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DOI: 10.4018/JITR.2016070102
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Volume 9 • Issue 3 • July-September 2016
Margarita Martinez-Nuñez, Technical University of Madrid, Madrid, Spain
Oriol Borras-Gene, Technical University of Madrid, Madrid, Spain
Angel Fidalgo-Blanco, Technical University of Madrid, Madrid, Spain
Two major educational strengths that MOOCs provide are informal learning and harnessing the
collective intelligence of the students and the interactions among other users like former students,
future students, business professionals, other universities, etc. These features may lead to the emergence
of new sustainable in time educational elements wherein knowledge and learning continue enriching
once the course finished. At present, one of the main limitations of the MOOC platforms is the lack
of social open tools to enhance and take advantage of the collective intelligence generated in the
course. This article proposes a new model to allocate informal learning and collective intelligence
in MOOCs using external virtual learning communities through social networks, based on Google
+. The main aim of this article is to assess the virtual learning community performance and analyze
the interactions and the kinds of learning that take place inside the community and over time. A case
of study of a MOOC course with Google + community is presented.
cMOOC, Collaborative Learning, MOOC, Open Knowledge, Social Networks, Social Platform, Virtual Learning
Community, xMOOC
During the last decade, new tools have emerged in the online learning and thus, the traditional
teaching models and methods have started to change. Several learning models (ie: informal or non-
formal) associated to new training method are now present in the academic and educational sector.
One of the main drivers of this transformation is the Massive Online Open Courses (MOOCs) that
is an online course aimed at unlimited participation and open access via the web. MOOCs are online
educational resources and may be seen as the logical evolution of the Open Course Ware (OCW) to
which is added the chance of interaction between teachers and participants, and among participants
themselves (peer to peer).
MOOCs offer new opportunities for learning because of their intrinsic characteristics: the
massiveness of participants, peer-to-peer interactions, free-of-charge, openness and scalability. These
features lead to a large heterogeneity of participants that are often unmanageable and may cause high
dropout rates of the courses.
One of the current challenges for this MOOC is to reduce dropout rates by providing customized
strategies and resources for the different profiles of participants. The integration of external social
18
Volume 9 • Issue 3 • July-September 2016
19
tools in the training model of the MOOC arises as an opportunity to perform that customization.
The incorporation of virtual learning communities (VLC) may provide greater interaction between
participants, support and guidance to people with difficulties and may increase collaborative processes
between participants (García-Peñalvo, Cruz-Benito, Borrás-Gené and Fidalgo Blanco, 2015).
If the MOOC course has a rigid learning design (same educational level or methodology for
all students), it may lead participants to give up even before the course starts. The same applies to
learning networks and connectivist activities: an activity may be of interest to a group, but not for
others. During these courses the flexibility of the work plans must be seeked. The identification
of those most active and expert participants that will be defined as group leaders and may become
facilitators of the VLC is one of the key factors for the MOOC success.
Two editions of the MOOC course “Application of social network to education: virtual
communities (Borras-Gene, 2014) took place on November 2013 and October 2014. This course
combined a more traditional MOOC course (xMOOC) with a connectivist type of course (cMOOC)
based on the cooperative model proposed by Fidalgo, Sein-echaluce and García-Peñalvo (2013) and
on the adaptability between them. This course is the case of study of this paper.
This work explores the elements of the course that have been identified as enriching factors for the
virtual learning community. The different kind of learning associated to these factors is also studied.
The course is focused on the incorporation and monitoring of virtual communities and external tools
in the MOOC, engaging innovative methodologies and resources.
This paper aims to present the design, development and results obtained in this experience, for
if, given its success, it may be useful as a reference for the design and development of future MOOC
implementations and for opening new research lines, proposes a comprehensive analysis of how social
tools are managed and used by the participant of the MOOC. This analysis includes:
• Assessment of the evolution and dynamics of the virtual learning communities throughout time
and the perception that participants have of them.
• Analysis of the factors involving the generation of a stable learning community, even after the
MOOC finished and the type of learning, the learning results and the knowledge that these
factors have generated
Experts from the major and most prestigious Universities of the world are offering training through
ubiquitous and free courses, opening up new opportunities for defining new pedagogies (Martin, 2012).
In this regard, the main pedagogical principle behind a MOOC proposal should be that participants
would be able to create new knowledge in a social and collaborative way, allowing that knowledge
may be openly used both to improve the MOOC itself and to give continuity to the MOOC learning
community.
Most of the MOOC platforms include social tools like forums to centralize learners’ contributions,
discussions and queries or wikis. But these tools are only accessible inside the platform, so there are
limitations in the interactions that can be established.
In the Web 2.0 (O`Reilly, 2005), there are several external tools known as Social Network, such
as Google +, Twitter or Facebook, that are a suitable environment to effectively build connections
and collaboration among learners instead of introducing a pool of them randomly (Khalil & Ebner,
2013; Kop, Fournier & Mak, 2011).
Volume 9 • Issue 3 • July-September 2016
20
There is an increasing influence of students’ online social networking in their social and academic
learning (Tian, Yu, Vogel & Kwok, 2011). Social networking has been established as a part of the
e-learning settings. Furthermore, it has been found that social network properties (e.g. centrality)
significantly influence learners’ performance (Cho, Gay, Davidson & Ingraffea, 2007; Moreno, 2013).
The Web 2.0, being user-centric, brought a collaborative and participative role for its users. Internet
users are no longer simple information consumers but they are also information producers and are
called prosumers (Ritzer, Dean & Jurgenson, 2012).
An appropriate selection of social tools is a good way to engage students and promote their
participation in the course (Alario-Hoyos, Pérez-Sanagustín, Delgado-Kloos, Muñoz-Organero &
Rodriguez-de-las-Heras, 2013) and enhance and enable VLC associated with it.
A virtual community is defined as communities of people who share common values and interests,
and that are connect via different communication tools that such networks offer, whether synchronous
or asynchronous (Cabrero, 2006). These communities offer new learning values from the traditional
learning. The VLC is characterized by the exchange of information in different formats, and by
the generation and construction of new knowledge; usually flexible in time and a multidirectional
communication, ranging from one to one or one to all is done. According to Cabrero (2007) “... learn
in VLC is a group learning, and learning in a collaborative and non-competitive environment, where
all community members contribute with their knowledge to achieve common goals, which can range
from solving a problem or project, to the development of a single activity”. These communities are
sources of important knowledge management and represent an important model of social learning
(Cruz-Benito, Borrás-Gené, García-Peñalvo, Fidalgo Blanco and Therón, 2015a).
Openness offers the possibility for new opinions to join the discussion, and although opinions can
dissent sometimes for the benefit of those involved, they can sometimes be disruptive and unproductive
(Mackness, Mak & Williams, 2010). Optimal facilitation of students resides somewhere between
allowing the students to guide their own learning while at the same time creating an atmosphere
of open communication (Poy & Gonzales-Aguilar, 2014). The participants should be stimulated to
provide own content and enhancements to existing content. This can be accomplished by introducing
the concept of Fisher (2011) on defining culture of participation of three parts that must be taken into
account when designing the community associated with a MOOC:
• Meta-design: where collaborative design is enabled by the infrastructure
• Social creativity: that shall support collaboration among learners
• Different levels of participation: those levels should allow different degrees of engagement with
the system and its content
According to Downes (2012), Connectivism is “the thesis that knowledge is expanded through
the connections and where learning is the ability to build that knowledge for yourself.”
The following section describes the design of a MOOC course, based on the cooperative model
proposed by Fidalgo et al. (2013), that integrates the features of xMOOC (included in traditional
courses online platform e-learning) and an external learning community that offers the connectivist
features of cMOOC. The proposed model adds a fourth layer (Gamification) representing a set of
elements of gamification applied to the other three layers (Technological, Training and Cooperative)
that are integrated in the cooperative model of Fidalgo et al. (2013). These four layers are continuously
interacting among them. The description of each layer is as follows:
• “Technological layer”, formed by the e-Learning platform that will support the course and a
social network which constitutes the learning community which promotes the connectivism part
of the course
• “Training layer” where they are on one side of the course and basic general knowledge for
all students (based on the behaviorist learning) this part is carried out on the platform; on the
Volume 9 • Issue 3 • July-September 2016
21
other hand, those activities designed for a more individualized learning and looking to generate
resources by students (connectivist learning), this part is mostly seen in the learning community;
finally the results are generated resources, both on the platform and in the community organized
• “Cooperative layer,” based on the cooperative flow of both course participants and the faculty
to generate knowledge resources
• “Gamification layer,” adds elements to improve motivation in the previous three layers
The identification of the different types of learning that can be found in MOOC is a relevant
issue, especially in those MOOCs where there are collaboration-based external elements like learning
communities (Cruz-Benito, Borrás-Gené, García-Peñalvo, Fidalgo Blanco and Therón, 2015b).
There are three types of learning associated with the concept of lifelong learning (UNESCO,
1972). Their main differences (Eshach, 2007; Cruz-Benito et al., 2015b) relay on: 1.- where does
the learning take place, at school or outside (in the case of online learning, the platform becomes in
the school as the institutional place for learning), 2.- if the learning is structured or unstructured, 3.-
whether the learning is guided or not by the instructors, and 4.- if there is any validation or certification
(European centre for the development of vocational training (CEDEFOP, 2008).
According to these differences, the first and more institutionalized learning is the formal learning
that occurs in an organised and structured environment and leads to validation and certification
(CEDEFOP, 2008). The following types of learning take place in less organized spaces. At the other
extreme from the formal learning, there is a voluntary and unstructured learning named informal
learning, which arises from an intrinsic motivation (Csikszentmihalya & Hermanson, 1995) of the
student. In this type of learning, the student chooses the way to acquire the knowledge, the learning
is given everywhere and applies to any situations in common life (Eshach, 2007) and is not evaluated.
Finally, in a mid-way point, there is the non-formal learning, which is structured and guided by the
instructor, but is generally voluntary and is usually not evaluated.
This section presents the model and methodology that has been applied to the case of study for
this work: the “Application of social networking to education: virtual communities” MOOC course
(Borras-Gene, 2014) of the Technical University of Madrid (UPM) that had two editions (November
2013 and October 2014). The methodology of this course combines elements of gamification with
the cooperative model proposed by Fidalgo et al. (2013). It also shows how the data were extracted
for further analysis.
Organization
The course was established in the MOOC MiriadaX Platform (Miriada X, 2015) and was divided into
5 modules scheduled in 5 weeks with a time commitment of 4 hours per week. The course planning
is shown in Table 1.
The module 0 was a tutorial with information regarding the operation of the course. The other
modules contained the theoretical and technical part of the course. Module 1 presents the concept
of virtual learning communities within the social networks. The two next modules were devoted to
explain two of the most extended social networks (Facebook and Twitter). These modules are in turn
divided into two lessons where the first was based on the operation and configuration of the network
and the second in its application to education. The final module focused on the presentation of ten other
social networks and four auxiliary applications for managing social networks (monitoring, automation
and curation) in this case was not entered into as much detail as in the case of the above modules:
Volume 9 • Issue 3 • July-September 2016
22
Resources
The main resource of the course was the video-lecture, each module consisted of a series of topics,
devoting video by subject 75 videos with a mean duration of 5 minutes, not exceeding in any case
15 minutes. These resources were mostly videos that were uploaded before to the UPM Channel in
YouTube. For each topic there was a video embedded in a html page accompanied, in most cases, with
a completed and strengthened text content, such as definitions, links to examples used to bibliographies
or any web or application discussed. Specific examples of the given topics and exercises for the students
could be also found. Finally, there is a part of updating content once the course has begun applying
the “Cooperative Layer” (Fidalgo et al., 2013) of the model in which a feedback of the course is
produced. Throughout the course topics go editing as needed. But Miriada X have a strength policy
to close the edition of the course once it started and it was impossible to edit in real time. Therefore,
the contributions of the students were added to the next edition, once the current edition finished. A
supplementary material documentation was offered in text (pdf) to reinforce some issues. Activities
The course offers a number of voluntary activities of diverse nature to strengthen the assimilation
of concepts, generate content on the course and increase participation, involvement and interaction in
the community MOOC also associating a series of hashtags proposed by the teaching team to achieve
these objectives and classify the resources thus generated. The hashtags associated to the different
activities are presented in Table 2. Outcomes of the activities are always presented as publications
in the community.
Three types of activities were proposed throughout the course:
• Two videoconferences, with free Google tool “Hangouts” that allowed a live broadcast with the
possibility of intervention by more than one participant webcam and automatically upload to
UPM Youtube channel, in this case the teacher, any course participant who has the link can view
live or recorded videoconference after retransmission. All course students could participate by
presenting a proposal related to course topics in an event created in Google +. A maximum of 8
presentations allowed by hangout for what was required by the + 1s all members of the community
should vote the proposals for them more interesting. Most voted could live presentation for a
maximum of 10 minutes’ experience.
Table 1. Planning of the course
Module Duration Assessment
0 Introduction 1 week 1 Test
1 Virtual Communities
2 Twitter 1 week 1 Test
3 Facebook 1 week 1 Test
4 Other Social Networks 1 week 1 Test / 1 Peer-to-peer activity
Table 2. Special hashtags proposed for activities
Activity Hashtags
Hangout #ARSEHangout
Exercises
#ARSEMalasPracticas
#UsosTwitterEnseñanza
#ARSEEjemplosRRSS
Contest #IConcursoARSE
Volume 9 • Issue 3 • July-September 2016
23
• Exercises to develop concepts accompanying video-lectures.
• Instagram contest to deepen the study of the network and generate examples from the proposals
of the participants.
The assessment was carried out within the Miriada X platform by using mandatory “quizzes” for
self-evaluations, one per module, and “p2p” tool for peer review final activity. Problems arose in p2p
activities for technical side due to ignorance of the platform, many students did not know where to
deliver their activities; understanding of problems and heading for the assessment of other colleagues.
The adequate environment for the interactions in the collaborative activities between students and
the teaching staff was the use of a Virtual Learning Community. This environment becomes in the
place to raise questions and establish conversations about the course, substituting the typical existing
forum in other online courses (Cruz-Benito et al., 2015a; Cruz-Benito et al., 2015a).
The development of the virtual community was based on social networking. A previous study
among the major generalists social networks like Facebook, Twitter, Google + and LinkedIn was made.
The criteria taken into account to choice the most adequate social network in this study were:
• Number of users allowed.
• Existence of a mechanism to organize and find content within the community.
• Chance of isolate the student publications through URLs to reuse educational evidence as to
the course itself.
• Sense of community, a network that collects all publications generated in a common space.
• Advanced knowledge by the teacher network.
• Self-hierarchical level of all participants in the community, so that all publications have the same
relevance, whether teacher or student.
The chosen social network was Google + and its “community” tool in Google. Twitter was only
used in the first edition of the course due to the difficulties in managing two networks simultaneously
and some other problems associated with Twitter characteristics like the limitation in length
publications or the lack of sense of community that appears when a user could have in his/her time
line a mixture of tweets coming not only from members of the community.
Taking advantage of the features of Google + nine categories were created to classify all
publications: Member presentations, announcements, discussions, doubts, activities and exercises,
examples of application, interesting links, various and contests. All the outcomes of the activities
should always be presented as community posts.
This methodology allows the three types of learning that was described in the previous sections. First,
it can be found the formal learning, typical of MOOC courses that is institutionalized and structured
by the instructors through an eLearning Platform like MiriadaX. Inside the Google + Community,
the non-formal learning can be identified, which is led by instructors, voluntary and not evaluated.
The outcomes for this type of learning are publications, post, followings, hashtags and categories
proposed in the course. These outcomes reflect the exercises, debates and other activities suggested in
the course. Finally, the informal learning is associated to a voluntary activity of the course participants.
This activity doesn’t follow the structure or guidance of the instructors, takes place in the community
but with publications, hashtags or debates that are chosen and initiated by themselves.
Volume 9 • Issue 3 • July-September 2016
24
The latter type of learning (informal learning) continues in the community, not only during the
course, but it is still open and running in the community once the course finishes.
The relationship between the course elements, participants and instructors with the different
types of learning is presented in Figure 1.
Due to the impossibility to retrieve data from communities through API (Application Programming
Interface) of Google + was necessary to develop an application to know the interactions that occur
in the community. The course team developed GILCA (Google Analytics Informal Learning
Communities), a web application programmed in PHP to extract, from the Google + notifications sent
by email, information and new requests for access to community publications participants, comments
to the posts and hashtags used in a database (MySQL).
The GILCA application consists of two main elements:
• The “Harvester” collects data (participants, posts, comments and hashtags) and stores them in
the database. You need before launching the harvester export emails in txt format and copy them
to a folder for later data mining. This procedure should be done periodically.
• The “viewer” shows the information from the community, from the data stored in the database.
Allows different views: list of hashtags (sorted by number of occurrences or alphabetical) list
of users (sorted by number of publications or number of responses to their publications) and
aggregate information (number of new users, total number of publications, number of new
publications and number of responses) by course edition or in periods between editions.
Throughout the two course editions, an initial and end surveys were raised. It was attempted to
understand and characterize the participants and identify their evolution in learning and satisfaction
throughout the course. An adaptation of SEEQ (Student’s Evaluation of Educational Quality) validated
survey was used to obtain this information (Marsh, 1982).
The first survey was included in the zero module as a resource named “Welcome Survey” which
was completed, in the first edition, by a total of 3160 students, 77.4% of students who started, and in
Figure 1. Type of learning in the proposed model
Volume 9 • Issue 3 • July-September 2016
25
the second edition, by 4747 students, 68.3% of students who started the course. The purpose of this
survey was to understand the general characteristics of students, their background and objectives of
the course.
The second survey was included in the last module also as a resource, called “goodbye Survey”.
In the first edition, it was answered by 1228 students, representing 30% of students who started the
course. In the second edition, it was answered by 2143 students, representing 37.6% of students who
started. This survey sought the views of students about the quality of the course and methodology
conducted.
The course progress indicators and the social analysis of the tools employed in the MOOC are presented
in this section. These results were obtained from different sources: several surveys conducted during the
course and after its completion to fulfil the SEEQ (Student´s Evaluation of Educational Quality) and
the GILCA (Google Analytics Informal Learning Communities) application, specifically programmed
and developed for this course. These sources have been described in the previous section. The results
are presented in the same order in which the objectives were stated in the introduction. The scope of
these results will be also demonstrated.
The two editions of the “Application of social networking to education: virtual communities” course
(Borras-Gene, 2014) of the Technical University of Madrid had a combined total of 17721 students
enrolled. The course was started by 62.2% of them and ended by the 16,3% of the total students that
started the course. Table 3 shows the data disaggregated by each edition. The second edition of the
course achieved better data in all of the indicators.
The SEEQ results for the first edition stated that 50% of the students were women. Most of the
students (58%) were related to teaching activities. The students that had a job were 53% versus the
18% who studied or the 13% who were unemployed. Other remarkable results were that for 54%
of the students it was their first MOOC and that 59% of the students came from Spain and most of
the remaining participants came from Latin American Countries. In the second edition the results
for gender of the participants were practically the same, as is the employment status of these with a
45% working. Notable in this edition a considerable increase in the number of participants related to
teaching, with 69% of the total and an increase in the number of those who had participated before in
a MOOC course 61%. Finally, a slight increase in students from outside Spain these 48% is observed.
The Google + community are where both holistic and empirical knowledge generated during the
MOOC is organized. The data and indicator for the Google + community activity were collected
using the GILCA application. The first indicator of the success and sustainability of this community
is the level of activity in the community after the course ended. Note that no one has done the time
Table 3. Students participation in the course
Miriada X MOOC (Data)
Enrolled Starts 75% ended 100% ended
First edition 4872 4083 1315 819
Second edition 12849 6948 2779 977
Volume 9 • Issue 3 • July-September 2016
26
entertainer of the network; this is no longer free to use. During the 10 months that was between the
two editions of the course MOOC, the Google + social network, in which the learning community
is based, had 1498 new members and an average of 2.5 plus diary posts participation of members
sharing partners or other publications focusing (Figure 2). Their indicating satisfaction with “+1 s”
in more than 700 new publications. all these correspond to an informal community behavior, not
directed by the docents of the course. It is at this point that the community continues active, without
manages or energize by the teaching staff who only perform maintenance of the community is to
accept moderate members or, if necessary, any publication. Therefore, voluntarily from their members,
content and resources that provide great value to the community and its members are generated. This
community, therefore, turns sustainable over time and becomes independent of the course MOOC.
Comparing the evolution of participants in the two editions over time with the incorporation and
activity on Google + community (Table 4), it can be seen an increase of more than twice community
activity along the second edition the course. A 120% increase in new members and 71% more
publications in total (new and comments or replies). The increased activity in the community during
the second edition of the course is not only due to the greater number of participants, also participants
from the previous edition of the course even if not registered in the current edition have continued to
Figure 2. Evolution of new members over the two editions (top graph) and zooming new members between editions (bottom graph)
Volume 9 • Issue 3 • July-September 2016
27
participate in the community. The virtual community of the MOOC has not only stimulated social
interactions but may have contributed to achieve the learning objectives as is indicated by Shi, Al
Qudah and Cristea (2013).
Might expect that the total new members of the community outside the sum of members of
both communities and ascended to a total 3827 members, but the community is open and operates
autonomously. Thus, the community now has 5034 users and growing, with users of the two editions
of the course Miriada X and network users that join without enrolled in any course, just for interest
in the subject. In Figure 2 the addition of new members is shown. A total of 1498 users asked for
admission in the community between the two editions of the course. Currently once the second
edition followed up new users.
The sustainability of the community over time is closely linked to the perception of learning of
new users, especially those entering from the MOOC. Figure 3 shows the students’ incorporation to the
community throughout the course and the perception they get to work within it, both for satisfaction
and learning that can lead to an improved completion rates of course, to feel like a member of the
educational process, and a commitment to continue working in the community after the course finished.
The interaction between a user and a tool may become determinant and should be considered in the
process of forming an attitude toward technology use (Mao, 2014). This may be especially true when
research on learner attitudes and beliefs is expanded from learner traits and learning environment, to
the interaction between the learner and the environment (Wesely, 2012).
Throughout the second edition of the course, 1127 members have been involved in the community
of Google +, some of them also from the previous edition. Out of these group, 85 members have made
more than 5 publications. The current uses of virtual communities in a formal learning environment are
not only limited in the frequencies of use, but also in the shortage of meeting the students’ expectations.
The percentages of respondents in reporting their perception about learning and collaborative
activities in MOOC is shown in Table 5. In general, students showed very positive attitudes about the
use of social networks to foster collaboration between peers (86.4 –84% agreed or strongly agreed
in both edition). The majority of the participants felt that the course methodology has encouraged
collaboration (78.75% - 80.30% agreed or strongly agreed). Fewer participants, but still a majority
Table 4. General information about the community Google +
Google + community (Data)
New members New publications Replies Publications (total)
First edition 1181 1199 460 1659
Second edition 2646 2106 745 2851
Figure 3. Evolution of new members of the community MOOC (Second edition)
Volume 9 • Issue 3 • July-September 2016
28
of them (74.6% - 77.5% agreed or strongly agreed), showed a positive perception about the resources
provided cooperatively. These collaborative activities were considered useful for a better understanding
(86.4% – 85.1% agreed or strongly agreed) and for improving the contents of the course (86.48% -
83.7% agreed or strongly agreed).
Incorporation of collaborative and the use of social networks for such purpose are widely accepted
by the participants of the two editions of the course, as Table 5 shows. Educational uses of social
networks by participants on their own for learning purposes seem to be abundant but also incidental
and informal. Emotional comfort and the usability features of social media are the main motivators
for using social media in education (Mao, 2014) .
An improved understanding of students’ perspectives and new roles in participatory culture may
help improve the design of learning activities utilizing new technologies (Mao, 2014). Consequently,
Table 5. Percentages of participant responses regarding their perception about learning and collaborative activities in MOOC
Frequency (%)
Strongly
disagree Disagree Neither agree
nor disagree Agree Strongly agree
1ª
EDIT
2ª
EDIT
1ª
EDIT
2ª
EDIT
1ª
EDIT
2ª
EDIT
1ª
EDIT
2ª
EDIT
1ª
EDIT
2ª
EDIT
The course methodology
has encouraged
collaboration
0.65 0.70 3.50 2.70 17.10 16.30 39.01 37.80 39.74 42.50
The resources provided
cooperatively offer
different views from those
chosen by the teachers
1.38 1.30 2.93 2.40 21.09 18.60 36.48 38.10 38.11 39.60
The resources provided
cooperatively present
the progress and current
situation in the topics.
0.49 0.50 2.44 1.90 18.65 17.90 39.74 40.30 38.68 39.40
Students have been
encouraged to solve
questions from other
students in the course.
1.47 1.70 3.99 4.10 20.85 22.80 36.16 34.20 37.54 37.20
I have cooperated with
other students of the
course in the activities
proposed
13.27 19.70 13.52 14.70 25.41 27.00 25.73 20.60 22.07 18.00
The use of social
networks is interesting
to foster collaboration
between peers in this type
of course
0.73 1.10 1.14 1.60 11.73 13.40 28.66 31.50 57.74 52.50
Share resources and
interact through social
networks improves course
learning.
0.98 0.70 1.38 1.70 11.24 12.50 28.91 31.10 57.49 54.00
Share resources and
interact through social
networks improves the
initial contents of the
course.
0.73 0.70 0.98 1.60 11.81 14.00 32.41 32.20 54.07 51.50
Volume 9 • Issue 3 • July-September 2016
29
the knowledge of the MOOC users’ perception about motivation, utility and learning, is essential to
improve the deployment of MOOC courses. In addition, virtual community to be used as effective
learning tools and to adjust students’ prior affordances with these tools, complicated efforts in
designing, scaffolding, and interacting with participants during the process are necessary. Therefore,
it seems necessary to study how many publications are posted and the typology of these publications
to evaluate the learning process.
The community and the knowledge generated inside are closely linked to the publications and the
comments posted to the community as a result of the interaction between the members and the authors
of these publications. Students’ interactions in the community through comments allow the questions
of key issues of the area of study (Rennie & Morrison, 2013).
This Google + Community provides the tolos to address informal learning, clarifying concepts
or strengthening relationships with other members (Rennie & Morrison, 2013). Following Barron
this learning ecology or community is a ‘set of contexts found in physical or virtual spaces that
provide opportunities for learning’ (2006, pp. 195) and represent an improvement in learning (De
Vry & Watson, 2003).
Figure 4 shows the evolution overtime of the publications in the community. The number of
these publications, desaggregated by each edition, is presented in Table 4. These results also take
into account the comments associated to publications. The left graph shows the publications during
the two editions of the course. The right graph presents a zoom of the period of time between the two
editions. There is a constant activity of publications in the community, with a total of 739 publications.
These results confirm that this community is always generating contents and incorporating new
members, even in the period between editions
Baird and Fisher (2006) characterize the social learning environment as participatory and
interactive, where participants, students and teachers can easily, directly and openly interact with
each other, can share resources and communicate immediately and simultaneously. Thereby, the
Figure 4. Publications and comments during the course (top graph) and in the period between editions (bottom graph)
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student can rebuild and elaborate meaningful knowledge for him with the help of the human elements
of the environment. This study proves that the evolution of the community is closely linked to the
publications and comments posted. There isn´t a high ratio of passive participant, but the connection
of the participants to the course reinforces the community as an interaction and learning place.
The use of metadata, such as hashtags in the learning process provides greater interoperability
between different systems used to automate the process of knowledge creation and structure and unify
educational resources to finally share and reuse content created (Ghenname et al., 2013). Focusing on
the semantics of the publications, a study of the use of hashtags, key elements for the classification
of publications, has been carried out to the second edition of the course, given the large number of
publications, more illustrative than the first edition.
In the Google + Community, 1759 members have used 436 different hashtags in their publications.
The total number of hashtags used, including repeated, is 1676. Figure 5 shows the daily use of the
hashtag associated to post, during the second edition of the course. The average was the use of 33.2
hashtag per day.
There are two well differentiated areas in Figure 5. The first one matches the period of the two
first modules of the course (two weeks), in which most of the exercises were proposed, hence the high
number of hashtags. When analyzing the maximum values, corresponding 18, 24 and 28 October 2014,
it can be found that the most used hashtags were those referring to the first two modules, specifically
the first one: #RedesSociales, #Modulo1Arse, #ARSEMalasPracticas, #RRSS, #ARSEEjemplosRRSS
and #UsosTwitterEnseñanza.
The list of the most used hashtags is presented in Table 6. These hashtags are classified in those
proposed by the teaching staff during the course (non-formal learning) and those that have been
suggested by the students themselves (informal learning). Thus, based on the hashtags, two different
types of learning in virtual communities can be identified.
The collaborative tagging [O1] arises in the community, closely related to the Semantic Web, and
required to classify publications. Figure 6 shows the awareness of the community in using hashtags.
On one hand, 1336 of the 2851 publications had at least one hashtag, which mean that almost half
of the publications are classified. On the other hand, more than 200 members have written at least
one hashtag in these publications.
As a result of the collaborative tagging, there is a lack in the semantic use of tagging (García-Silva
& Szomszor, 2009). Users can write different tags to represent the same concept or may incorrectly
post a hashtag, either misspelling or just in a different word order. This is one of the main limitations
of hashtags because they are not produced automatically, but is the user who must write them. Table
7 shows the analysis of a hashtag which has several misspelled versions. These 32 incorrect hashtags
are information lost because they are not going to appear associated to the initial publications.
Figure 5. Hastags evolution over time
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Finally, and focused on the informal learning within the community, it is remarkable the
spontaneous publication (it wasn’t a proposal of the teaching staff) by the members of the community
of 56 activities with 72 comments, 221 +1’s and 21 reshares associated. This fact is another informal
learning characteristic that has been detected in the virtual community, and is joined together with
the point that students of other editions of the course still continue publishing contents linked with
the community, without any guidance, unless the own rules of the community.
This informal learning that occurs in the community allows members, therefore a space to display
the skills acquired after taking the course (García-Peñalvo, García-Holgado and Cruz-Benito, 2013).
The MOOC course “Application of social network to education: virtual communities” based on a
cooperative model has achieved high rates of completion betting on virtual communities through
social networks.
The aim of the course was to teach to create virtual learning communities and the course itself
has become a practical example.
The course has managed to attract around it a major learning community whose goal was to
stay alive beyond the course and has achieved, course participants still running and interacting with
them in the community.
Table 6. List of the most used hashtags
Number Hashtag Times Type of learning
0 arsemalaspracticas 288 non-formal
1 arseejemplosrrss 284 non-formal
2 arsehangout 81 non-formal
3 arsemooc 74 non-formal
4 usostwitterenseñanza 43 non-formal
5 españa 34 informal
6 redessociales 33 non-formal
7 debatesarse 33 non-formal
8 iconcursoarse 33 non-formal
9 dudasarse 31 non-formal
10 modulo1arse 29 non-formal
11 rrss 28 non-formal
12 pdapuj 26 informal
13 facebook 20 informal
14 mexico 20 informal
15 twitter 15 informal
16 arse 13 informal
17 educación 11 informal
18 colombia 10 informal
19 arsefacebook 10 informal
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Another key to the success of the community are the characteristics of the participants favored
that while different, given the course material, cooperation, as we are highly experienced teachers
but with little technical knowledge and experience related to social networks and on the other hand
young students involved teachers and very familiar with the world of social networking.
Even performing well as courses in this interaction, this aspect is still for improvement and
must find new ways to motivate students to participate in the learning community not only during
the course but also after this.
The proposed exercises of the MOOC course aim to generate a habit in using hashtag for
classification and also aim to promote involvement and interactions between members of the
community.
Figure 6. Relation between number of publications and hashtag/pub (top graph). Relation between users and number of hashtag
used/user (bottom graph)
Table 7. Example of misspelled hashtag
Correct Incorrect
#arseejemplosrrss
(284)
#arseeejemplosrrss (9) #arseejemplorrss (5) #arseeejemplorrss (4)
#arseejemplosrss (3) #arseejemplosrsss (3) #arsseejemplosrrss (3)
#arseejemplorrs (2) #arseejemplos (2) #arseejemplosrrssuna (1)
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There are limitations in the use of hashtags to classify contents due to the subjectivity of the
users when choosing the hashtags, and sometimes, when writing them. These limitations cause a loss
of information and a difficulty in post classification, although most publications are well classified.
A future research line is the improvement of the quality of contents classification. There are
two main actions to be done. First, the MOOC courses should be used to aware of the correct use of
hashtags and the effects that a misspelling can produce. It is also important to strength the digital
alphabetization of the students and the sense of belonging to the little educational environment that
takes places within the community. The second action is the development of reviewing and reporting
mechanisms of mislabeled publications that the members of the community could identify. The
identification of the most active members in the community and their designation as community
moderator (a new role in the community) would be an interesting issue to carry out this second action.
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Margarita Martinez-Nuñez is a Lecturer Professor in the Department of Business Organization, Management and
Statistics at the Technical University of Madrid (Spain). Her research interests are designed to promote knowledge
focusing on ICT and their role in improving communication and learning, technological innovation and competitive
advantage in organizations. She focuses her research on the conceptual change ICT has brought about in education,
particularly, in social networking and mobile device.
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Oriol Borras-Gene is a PhD candidate, telecommunications engineer and technician in e-learning in the Tele-
Education Cabinet (GATE) from Technical University of Madrid (Spain). His research lines are Social Networks,
e-Learning, Collaborative Learning and Gamification. He was collaboration at Resultados de la búsqueda Alexander
von Humboldt Institut für Internet und Gesellschaft (Berlin) and with Telefonica Digital Education.
Angel Fidalgo-Blanco has a PhD in Computer Science from the University of Las Palmas de Gran Canaria. He is a
professor at the Technical University of Madrid (UPM, Spain), director of the Laboratory for Innovation in Information
Technologies and member of the research group “Computer Science in Education and Knowledge Management”.
His main research lines are cooperative work, knowledge management and e-learning. Highlights of software
products include search engines on ontologies, which currently offers the official service at two universities and two
Spanish Government Ministries. He was founding partner of spin-off on software solutions and author of registered
software “CSORA: Search by Ontology” He has been the principal researcher of the project “Searcher of Educational
Innovation Good Practices” (funded by Spanish Government) and over 40 R+D+i projects. He is chairman and
member of various scientific committees of international conferences and publishes in different scientific journals.