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Development and validation of a social network instrument to assess and strengthen teacher collaboration in inclusive education

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A social network approach provides a valuable framework to assess and strengthen teacher collaboration, which is considered important in realizing inclusive education. However, to our knowledge, there is no research that has used a social network approach to measure and strengthen teacher collaboration in the context of inclusive education. Therefore, this study aims to develop and validate a social network instrument that provides teachers, school teams and researchers insight into teacher collaboration in the light of inclusive education. Regarding the development, specific issues that need to be taken into account in developing a network questionnaire are shown and applied. Regarding the validation, evidence on the content, response processes and internal structure of the instrument are provided. Additionally, the cognitive load to complete the instrument and the value of feedback after completing the instrument are studied. Data were gathered in three primary and two secondary schools through a mixed method design, using an online questionnaire (N = 91) and focus groups and interviews with a subset of participants (N = 23). The findings suggest that our instrument is a valid tool to assess teacher collaboration, and to strengthen teacher collaboration by providing teachers and teams feedback on their networks. (http://www.pedagogischestudien.nl/search?identifier=692574)
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2019 (96) 190-207
Abstract
A social network approach provides a valuable
framework to assess and strengthen teacher
collaboration, which is considered important
in realizing inclusive education. However, to
our knowledge, there is no research that has
used a social network approach to measure
and strengthen teacher collaboration in the
context of inclusive education. Therefore,
this study aims to develop and validate a
social network instrument that provides
teachers, school teams and researchers
insight into teacher collaboration in the
light of inclusive education. Regarding the
development, specific issues that need to be
taken into account in developing a network
questionnaire are shown and applied.
Regarding the validation, evidence on the
content, response processes and internal
structure of the instrument are provided.
Additionally, the cognitive load to complete
the instrument and the value of feedback
after completing the instrument are studied.
Data were gathered in three primary and two
secondary schools through a mixed method
design, using an online questionnaire (N =
91) and focus groups and interviews with
a subset of the participants (N = 23). The
findings suggest that our instrument is a
valid tool to assess teacher collaboration,
and to strengthen teacher collaboration by
providing teachers and teams feedback on
their networks.
Keywords: inclusive education; teacher
collaboration; social network approach;
instrument development; mixed method
design
1 Introduction
Worldwide, a shift is taking place from
segregated towards more inclusive education
(Banks et al., 2007). Despite the tendency
towards more inclusive education, there are
various interpretations of the concept, varying
from the inclusion of certain groups who
share a history of segregation (e.g., students
with a disability) in mainstream education, to
a broader view of inclusion as a reform that
appreciates and responds to the diversity of
all learners (Ainscow & Miles, 2008). In
implementing inclusive education teachers
are central agents, by ensuring that the
learning environment (LE) addresses the
educational needs of all students. However,
one cannot expect that a single teacher,
working alone, is able to meet all students’
needs (Carroll, 2009). Teacher collaboration
is therefore assumed to be a pivotal factor in
realizing inclusive education (e.g., King-
Sears, Janney, & Snell, 2015; Mitchell, 2014;
Santoli, Sachs, Romey, & McClurg, 2008).
1.1 Teacher collaboration
In the current study, teacher collaboration is
defined in a broad sense as “joint interaction
in the group in all activities that are needed to
perform a shared task” (Vangrieken, Dochy,
Raes, & Kyndt, 2015, p. 23). If we apply this
definition to the context of inclusive
education, teacher collaboration concerns
joint interaction between all actors involved
in improving and adapting the LE to the
educational needs of the student so that the
student is truly included in mainstream
education. The particularity of teacher
collaboration in the context of inclusive
education is that it pursues a specific
objective, namely realising inclusive
education, which implies that other and often
more actors are involved. These actors
Development and validation of a social network
instrument to assess and strengthen teacher
collaboration in inclusive education1
J. Sannen, N. Ferbuyt, S. De Maeyer, E. Struyf, P. Van Avermaet and K. Petry2
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include school internal professionals (e.g.,
teachers, special educational needs (SEN)
coordinators), as well as school external
professionals (e.g., pedagogical counsellors,
teachers from special schools), as well as
parents and pupils (Alquraini & Gut, 2012;
Hunt, Soto, Maier, Müller, & Goetz, 2002;
Keay & Lloyd, 2011).
Despite the acknowledged importance of
teacher collaboration in realizing inclusive
education, there are some challenges in
research and practice. First, previous research
has mainly focused on formal teacher
collaboration, for instance, on consultation
sessions offered by special education teachers
to general teachers, or on formally organised
meetings (Hunt et al., 2002; Sundqvist, von
Ahlefeld Nisser, & Ström, 2014). Although
teachers in inclusive education do not often
work together (see below), if they do, they
often collaborate in an informal way, for
example discussing a student’s need in the
hallway or lunchroom (Kugelmass, 2001;
Nochajski, 2002). However, this informal
collaboration is less taken into account.
Second, little is known regarding how
collaboration takes shape in the context of
inclusive education, which is expected to be
different from collaboration in other contexts
given the challenges and complexity of
inclusive education. Previous research has
mainly focused on the prerequisites for
successful collaboration such as teachers’
communication skills, working towards a
shared goal (e.g., Alquraini & Gut, 2012;
Hunt et al., 2002; Thousand & Villa, 2000),
and teachers’ general experiences with and
perception of their collaboration (e.g., Nel,
Engelbrecht, Nel, & Tlale, 2014; Sandberg &
Ottosson, 2010; Xu & Malinen, 2015).
Although this research provides interesting
findings on the preconditions for teacher
collaboration, it gives little information on
how collaboration is realised in daily practice,
for example, with regard to frequency and
actors involved.
Third, the image of the teacher working
alone in his/her class is still prevalent
(European Commission, 2013; Klassen &
Durksen, 2012; Leonard & Leonard, 2003;
Struyf et al., 2012). This is not surprising
since teachers are not prepared to collaborate
with their colleagues during teacher training
and therefore do not feel competent to
collaborate (EVALO, 2012; Malinen,
Savolainen, & Xu, 2012; Zagona, Kurth, &
Macfarland, 2017). Teachers’ self-efficacy in
collaboration, however, seems to be the
strongest predictor of attitudes towards
inclusive education, which suggests that
collaboration can be particularly important to
improve attitudes towards inclusion (Malinen
et al., 2012; Savolainen, Engelbrecht, Nel, &
Malinen, 2012; Yada & Savolainen, 2017).
Hence, there is an urgent need to strengthen
teachers in establishing collaboration. As will
be shown in the next section, a social network
approach (SNA) offers opportunities to
address these challenges.
1.2 A social network approach to teacher
collaboration
Before considering the opportunities offered
by a SNA, we will briefly explain this
approach. A SNA focuses on the social
relationships between actors and the patterns
of these social relationships (i.e., the social
network structure; Wasserman & Faust,
1994). Three key assumptions characterize
this approach (Degenne & Forsé, 2004).
First, individuals are seen as interdependent,
rather than independent, because of their
embeddedness in a social structure (e.g., a
teacher has a dyadic relationship with a close
colleague, that is nested in a grade-level team
within a school). Social network researchers
therefore argue that changes at an individual
level (e.g., a teacher’s attitude towards
inclusion) will have effects on a higher-order
level (e.g., school-level attitude towards
inclusion). Second, social relationships are
seen as ‘pipes’ for the exchange of resources,
such as information or didactic materials.
These resources are transferred through
social interaction among individuals, for
example, by asking a colleague for support.
Third, a social structure may provide
opportunities (e.g., exchange of successful
instructional strategies for including students
with SEN), but also constraints for individual
and organizational performance (e.g., the
lack of access to necessary or valuable
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resources for creating an inclusive LE because
teachers are disconnected). In sum, adopting
a SNA implies that researchers go beyond the
level of individual actors and their outcomes,
but also take the interdependency and flow of
resources into account.
A SNA provides opportunities to address
the challenges noted above. First, this
approach enables researchers to measure
teacher collaboration without assuming
formal boundaries, since both formal and
informal interactions can be mapped (Penuel,
Riel, Krause, & Frank, 2009). Second, it
helps to produce a close understanding of
how collaboration is shaped in inclusive
education as it focuses on the patterns of
social relationships that result from teachers’
(in)formal interactions in daily practice
(Moolenaar, 2012). Third, a SNA can be
considered as a tool to foster teacher
collaboration in inclusive education. Its
distinctive methodology, which takes into
account the interdependency of individuals,
allows researchers to capture and to visualize
the ties and overall network structure in
schools (Borgatti, Everett, & Johnson, 2013).
Thus, the approach gives school teams insight
into their network by making visible the
patterns of relationships (Ooghe, Thomas,
Tuytens, Devos, & Vanderlinde, 2016) and by
giving information on network characteristics
such as its density and diversity, which can
help school teams to exploit relationships as
resources for support in creating an inclusive
LE. The underlying assumption is that actors
who are aware of their network and the
(dis)advantages of their network charac-
teristics, interact more intentional with others
(e.g., they actively reach out to colleagues to
discuss their daily practice) (Borgatti &
Cross, 2003; Moolenaar et al., 2014). Despite
the great potential of a SNA to make teachers
aware of their network and its characteristics,
this approach is still only rarely applied in
educational practice.
2 Objectives
A SNA is only recently introduced in
educational research (Moolenaar, 2012;
Moolenaar, Sleegers, Karsten, & Daly, 2012)
and has already proven its value by, for
example, showing the importance of teacher
collaboration for school reforms (Penuel et
al., 2009), instructional improvement in
mathematics (Hopkins, Spillane, Jakopovic,
& Heaton, 2013) and student achievement
(Moolenaar, Sleegers, & Daly, 2012).
However, to our knowledge, there is no
research that has used a SNA to teacher
collaboration in inclusive education. As a
consequence, there is no social network
instrument (SNI) to assess and strengthen
teacher collaboration in inclusive education.
If we aim to measure teacher collaboration in
inclusive education, it is important to develop
an instrument that focuses on this specific
purpose, namely realizing an inclusive LE, as
previous research has shown that the purpose
of interaction, and consequently also the
content of interaction, partly determines the
network structure (Burt, 1997; Moolenaar,
2012). For example, if the purpose of
interaction is to realize an inclusive LE, and
the content of interaction is sharing ideas on
how to adjust the LE to the SEN of a student,
the SEN coordinator may play a central role
in this network. Whereas when it comes to
improving mathematical instruction, the SEN
coordinator will probably not play a central
role. Therefore, this study aims to develop
and validate a SNI that provides school teams
and researchers insight into social networks
regarding the creation of an inclusive LE.
In developing a SNI some specific issues
need to be taken into account, which are
shown and applied in this study. First, social
network studies can investigate various types
of networks at different levels, for example,
school internal collaboration or collaboration
with external partners, at the level of a teacher
(ego network) or the level of a school (whole
network). A first step in developing a SNI is
therefore deciding whether to use an ego or a
whole network design and defining network
boundaries. Next, it is critical to properly
select the network questions and questionnaire
format, and consider the way in which the
questionnaire is administered, as this greatly
influences the validity and reliability of
responses due to issues such as question
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clarity and cognitive demand (Borgatti et al.,
2013). Finally, as we want to provide school
teams insight into their network, the SNI
should also provide feedback to respondents,
which is new in the context of (inclusive)
education.
To validate the SNI, evidence is provided
on the content, response processes and
internal structure, following the Standards for
Educational and Psychological Testing
(AERA, APA, NCME, 1999). Regarding the
content, we examine whether the network
questions are clear and comprehensive to
participants and whether participants interpret
the network questions in the intended way.
With respect to the response processes, we
explore how and why participants respond to
the network questions the way they do.
Concerning the internal structure, we
investigate whether the network questions
measure different aspects of teacher
collaboration. Additionally, the cognitive
load (i.e., how much effort it takes to
complete the instrument) and experiences
with the feedback are studied.
3 Developing the social network
instrument
3.1 Network design
When researchers are interested in the
network of a single actor, an ego network
design is recommended. This network
constitutes the central actor and his ties to
others. In a whole network design, the ties
among all pairs of actors in a bounded sample
are investigated. This design enables
researchers to create a picture of a whole
network, and its structural features (e.g.,
density, centrality) (Borgatti et al., 2013). As
inclusive education can only be achieved if
all school team members work together
(Booth & Ainscow, 2015; Mitchell, 2015), a
whole network design has been applied.
Collecting data through a whole network
design starts with defining who comprises the
network (Marin & Wellman, 2011). We
decided to include every school staff member
with a pedagogical and/or coordinative
function.
3.2 Network questions
Since applying a whole network design has a
high cost to the researcher (analysing this
network takes a lot of time) and the respondent
(responding one network question takes
much longer than, for example, answering a
question about one’s attributes), a SNI can
only consist of a few network questions
(Borgatti et al., 2013). The literature on
inclusive education was explored to identify
what types of teacher interaction are
important in creating an inclusive LE, and to
determine what should be the object of
interaction (e.g., Ainscow & Miles, 2008;
Van De Putte & De Schauwer, 2013; Wang et
al., 2015). In addition, to enhance the content
validity of the instrument, experts in the
educational field (e.g., pedagogical
counsellors, pre-service teacher educators,
academics) contributed to the development
and refinement of the questionnaire.
Regarding the types of interaction, we
decided to focus on (1) asking for support,
and (2) giving support, since getting support
of other teachers and professionals seems to
be a prerequisite for successful inclusion
(Sanahuja-Gavaldà, Olmos-Rueda, & Morón-
Velasco, 2016; Van de Putte, 2013; Wang et
al., 2015). Regarding the object of interaction,
we tried to adhere to both visions of inclusive
education (i.e., inclusion focused on certain
groups who share a history of segregation,
and inclusion focused on appreciating and
responding to the diversity of all learners). As
such, the two objects concern (1) support in
order to adopt the LE to the SEN of an
individual student, and (2) support in order to
create a powerful and accessible LE for all
students. Combining the types and objects of
interaction resulted in the following four
network questions:
(1) Who do you usually ask for support
to adjust the LE to the SEN of an individual
student?
(2) Who do you usually give support to
adjust the LE to the SEN of an individual
student?
(3) Who do you usually ask for support
to create a powerful and accessible LE for all
students?
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(4) Who do you usually give support to
create a powerful and accessible LE for all
students?
Next, information on the nature and quality of
these interactions was gathered. For each
person selected, respondents have to indicate
the frequency of interaction ranging from at
least once a year to daily, and which type(s)
of support they ask or give, for instance,
information, emotional support, super-/
intervision. These options are based on an
exploration of the literature on the most
relevant types of support in the context of
inclusive education (e.g., Bouillet, 2013;
King-Sears et al., 2015; Knackendoffel, 2007;
Miltenienė & Venclovaitė, 2012), and were
refined in close collaboration with educational
experts. Third, for each person selected,
respondents have to indicate to what extent
the support they asked, effectively supports
them in creating an inclusive LE, with seven
options going from not supportive at all to
very supportive. As shown by Van der Rijt et
al. (2013), provided support is not necessarily
helpful to a teacher, which underlines the
importance of evaluating the effectiveness of
support.
3.3 Questionnaire design
With regard to the format, a first issue to
consider was whether to use an open- or
closed-ended format. While in an open-ended
format respondents are asked to freely recall
any person with whom they interact, in a
closed-ended format they are presented with
a list of network members to answer the
network questions. The main advantage of a
closed-ended format is that respondents are
less subject to recall error. Because a closed-
ended format is preferred when the list of
network members is not too large (Borgatti et
al., 2013; Marsden, 2011), this format was
chosen. A second issue concerns the structure
of the questions and name list. The two main
formats for closed-ended questions are
multigrids and repeated rosters. A multigrid
places the name list in a series of columns
with each column associated with a network
question, whereas in a repeated roster the
same name list is repeated following each
network question. As previous research
shows that data is more reliable when a
respondent answers one network question
about the list of network members before
moving on to the next network question
(Vehovar, Lozar Manfreda, Koren, & Hlebec,
2008), the repeated rosters format was
chosen. A third issue is whether respondents
can indicate as many people as they want or
whether the number of people a respondent
can indicate is fixed. As the latter can bias the
resulting networks (Borgatti et al., 2013),
respondents can indicate an unlimited number
of people in our instrument.
Finally, we decided to collect network
data by means of an online survey. Although
online surveys typically have lower response
rates, they are less emotionally sensitive as
they are self-administered and they are very
convenient for the researcher in terms of cost
of administering and data management
(Borgatti et al., 2013). Additionally, in this
manner the data can be processed
automatically to generate feedback for
respondents (see below).
3.4 Feedback
To make school teams aware of their network
and the associated benefits, and to facilitate
their network intentionality, we developed a
feedback tool. The feedback is automatically
generated for every respondent and
encompasses a picture of the school network,
in which the respondent can see his/her own
position in the network (see Appendix A for
an example). The picture is interactive as
there is the possibility to zoom in, and to
generate a network for each type of support
(e.g., information, emotional support)
separately. Although Cross, Borgatti, and
Parker (2002) argue that putting people’s
names on a network picture can be a powerful
diagnostic tool and a catalyst for change, this
may harm respondents, for instance if
information about the isolation of teachers is
revealed (Penuel, Sussex, Korbak, & Hoadley,
2006). Therefore, only if all respondents of a
school agree to include their names in the
network picture, the names are visible.
Otherwise, an anonymous network picture is
shown. Furthermore, an overview of the types
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of support present in a school, and the
frequency and perceived effectiveness of
support is presented. Although we focus on
the whole school network in this study, we
also gave feedback to a teacher on his/her
personal network, in which a picture of one’s
personal network is shown and several
network concepts (e.g., the strength of ties,
network diversity) are introduced and
applied. After developing the SNI, this
instrument was tested in a pilot study by
using a mixed method design consisting of an
online questionnaire, focus groups and
interviews.
4 Testing the social network
instrument
4.1 Sample
Data for this study were collected in three
primary and two secondary schools in
Flanders. A total of 75 teachers, 11 principals
or coordinators and 5 student counsellors or
special needs coordinators completed the
SNI, reflecting a return rate of 42.5%. The
participants had on average 18.2 years of
experience and 71.8% of them were female.
A subset of participants, more specifically 15
teachers, 5 principals or coordinators and 3
student counsellors were interviewed or
participated in a focus group. Additional
school demographics and the number of
participants in each school are presented in
Table 1. One primary (school 1) and one
secondary school (school 4) were excluded in
the quantitative network analysis (see section
4.3) as the response rates were too low (less
than 30%) to reliably explore the school
network (however, these two schools are still
included for the analysis of the cognitive load
and/or the interviews and focus groups). The
average response rate of the schools included
in the quantitative network analysis was
70.4%. To control for potential nonresponse
bias, we compared respondents and non-
respondents concerning their indegree, i.e.,
the number of ties they receive, by using
t-tests. The results of these tests revealed no
significant differences between respondents
and non-respondents.
4.2 Data collection
The SNI was administered to collect social
network data. Additionally, a cognitive load
scale, developed by Paas, Van Merriënboer,
and Adam (1994), was administered. In this
one-item scale participants were asked how
much effort it takes to complete the SNI.
Next, we implemented three focus groups (in
schools 3, 4 and 5), and conducted six semi-
structured interviews with primary school
teachers (in school 2). The focus groups
lasted between 40 and 90 minutes, while the
interviews lasted between 15 and 35 minutes.
In the focus groups we conducted a collective
interview, directed by the researcher, who
moderated the discussion. The purpose was to
Table 1
School demographics and number of participants in each school
School 1 School 2 School 3 School 4 School 5 Overall
Educational level Primary Primary Primary Secondary Secondary
Team size 23 31 16 93 51 214
Average years of
experience
14.75 20.72 18.64 18.22 16.67 18.22
Gender ratio1100.00 66.67 92.86 72.22 58.33 71.79
Participants SNI 6 17 15 20 33 91
Response rate SNI 26.09254.84 93.75 21.51264.71 42.52
Participants focus
groups/interviews
0658423
1Gender ratio is calculated as the percentage of female team members.
2School was excluded in the quantitative network analysis.
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(1) assess whether the network questions were
clear and comprehensive to the participants,
(2) explore whether the participants interpreted
the network questions in the intended way, (3)
examine how and why they responded to the
network questions the way they do, (4)
investigate how much effort it takes to
complete the network questionnaire, and (5)
explore experiences with the feedback. The
same objectives apply to the interviews.
4.3 Data analysis
We calculated Quadric Assignment Procedure
(QAP) correlations in UCINET to determine
whether the four network questions measure
different aspects of teacher collaboration
(Borgatti, Everett, & Freeman, 2002). The
QAP is a technique to estimate correlations
between social networks, as it takes into
account the interdependence of observations.
To calculate QAP correlations, we first
constructed matrices for each network
question for each school. If teacher i
nominated teacher j in the network question,
a 1 was entered in cell Xij. If teacher i did not
nominate teacher j, a 0 was entered in cell Xij.
Then a Pearson correlation is calculated for
two corresponding cells of two matrices of a
school (i.e., the observed correlation). To
calculate the significance of the observed
correlation, the observed correlation is
compared to the correlations between
thousands of pairs of matrices, which are
constructed by randomly rearranging the
rows (and matching columns) of one of the
observed matrices (Borgatti et al., 2013). We
calculated QAP correlations for the four
networks (one for each network question)
within each school and then aggregated these
correlations by computing the mean
correlation among the four networks, over the
three sample schools included for this
analysis. In addition, a descriptive analysis
was conducted on the cognitive load scale.
The interviews and focus groups were
recorded and transcribed. The transcriptions
were thematically analysed in four steps,
based on the guidelines of Braun and Clarke
(2006). First, each sentence was provided
with a code which describes the content of
that sentence, resulting in 69 codes. This
coding process was partially guided by the
research framework (e.g., the validation
standards) used in this study. When the initial-
coding stage was completed, all sentences
with the same codes were put together.
Second, the codes were categorized into
meaningful groups of codes, called themes
(e.g., evidence based on content and response
processes, experiences with feedback on
school network). Third, these themes were
examined against the original data by putting
together all sentences which relate to the
same theme. We checked whether the themes
appear to form a coherent pattern. Fourth, the
themes were refined, labelled and precisely
defined in consultation with another
researcher. The final themes are presented in
the results section.
4.4 Results
Evidence based on content
Most participants indicated that the questions
were clear and comprehensive. However,
some concepts in the network questions (e.g.,
SEN) or in the additional question on the
types of support (e.g., co-teaching) required
further explanation. Furthermore, the majority
of participants interpreted the network
questions in the intended way. Some teachers,
however, reported that they interpreted
adjusting the LE to the SEN of an individual
student (SEN of a student) and creating a
powerful and accessible LE for all students
(LE for all students) similarly.
Evidence based on response processes
The majority of participants, in particular
teachers, tended to select the same colleagues
when it comes to SEN of a student, as when it
comes to LE for all students. Furthermore,
several participants indicated that the
questionnaire was insufficiently introduced.
For example, to some it was unclear that
instead of simply reporting the support
relationship with one teacher as a
representative of a group of teachers with
whom they have support relationships, they
had to identify all the people whom they ask
for or give support. Only by giving a full
overview of the people in their personal
network, a comprehensive picture of the
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whole school network can be constructed.
Finally, the questionnaire was perceived to be
very personal and sensitive because they
were asked to indicate names of their
colleagues and because to some it was
unclear who of their school members would
have access to which results. To some, this
was a threshold to complete the questionnaire.
Evidence based on internal structure
Table 2 summarizes the QAP correlations
between the four networks within each school
and the average QAP correlations over the
three sample schools. The results indicate
that there is a strong and significant
correlation between the network around
asking support - SEN of a student and the
network around asking support - LE for all
students. In addition, the network around
giving support - SEN of a student is strongly
and significantly correlated to the network
around giving support - LE for all students.
The other correlations appear to be weak to
moderate (between .17 and .49).
Table 2
QAP correlations
School 2 School 3 School 5 Overall
QAP correlation Q1-Q2 0.27 0.42*** 0.24*** 0.31
QAP correlation Q1-Q3 0.49*** 0.65*** 0.58*** 0.58
QAP correlation Q1-Q4 0.17 0.41*** 0.29*** 0.29
QAP correlation Q2-Q3 0.26*** 0.44*** 0.25*** 0.32
QAP correlation Q2-Q4 0.67*** 0.71*** 0.71*** 0.69
QAP correlation Q3-Q4 0.24** 0.49*** 0.43*** 0.39
Note. Q1 = asking support – SEN of a student; Q2 = giving support – SEN of a student;
Q3 = asking support - LE for all students; Q4 = giving support- LE for all students
***p<.001, **p<.01
13
Figure 1. Bar chart of cognitive load.
Figure 1. Bar chart of cognitive load.
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Cognitive load
For most participants it did not take much
effort to complete the network questionnaire
(see Figure 1). However, the interviews and
focus groups revealed that for some
participants the sub-questions related to the
frequency, type of support, and perceived
effectiveness of support, made it difficult to
fill out the questionnaire, as there were, for
example, too many answer options. The
majority of participants took 20 minutes to
complete the network questionnaire.
However, several participants in the context
of secondary education (especially
coordinators and student counsellors)
purposefully selected only a few people in the
network questionnaire when they noticed it
would take more time to fill out the
questionnaire if they selected more people.
Experiences with the feedback based on the
network questionnaire
Some teachers reported that the feedback on
the school network was mainly useful for
management staff to gain insight into the
school network. However, for them as
teachers it was very interesting to see their
own position in the school network. Finally,
participants reported both advantages of
making names visible (e.g., it is useful to
know the central people in the network, so
their time can be made available to support
others), and disadvantages (e.g., it can be
harmful when everyone knows you are
isolated). All schools, however, received an
anonymous network picture, as there was at
least one staff member in each school who
disagreed to visualize names in the network
picture.
As to the feedback on their personal
network, most participants reported that the
picture of their personal network had no
added value. They argued that it would be
interesting to compare the four networks
(e.g., Is there a difference between my
networks concerning asking for support
versus giving support?). Moreover, some
participants indicated that the feedback
contained too much text and that the wording
was too complex. Finally, some participants
thought that this feedback could help one to
reflect on one’s functioning and that it would
be interesting to discuss this with each other.
4.5 Adjustments in response to the results
The network questionnaire was adjusted
based on the findings in this study. First, we
combined the network questions related to
SEN of a student and the network questions
related to LE for all students. The distinction
between asking support and giving support
was maintained, resulting in the following
two network questions: (1) Who do you
usually ask for support to create a powerful
and accessible LE for one or more student(s)
with SEN? and (2) Who do you usually give
support to create a powerful and accessible
LE for one or more student(s) with SEN?. In
order to make the concepts (e.g., SEN)
clearer, additional explanations and examples
were given. Second, an instruction video was
developed to clarify the purpose of the
instrument, how to fill out the questionnaire,
and how and to whom feedback is provided.
Lastly, the format of the questionnaire was
changed into a multigrid so that participants
only have to go through the whole list of
names once at the beginning of the
questionnaire. This way, it is unlikely that
participants purposefully select fewer people
to have less work. Additionally, a multigrid
makes the questionnaire appear shorter,
which may have a beneficial psychological
effect on participants (Borgatti et al., 2013).
An overview of the adjusted network
questionnaire is offered in Appendix B.
Also the feedback module was optimized
based on the results. With respect to the
school network, extra tools on how to
interpret the network picture were offered and
it was shown how to look at the picture from
different perspectives. Concerning the
personal network, we presented less text, we
simplified the wording and we changed the
picture into a textual overview so that the
networks can be compared.
5 Discussion
A social network approach (SNA) offers a
valuable framework to assess teacher
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collaboration in the context of inclusive
education, as this approach allows researchers
to map a combination of formal and informal
interactions and to get a close understanding
of how collaboration takes shape in inclusive
education. Moreover, this approach enables
school teams to gain insight into, and to be
more aware of their networks, in order to
strengthen their collaboration. A SNA is only
recently introduced in educational research,
and to our knowledge no social network
instrument (SNI) exists to assess and
strengthen teacher collaboration in inclusive
education. Therefore, a SNI was developed
based upon existing literature and in close
consultation with experts in the educational
field. Next, the SNI was tested to guarantee
the validity of the instrument. Concerning the
validation, evidence was provided on the
content, response processes and internal
structure.
To provide evidence on the content and
response processes, interviews and focus
groups were conducted, which revealed that
the questions were clear and comprehensive
to most participants. Moreover, the majority
of participants interpreted the network
questions in the intended way. Some
participants, however, interpreted adjusting
the learning environment (LE) to the special
educational needs (SEN) of an individual
student and creating a powerful and
accessible LE for all students similarly.
Partly due to the latter finding, there was a
tendency to select the same colleagues when
it comes to adjusting the LE to the SEN of an
individual student, as when it comes to
creating a powerful and accessible LE for all
students.
The pattern of Quadric Assignment
Procedure (QAP) correlations, which
provides evidence on the internal structure of
the instrument, confirmed the above findings.
The correlational data suggest that there is a
large overlap between the networks
concerning adjusting the LE to the SEN of an
individual student and the networks
concerning creating a powerful and
accessible LE for all students. The overlap
seems to indicate that although these
constructs are theoretically different, they are
inherently intertwined in practice. For
example, when a teacher visualises the daily
routine for a student with autism spectrum
disorder, all classmates can benefit from the
structure that is offered. This intertwinement
is also underlying Universal Design for
Learning: a LE that is accessible for students
with SEN from the outset tends to yield
benefits that make all students’ learning
experiences better (Hall, Meyer, & Rose,
2012). On the other hand, there seems to be a
difference between the networks around
asking for support and the networks around
giving support, as the correlations between
these networks are weak to moderate. This
suggests that teachers ask other colleagues
for support than the people they give support
themselves. The difference might indicate
that they ask support from colleagues they
view as experts in creating an inclusive LE,
and as these colleagues are viewed as experts,
they do not give them support. It would be
interesting to study more closely why
teachers ask other people for support than the
people they give support themselves.
The analysis of the cognitive load scale,
interviews and focus groups revealed that for
most participants it did not take much effort
to complete the instrument. However, a
remarkable finding is that several participants
in the context of secondary education
purposefully selected only a few people in
the network questionnaire when they noticed
it would take more time to fill out the
questionnaire if they selected more people.
Thus, it seems probable that fatigue effects
were present in the questionnaire, which may
have led to a diminished average out-degree,
a bias that would be of concern when
researchers aim to compare the density (i.e.,
the number of ties divided by the total number
of possible ties) of different networks
(Pustejovsky & Spillane, 2009).
Finally, experiences with the feedback on
one’s school and personal network were
explored by implementing interviews and
focus groups. Although there were some
aspects for improvement, the results show
that the SNI can be a valuable tool to foster
reflection on one’s collaboration and to gain
insight into one’s network, which are
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important steps in facilitating effective
teacher collaboration (Baker-Doyle & Yoon,
2011).
5.1 Contributions
The development and validation of our SNI
contributes to research in two ways. First, the
instrument offers a novel approach to assess
teacher collaboration in inclusive education,
mapping a combination of formal and
informal interactions. Our SNI can be applied
to fully grasp the nature of teacher
collaboration in inclusive education. For
example, it can be examined how the type of
interaction (i.e., asking for support and giving
support) and the type of support (e.g.,
information, emotional support) shape social
network structure in school teams. Second,
this study shows some considerations that
researchers need to take into account when
developing and validating a network
questionnaire. Since a wide variety of
network types can be investigated (e.g.,
asking support, spending breaks, friendship)
and every study is generally interested in a
specific type of network, new network
questionnaires are often developed to collect
the appropriate data (Meredith, Struyve, &
Gielen, 2014). By showing the different steps
that need to be taken in developing a network
questionnaire, this study can help researchers
to develop high-quality network
questionnaires. Additionally, our research
demonstrated how a network questionnaire
can be validated, which may be valuable and
inspiring for researchers as validation of
social network questionnaires is scarce and
generally used reliability and validity checks,
such as Cronbach’s alfa and convergent
validity, are difficult to apply to network
questionnaires (Meredith et al., 2014).
The current study also adds to educational
practice by providing a feedback tool, which
is new in the context of (inclusive) education.
Individual teachers can use the SNI to map
and reflect on their network, what can be a
first step in strengthening their collaboration.
Principals can use the instrument to get an
overview of collaboration in their school
team (e.g., the cohesion and central actors in
one’s team) and then use these results in their
policy making. E.g., to engage in dialogue
with their team about what collaboration
looks like ideally and about how to improve
their collaboration in order to promote a more
inclusive LE. The instrument can also be used
in the context of professionalization, for
example to explore whether there is sufficient
interaction between team members to
disseminate the new information and
expertise across the network, or whether there
are subgroups that hinder the dissemination
of expertise (Daly, Moolenaar, Bolivar, &
Burke, 2010; Penuel et al., 2009)
5.2 Limitations and future directions
In addition to these contributions, some
limitations that suggest additional paths for
future research should be considered. Firstly,
in defining the network boundaries, we
decided to include only school staff members.
Although external partners, parents and
students are also important actors in realizing
inclusive education (Baglieri & Shapiro,
2012; Hornby & Witte, 2010), they are not
included because of practical and
methodological considerations. A first issue is
that it would be hard to clearly define the
network boundaries if these actors are
included. Additionally, in order to apply a
whole network design every network member
needs to fill out the questionnaire and a high
response rate is needed to reliably analyse the
network structure (Wasserman & Faust,
1994). These requirements would be
cumbersome to meet if external partners,
parents and pupils were members of the
network. A final practical concern is that the
name list offered to respondents would
become very long, which increases the cost
fill in the questionnaire. It would be valuable
for future research on teacher collaboration in
inclusive education to include external
partners, parents and students by adopting an
ego-network design, in which respondents are
allowed to mention any person they like.
Secondly, some participants interpreted
adjusting the LE to the SEN of an individual
student and creating a powerful and
accessible LE for all students, similarly. It
might be that this would not be the case if the
order of the questions was changed, as a
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STUDIËN
respondent relies on contextual clues from a
previous question to understand the meaning
of a following question (i.e., question-scope
redefinition) (Pustejovsky & Spillane, 2009).
We have not explicitly investigated whether
question scope redefinition could play a role
here. However, the interviews and focus
groups suggest that some participants
interpreted the constructs similarly,
irrespective of the question order. Future
research might take into account question
order effects by randomizing the order in
which questions are posed and examine the
effect of the order on networks (e.g.,
similarity between networks).
6 Conclusion
Teacher collaboration is considered essential
in realizing inclusive education. As Carroll
(2009) argues, “The idea that a single teacher,
working alone, can know and do everything
to meet the diverse learning needs of 30
students every day throughout the school
year has rarely worked, and it certainly won’t
meet the needs of learners in years to come.”
(p. 13). This study opens new avenues by
drawing on a SNA to assess and strengthen
teacher collaboration in the light of inclusive
education. The findings suggest that our SNI
is a valid tool to assess teacher collaboration.
Moreover, the instrument can be used to
strengthen teacher collaboration by providing
school teams insight into their social networks
and by stimulating their network
intentionality.
Notes
1 This research was supported by Flanders
Innovation and Entrepreneurship [grant
150011].
2 The authors gratefully acknowledge the
support of the POTENTIAL research and
valorisation project (www.potentialproject.
be). Furthermore, we would like to thank
the stakeholders for their collaboration in
developing the instrument. Additionally, we
worked closely with IMEC, since they were
responsible for technical aspects regarding the
implementation of the instrument in an online
environment. Lastly, we want to express our
gratitude to the participants.
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Authors
Jasmien Sannen is a PhD student at the Faculty
of Psychology and Educational Sciences,
Parenting and Special Education Research Group,
KU Leuven. Nick Ferbuyt, MSc, currently works
on a doctoral study at the Department of Training
and Education Sciences & Antwerp School of
Education, University of Antwerp. Sven De
Maeyer and Elke Struyf are professors at the
Faculty of Social Sciences, Department of Training
and Education Sciences, University of Antwerp.
Elke Struyf is also associated to the Antwerp
School of Education, University of Antwerp. Piet
Van Avermaet is head of the Centre for Diversity
and Learning, associated to the Linguistics
Department of Ghent University. Katja Petry is a
professor at the Faculty of Psychology and
Educational Sciences, Parenting and Special
Education Research Group, KU Leuven.
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PEDAGOGISCHE
STUDIËN
Correspondence address: Jasmien Sannen,
Leopold Vanderkelenstraat 32 – bus 3765, 3000,
Leuven, Belgium. E-mail: jasmien.sannen@
kuleuven.be
Samenvatting
Ontwikkeling en validering van een sociaal
netwerk instrument om de samenwerking van
leerkrachten in het kader van inclusief
onderwijs te meten en versterken
Een sociale netwerk benadering biedt een
waardevol en innovatief kader om de
samenwerking van leerkrachten in het licht van
inclusief onderwijs in kaart te brengen en
versterken. Het doel van deze studie is daarom
het ontwikkelen en valideren van een sociaal
netwerk instrument dat leerkrachten,
schoolteams en onderzoekers inzicht verschaft
in de samenwerking van leerkrachten in het
kader van inclusief onderwijs. Betreffende de
ontwikkeling, worden specifieke aandachtspunten
in het ontwikkelen van een netwerkvragenlijst
aangehaald en toegepast. Betreffende de
validering, worden de inhoud, responsprocessen
en interne structuur van het instrument
onderzocht. Daarnaast worden de cognitieve
belasting om de netwerkvragenlijst in te vullen en
de meerwaarde van feedback op basis van deze
netwerkvragenlijst bestudeerd. Data werden
verzameld in drie lagere en twee secundaire
scholen aan de hand van een mixed method
design. De resultaten suggereren dat ons
instrument een valide tool is om de samenwerking
van leerkrachten te meten en versterken.
Kernwoorden: inclusief onderwijs; samen-
werking van leerkrachten; sociale netwerk
benadering; mixed method design
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PEDAGOGISCHE
STUDIËN
Appendix A
Example of a network picture of a school
Below you can see a network picture of your school about asking for support.
You are the red dot. Your colleagues are the grey dots.
If you ask a colleague for support, an arrow is signed from you to your colleague. If
the arrow is two directional, you ask your colleague for support and your colleague
also asks you for support.
The more colleagues you ask for support (in other words, there are a lot of arrows
coming to you), the bigger your dot is.
The line colour indicates how often you ask for support. The darker the colour, the
more often you ask for support (see legend).
When you click on the tabs above the network picture, you will only see the ties that
are characterized by that type of support. For example, if you click on information,
you will only see the ties where information is asked.
14
Appendix A
Example of a network picture of a school
Below you can see a network picture of your school about asking for support.
You are the red dot. Your colleagues are the grey dots.
If you ask a colleague for support, an arrow is signed from you to your colleague. If the
arrow is two directional, you ask your colleague for support and your colleague also asks
you for support.
The more colleagues you ask for support (in other words, there are a lot of arrows
coming to you), the bigger your dot is.
The line colour indicates how often you ask for support. The darker the colour, the more
often you ask for support (see legend).
When you click on the tabs above the network picture, you will only see the ties that are
characterized by that type of support. For example, if you click on
information
, you will
only see the ties where information is asked.
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PEDAGOGISCHE
STUDIËN
Appendix B
Adjusted network questionnaire
Type of interac-
tion
Network question Answer format
Asking support Who do you usually ask for support
to create a powerful and accessible
LE for one or more student(s) with
SEN?
Name list – multigrid
On average, how often do you ask
this (these) person(s) for support?
Frequency scale with 4 options:
• Once or several times a year
• Monthly
• Weekly
• (Almost) Daily
To what extent does this effectively
support you to create a powerful
and accessible LE for one or more
student(s) with SEN?
5-point Likert scale (not supportive at all –
very supportive)
What type(s) of support do you ask
exactly?
Closed question with 9 options (multiple
answers possible):
• Didactic material
• Emotional support
• Information
• Observation and feedback
• Super-/intervision
• Co-/team teaching
• Individual student support in class
• Student(s) support outside class
• Other
Giving support Who do you usually give support to
create a powerful and accessible
LE for one or more student(s) with
SEN?
Name list – multigrid
On average, how often do you give
this (these) person(s) support?
Frequency scale with 4 options:
• Once or several times a year
• Monthly
• Weekly
• (Almost) Daily
What type(s) of support do you give
exactly?
Closed question with 9 options (multiple
answers possible):
• Didactic material
• Emotional support
• Information
• Observation and feedback
• Super-/intervision
• Co-/team teaching
• Individual student support in class
• Student(s) support outside class
• Other
... We collected data on teacher collaboration by means of a social network instrument which was developed to assess teacher collaboration in inclusive education and was validated in a previous study (Sannen, Ferbuyt, De Maeyer, Struyf, Van Avermaet, & Petry, 2019). In this instrument every school member was asked two questions: (1) Who do you usually ask for support to create a powerful and accessible learning environment for one or more student(s) with SEN? and (2) Who do you usually give support to create a powerful and accessible learning environment for one or more student(s) with SEN? ...
... A second limitation involves the broadness of the concept support. In the study of (Sannen et al., 2019) asking and giving support were identified as important types of interaction in creating inclusive learning environment. Since support is a broad concept, we were able to capture a multitude of interactions. ...
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