SOCIAL MECHANISMS TO MOTIVATE LEARNING
WITH REMOTE EXPERIMENTS
Design Choices to Foster Online Peer-based Learning
Thieme Hennis and Heide Lukosch
Delft University of Technology, Delft, The Netherlands
Keywords: Remote experiments, Motivation, Reputation, Trust, Social learning.
Abstract: If we consider knowledge to be the result of a negotiation process about references and meaning between
individuals, then, we should consider it also a collective or social property. This view underlies numerous
initiatives worldwide providing unrestricted online access to educational content, software tools, and
implementation resources, commonly referred to as Open Educational Resources (OER). In earlier research
on the use of Open Educational Resources at the TU Delft, we addressed the issue of sustainability of OER
projects in terms of organization, motivation, types of resources, types of reuse, and funding and revenue
models. In this paper, we focus on how social mechanisms can contribute to increase motivation amongst
stakeholders to maintain and create useful content, and engage in meaningful interactions within learning
communities.
1 INTRODUCTION
The UN Declaration of Human Rights declares
universal access to education (United Nations
General Assembly 1948). Publishing educational
resources on the Web increases access to learning
materials to those that have Internet access. Still, the
provision of educational resources is not the same as
education. Education is more than a Powerpoint
presentation, syllabus, or reading list. It includes
structured guidance and feedback, mentoring,
assessment, building relationships, and in most cases
accreditation. There is a gap between this
conceptualization of education and the current OER-
projects where courseware is shared online for free.
Lately, we have seen initiatives that add
pedagogical support and tools to support interaction
and communication between peers about content
(Downes 2008). Social software is used to move
online learning from consumption of information to
co-creation, peer-production, and communication
about learning resources. Examples, including
commercial ones, are Learnhub, NIXTY, P2PU
(Peer-to-Peer University), WatchKnow, and Curriki.
In 2008, an EU-initiative called LiLa started.
“LiLa” is the acronym for the “Library of Labs”, an
initiative of eight universities and three enterprises,
for the mutual exchange of and access to virtual
laboratories (simulation environments) and remote
experiments (real laboratories which are remotely
controlled via the internet). LiLa builds a portal,
which grants the access to virtual labs and remote
experiments. It includes services like a
scheduling
system, connection to library resources, a tutoring
system, and an authoring tool. Moreover, LiLa
creates an organizational framework for the
exchange of experiments between institutions and
for the access to experimental setups. Supporting
this, Lila provides contract templates for institutions
and didactical help for lecturers for the integration of
remote and virtual experiments into curricula.
Primary target groups of LiLa are university teachers
and their students in undergraduate and graduate
classes of the natural sciences and engineering. In
this paper, we will highlight the design choices of
LiLa from the perspective of motivating meaningful
interactions and learning with LiLa.
2 LEARNING IN ONLINE
ENVIRONMENTS
In community-oriented learning environments,
learning relies on voluntary participation of
183
Hennis T. and Lukosch H..
SOCIAL MECHANISMS TO MOTIVATE LEARNING WITH REMOTE EXPERIMENTS - Design Choices to Foster Online Peer-based Learning.
DOI: 10.5220/0003307301830188
In Proceedings of the 3rd International Conference on Computer Supported Education (CSEDU-2011), pages 183-188
ISBN: 978-989-8425-50-8
Copyright
c
 2011 SCITEPRESS (Science and Technology Publications, Lda.)

members of the environment. In these environments,
peer-support and guidance should be supported and
encouraged. Through social software, intuitive
design, and intelligent support, learning from remote
experiments and virtual laboratories can (and
should) happen between students online. What we
give here is a framework that describes how social
mechanisms influence the behaviour of students and
teachers who are using and contributing to LiLa.
According to constructivist learning theories,
humans construct knowledge and meaning from
experience (Vygotsky & Cole 1978; Bruner 1991;
Piaget & Cook 1952). Personal development and
deep understanding happens through the
construction of meaning by the learner self, not
through transmission from one person (the teacher)
to another (the learner). The fundamental principle
of constructivism is that learners actively construct
knowledge through interactions with their
environment (Hout-Wolters et al. 2000; Rieber
1996).
The central point of social-constructivism is an
individual's making meaning of knowledge within a
social context (Vygotsky & Cole 1978). Learning as
a social practice is well established and dialogue is
one of the corner stones of social constructivism.
This makes online communities such potentially
effective places for learning, because it allows for
both synchronous and asynchronous interactions
through a number of modalities. The drawback is
that the online environment is not similar to face-to-
face environments in terms of trust and interaction.
Interactions in online communities are maintained
through a sense of community and social capital
through information flow, altruism, reciprocity,
collective action, identities, and solidarity (McLure-
Wasko & Faraj 2005; Kollock 1999; Bouman et al.
2007; Ackerman et al. 2004). These are central
elements that need attention in an online social
learning context. Social mechanisms that address
internal cohesion and sense of community are
important for learning and overall sustainability of a
social learning environment, and so are mechanisms
that impact interaction with the external
environment (Hennis & Kolfschoten 2010),
including reputation and recognition.
Furthermore, learning is situated, which means
that it is located in the process of co-participation
and in the field of social interaction, not in the head
of individuals to get an inter-subjective
understanding and meaning of something (Lave &
Wenger 1991). In
communities, learning means
moving from the peripheral (lurking, being
introduced into processes, people, etc) into the
center (sharing expertise, making decisions).
Peripheral participants do not
accumulate
knowledge and skills but are introduced in
processes, routines, networks, relevant issues, and
approaches within the community (Allert 2004).
Learning as knowledge creation is seen as
analogous to processes of inquiry, especially to
innovative processes of inquiry where something
new is created and the initial knowledge is either
substantially enriched or significantly transformed
during the process (Paavola et al. 2004). Hence,
learning goes beyond the information given and
engages the learner to participate and contribute.
This type of learning comprises of open, ill-
structured problem solving processes, focuses on
communication and collaboration. Stahl emphasizes
that meaning is collaboratively produced in a
cultural context, embodied in a physical or semantic
artefact, and is situationally interpreted within a
community or social system (Stahl 2003). Meaning
is not transferred from one thinker to another, but is
constructed.
New developments in the science of learning
also emphasize the importance of helping people
take control of their own learning. Since
understanding is viewed as important, people must
learn to recognize when they understand and when
they need more information. Effective learning
environments therefore focus on sense-making, self-
assessment, and reflection on what worked and what
needs improving (Stahl 2003; Paris & Winograd
2003; Stahl et al. 1999; Siemens 2005).
We understand learning as a lifelong, self-
directed and collaborative effort, in which one
engages with people and finds resources online.
Educational technology and institutions should focus
on supporting this process, and guide students in
assessing and evaluating knowledge they encounter
online. Rather than individual learning based on
competition and hierarchy, a more networked model
of learning is preferred, because it allows learning
from peers, and stimulates cooperation, partnering,
and mediation (Davidson & Goldberg 2009). The
ingredients of the Networked Learning model are
four complementary areas that play an important
role in knowledge development (Veen et al. 2008).
Each of the elements that are connected to these
areas is relevant for this development process in
which the technology is a major facilitator for
processes of communication, information retrieval
and information sharing. These areas are: Profiling,
Connectedness, Knowledge and Business
Development. Networked learning focuses on
interconnectedness between people and between
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184

people and resources (Veldhuis-Diermanse et al.
2006; Laat & Lally 2003; Vries 2008; Laat 2006).
Technology is used to integrate delivery of
knowledge with interaction, communication and
application (Jones & Steeples 2001). The earlier
mentioned concept of Communities of Practice
(Wenger 2000) is integrated in Networked Learning,
because learning practices and social practices are
interconnected, the learning practices emerge from
participants rather than be imposed by facilitators,
learners are involved in concrete practical actions
together, learning is not designed, rather designed
for, variation in levels of expertise can expand the
group’s learning, networked learning needs to
support visits to “otherness” (Paavola et al. 2004).
The above describes adequately the learning
philosophy and design approach for In the
following, we describe social mechanisms that can
be addressed in order to increase motivation to
participate in Open Educational Resources (OER)
projects like LiLa.
3 SOCIAL MECHANISMS OF
THE LILA PORTAL TO
FOSTER MOTIVATION
We have applied this framework into the design of
processes and technology of the EU-funded project
called LiLa, Library of Labs. The portal
disseminates and aggregates remote experiments,
learning resources (including assignments), and
lessons. A lesson is a set of learning activities that
contain LiLa content, such as experiments and
learning resources.
One of the most important things in the design of
an online community is its alignment with the
interests of the intended participants, and the
collective characteristics of the community (Preece
& Maloney-Krichmar 2003; Preece & Maloney-
Krichmar 2005). A person only contributes when
this effort helps to satisfy a need (i.e. psychological
needs) (Kollock 1999). If a person perceives as if a
technology brings personal benefit, participation will
be more likely (Pearson 2007; Rashid et al. 2006;
Garfield 2006). It is therefore required to know the
problems and objectives of (future) users. When
potential users and contributors can relate this to
their own needs, there is higher probability of
participation (Preece & Maloney-Krichmar 2003).
The primary audience of LiLa consists of university
teachers and students. In an internal review of
pedagogical scenarios amongst 5 European
universities, we identified different scenarios
regarding the use of experiments. The use of
experiments in education ranges from teacher-
centered education to student-led education. A
whole range of learning scenarios can be thought of
within the two ends of the spectrum. The strategy we
chose to accommodate the different learning
scenarios is by offering tools that support both
teacher- and student-led learning, like SCORM
compliancy and peer assessment. Next to
“consumers” of LiLa content, we have the content
providers, who are the institutes and individual
experiment owners (teachers etc.) who potentially
want to share their remote experiments online. The
same motivations for people to share OER (Hylén
2006) seem to apply to remote experiments.
Leaders in online communities can be important
for the success of the community. In addition,
leadership is an enabler for knowledge sharing
(Ardichvili 2008). Leaders support and engage
people, form connections, discuss strategies, choose
content and technology, and show exemplary
behaviour (Koh et al. 2007; Wenger et al. 2002).
LiLa members have a personal page where they can
add their field of expertise. In addition, users can
indicate their role as a student or teacher. This
information is used to tweak the portal’s interface
based on the role of a user.
With regards to organization, sustainable online
communities should offer services along four
dimensions: self-management (facilitation of
creation and management of presence and
resources), self-organization (facilitate interaction
and knowledge construction), self-categorization
(support classification and evaluation of
contributions), and self-regulation (offer tools to
manage privacy and spam) (Berlanga et al. 2009).
For reasons of sustainability, the design of LiLa
focuses on the decentralization of adding, managing,
and learning from LiLa content.
Uniqueness and social comparison can
encourage participation and sharing of information
(Ludford et al. 2004; Chen et al. 2009). Generally
speaking, heterogeneity is an important factor for
knowledge creation in online communities. In order
to bring together different perspectives, there has to
be an open dialogue, and different levels of
participation must be accepted. Large and small
contributions (such as comments) are needed to
sustain and create new interaction. Because true
membership grows over time and with interactions,
passive members may over time become active and
engaged (Berlanga et al. 2009; Wenger et al. 2002).
It also means that different people must be addressed
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185

in different ways (Kollock 1999). The LiLa portal
allows to design collaborative assignments that
require input from different disciplines. Also,
heterogeneity is accommodated in the metadata,
which allows for translation of content.
We mentioned relevancy as requirements for an
online community to become successful. One
important incentive for people to join and participate
in learning communities, is of course, their ability to
help you learn something (Bouman et al. 2007).
Learning can relate with heterogeneity in expertise,
support for questions, and getting useful
recommendations (automatic and social). Another
essential motivation for people to join online
communities is networking. Networking leads to
new trust relationships and collaboration. It is
especially effective when online and offline
interactions reinforce each other (Koh et al. 2007;
Wenger et al. 2002). Relationships are established
through social presence, empathy, and trust, possibly
by means of community managers or moderators
(Preece & Maloney-Krichmar 2003). Learning is the
core of LiLa. To support online learning, we have
developed a number of tools, including
recommending technologies, rating and peer-support
through forums and a specialized tutoring system to
support learners during learning activities. Also,
automatic emails are sent that contain interesting
contributions and comments on content one follows.
Students and teachers will only keep on visiting
LiLa, if they benefit from it. The benefits may relate
with learning, but an important incentive for OER
providers is also the ability to connect with peers
and get feedback. Online, you are able to follow
persons, so if someone you find interesting adds a
new resource, you will be notified. Offline, we
organize several meetings and visit conferences to
increase and improve the LiLa network.
Reputation relates to the concept of online
identity and trust and is a primary research focus in
Web science. Overview of past actions and
participant identification helps to create and sustain
trust relationships in communities (Moore & Serva
2007). Trust forms the basis of a relationship and is
one of the most important enablers of community
participation (Ardichvili 2008) and sharing
knowledge (Lee 2008). Reputation is used as virtual
currency (World of Warcraft), can be a conduit for
trust (eBay), and the information stored in reputation
profiles is used for recommendations of people and
content. Howard Rheingold describes status,
recognition or prestige as a key motivation of
individuals' contributions to the group (Rheingold
1993). This is especially true in knowledge-sharing
communities, and forms an important motivation for
people to contribute (Lampel & Bhalla 2007;
Pearson 2007). Recognition satisfies a person’s need
for self-esteem, as depicted in Maslow’s hierarchy
of needs (Kollock 1999). People tend to contribute
knowledge when it enhances their professional
reputations (McLure-Wasko et al. 2009; McLure-
Wasko & Faraj 2005). Increased recognition also
supports identity building and belonging (Bouman et
al. 2007). Visibility of contributions is similarly
important: if people see their contributions being
used and re-shared, they are more inclined to share
more information, especially when there is some
recognition or praise or encouragement (Endres et
al. 2007). We suggested a reputation architecture
that motivates individuals to be engaged in processes
that ultimately contribute to the sustainability of the
portal. For LiLa, we argue that these include
organizational processes of quality management,
contribution and aggregation of content, creation of
knowledge, and managing discussions. Also, helping
out people with questions and providing feedback on
requests are attributed. The reputation architecture
monitors the interactions and contributions, and
creates human readable profiles of someone’s online
activity on the portal. The interpretation of this
activity can be done by teachers, students, or others,
and will depend on the objectives for interpretation.
In addition to reputation, there is reciprocity, the
social norm that describes the expectation of people
to respond to each other in kind, both in a positive
and negative sense. People expect something to get
in return from others. Even though reciprocity is not
always an essential element (McLure-Wasko &
Faraj 2005b), many online communities and social
network sites encourage reciprocity with rewards
and acknowledge helpful responses (Preece &
Maloney-Krichmar 2003). We have suggested a
feedback tool for teachers to share their experiences
on experiments and pedagogy. Students can ask
questions and engage in discussions about
theoretical or practical issues. Registered LiLa
members are notified of changes and new
discussions, responses, and added content. If
someone posts a question, he or she expects to get a
response in time. Hence, each person has a personal
Watchlist, and is notified through e-mail with a
weekly digest of what happened on LiLa.
In many online communities, most activity
comes from of a small core group of experienced
people. It can be difficult for newcomers to
participate and to have enough confidence to
contribute (self-efficacy, see next paragraph).
Newcomers, therefore, should be treated carefully
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and given considerable attention. When people
signup, in LiLa we ask for some information,
including background and affiliation. Using the
affiliation of a person, we can connect newcomers
with active members and other newcomers, making
newcomers more comfortable.
The perception people have about themselves
and their ability to perform a specific task is called
self-efficacy. Self-efficacy is the central cognitive
mediator of the motivational process (Bandura
1997). In other words, if a person does not have a
positive perception about his or her ability to do or
contribute something, the (s)he will not do it. This
also applies to knowledge sharing (Endres et al.
2007). LiLa members must be able to contribute in
small, easy steps. For example, adding a comment is
very easy, and can give someone the confidence of
starting a discussion, or reviewing a solution.
Additionally, users can simply indicate that they find
a resource, comment or experiment useful. When
people get positive feedback, and are recognized for
their contributions, they are more likely to
contribute.
4 CONCLUSIONS
In this paper, we elaborate on our design of the
Library of Labs (LiLa) using a number of social
mechanisms, defined in an earlier study as to support
motivation of individuals in online knowledge
environments. The framework supports designing
for motivation by focusing on social and
psychological factors that influence the way people
behave and share information online.
In projects where Open Educational Resources
must continuously be contributed, created, updated,
managed, reliance on a central authority is costly
and sometimes not feasible. We linked this problem
with current approaches on learning, which address
a more active, creative, and conversational way of
learning. In addition to support for individuals to
connect, discuss, assess and create learning
materials, an OER project must also address their
motivation to communicate, collaborate and learn.
With social mechanisms, we can look for solutions
and support our design choices.
In our further research on LiLa, we are going to
focus on evaluating and merging individual social
mechanisms. Evaluating the use of the portal and the
behavior of the users will become a crucial part of
the online environment itself and thus an additional
functionality to foster motivation with providing
feedback to the users.
REFERENCES
Ackerman, M. et al., 2004. Communities and
Technologies: An Approach to Foster Social Capital?
Practice, 406-408.
Allert, H., 2004. Coherent Social Systems for Learning:
An Approach for Contextualized and Community
Centred Metadata. Journal of Interactive Media in
Education, 2004, 1-30.
Ardichvili, A., 2008. Learning and Knowledge Sharing in
Virtual Communities of Practice: Motivators, Barriers,
and Enablers. Advances in Developing Human
Resources, 10(4), 541-554.
Berlanga, A. et al., 2009. Guidelines to Foster Interaction
in Online Communities. In R. Koper Learning
Network Services for Professional Development.
Berlin, Heidelberg: Springer, pp. 27-42.
Bouman, W. et al., 2007. The realm of sociality: notes on
the design of social software, Amsterdam.
Bruner, J., 1991. The narrative construction of reality.
Critical inquiry, 18(1), 1–21.
Chen, Y. et al., 2009. Social Comparisons and
Contributions to Online Communities: A Field
Experiment on MovieLens. American Economic
Review, 1-51.
Davidson, C. & Goldberg, D., 2009. The future of learning
institutions in a digital age. The MIT Press, 81.
Downes, S., 2008. Places to Go : Connectivism &
Connective Knowledge. Innovate, 5(1), 6.
Endres, M. et al., 2007. Tacit knowledge sharing, self-
efficacy theory, and application to the Open Source
Community. Journal of Knowledge Management,
11(3), 92-103.
Garfield, S., 2006. Ten reasons why people don't share
their knowledge. KM Review, 9(2), 10-11.
Hennis, T.A. & Kolfschoten, G.L., 2010. Understanding
Social Mechanisms in Online Communities. In Group
Decision and Negotiation 2010. Delft.
Hennis, T. A., 2009. Platform voor promovendi - Lessons
learned leidt tot achtstappenplan. Intellektueel
Kapitaal, (4), 36-40.
Hennis, T. A., 2009. Platform voor promovendi -
Valkuilen op de werkplaats. Intellektueel Kapitaal,
(3), 40-42.
Hout-Wolters, B. V., Simons, R. & Volet, S., 2000. Active
Learning: Self-directed learning and independent
work. In R. Simons Springer. Kluwer Academic
Publishers, pp. 21-36.
Hylén, J., 2006. Open educational resources:
Opportunities and challenges. Open Education, 11.
Jones, C. & Steeples, C., 2001. Perspectives and issues in
networked learning. In Networked learning. Springer-
Verlag New York, Inc., p. 14.
Koh, J. et al., 2007. Encouraging participation in virtual
communities. Communications of the ACM, 50(2), 68-
73.
Kollock, P., 1999. The Economies of Online Cooperation:
Gifts and Public Goods in Cyberspace. In M. Smith &
P. Kollock Communities in cyberspace.
Laat, M. D. & Lally, V. I., 2003. Complexity, theory and
SOCIAL MECHANISMS TO MOTIVATE LEARNING WITH REMOTE EXPERIMENTS - Design Choices to Foster
Online Peer-based Learning
187

praxis: Researching collaborative learning and
tutoring processes in a networked learning
community. , 7-39.
Laat, M. D., 2006. Networked Learning. , 7-9.
Lampel, J. & Bhalla, A., 2007. The Role of Status Seeking
in Online Communities: Giving the Gift of
Experience. Journal of Computer-Mediated
Communication, 12(2), article 5.
Lave, J. & Wenger, E., 1991. Situated learning: Legitimate
peripheral participation, Cambridge Univ Pr.
Lee, H., 2008. The effects of socio-technical enablers on
knowledge sharing: an exploratory examination.
Journal of Information Science, 34(5), 742-754.
Ludford, P. J. et al., 2004. Think different: increasing
online community participation using uniqueness and
group dissimilarity. In Proceedings of the SIGCHI
conference on Human Factors in computing systems.
New York: ACM, pp. 631-638.
McLure-Wasko, M. & Faraj, S., 2005. Why should I
share? Examining social capital and knowledge
contribution in electronic networks of practice. MIS
Quarterly, 29(1), 35-57.
McLure-Wasko, M., Teigland, R. & Faraj, S., 2009. The
provision of online public goods: Examining social
structure in an electronic network of practice. Decision
Support Systems, 47, 254-265.
McMillan, D. & Chavis, D., 1986. Sense of community: A
definition and theory. Journal of Community
Psychology, 14(1), 6-23.
Moore, T. D. & Serva, M. A., 2007. Understanding
Member Motivation for Contributing to Different
Types of Virtual Communities: A Proposed
Framework. In SIGMIS-CPR '07: Proceedings of the
2007 ACM SIGMIS CPR conference on 2007
computer personnel doctoral consortium and research
conference. New York: ACM, pp. 153-158.
Paavola, S., Lipponen, L. & Hakkarainen, K., 2004.
Models of Innovative Knowledge Communities and
Three Metaphors of Learning. Review of Educational
Research, 74(4), 557-576.
Paris, S. & Winograd, P., 2003. The role of self-regulated
learning in contextual teaching: Principles and
practices for teacher preparation. Preparing Teachers
to Use Contextual Teaching and Learning Strategies
to Improve Student Success in and beyond School.
Pearson, E., 2007. Digital gifts: Participation and gift
exchange in Livejournal communities. First Monday,
12(5).
Piaget, J. & Cook, M., 1952. The origins of intelligence in
children, International Universities Press New York.
Preece, J. & Maloney-Krichmar, D., 2005. Online
communities: Design, theory, and practice. Journal of
Computer-Mediated Communication, 10(4).
Preece, J. & Maloney-Krichmar, D., 2003. Online
communities: focusing on sociability and usability. In
J. Jacko & A. Sears Handbook of human-computer
interaction. Mahwah, New Jersey: Lawrence Erlbaum
Associates Inc. Publishers, p. 596–620.
Rashid, A. M. et al., 2006. Motivating participation by
displaying the value of contribution. In Proceedings of
the SIGCHI conference on Human Factors in
computing systems - CHI '06. New York, New York,
USA: ACM Press, p. 955.
Rheingold, H. L., 1993. Virtual Communities and the
WELL. GNN Magazine, (1).
Rieber, L., 1996. Seriously considering play: Designing
interactive learning environments based on the
blending of microworlds, simulations, and games.
Educational technology research and development,
44(2), 43–58.
Siemens, G., 2005. Connectivism - A learning theory for
the digital age. International Journal of Instructional
Technology and Distance Learning, 2(1), 3–10.
Stahl, G., Koschmann, T. & Suthers, D., 1999. Computer-
supported collaborative learning: An historical
perspective. In S. Sawyer Cambridge handbook of the
learning sciences. Cambridge, UK: Cambridge
University Press.
Stahl, G., 2003. Meaning and interpretation in
collaboration. In B. Wasson, S. Ludvigsen, & U.
Hoppe Designing for Change in Networked Learning
Environments: Proceedings of CSCL ‘03. Bergen:
Kluwer Academic Publishers, pp. 523-532.
United Nations General Assembly, 1948. Universal
Declaration of Human Rights. Wikipedia.
Veen, W., Lukosch, H. & Vries, P. D., 2008. Improving
organizational learning through Networked Learning.
In GI2008. pp. 22-31.
Veldhuis-Diermanse, A. E. et al., 2006. Analysing
Learning Processes and Quality of Knowledge
Construction in Networked Learning. The Journal of
Agricultural Education and Extension, 12(1), 41-57.
Vries, P.D., 2008. Networked Learning for Lifelong
Learners. Journal of documentation, (September), 26.
Vygotsky, L. & Cole, M., 1978. Mind in society: The
development of higher psychological processes,
Wenger, E., McDermott, R. & Snyder, W., 2002.
Cultivating communities of practice: A guide to
managing knowledge, Boston, MA: HBS Press.
Wenger, E., 2000. Communities of practice and social
learning systems. Organization, 7(2), 225-246.
CSEDU 2011 - 3rd International Conference on Computer Supported Education
188