Analysis of Social Networks of Students' Learning with a Focus on
Their Performance
Waldir Siqueira Moura
a
, Mônica Ferreira da Silva
b
,
Jonice de Oliveira Sampaio Guimarães de Souza
c
and Tainá Souza
d
Computer Science Graduate Program, PPGI, Federal University of Rio de Janeiro, Térreo, Bloco E, CCMN/NCE,
University City, post code 68.530, Rio de Janeiro, Brazil
Keywords: Analysis of Social Networks, School Performance, Method.
Abstract: The low performance of students in high school is a problem that has had considerable growth due to the
constant transformations generated by the current pandemic. The formation of groups to develop collaborative
work in the classroom is a rich tool that can effectively develop Collective Knowledge, provided there is
planning. Furthermore, through the analysis carried out, we realised that the way the learning occurs affects
the students' performance and can be reorganised by the teachers to enable a better group (and even individual)
development within the group.
1 INTRODUCTION
Low school performance is already an old problem
(Moura et al., 2020). Based on this reality and related
articles, we seek to determine how social interactions
and school performance influence the formation of
tribal and selective participation. In this way,
understanding how these social networks are built can
help us to understand and delimit the main difficulties
and individual deficits, which may allow us to
elaborate strategies for an integral development of
individuals within groups since a low level of
collaboration results in a low level of participation
(Delbem et al., 2014).
We observed collaborative working relationships
in creating the metrics to map these social networks'
tangency (Xavier, Jr., 2004). The formation of groups
to develop collaborative work in the classroom is a
rich tool that can effectively develop Collective
Knowledge. Therefore, understanding how social
interactions and school performance influence the
formation of these interactions is relevant. Moreover,
the act of understanding how these social networks
are built can help us to understand and delimit the
a
https://orcid.org/0000-0003-1545-7487
b
https://orcid.org/0000-0003-0951-6612
c
https://orcid.org/0000-0002-2495-1463
d
https://orcid.org/0000-0002-8311-5043
main difficulties and individual deficits of each
student, which can allow us to elaborate strategies for
the full development of each individual within groups
since a low level of collaboration can result in a low
level of interaction.
Our main goal is to create a method to promote
and operate this integration. For that purpose, we
collected data, 40 social networks were analysed, and
the degree of interrelationship between groups. This
provided us with the means to develop metrification
and implement Collective Knowledge construction in
the classroom.
The applied experiment analysis data found a
strong correlation between networks of friendships
and their grades. This allowed us to verify that
retained students do not fit in with students with
similar grades. We also found that students with good
grades have many bonds of friendship. However,
these bonds are weak because they revolve around
interest in grades.
The Collective Knowledge applied by the teacher
should collaborate with the interrelationship of the
students and, consequently, with the strengthening of
bonds and grades. Although social media increases
Moura, W., Ferreira da Silva, M., de Souza, J. and Souza, T.
Analysis of Social Networks of Students’ Learning with a Focus on Their Performance.
DOI: 10.5220/0011052300003182
In Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022) - Volume 1, pages 257-264
ISBN: 978-989-758-562-3; ISSN: 2184-5026
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
257
connectivity among students, it is noticeable that the
collective work in person lacks low quality.
Furthermore, participating should promote ways of
integrating of being close to - the native and non-
native capacities of each student.
Therefore, the solution presented to the problem
of tribal participation aiming to improve the student's
performance is the improvement of the articulation of
native instances, which must be activated through
interrelationship and collaboration. The article's
discussion has organized the propositions to reach our
goal, divided into the following sections. Section 2
and 3 present the conceptual foundations. Section 4
describes the methodology used to conduct the study
presented in this article. Section 5 displays the data
analysis and its results. Section 6 presents the related
articles. Moreover, section 7 presents the conclusions
and future work of this research.
2 PERSONALITY
CLASSIFICATION
The primary literature chosen for this research is the
Psychogenetics by Prof. Xavier (Xavier, Jr., 2004),
which originates in Piagetian psychogenetics,
studying the genesis of intelligence. The study is
adopted with the primary motivation of interest in
deepening human functioning, having as its
imperative's: cognition, metacognition, and
interactions.
Prof. Xavier's Psychogenetics points out that it
studies how the "Person System" develops, studies
the genesis of human functioning and development in
its age groups, and researches the fruition or
intentionality of immaterial operations. It also states
that psychogenetics enters the universe of observable
and measurable sciences. (Delbem et al., 2014). Thus,
a scenario of study and research has been created that
generates words reserved for this area of science with
the meanings that articulate among themselves.
The Psychogenetic Theory states that human
nature is interactive; in his words, interactive
development is a diachronic process. Therefore, its'
understood that diachrony is a fundamental element
in interrelational development. (Xavier, Jr., 2004)
Thus, we found some words reserved for this area of
study in this research. For better understanding, we
elucidated their meanings whenever necessary.
The respect the selective participation we may say
that is analogous to the practical community since its
grouping often takes place informally among the
students; all those involved have a final goal to be
achieved; the members form interaction relationship
mechanisms to achieve the proposed goal and,
through these interactions, create a shared repertoire.
About tribal participation, the constitution of
informal groups occurs similar to the selective
grouping, but the shared practices and their objectives
may vary. This means that although tribal groupings
have objectives, they are exclusively a priority for
that group of young people who group automatically.
As far as the results of the two types of participation
are concerned, we can say that the productivity
considered in the different objectives can differentiate
concerning the collaborative work and its production.
In strictly tribal groupings, we highlight
communication and cooperation. This is because the
members of these groups associate themselves not
with an objective and its development but with
common affinities and tastes. This creates a robust
inter relational bond between the members but
specifically disregards the productive capacity.
Therefore, these groups have inter relational solid and
collaborative bonds as their characteristics.
Although they may occur as practical
communities, different, selective groupings tend to
occur in the face of a specific activity, challenge, or
need. In this case, the communication between the
members already has a character of commitment to
the objective. Coordination is a fundamental
characteristic because, once because of the objective,
the members are divided to solve the problem
according to their primary skills. After the division of
tasks, the group tends to operate to fulfil their role,
and thus, together, they cooperate simultaneously and
synchronously.
Xavier (Xavier, Jr., 2004) explains that
psychogenetics is a structuralist approach. It focuses
on the universe of global and partial human
behaviours observable through the structures of Vital
Energy mobilised in them psychogenetics studies
reality since it approaches the "Human Person
System," contextualised in the ecosystem.
3 COLLABORATIVE
PRODUCTION IN ANALYSIS
OF SOCIAL NETWORKS
One of the aspects that marks the 2.0 generation of the
Internet is the idea of co-authorship, that is,
collaborative production. This is because cyberspace
is an environment of production and consumption in
an expanded way. The collaborative production is
achieved through co-authoring, which we can call
cyberculture (Fuks, Hugo; Pimentel, 2011).
CSEDU 2022 - 14th International Conference on Computer Supported Education
258
Collaborative groups are those in which the
components share the decisions made and are equally
responsible for the quality of what is produced
together.
However, the mere existence of collaboration does
not mean that there is, in fact, a culture of
collaboration, says Damiani (Damiani, 2008). That is
because alternative ways of collaboration may not
constitute collaborative cultures, although they
involve working together. After all, they present
competing subgroups or only occasional jointactions.
The model (Fuks, Hugo, Pimentel, 2011)
classifies the systems that support group work into
three dimensions: communication, coordination, and
collaboration. This classification gave rise to the 3C
Collaboration model, which was later formulated. In
this model, cooperation strictly refers to operating
together, while collaboration refers to doing all the
work together, which involves communication,
coordination, and cooperation.
The benefits of collaborative work among
students have been presented by several researchers
(Colaço, 2004). Among the significant gains of the
implementation of these works in the educational
process is the socialisation among students - which
includes the learning of communicational modalities
and coexistence -,the control of aggressive impulses,
the adaptation to the established norms - including the
learning related to the performance of social roles -,
the overcoming of self-centeredness - through the
progressive relativisation of the own point of view -,
the acquisition of aptitudes and abilities - including
improvements in school performance -, and the
increase in the level of school aspiration.
The network concept can be recognised through
its effectiveness, both from the static and dynamic use
points. The fixed point of use exploits the network's
structure, while the dynamic point exploits the system
that constitutes the network. The analysis of social
networks establishes a new paradigm since the study
of the behaviour or opinions of individuals depends
on the structures in which they are inserted. Thus the
unit of analysis is not individual - sex, class, age,
gender, between others. - but the whole is built
through the interpellation ofthen whole. (Deroy-
Pineau, 1994). This structure is illustrated and
apprehended concretely by the network of
relationships and limitations that weigh on
individuals' choices, orientations, behaviours, and
opinions, as (Bezerra et al., 2014) explains.
Social networks are an essential part of humanity
(Delbem et al., 2014) (Moura et al., 2020). These
networks are based on the interrelationships between
humans seeking a common goal, between entities
and can be mediated and metrified using technologies
(Silva et al., 2018). The observation and research to
raise patterns of connection between social groups
and how connections are established between
individuals are already found in current research.
However, no metric can see how social interactions
within specific networks interfere with academic
development.
The basic premise of information technology is
management through the epistemic- ethical posture of
the individual in the exercise of his autonomy in social
media (Delbem et al., 2014). Its starting point is the
'Inter-relationship' as a marker of cognitive
development. Thus, interaction precedes and
determines knowledge. Therefore, it is investigated
what to do, live together, collaborate, produce, know,
get to know each other, and reciprocate. In short, the
interrelationship.
Therefore, the operations of academic subjects
carried out in virtual spaces by adolescents maintain
the concreteness of proprioception coming from the
instantiated functioning in 'somesthesia.' The virtual
space aggregates the conceptual data, but without
losing the corporal reality, it only changes the state
from real to virtual, preserving the experience of
contact with the actual object (Fuks, Hugo; Pimentel,
2011).
4 PROPOSED METHODOLOGY
We analyse the built social networks from the data
collection to identify patterns and characteristics that
can be metric, proven, and altered. From the
verification of these patterns, the computational
ingenuity succeeds, which, assembled on the relevant
topics that were mathematised in the empirical phase,
serve as an instrument for mapping and automatic
analysis of social networks and behavioural patterns
of participation.
In the first instance, the mediators of data
collection and analysis are the researcher and the
teachers trained to monitor and collect data directly.
In the second instance, using experiments for data
collection is done by the teachers of the network and
their respective coordinators. However, the
researcher's sole responsibility is the data analysis and
mapping of social networks. Moreover, in the third
instance - after the development of the computational
engine - the teachers and pedagogical teams of each
school are responsible for the collection of digital data,
which should be placed directly on the developed
platform that should map and make the analysis of
social networks and the patterns of participation
Analysis of Social Networks of Students’ Learning with a Focus on Their Performance
259
found, giving as proposal the best possible selective
participation within that analysis.
The first part of our research was the stage of the
bibliographic survey regarding the topics of interest:
psychogenetics, analysis of social networks, and
collaborative systems. This deepening and theoretical
background stage covered our problem's definition,
the hypothesis's formulation, and the proposed
solution. The systematic bibliographic review was
carried out in the scientific's base (ACM, IEEE and
Springer).
The second stage of the research includes the
metrification survey to analyse social networks
formed by collecting students' data. After identifying
the participation patterns and the topics of social
network analysis that would be considered for the
metrification of these patterns, the validation stages
were followed, such as the pilot experiment and the
elaboration of the collaborative work method. This
stage still verifies the feasibility of creating
participation patterns and their analysis. In
constructing the computational engine, the agile
development process is used. The requirements are
collected as a concept, functionality, user history
(students and researchers), analysis of individual and
group metrifications, and tests with selective
participation proposals.
Based on the analysis of social networks, the
organisation of selective groups is part of the third
stage. It corroborates the enturmation's model, which
potentially includes the best native instances of the
students. All development is based on data analysis
and empirical collaborative work, whose psycho-
pedagogical evaluations constitute a theoretical and
operative educational reference.
5 RESULTS AND ANALYSIS
Through the results gathered in the initial experiment,
it was noted that the main difference highlighted for
the differentiation of these groupings is the planned
coordination. It has interrelation
1
as a fundamental
premise in human development; interaction precedes
and determines knowledge. Thus, psychogenetics
investigates doing, living together, collaborating,
producing, getting to know, and reciprocating, in
short, interrelationship. Based on the 3C model, we
propose some of the main differences that we believe
are distinct in both groupings, which can be observed
in the following subtopics.
5.1 Mapping of the Self-centred Social
Network
For the metrification of students' social networks, a
questionnaire was first elaborated applied individually
to the previously selected students, considering that
they have studied together since the sixth grade of
elementary school II. This questionnaire considers
the students' preferences in several psychic and motor
activities and a previous spontaneous survey of their
networks of friends. In constructing these networks,
it was possible to show which friends were for
specific activities - in sports, collaborative digital
games - such as RPG, school work, proximity to
residence, between others). Data collection from
egocentric networks was carried out using the
questionnaire below:
Table 1: Questionnaires applied.
Application questionnaire template
Student:
Age:
Friend of:
A
pp
li
e
d
quest
i
ons
Do you practice any sport?
Yes
No
Which
one
Do any
f
r
i
en
d
sp
l
ay on you
r
team
?
Do you p
l
ay v
eo games o
r
on
li
ne games
?
Do you usually play alone o
r
in
a
group?
Do any c
l
assmates
li
ve nea
r
you
r
h
ome
?
L
ik
etorea
d?
I
f
so, w
h
a
t
genre
?
Do you do any kind o
f
artistic activity?
Soc
i
a
l
me
dia
you use:
Because of this reality, we followed the
participation. We analysed the social networks of 40
students to metrify the degrees of the interrelationship
among the groups to implement collective knowledge
in the classroom. Furthermore, one of the main
challenges found for the development of this
experiment was the participation between the native
psychic and somesthetic students.
5.2 Creation of the Complete Social
Network
After these findings returned from the comparative
data between the interview and observation, the data
were analysed within Cytoscape (2020)
1
, an open-
source software platform for viewing complex
networks. After constructing the graphs of the social
networks built with the help of the software, the
following metric was analysed and calculated: In-
degree (which is the degree of entry of the vertex). It
was calculated based on the number of friends of each
1
https://www.answerminer.com/
CSEDU 2022 - 14th International Conference on Computer Supported Education
260
student and based on their relationships. For example,
a student x can have a number y of friends and a
number z of friends of works only, so first, the total
entry-level was raised and then subdivided between
friends of worksand personal friends.
Although this relationship between the number of
friends and grades was evident in the graphs, we
sought a means to prove, based on data, that this
relationship was indeed strong and therefore should
be considered. For this, we used the Pearson
Correlation Coefficient - CCP.
Initially, to calculate the CCP, we used the online
AnswerMiner3 automatic calculation platform.
However, after several test calculations, including the
use of the same data, we noticed that there was a slight
divergence of results between one round and another;
with this, fearing the compromise of the truthfulness
of the research and considering increasing its
reproducibility, we decided to create a specific CCP
calculator for this work.
Therefore, based on the metrics of social network
analysis and the CCP calculation, we propose a
formal system that has ruled for analysing
interactions and their representations. According to
psychogenetics (Delbem et al., 2014), psychism and
somesthesia are propositional concepts. Thus,
psychism groups the competencies for so-called
"superior" activities, while somesthesia groups the
bodily functions correlated to the so-called "human"
activities.
As we have already seen, tangency is the
articulation of these two instances, and it is
understood as an articulation of the evolutionary
structure, measurable by seasonal diachrony. The
articulation is the meeting of two energies, which can
be understood as hybridization4 because the energies
co-exist in complementing one within the other. They
do not merge into one another (Xavier, Jr., 2004).
Therefore, it can be understood that a higher
density in one instance does not require damage to the
other because one instance has no quota to the
detriment of another. Therefore, articulation is
summed up as being the regulation between
somesthesis and psychism, and tangency is the
balance between both. This thing that is understood
as "native" is the predominant energy in the
individual that can also be called a pioneering
competence, which is the individual's strong point.
5.3 Complete Social Network
In this first graphic representing the first high school
grade (Figure 1), we can observe how their networks
are structured. With that, we can conclude that: 1 -
student number 13, located in the right median corner,
has the highest average in the class. We can also
observe a large number of entries he has.
However, although he considers all the entries as
reciprocal friendship, the vast majority of the entries
consider him only as a work friend and not as a
personal friend, as can be observed by the pink arrows.
Another essential piece of data that we can
observe in this graph is the relation of the students
(numbers 05, 06, and 03) located in the upper left
corner, the trio's grades are below average, and they do
not relate to anyone in their class. For this more
profound analysis, the first year of High School was
considered because it is a class where the students
have lived together in class since the sixth year of
Elementary II. That is, they keep the same group as the
previous year and keep the interrelations with the
friends who were approved. This fact leads us to
consider a cause-and-effect relationship between low
performance because they do not interact with their
colleagues in the current grade.
Figure 1: A Detailed analysis of the social networks of first-
grade high school students.
The other two series (Figure 2) are presented here
only in their simplified form to highlight the issues
discussed in this research. After structuring the social
networks of each room and analysing the data
according to the graph theory, the comparative tables
were constructed with the information gathered to
prepare the graph of the Pearson's Correlation
Coefficient.
Figure 2: Social network graph of High School First Grade
students.
Based on the detailed chart, we can consider a way
of approaching to improve student performance, being
the implementation of a model of induced
collaborative work, where the teacher should naturally
Analysis of Social Networks of Students’ Learning with a Focus on Their Performance
261
include student number 13 to work with the students
(numbers 05, 06 and 03); this way the network of
interest for his grade is broken and the failed students
have the opportunity to produce and be approved.
In chart one, we have the number representing the
student, which is a standardised numbering and does
not correspond to the actual call number made to
make it impossible for the student to be recognised by
an external agent. As can be observed, there is a
positive linear correlation between Input Grades and
Notes. In detail, this means that the higher the Entry
Grade number, the higher the student's grade, i.e., the
more friends the student has, the better chance of
achieving a grade.
As can be seen, there is a positive linear
correlation between Input Degrees and Notes. In
detail, this means that the higher the Entry Grade
number, the higher the student's grade, i.e., the more
friends the student has, the better chance of achieving
a grade. Considering that Pearson's correlation
coefficient in the 2nd year MS analysis is 0.8030, we
can conclude that this correlation is strong.
Table 2: Analysis input degree x grade 1st High School and
Pearson correlation coefficient for input degree x grade.
Studen
t
Input degree Grade
Studen
t
Input degree Grade
1 6 58,9 9 4 62,6
2 6 70,5 10 5 65,9
3 2 49,0 11 5 58,4
4 4 57,5 12 6 73,9
5 2 56,9 13 9 76,1
6 1 35,0 14 4 49,2
7 4 50,0 15 4 57,3
8 4 64,8 16 5 37,7
17 3 56,6
After the data collection of the experiment, it was
evidenced that there is a strong correlation between
the networks of friendships and the grades, which
allowed us to verify that repeat students do not get in
touch with students of the grade they are in and that
students with good grades have many bonds of
friendship. However, these bonds are weak since they
are only interested in grades. The Collective
Knowledge applied by the teacher should collaborate
for the interrelationship of the students and,
consequently, in the fortification of the bonds and the
grades.
5.4 Validation of the Social Network
As an answer to this problem of low school
performance, we propose a collective work, together
with the teaching staff of the whole school network,
that they work, with the use of a Crowdsource tool,
considering that the school network has several
different cities and states. In this way, crowdsource
enable all teachers to work collaboratively, sharing
their experiences and building workgroups that they
use in their daily classroom. Thus, based on the
exchange of the various and different experiences of
teachers supported by the Crowdsource tool, we can
build a unique method that includes all the benefits of
the various experiences reported.
After using Crowdsource to solve this problem,
we hope to build a method that promotes interaction
between students, enabling the split with the
traditional method, based on the exposure of content
solely from the teacher. After the interview, the
teachers started an observation, considering the data
collected, where everyone was previously instructed.
This observation was intended to confirm or refute
the interview data.
Based on the reports of teachers who have
followed the development of students since the sixth
grade of elementary school II, it was possible to see
how interactions occur. These reports provided data
that confirmed much of the information gathered in
the interview, reinforcing the informed social
networks.
This, considering that the interrelationship
between students is a great facilitator in the
construction of knowledge and cognitive, affective,
and social development, we believe that this shared
method can also improve relational, dialogical, and
argumentative skills, which enable a joint reflection
and favour the creation and strengthening of the
bonds of friendship.
5.5 Validation of the Results
As an answer to this problem of low school
performance, we propose a collective work with the
teaching staff of the whole school. After developing
the method for optimal groupings is completed, we
resume Social Network Analysis based on its
parameters. We choose the most appropriate metrics
for the diagnosis and organisation of students
according to their native instances.
Using the method developed with the teachers
specifically to solve this problem of the students'
academic performance, we created a comparative
graph to demonstrate the effects of the new groups on
CSEDU 2022 - 14th International Conference on Computer Supported Education
262
the performance of each individual. There was a
considerable improvement when comparing students'
grades before and after applying the method based on
social network analysis. The metrics used to prove
this hypothesis were constructed according to the
realities considered a priority within the educational
environment.
We can see how each metric is viewed
individually theoretically. However, after a detailed
analysis of the data that resulted from applying the
applied methodology, we built a comparative table of
these metrics before and after the new grouping
model.
This table can analyse the groups' gains after
applying the method. The first fact that we can notice
the difference is the absenceof a small component
after applying the method. That means an evident
division among the students before applying the
participation method, which formed closed
relationship groups that made the interaction between
certain groups difficult. With the new method,
everyone becomes part of the Giant Component.
What this means is that the proximity among the
students has been so strengthened that there are no
more excluded groups
Indegree and Outdegree also increased almost
100% concerning previous data. The application of
the methodology which caused this was an increase
in interaction between students in the classroom,
which justifies the disappearance of the Small
Component; Betweenness Centrality decreased
because the importance of some specific nodes also
decreased; that is, the information runs similarly
among all members of the network reducing the
dependence of specific nodes for the dissemination of
information; Network Connectivity has also been
enhanced thanks to the degree of interaction that has
increased and eliminated the Small Components.;
Clustering Coefficient also had a drop due to the
strengthening of the participation. All this data can be
visualised in the table below that provides the average
of the metrics explained above.
6 RELATED WORKS
As we can see today, students have a great tendency
to spend their hours in cinemas andsocial media.
However, schools have great difficulties
implementing technology as a support and incentive
for learning (Moura et al., 2020). The present work
proposes one more possible way to use technology as
a pedagogical aid tool. As with other sectors of
society, education was improved with technology. In
the virtual school, social network environments allow
learning communities to group and exchange
experiences among students (Marinho et al., 2015).
Other authors have already proposed using social
network analysis as a basis for school performance.
In 2011 (Fuks, Hugo, Pimentel, 2011) analysed the
social networks of an undergraduate course and how
the influence of the student reflects on their
performance. The experiment took place in six
months. Students were offered a social networking
site with games and collaborative work as a tool.
After the students' use, the researcher generated a
graph with four measures of the public network and
nine of each student. The individual measurements
obtained were used as predictors for evaluating the
students' performance. All tests and analyses have a
common opinion about the potential of structural
metrics aspredictors of school performance analysis,
and it is a helpful tool. (Fuks, Hugo, Pimentel, 2011).
In the school environment, social networks allow
predicting the success of educational learning with
their tools, offering results that can direct the teacher's
attention to theirs teaching practice. Through the
analysis of the environment, modification tools are
added to the physical environment in which the
research actors are inserted (Sousa-Vieira et al.,
2018). Furthermore, students with better performance
generate greater engagement due to their prestige and
influence. It is also noticeable that the involvement of
students with other people in the platform
(networking) partially predicts its outcome (Liu et al.,
2018).
Table 3: Metrics analysis.
Métrics:
Grade
Alunos:
1
02
0
08 07 08 0
3
04
05
05 08 04 07
6
07
08
09
0
6 07 07 06 07 06
10
0
8 06
11
12
13
07 07 06 08 08 08
4
15
16
17
0
7 06 07 07 07 02
Component
G G G
P
G G P G G G G G G
G
G
G G G G G G G G G G G G G
Indegree
05
04 06 0
2
03 05 02 05 05 03 05 04 06 0
3
6
02 0
6
02 05 05 08 04 08 06 03 07 04 08 03
Outdegree
05
02 04 0
1
2 4 5 8
06
02 04 03 05 0
4
8
02 0
5
04 07 05 07 09 12 07 00 05 00 04 08
Betweennes centrality
0.107
0.092 0.189 0.
0
0
.072 0.115 0.85 1.64
0.345
0.0 0.027 0.154 0.102 0.5
0
6 0.0 0.1
0
0
.716 0.417 1.998 0.518 2.70 0.893
0.588 0.0 0.147 0.0 0.247 2.414
Network Density
0,276
0,145 0,276 0,1
4
0
,145 0,276 0,145 0,276
0,276
0,145 0,276 0,145 0,276 0,1
4
6
0,145 0,2
7
0
,145 0,276 0,145 0,276 0,145 0,276
0,276 0,145 0,276 0,145 0,276 0,14
5
Neighborhood connectivity
8,5
6.0 8.7
3.
5.5 8.3 1.4 4.3
7.8
6.33 9.0 5.75 8.6 5.
6
3
5.0
4.5 7.4 4.83 7.1 4.77 7.2
8.2 5.0 8.2 5.5 7.7 4.5
Clustiring Coefficient
0,53
0.35 0.47
1.0
0.25 0.43 0.05 0.12
0.46
0.83 0.7 0.66 0.6 0.
4
5
0.66 0.
5
0.25 0.33 0.43 0.33 0.27 0.36
0.37 0.83 0.48 0.25 0.35 0.23
Closeness Centrality
0,527
1.0 0.513
0.5
5
1.0 0.153 1.0 0.59
3
0.59
0.371 0.452 0.406 0.475 0.43
7
5 0.351 0.
5
0.5 0.558 0.541 0.558 0.764 0.655
0.612 0.0 0.527 0.0 0.452 0.72
2
Aluno
Nota
Componente
Grau de entrada
Grau de saída
Centralidade de
intermediação
Densidade da
rede
Conectividade
de vizinhança
Coeficiente de
agrupamento
Centralidade de
aproximação
Nota
Componente
Grau de entrada
Grau de saída
Centralidade de
intermediação
Densidade d a
rede
Conectividade
de vizinhança
Coeficient e de
agrupamento
Centralidade de
aproximação
01
8
G
5
5
0.107 0,276 8.5 0.53 0.527
Antes
5,47
G e P
3,17
3,23
0,579
0,145
5,510
0,52
0,548
02
8
G
6
4
0.189 0,276 8.7 0.47 0.513
Depois
7,29
G
5.88
6,17
0,404
0,276
7,705
0,42
0,546
03
7
G
3
4
0.526 0,276 7.0 0.40 0.558
04
8
G
5
4
0.115 0,276 8.3 0.43 0.513
05
7
G
5
8
1.64 0,276 4.3 0.12 0.593
06
6
G
5
6
0.345 0,276 7.8 0.46 0.590
07
7
G
5
4
0.027 0,276 9.0 0.70 0.452
08
7
G
6
5
0.102 0,276 8.6 0.60 0.475
09
8
G
6
8
0.306 0,276 7.3 0.35 0.575
10
7
G
6
5
0.104 0,276 8.6 0.56 0.527
11
7
G
5
7
0.417 0,276 7.4 0.33 0.558
12
8
G
8
7
0.518 0,276 7.1 0.33 0.558
13
8
G
8
12 0.893 0,276 7.2 0.36 0.655
14
7
G
6
7
0.588 0,276 8.2 0.37 0.612
15
7
G
7
5
0.147 0,276 8.2 0.48 0.527
16
7
G
8
4
0.267 0,276 7.7 0.35 0.452
17
7
G
6
10 0.578 0,276 7.1 0.34 0.612
Figure 3: Metrics for group analysis.
Analysis of Social Networks of Students’ Learning with a Focus on Their Performance
263
7 CONCLUSIONAND FUTURE
WORK
In the development of this article, we seek to
understand how the grouping of students occurs
through the method presented, and we can regroup
students so that there is an improvement in the
processes of participation. The analyses were carried
out in high school.
Thus, we found the method presented above as a
solution to the problem of tribal participation aimed
at improving student performance improving the
articulation of native bodies, which should be
triggered through inter-relationship and collaboration.
We seek to develop a method to promote and
operationalise this integration among students to
increase their school performance.
However, our research cannot be continued and
applied in the long term by the pandemic, so we
recommend that we suggest a reproduction of this
research on a larger scale as future work. We also
recommend a reproduction in elementary school in
the early years to note a difference in behaviour in
different age groups and an article that is a manual of
applying the method. We also recommend replicating
this method during the pandemic for online
education.
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