ERIC EJ1010756: Analysing Interactions in a Teacher Network Forum: A Sociometric Approach

2013·0.15 MB·English

by  ERIC

Analysing Interactions in a Teacher Network Forum: A Sociometric Approach
Eliana Santana Lisbôa
Clara Pereira Coutinho
Minho University
Abstract
W
This article presents the sociometric eb 2.0, or the Social Web, environments. To promote collabora-
analysis of the interactions in a forum brings multiple possibilities for tive learning among the social network
of a social network created for the pro- the socialisation of individu- members, the researchers and the
fessional development of Portuguese- als. This form of socialisation happens community members launched several
speaking teachers. The main goal of the in different ways, including through forums.
forum, which was titled Stricto Sensu, sharing photos, music, and interactions Like Clark (2006), we believe that
was to discuss the educational value of in discussion groups, via the many ap- information is the basic principle that
programmes that joined the distance plications available in cyberspace called flows across networks and therefore
learning model in Brazil. The empiri- social networks or virtual communities. must be considered its supreme good.
cal study focused on the sociometric Some studies have proved that these Thus, social network analysis (SNA)
analysis of the social interactions that spaces are mostly informal and, in addi- is set up as a resource, or even a strat-
take place in asynchronous online en- tion to socialising, have the potential to egy, that facilitates an explanation of
vironments. This approach, according be educational because learning happens the communication flows, enabling an
to literature, allows for new means in a social network (Lisbôa & Coutinho, understanding of the relationships made
to observe, analyse, and interpret the 2011). The use of social networks is and an identification of any bottlenecks.
reality of a new social paradigm. This common in the teaching and learning The identification and understanding of
type of analysis tries to understand process as a complement to face-to- these factors may offer possibilities to
the relationship established between face teaching, in distance education, or interfere in its dynamics (i.e., proposing
the different actors, seeking to verify if even in the professional development of actions for improvement in its organisa-
the roles they play in both the access teachers (Pinto, 2009), as these profes- tion and functioning), especially those
to information and the construction sionals face the current demands of so- related to the role of the e-moderator in
of shared knowledge. The data col- ciety and feel the need to keep up to date the whole process.
lected allow the researchers to deduce and continue lifelong learning through In the literature, SNA is widely used
that the indicators used in the analy- interaction and knowledge sharing. to analyse interactions in social net-
sis are important for understanding In this context, Senge (1990) empha- works for the study of a diversity of
and intervening in the dynamics and sises that knowledge is seen as a social different and heterogeneous contexts,
functioning of the network to propose construct and that learning organisa- such as political organizations, enter-
improvements in its structure and or- tion necessarily involves the search for prises, and marketing and health studies
ganisation. In the specific case of the knowledge. Within this social construct, (Eveland & Kleinman, 2013; Pinto &
aforementioned discussion forum, individuals are encouraged and feel the Junqueira, 2008; Raeymaeckers, 2013;
the results of the sociometric analysis need to continuously develop “their Zelner et al., 2012). Regarding educa-
of the perceived interactions were not ability to create the results they truly tional research, a systematic search of
surprising, considering that the nature desire, with high standards of reasoning, academic databases, such as Scopus
of the topic did not demand deep re- where collective aspiration is set free, and Ebsco, verified that social network
flection to contribute to the debate. and people learn continuously in group” analysis was mainly used as a strategy
(Keywords: teacher networks, forum (Senge, 1990, p. 11). to analyse the processes of knowledge
interactions, sociometric analysis, We created the Teachers in the construction and collaboration in online
collaborative learning, e-moderator) Digital Age (PROEDI) social network and distance education (Jablokow &
(www.proedi.ning.com) to promote Vercellone-Smith, 2011; Jimoyiannis
the professional growth of a group & Angelaina, 2012; MacKellar, 2012;
of Portuguese-speaking teachers Rice Doran, Doran, & Mazur, 2011;
who sought to share their knowledge Romero-Moreno & Lucena, 2010; Silva
and experience in informal learning & Figueira, 2012; Thornton & Leahy,
Volume 29 Number 4 | Journal of Digital Learning in Teacher Education | 141
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.
Lisbôa & Coutinho
2012). The position a member occupies
in a sociogram allows researchers to
understand the individual processes
of knowledge acquisition (Oshima,
Oshima and Matsuzawa, 2012) or even
the construction of the so called “social
capital” inside the community (Cor-
omina, Coenders, Ferligoj & Guia, 2011;
Recuero & Zago, 2009; Recuero, 2006;
Rice Doran, Doran & Mazur, 2011).
However, we did not find reports of the
use of SNA to study the processes of e-
moderation and shared leadership inside
a social network, so we believe our study
is a contribution to the state of the art.
Considering the above, we formulated
a research question to guide the empiri-
cal study: How does the SNA analysis
clarify the understanding of the dynam-
ics of communication inside a social
network, particularly those related to the
e-moderation process? Can we improve
organisation and functioning of a virtual Figure 1. Distributed networks (Baran’s diagram, 1964).
community based on the SNA analysis?
tween these individuals through various In addition, interconnection contains
interactions: “When this happens, we say various forms of interaction and collec-
Review of Literature
that a connection has been established” tive intelligence that represent the result
Defining Social Networks (Franco, 2008b, p. 113). of the collaborative process that is pos-
Based on the studies of Castells (2000), In a successful network, information sible in cyberspace, given that everyone
Levy (2003), Capra (2002), Barabási must flow in a decentralised manner for can be producer of knowledge. Indeed,
(2002), and Franco (2008a), we can members to feel free to participate and be according to Levy (2003), the possibility
characterise social networks as a set respected in their cultural diversity. The of interaction within the community is
of relationships or connections where environment must be democratic for the related to the same theme, which makes
messages flow (nodes). Graphically, we exercise of shared leadership (Dias, 2008). virtual communities a space conducive to
can say that these connections can be the spread of cyberculture. Thus, we can
represented by edges, and the nodes can Social Networks and the say that virtual communities represent
be represented by vertices (Lisbôa & Construction of Knowledge the interest of a certain group of people
Coutinho, 2010). Thus, from the existing According to Levy (1998), cyberspace in sharing common information, which
connections in relation to the nodes, we represents a new medium in which makes them a location for the most di-
can identify whether an organisation can everyone can contribute to its growth and verse artistic and cultural manifestations,
be considered a network (see Figure 1). development through the production and promoting approximation and uniting
The figure illustrates how people are dissemination of information and knowl- individuals by the most diverse interests
linked to each other without the predom- edge. This growth is associated with (Lisbôa & Coutinho, 2011).
inant figure of a coordinator. Each node cyberculture, as it is the manifestation
is connected to several of its neighbour- of the practices, cultures, and opinions Sociometric Analysis
ing nodes, and there are many degrees of several users who attend the virtual In the literature, several techniques have
of distribution, as each node has several environments. It is in this context of col- been used in SNA. In the specific case
possible routes to send data. If a route or laboration that social networks arise, sup- of the present study, we will focus on
neighbouring node is destroyed, another ported by interconnection and collective the sociometric analysis. According to
path will be available (Baran, 1964). intelligence. Interconnection is related to Varanda (2000), this analysis has been
Therefore, we believe that the nodes and the different forms of interaction avail- considered by a large number of theo-
connections are constituent elements able online, and collective intelligence is rists to be the new social paradigm due
of the network, in which the nodes are the result of online collaboration, as all to its original way of observing, analys-
represented by people and the connec- cybernauts are potential producers of ing, and interpreting reality. Overall, this
tions are the relationships established be- knowledge (Harasim, 2012). kind of analysis tries to understand the
142 | Journal of Digital Learning in Teacher Education | Volume 29 Number 4
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.
Analysing Interactions in a Teacher Network Forum
relationship between the different actors, of network elements in order to help or virtual community in the past. The
seeking to verify if the roles that they researchers understand the behaviour forum titled Stricto Sensu, which is the
occupy may influence access to informa- and attitudes of the actors participating focus of this article, started from the
tion, knowledge, and the construction of in the discussion forum. According to initiative of a participant who wanted to
knowledge (Clark, 2006). Wellman (2001), the SNA is a very effec- listen to the group’s opinions on Stricto
The SNA aims to characterise the orga- tive method through which to under- Sensu programmes in Brazil and its
nizational structure of a social group, rep- stand the organisation and arrangement adherence to b-learning. This proposal
resenting visually the existing individual of members in a social network, which was not planned in the programme, nor
connections to find out if there is reciproc- in the specific case of our study was the was it directly connected to the training
ity in the communication flows (unidi- social network Teachers in the Digital activities mentioned above.
rectional or bidirectional), if the group Age (PROEDI).
is cohesive, who the members are who The PROEDI was created on the Data Collection and Analysis
exercise leadership, and how the group Ning social software tool and has been To collect data, we used a survey with
functions as a whole (Newman, 1999). By online since January 2011. Its main a main objective of characterising the
building graphical representations of net- objective is to explore new approaches sample. This instrument is associated
works, the researcher is able to understand to the training and professional develop- with the Ning social network and serves
how they are organised and the types ment of teachers that emerge from the as a criterion to access it.
of existing interactions, as well as their context of the paradigm known as Web For the structural analysis of the
joints, providing them with the authority 2.0. This online environment has been network, we used direct observation,
to propose actions for improvement or used in various contexts, including as an which was reported in literature as the
reorganisation of its structure (Kauchakje informal learning environment and as a most adequate technique to study the
& Delazari, 2007). According to Scott complement to the activities of formal interactions between the members of
(2004), some of the essential characteris- teacher training programmes. a restricted group (Bernard, Kilworth,
tics of a network can be analysed through The present study involved a group & Sailer, 1990; Freeman & Michaelson,
matrixes. In this design, the graph theory of teachers from the Federal University 1988, 1989; Freeman & Romney, 1987;
describes the networks rigorously and of Maranhão (UFMA) and the State Killworth & Bernard, 1976; Lemieux &
carefully, describing them through master University of Piauí (UESPI), who were Ouimet, 2008). We used the software
data that can be translated into concepts participating in the programme Promot- Ucinet to analyse the indicators (density,
and/or theorems and stored and/or related ing the Use of ICT in Undergraduate degree of centrality, index of centrality,
in specific computer programs, allowing Courses, which was directed at teachers intermediation, and closeness) and Net-
a much easier and objective approach. of public universities whose projects draw to create graphical representations
However, for a more detailed and fruitful had been approved by the Foundation of interactions (Borgatti, 2002).
network, an analysis of its main indicators for Co-ordination and Improvement of
is required, including: (a) network density, Higher Education Personnel (CAPES). Sample
(b) degree of centrality, (c) centralization This course focused on offering a Participants in the PROEDI network cre-
index, (d) intermediation degree, and (e) theoretical and practical basis to pro- ated the Stricto Sensu forum. Fifty mem-
closeness degree. mote integration between the classroom bers (29 females and 21 males) partici-
education and distance education pated in this forum. Regarding age, 28%
Method system (b-learning) in higher education of the participants were 26–30 years old
The present study followed a qualitative institutions (IES) of the federal and state (14 members), 20% were 36–40 years old
mainstream line, as its main purpose sphere, and also those that integrate the (10), 16% were 31–35 years old (8), 14%
was to analyse the interactions estab- Open University of Brazil (OUB) sys- were 46–50 years old (7), 8% were 51–55
lished between the actors of the network tem. In addition, the programme aimed (4), 6% were 41–45 years old (3), 6% were
as well as the behaviour and position of to promote the development of digital 56–60 years old (3), and 1 member did
each member (Hirschi, 2009). To this literacy and to develop participants’ not report. With respect to employment,
end, we used a number of techniques desire and need to use information and the majority (31 members) were teachers.
related to SNA that allowed us to repre- communication technology (ICT) in the As for the social networks used, Face-
sent the interactions and relationships teaching and learning process. book (22) took the lead, in addition to
between the actors, not only by means of With these goals in mind, the in- PROEDI. Concerning the participation
graphic representation, but also through structor presented the PROEDI social in virtual communities, an overwhelming
some indicators that provided inputs network, requested the adherence of all majority (35) indicated that they had not
to explain the network’s functioning teachers, and familiarised them with participated in any virtual community.
(Hirschi, 2009). an environment focused on the train- Furthermore, 28 members reported a
In general terms, the SNA aims to ing of teachers, as most of them had basic knowledge in ICT training, 11 re-
describe and represent the interactions not participated in this kind of network ported an average knowledge, 6 claimed
Volume 29 Number 4 | Journal of Digital Learning in Teacher Education | 143
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.
Lisbôa & Coutinho
to possess no knowledge, 4 claimed to
have advanced knowledge in ICT, and 1
person did not report.
Results
In this section, we present the results of
the sociometric analysis of the perceived
interactions in the discussion forum
Stricto Sensu according to the set of
indicators previously mentioned.
Density
Most theorists who discuss the subject
consider the analysis of the frequency
of the interactions as one of the most
basic features within a sociometric
analysis. Fifty members participated in
this network, which presented 115 links.
To provide a better visualisation of the
generated discussions on the theme of
discussion forum, Figure 2 presents the
graph of interactions.
Figure 2. Analysis of interactions.
Each point of the sociogram rep-
resents a member of the network. The Ouimet (2008), we calculate the number works conversely: It is the number of
lines that have no arrow at the end of possible relationships by multiplying interactions that the actor has with other
represent a unidirectional relationship, the total number of nodes (NTN) by the members (Clark, 2006; Velázquez &
meaning that the member received an total number of nodes minus 1 (NTN- Aguilar, 2005).
invitation to participate in the discus- 1), as follows: RP = NTN x (NTN -1). The Ucinet presents the actors organ-
sion but did not interact (see A11 or We calculated that, in theory, the net- ised by their level of centrality through
A13). When the lines have arrows at work could have 2,450 possible relations the following columns: (a) outDegree
the extremities, this member received (RP = 50 x [50-1] = 50 x 49 = 2450). (output degree), (b) InDegree (input de-
and sent messages (A49–A43). There is However, it was only possible to envision gree), (c) NrmOutDeg (standard output
no loose node in this sociogram, as all 115 relationships. Therefore, the density degree), and (d) NrmInDeg (standard
members connected at least once with is the ratio of the number of existing input degree). The last two columns
the e-moderator (A03). relations and the possible relations: D = show the percentage representation of
A global glance at the sociogram RE/RP x 100 (i.e., D = [115/2450] x 100 their degrees. Accordingly, Table 1 il-
immediately reveals that there was little = 4.69%). Based on this result, we can lustrates that the actor A01 has a higher
interaction between the members. The say that the ties are mostly considered level of centrality reflected in an input
great majority are not loose nodes (i.e., weak, as the relationships observed are degree of 48 (this number means that
A07, A09, A43) because the actor A01 dispersed, without any closeness, and potentially A01 was available to 48 of
maintains contact with them and is they do not converge to achieve a greater the other members of the community),
responsible for establishing and shar- engagement of the group (Granovetter, which corresponds to a standard input
ing information. A larger interaction 1973; Wellman, 1997). degree of 97.9%. This was followed by
volume can be identified on the left side A03, who had an input degree of 5 and
of the graph, where the nodes A03 and Degree of Centrality a standard input degree of 10.2%. Less
A01 preserve the cohesion and connec- The degree centrality on a network is an significant, the actor A02 possessed an
tion within the group. indicator that measures the number of input degree of 4 and a standard input
According to the graph, it is evident direct links that each actor or member degree of 8.16%. On The nodes A11 and
that the network is not very dense. has within the network. Depending on A13 do not have input degrees, as none
However, to calculate the density of the the direction of flow, it can be classi- of the members established communica-
network, we need to know the number fied as a degree of input or output. The tion with these actors.
of possible relationships, with refer- degree of input can be defined as the
ence to the number of participants in sum of the interactions that the other Centralization Index
this forum (50), which we have already members establish with a particular The centralization index is the indicator
called nodes. According to Lemieux and actor. However, the degree of output that defines whether an actor is the cen-
144 | Journal of Digital Learning in Teacher Education | Volume 29 Number 4
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.
Analysing Interactions in a Teacher Network Forum
Table 1. Degree of Centrality tral element of a network—if, apart from
ID OutDegree InDegree NrmOutDegree NrmInDegree stopping the flow of communication,
A01 47.000 48.000 95.918 97.959 the actor is also the communication
A03 14.000 5.000 28.571 10.204 point between the other members of the
A32 2.000 1.000 4.082 2.041 network (Velázquez & Aguilar, 2005). In
A49 2.000 2.000 4.082 4.082 general, we noticed that the network is
A25 2.000 2.000 4.082 4.082 highly centralised, as the data displayed
by the software confirm that the network
A46 2.000 2.000 4.082 4.082
in its entirety has an output centralisa-
A02 1.000 4.000 2.041 8.163
tion degree (Outdegree) of 95.026% and
A08 1.000 1.000 2.041 2.041
an input centralisation degree (Indegree)
A04 1.000 1.000 2.041 2.041
of 97.151%.
A11 1.000 0.000 2.041 0.000
A06 1.000 1.000 2.041 2.041
Intermediation Degree
A10 1.000 1.000 2.041 2.041
The intermediation degree is an indica-
A14 1.000 1.000 2.041 2.041
tor that allows the researcher to identify
A15 1.000 1.000 2.041 2.041
the position that the actors have in the
A16 1.000 2.000 2.041 4.082 network. To theorists such as Varanda
A17 1.000 1.000 2.041 2.041 (2000); Flap, Bulder, and Volker (1998);
A18 1.000 1.000 2.041 2.041 and Velázquez and Aguilar (2005),
A19 1.000 1.000 2.041 2.041 among others, the higher the interme-
A20 1.000 2.000 2.041 4.082 diation degree, the greater the likeli-
A09 1.000 1.000 2.041 2.041 hood that the individuals have access
A22 1.000 2.000 2.041 4.082 to information and, consequently, have
A23 1.000 1.000 2.041 2.041 more control of communication com-
pared to members who have a periph-
A12 1.000 1.000 2.041 2.041
eral, marginal participation, or even
A13 1.000 0.000 2.041 0.000
compared to those who are isolated
A26 1.000 1.000 2.041 2.041
(loose nodes).
A27 1.000 1.000 2.041 2.041
From the data, we recognised that
A28 1.000 1.000 2.041 2.041
the actor A01 has the greatest degree of
A29 1.000 3.000 2.041 6.122
intermediation with 2204.5, which ex-
A05 1.000 2.000 2.041 4.082
presses the number of peers with which
A31 1.000 1.000 2.041 2.041
the actor can connect. This represents
A07 1.000 1.000 2.041 2.041 a total percentage of 93.72% (degree
A33 1.000 1.000 2.041 2.041 of normalised intermediation). Next,
A34 1.000 1.000 2.041 2.041 A03 has a degree of normalised inter-
A35 1.000 1.000 2.041 2.041 mediation of 2.7%, and finally the node
A36 1.000 1.000 2.041 2.041 A02 represents the others who have no
A37 1.000 1.000 2.041 2.041 degree of intermediation.
A38 1.000 2.000 2.041 4.082
A39 1.000 2.000 2.041 4.082 Closeness Degree
A40 1.000 1.000 2.041 2.041 The closeness degree is the “capacity of
a node to connect to all the actors of a
A41 1.000 1.000 2.041 2.041
network” (Velázquez & Aguilar, 2005, p.
A42 1.000 1.000 2.041 2.041
24). It is the indicator that specifies the
A43 1.000 2.000 2.041 4.082
closeness degrees of an author in rela-
A44 1.000 1.000 2.041 2.041
tion to others on the network. Accord-
A45 1.000 1.000 2.041 2.041
ing to Fidalgo and Freitas (2011), “the
A21 1.000 2.000 2.041 4.082
geodesic distance—that is, the shortest
A47 1.000 1.000 2.041 2.041
route—between pairs of actors is one of
A48 1.000 1.000 2.041 2.041
the most widely used measures of close-
A24 1.000 1.000 2.041 2.041 ness” (p. 1396). When we observe a net-
A50 1.000 1.000 2.041 2.041 work and verify that a given node has a
higher closeness degree, this means that
Volume 29 Number 4 | Journal of Digital Learning in Teacher Education | 145
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.
Lisbôa & Coutinho
Table 2. Intermediation Degree group of teachers on the PROEDI social and customise their formative courses
ID Betweeness nBetweeness network and to analyse the type of rela- while increasing their digital literacy.
A01 2204.500 93.729 tionships that were established as well On the other hand, lessons learned
A03 64.500 2.742 as ascertain who the leaders were inside from our study show that SNA is a
A02 0.000 0.000 the community. In the specific case of powerful tool to inform social network
this forum, which was launched to listen leaders/administrators, as it functions
it exceeds the rest in its ability to con- to the members’ opinion about a specific as a kind of a mirror that reflects the
nect to other actors in the network. In distance education program in Brazil, organization of the whole community.
the sociogram, those are the nodes that the data we obtained were not surpris- Through the analysis of the visual socio-
are closer to the center of the network ing, considering that the nature of the gram as well as the numerical indicators,
(see Figure 2). subject did not require deep reflection to one can gather useful data in order to
Table 2 (p. 146) shows two types of contribute to the debate. implement strategies that allow informa-
closeness (incloseness and outcloseness), However, it is clear that the actors tion to flow horizontally inside the com-
which refer to the input closeness degree who present a greater centralization munity, allowing the group to become
and the output closeness degree. In addi- index and hold more information also more and more cohesive.
tion, it illustrates the deviation degree of have the opportunity to receive more
input and output of each member of the information and therefore are the most Acknowledgments
network (infarness and outfarness). In popular and influential in the network. This work is funded by Portuguese Foundation for
Science and Technology under the doctoral grant
our analysis, we will take only the close- In the forum we analysed, these ac-
SFRH/BD/60677/2009.
ness degree and the deviation degree as tors were the creators of the discussion
references. Thus, we can see that A01 has forum and the e-moderator. Author Notes
a greater closeness degree with a value On the other hand, we see that the
Eliana Santana Lisbôa has a master’s in educational
of 98.000, followed by node A03 with network is highly centralised, as es- technology and is a doctoral student at the Universi-
a value of 52.688. In a more extreme sentially two actors hold the largest ty of Minho, Braga, Portugal. She develops research
position, the actors A11 and A13 have a number of possibilities to interact with in the field of virtual social networking, with special
emphasis in the professional development of teachers
lower closeness degree, assuming a value others. This is apparent in the graph,
in educational technology. She has published widely
of 2.000. which shows that the two actors who
in national and international educational journals
Supported by the literature on the participate most frequently have an and conference proceedings as well as two book
subject, (Borgatti, Everett, & Freeman, important function: to keep any element chapters. Please address correspondence regarding
2002), it is apparent that the actors from being a loose node (i.e., a person this article to Eliana Santana Lisboa, Institute of
Education, University of Minho, 4710-057 Braga,
A01 and A03 have a greater power of who does not maintain communication
Portugal. E-mail: [email protected]
influence when imposing their opinions with any element of the network). How-
and interfering directly over the other ever, even though they were not active Clara Pereira Coutinho is an assistant professor at
the Institute of Education, Minho University, Braga,
elements. In contrast, nodes A11 and members in this discussion forum, those
Portugal. She teaches educational technology and
A13 have the lowest closeness degree members had a peripheral participation,
research methods in master’s and doctoral education
and therefore have the greatest deviation which, according to Wenger (1988), programs and has wide experience in the design of
degree. This means that, in theory, these enables learning. We believe that mere teacher education programs as well as in the evalua-
actors are more autonomous regarding participation and reading some con- tion of the impact of integrating information commu-
nication technology in basic and secondary schools.
their choices and behaviours (Freeman, tributions on the discussion forums
Her previous experience also includes research in the
1978). provide opportunities to learn. How-
areas of Web 2.0 educational uses and affordances as
ever, in the current context in which we well as participation in several projects on e-learning,
Conclusions live, where collaborative learning is a multimedia technologies, and digital storytelling.
The study proves that the SNA is an effec- subject much in vogue, there was a lack She has published widely in prestigious national and
international journals and conference proceedings.
tive methodology with which to analyse of member engagement and participa-
Please address correspondence regarding this article
the existing interactions between people tion and, consequently, contribution to
to Clara Pereira Coutinho, Instituto de Educação,
within a specific group, particularly social the growth of the group. As Ally (2004, Universidade do Minho, 4710-057 Braga, Portugal.
networks and virtual communities. p.24) remarked, it is necessary for each E-mail: [email protected]
The data allowed us to deduce that member to be “able to interact within
References
the indicators we used in our analysis their context to customize information
Ally, M. (2004). Foundations of educational theory
are of great value in understanding and construct their own meaning.” We
for online learning. In T. Andreson & F. Elloumi
and intervening in the dynamics of the expect teachers to gradually realise the
(Eds), Theory and practice of online learning.
functioning of the network to propose importance of participation in these new Athabasca, Canada: Athabasca University.
improvements to its structure. In our informal learning environments, where, Barabási, A. (2002). Linked: How everything is
study, they served as a thermometer to in addition to gathering information, connected to everything else and what it means.
New York: Basic Books.
measure the engagement of the informal they can exchange ideas, collaborate,
146 | Journal of Digital Learning in Teacher Education | Volume 29 Number 4
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.
Analysing Interactions in a Teacher Network Forum
Baran, P. (1964). On distributed communications: Harasim L. (2012). Learning theory and online Ibero-Americana de profissionais de educação
I. Introduction to distributed communications technologies. New York: Routledge [Collaboration and leadership in na online
networks. Santa Monica: The Rand Corporation. Hirschi, C. (2009). Introduction: Applications of community of practice: The case of @rcaComum
Borgatti, S. P. (2002). Netdraw: Network social network analysis. Paper presented at in an Ibero-American communty of education
visualization softwares. Harvard, MA: Analytic the 6th Conference on Applications of Social professionals]. PhD dissertation. Braga, Portugal:
Technologies. Network Analysis, University of Zurich. University of Minho.
Borgatti, S. P., Everett, M. G., & Freeman, L. C. Jablokow, K., & Vercellone-Smith, P. (2011). The Raeymaeckers, P. (2013). From a bird’s
(2002). Ucinet for Windows: Software for social impact of cognitive style on social networks in eye view? A comparative analysis of
network analysis. Harvard, MA: Analytic on-line discussions. Advances in Engineering governance and network integration among
Technologies. Education, 2(3), n.p. human service organizations. Journal
Capra, F. (2002). As conexões ocultas [Hidden Jimoyiannis, A., & Angelaina, S. (2012). Towards of Social Service Research, 39(3), 416–431. doi:
connections]. São Paulo: Cultrix/Amana-Key. an analysis framework for investigating 10.1080/01488376.2013.775091
Castells, M. (2000). A era da informação: students’ engagement and learning in Recuero, R. (2006). Dinâmicas de redes sociais no
Economia, sociedade e cultura—a sociedade em educational blogs. Journal of Computer Assisted orkut e capital social. [The dynamics of social
rede (Vol. 1) [The era of information: Economy, Learning, 28(3), 222–234. networks in Orkut and social capital]. Razón Y
society and culture—the networked society]. Kauchakje, S., & Delazari, L. S. (2007). Análise de Palabra, 52, n.p. Retrieved from: http://www.
Lisboa: Fundação Calouste Gulbenkian. redes de proteção social na cidade de Curitiba: razonypalabra.org.mx/anteriores/n52/alaic.html
Clark, L. (2006). Network mapping as a diagnostic Visualização cartográfica como estratégia Recuero, R., & Zago, G. (2009). Em busca das
tool. La Paz, Bolívia: Centro Internacional de metodológica. Revista Tecnologia e Sociedade, “redes que importam”: Redes sociais e capital
Agricultura Tropical. 4(1). social no Twitter [In search of social networks
Coromina, L., Coenders, G., Ferligoj, A., & Guia, Lemieux, V., & Ouimet, M. (2008). Análise and social capital in Twitter]. Líbero—São
J. (2011). PhD students’ research group social estrutural das redes sociais [Structural analyis of Paulo, 12(24), 81–94. Retrieved from http://
capital in two countries: A clustering approach social networks]. Lisboa: Instituto Piaget. www.revistas.univerciencia.org/index.php/
with duocentred network measures. Advances Levy, P. (1998). A inteligência coletiva—por libero/article/viewFile/6787/6129
in Methodology & Statistics/Metodološki Zvezki, uma antropologia do ciberespaço [Collective Rice Doran, P., Doran, C., & Mazur, A. (2011).
8(2), 137–155. intelligence—for an anthropology of cyberspace]. Social network analysis as a method for
Dias, P. (2008). Da e-moderação à mediação São Paulo: Loyola. analyzing interaction in collaborative online
colaborativa nas comunidades de aprendizagem. Lévy, P. (2003). Cibercultura [Cyberculture]. São learning environments. Journal Systemics,
In Revista Educação, Formação & Tecnologias, Paulo: Editora 34. Cybernetics & Informatics, 9(7), 10–16.
1(1), 4–10. Retrieved from http://eft.educom.pt. Lisbôa, E. S., & Coutinho, C. P. (2010). A Retrieved from: http://www.iiisci.org/journal/
Eveland, W., & Kleinman, S. (2013). Comparing problemática da e-moderação à luz da teoria CV$/sci/pdfs/SP319EB.pdf
general and political discussion networks within ator-rede [The problematics of e-moderation Romero-Moreno, L. M., & Lucena, I. (2010).
voluntary organizations using according to Actor-Network Theory]. Paper Evaluating collaboration using the methods
social network analysis. Political Behavior, 35(1), presented at the I Encontro @rcaComum, of social network analysis in a virtual
65–87. doi: 10.1007/s11109-011-9187-4. Tese de Braga, Portugal. training system. In Proceedings of the IADIS
Doutoramento. Instituto de Estudos da Criança. Lisbôa, E. S., & Coutinho, C. P. (2011). Informal International Conference e-Learning 2010, Vol. 2
Braga, Portugal: Universidade do Minho. learning in social networks: A study of the (pp. 292–294).
Fidalgo, P., & Freitas, J. C. (2011). Does teacher’s Orkut social network. Issues in Educational Scott, J. (2004). Social network analysis: A
experience matters? Social network analysis Research, 21(2), 162–174. Retrieved from http:// handbook. London: Sage Publications Ltd.
applied to learning forums. Paper presented at www.iier.org.au/iier21/lisboa.pdf. Senge, P. (1990). A quinta disciplina: arte, teoria
the VII International Conference on ICT in MacKellar, B. (2012). A case study of group e prática da organização de aprendizagem [The
Education, Braga, University of Minho. communication patterns in a large project fifth issue: Art, theory, and practice of designing
Flap, H., Bulder, B., & Volker, B. (1998). Intra- software engineering course. In Proceedings learning]. São Paulo: Best Seller.
organizational networks and performance: of the 25th IEEE Conference on Software Silva, A., & Figueira, Á. (2012).
A review. Computational and Mathematical Engineering Education and Training (pp. Visual analysis of online interactions
Organization Theory, 4, 109–147. 134–138). through social network patterns. In Proceedings
doi: 10.1023/A:1009675906926 Newman, M. (1999). Small worlds: The structure of the 12th IEEE International Conference on
Franco, A. (2008a). Escola de redes: Novas visões of social networks. Journal of Statistical Physics, Advanced Learning Technologies, ICALT 2012
sobre a sociedade, o desenvolvimento, a internet, 101, 1–8. doi: 10.1.1.17.3222 (pp. 639–641). 
a política e o mundo globalizado [Networked Oshima, J., Oshima, R., & Matsuzawa, Y. (2012). Thornton, T., & Leahy, J. (2012). Changes
schools: New visions of society, development, Knowledge building discourse explorer: in social capital and networks: A study of
internet, and globalised world]. Curitiba: Escola- A social network analysis application for community-based environmental management
de-Redes. knowledge building discourse. Educational through a school-centered research program.
Franco, A. (2008b). Escola de redes: Tudo Technology Research & Development, 60(5), Journal of Science Education and Technology,
que é sustentável tem o padrão de rede— 903–921. doi: 10.1007/s11423-012-9265-2. 21(1), 167–182.
sustentabilidade empresarial e responsabilidade Pinto, A. M. G., & Junqueira, L. A. P. (2008). Varanda, M. (2000). A análise de redes sociais
corporativa no século 21 [Networked Schools: A Análise de redes sociais como ferramenta e sua aplicação ao estudo das organizações:
Enterprise sustainability and responsibility in the de diagnóstico das relações de poder [Social Uma introdução [The analysis of social
21st century]. Curitiba: Escola-de-Redes. network analysis as a tool to diagnose power networks and its application to the study of
Freeman, L. C. (1978). Centrality in social relationships]. eGesta—Revista Eletrônica de organizations: An introduction]. Revista de
networks conceptual clarification. Social Gestão de Negócios, 4, 33–59. Retrieved from Psicologia Organizações e Trabalho Organizações
Networks, 1, 215–239. doi: 10.1016/S0140- http://www.unisantos.br/mestrado/gestao/ e Trabalho, 23, 87–106.
6736(00)02113-9 egesta/artigos/138.pdf Velázquez, Á., & Aguilar, N. (2005). Manual
Granovetter, M. S. (1973). The strength of Pinto, M. S. (2009). Processos de colaboração e Introdutório à análise de redes sociais. Medidas
weak ties. American Journal of Sociology, 78, liderança em comunidades de prática online—O de centralidade [Tutorial to the analysis of
1360–1380. doi: 10.1086/219949 caso da @rcaComum, uma comunidade social networks: Measures of centrality]. (M. L.
Volume 29 Number 4 | Journal of Digital Learning in Teacher Education | 147
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.
Lisbôa & Coutinho
Aires, J. B. Laranjeiro, & S. C. de Almeida Silva, Wellman, B. (2001). Computer networks as Zelner, J., Trostle, J., Goldstick, J., Cevallos,
Trans.). Retrieved from http://www.aprende. social networks. Journal Computers and W., House, J., & Eisenberg, J. (2012).
com.pt/fotos/editor2/Manual%20ARS%20 Science, 293, 2031–2034. Retrieved from: Social connectedness and disease
%5BTrad%5D.pdf http://www.ee.oulu.fi/~vassilis/courses/ transmission: Social organization, cohesion,
Wellman, B. (1997). An electronic group is socialweb10F/reading_material/1/Wellman01- village context, and infection risk in rural
virtually a social network. In S. Kiesler (Ed.), ComputerNetworksAsSocialNetworks.pdf Ecuador. American Journal of Public Health,
Culture of the Internet (pp. 179–205). Hillsdale, Wenger, E. (1998). Communities of practice: 102(12), 2233–2239.
NJ: Lawrence Erlbaum. Learning, meaning, and identity. USA:
Cambridge University Press.
148 | Journal of Digital Learning in Teacher Education | Volume 29 Number 4
Copyright © 2013, ISTE (International Society for Technology in Education), 800.336.5191 (U.S. & Canada) or 541.302.3777 (Int’l), [email protected], iste.org. All rights reserved.