses 1 to 4, a multilevel model predicting team learning behaviour was built up
in several steps. Firstly, a model without predictors including a fixed intercept was calculated
(Model 1). Model 1 was compared to a second model without predictors including a random
intercept (Model 2) using the chi-square likelihood ratio test. Model 2 showed a better fit,
indicating that a multilevel approach was necessary. In a following step, the variable
psychological safety was added to as a first predictor, because psychological safety has been
shown to be a key factor in team learning (e.g., Decuyper et al., 2010; Van den Bossche et al.,
2006). Model 3 showed a better fit than Model 2. In Model 4, social cohesion and group
potency were added as predictors. In a next step, the individual characteristic self-efficacy
was included in the model (Model 5). Model 6 includes the within-agreement per team (mean
rwg) as a level-2 predictor for team learning behavior. The fit of Model 6 was better than
Model 5, showing that the within-agreement of a team is important for the emergence of team
learning behaviours. In Model 7 – which showed a better fit than Model 6 – the slope of
psychological safety was set to random to examine whether the relationship between
psychological safety and team learning behaviour varies significantly among teams. The
inclusion of this random slope resulted into a better model. Finally, a cross-level interaction
effect between psychological safety and within-group agreement was included in Model 8 to
explore whether within-agreement can explain the variation in the slope of psychological
safety. Since this cross-level interaction improves the model fit, this Model 8 is considered as
our final model on which conclusions will be based. The results of the multilevel analyses
predicting team learning behaviour are displayed in Table 2.
[Insert table 2]
The final multilevel model shows that social cohesion is a significant predictor for
team learning behaviours (b = .15, t = 6.23, df = 637, p < .001), meaning that H2a can be
rejected. Hypotheses 1 and 2b cannot be discussed, since the variables interdependence and
task cohesion were not included in our analyses. Furthermore the results show that
psychological safety is the best level-1 predictor for team learning behaviour (b = .76, t =
4.71, df = 637, p < .001), followed by group potency (b = .27, t = 8.30, df = 637, p < .001) and
self-efficacy (b = .18, t = 5.50, df = 637, p < .001). These results confirm hypotheses H3, H4
and H8a. Furthermore, a positive relation between the level-2 predictor within-group
agreement and team learning behaviours (b = 3.26, t = 3.09, df = 637, p <.01) and a
significant negative interaction effect of psychological safety (level 1) and within-group
agreement (level 2) (b = -.53, t = -2.63, df = 637, p < .01). This cross-level interaction effect
together with the significant random slope of psychological safety shows that the relationship
between psychological safety and team learning behaviour varies between teams and that this
variation is related to the within-group agreement. The effect of psychological safety is
stronger in teams with a low within-group agreement, but remains positive even when intergroup agreement is high. This cross-level interaction effect is displayed in figure 2. The final
model has a pseudo-R2 equal to .77
[Insert figure 2]
The mediation of mutually shared cognition on the relation between team learning behaviour
and team effectiveness.
To test the hypotheses 5, 6, 7 and 8b a second multilevel model is built up. The first model
that was tested (Model 1) only included a fixed intercept. In Model 2, which fitted
significantly better, the intercept was set to random. Model 3 includes mutually shared
cognition as a predictor for team effectiveness. Another predictor, team learning behaviour
was included in Model 4, which fits better than Model 3. Finally, in Model 5 we added selfefficacy as a predictor. Model 5 shows a significant improvement compared to Model 4. In a
last model (Model 6,) the level-2 predictor within-group agreement was included. Model 6
however did not show a significant improvement compared to Model 5. Therefore, Model 5 is
considered our final model. The results of this multilevel analysis can be found in Table 3.
[Insert table 3]
The results of the final model show that team learning behaviours (b = .59, t = 15.54, df =
640, p < .001) and self-efficacy (b = .27, t = 9.05, df = 640, p < .001) significantly predict
team effectiveness. In addition, mutually shared cognition positively predicts team
effectiveness (b = .18, t = 6.85, df = 640, p < .001). These results support H7 and H8. To test
whether mutually shared cognition is a mediator for the relationship between team learning
behaviours and team effectiveness, a Sobel’s test is performed. The test is significant (indirect
effect = .17, z = 6.19, p < .0001), which means that mediation takes place. However, the
contribution of team learning behaviour remains strong (b = .76, t = 21.57, df = 641, p < .01)
indicating a limited mediation effect. The pseudo-R2 of this final model equals .72.
Differences among types of teams.
As a last step in our analyses one-way ANOVA’s were conducted to test our last hypothesis
concerning team meeting frequency, and check our data for significant differences among
groups.
Teams with a different frequency of meetings were compared to each other. Significant
differences were found for social cohesion (F(5,763) = 5.28, p < .001, η² = .033), group
potency (F(5,765) = 10.51, p < .001, η² = .064), self-efficacy (F(5,765) = 5.33, p < .001, η² =
.034), psychological safety (F(5,765) = 7.43, p < .001, η² = .046), team learning behaviour
(F(5,765) = 9.68, p < .001, η² = .060), mutually shared cognition (F(5,765) = 8.39, p < .001,
η² = .052) and team effectiveness (F(5,765) = 8.37, p < .001, η² = .052), which overall
supports our hypothesis. More specifically, post-hoc tests revealed teams that only meet halfyearly, score significantly worse than all other teams on social cohesion, group potency,
mutually shared cognition, team learning behaviours and team effectiveness and score worse
than teams that meet (more than) weekly and two-monthly on psychological safety and selfefficacy. The p-values for these findings are displayed in table 4. Teams that gather weekly
score significantly better than teams that gather more on social cohesion (p < .05), group
potency (p < .01), psychological safety (p < .01), team learning behaviours (p < .05) and
mutually shared cognition (p < .05). These results overall confirm H9.
[Insert table 4]
Furthermore the differences between police- and fireman teams were investigated. Firemen
teams significantly score higher on group potency (F(1,769) = 10.1, p < .01, η² = .013) and
self-efficacy (F(1,769) = 6.65, p < .05, η² = .009); police teams score higher on psychological
safety (F(1,769) = 8.70, p < .01, η² = .011).
Conclusion and discussion
This study generally confirms the existing TLB&B model as proposed by Van den
Bossche et al. (2006). Teams of police- and firemen profit from a high amount of
psychological safety. Being able to depend on and trust each other when working together
without having to fear rejection or negative reactions from other team members is positively
related with team learning behaviours and team effectiveness in this context. Together with
the confidence in oneself and in the abilities of the team, these beliefs create a context in
which knowledge sharing and creation, discussion and communication is fostered and conflict
is not avoided but exploited as an opportunity to tackle problems. Through these team
learning processes the team will be able to build mutually shared cognition, which enhances
the team’s effectiveness. Mutually shared cognition can thus be seen as a mediator of the
relationship between team learning behaviour and team effectiveness. This mediation is only
partial, team learning behaviours also directly influence team effectiveness. Thus police- and
firemen teams profit from working in a collaborative learning environment by building a body
of shared knowledge and enhancing their team effectiveness.
As stated above, we added within-group agreement as a variable in our analyses in
order to acknowledge the ‘nestedness’ of the individual respondents in teams. Results show
that the level to which team members think the same of their team and team work has a
positive influence on the emergence of team learning behaviour. A direct effect between
within-group agreement and team effectiveness was however not found.
Another important conclusion of this research is the finding that firemen teams score
higher on group potency, self-efficacy than police teams. An explanation for this finding
could be that the interventions of firemen are orchestrated with e.g. very strict safety rules.
This might enhance the feeling of skill which could lead to a higher individual and team
effectiveness in performing the team task. Police teams in score higher on psychological
safety. This could be explained by their temporal stability, because team members work
together for a long period of time trust is build and psychological safety grows.
This research also shows that teams with a higher average amount of team meetings
score higher on social cohesion, group potency, psychological safety, team learning behaviour
and mutually shared cognition. Members of teams that gather more often, develop a stronger
sense of closeness to each other, feel more free to make mistakes and have a stronger belief in
the abilities of the team. Furthermore, members of teams with more team meetings exhibit
more team learning behaviour, mutually shared cognition and are overall more effective than
teams with less team meetings. As a result organising meetings more regularly, preferably at
least one meeting per week seems to be an important practical intervention for police- and
firemen.
In other words, these findings show the necessity to not only cross-validate the team
learning model in various contexts but also to investigate possible variations to the model
depending on the context.
Limitations and issues for future research
First a limitation concerning the questionnaire is mentioned. The role of both task
cohesion and interdependence in the TLB&B model could not be investigated since the
scales’ internal consistencies were too low. The items of the task cohesion scale were
formulated inversely, which could be confusing for respondents. In line with this fact, it is
important to take a critical look at the significant effect of social cohesion on the team
learning behaviours. This effect is in line with research from Veestraeten et al. (submitted).
Other studies found no such significant effect (e.g. Van den Bossche et al, 2006). The fact
that task cohesion was not included in the analysis might have influenced occurrence of a
significant relationship between social cohesion and team learning behaviour.
Some remarks can be made concerning the research method. First of all this survey
research examines team members’ perceptions of team level constructs. One could argue that
team members are not the best observers of team processes in the teams they are a part of
themselves. We attempted to (to some extent) counter this concern by analysing the data on
an individual level, and acknowledging that these individuals are nested in teams by adding
within-group agreement as a variable in our analyses. Another concern is that of the social
desirability bias. This bias occurs when respondents give socially accepted answers instead of
their own opinion. In order to make these measures more reliable it is recommended to
measure the constructs by questioning different stakeholders of the team (internal or external).
When data about team performance are collected from for example team members, clients and
a manager, these data could then be triangulated and this would result in stronger
measurements (Mathison, 1988). An external observer could also counter both concerns about
the research method and be a valuable addition for the collected data.
Another dynamic that influences teams and their functioning is the fact that teams
develop and change over time (Wheelan, 2005) and as a consequence the same team could
score differently on certain constructs on different moments in time. Measuring the different
constructs on different moments in time might shed a better light on the dynamics of team
learning.
Finally, future research is necessary to investigate the TLB&B model in different
contexts with different team types. An interesting path could be to test the model in temporary
project teams (Cohen and Bailey, 1996). These teams consist of people with different
expertise and are composed in order to create innovative results. Taking into account the
finding that teams with a higher average meeting frequency seem to operate in a better team
learning environment, it seems interesting to find out what the influence of the temporary and
intensive nature of project teams is on the different variables in the TLB&B model (Van den
Bossche et al., 2006).
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Figure 1
Team Learning Beliefs and Behaviors - model (Van den Bossche et al., 2006)
Figure 2
Cross-level interaction effect
Team Learning Behaviours
Low Within-group
agreement (level 2)
High Within-group
agreement (level 2)
Low Psychological Safety
High Psychological Safety
Note: Unstandardised bs are reported
Table 1
Descriptive statistics, correlations among variables and Cronbach’s alfas
Variable
M
SD
1
2
3
4
5
6
7
8
9
1. (Outcome)
Interdependence
2. Social cohesion
5.44 1.10 .53
3. Task cohesion
5.24 1.38 .41** .37** .52
4. Psychological safety
5.16 1.04 .60** .58** .55** .77
5. Group potency
5.40 .96
.63** .63** .43** .66** .86
6. Self-efficacy
5.36 .86
.55** .58** .30** .54** .72** .82
7. Team learning
behaviour
5.36 .96
.71** .66** .49** .75** .75** .66** .90
8. Mutually shared
cognition
4.90 1.22 .65** .51** .44** .67** .66** .51** .79** .86
9. Team effectiveness
5.51 1.07 .65** .73** .50** .74** .83** .67** .84** .73** .88
10. Within-group agreement
* p < .05, ** p < .01
.81
10
5.63 1.08 .49** .75
.10
.14** .16** .16** .20** .14** .07* .22** .21** .19** .79
Table 2
Results Multilevel Analyses (Team Learning Behaviour as dependent variable)
Model
1
2
3
4
5
6
7
8
154.40***
97.15***
14.89***
4.45***
2.29*
-.88
-.35
-2.64**
(769)
(643)
(642)
(640)
(639)
(638)
(638)
(637)
29.62***
13.93***
13.82***
13.49***
12.12***
4.71***
(642)
(640)
(639)
(638)
(638)
(637)
7.64***
6.46***
6.27***
6.35***
6.23***
(640)
(639)
(638)
(638)
(637)
12.34***
8.53***
8.55***
8.36***
8.30***
(640)
(639)
(638)
(638)
(637)
5.14***
5.36***
5.26***
5.50***
(639)
(638)
(638)
(637)
2.88**
2.34*
3.09**
(638)
(638)
(637)
Fixed effects – tstatistc (df)
(Intercept)
Psychological Safety
Social Cohesion
Group Potency
Self-efficacy
Within-group
agreement
(level 2 predictor)
Psychological Safety*Withingroup
agreement
(cross-level interaction)
-2.63**
(637)
Random effects –
variance
components
(Intercept)
.26
.05
.02
.02
.02
Psychological Safety
Residual
.40
.29
.01
.01
.67
.35
.25
.24
.24
.23
.23
2024.16
1455.97
1173.23
1147.15
1138.97
1130.98
1124.41
Models compared
1 vs. 2
2 vs. 3
3 vs. 4
4 vs. 5
5 vs. 6
6 vs. 7
7 vs. 8
χ2
99.86***
568.19***
282.74***
26.09***
8.17**
7.99*
6.57*
(df)
(2, 3)
(3, 4)
(4, 6)
(6, 7)
(7, 8)
(8, 10)
(10, 11)
Model comparison
-2log likelihood
2124.02
Note: Nobservations = 769, Ngroups = 126; *p<.05, **p<.01, ***p<.001; Model 1: fixed intercept; Model 2: random intercept; Model 3: psychological safety; Model 4: adding social cohesion and group potency; Model 5:
adding self-efficacy; Model 6: adding level-2 variable (within-group agreement); Model 7: adding random slope psychological safety; Model 8: adding cross-level interaction effect psychological safety*within-group
agreement
Table 3
Results Multilevel Analyses (Team Effectiveness as dependent variable)
Model
Fixed effects
statistc (df)
–
Team
Behaviours
2
3
4
5
6
142.44***
92.55***
20.95***
5.01***
-.03
-.47
(769)
(643)
(642)
(641)
(640)
(639)
28.55***
6.31***
6.85***
6.79***
(642)
(641)
(640)
(639)
21.57***
15.54***
15.35***
(641)
(640)
(639)
9.05***
9.06***
(640)
(639)
t-
(Intercept)
Mutually
Cognition
1
Shared
Learning
Self-efficacy
Within-group
agreement
(level 2 predictor)
-.58
(639)
Random
effects
–
variance components
(Intercept)
.29
.03
.01
.02
.02
Residual
.88
.51
.33
.55
.55
Model comparison
-2log likelihood
2290.37
2211.95
1694.46
1330.78
1253.24
1252.90
Models compared
1 vs. 2
2 vs. 3
3 vs. 4
4 vs. 5
5 vs. 6
χ2
78.42***
517.49***
363.69***
77.53***
.34
(df)
(2, 3)
(3, 4)
(4, 5)
(5, 6)
(6, 7)
Note: Nobservations = 769, Ngroups = 126; *p<.05, **p<.01, ***p<.001; Model 1: fixed intercept; Model 2: random intercept; Model 3: MSC; Model 4: adding TLB; Model 5: adding self-efficacy; Model 6: adding level-2
predictor
Table 4
Results ANOVA analyses
Mean differences between groups
Team Meeting Frequency
Social Cohesion
More than once a week vs. Weekly
-.36 *
More than once a week vs. Two-monthly
Group Potency
Psychological
Safety
-.38 **
-.40 **
-.40 *
-.50 **
Self-efficacy
Team Learning
Mutually Shared Team
Behaviours
Cognition
-.36 *
-.44 *
-.53 *
Two-weekly vs. Weekly
-.53 *
-.48 *
Two-weekly vs. Two-monthly
-.62 **
-.49 *
-.38 *
Monthly vs. Weekly
-.47 ***
-.41 *
Monthly vs. Two-monthly
-.50 **
-.51 **
Effectiveness
Half-yearly vs. More than once a week
-.54 **
-.68 ***
-.46 *
-.51 **
-.68 ***
-.76 ***
-.75 ***
Half-yearly vs. Weekly
-.90 ***
-1.06 ***
-.86 ***
-.64 ***
-1.04 ***
-1.20 ***
-1.07 ***
Half-yearly vs. Two-weekly
-.70 **
-.62 **
-.56 *
-.90 ***
-.76 **
Half-yearly vs. Monthly
-.57 **
-.59 **
-.66 ***
-.83 ***
-.73 ***
Half-yearly vs. Two-monthly
-.81 ***
-1.08 ***
-1.06 ***
-1.29 ***
-1.17 ***
Note: Only significant differences were reported; *p < .05, ** p < .01, *** p < .001
-.95 ***
-.74 ***