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Visualizing Social Learning Ties
           by Type and Topic:
Rationale and Concept Demonstrator
Bieke Schreurs, Chris Teplovs, Rebecca Ferguson,
  Maarten de Laat and Simon Buckingham-Shum
Interdisciplinary Collaboration

                     Network Awareness Tool
Networked learning                                     Visualising Networks
of teachers in the                                     TEL
workplace based on
practice-based
research
                          Plugin for SocialLearn




                          (Social) Learning Anaytics
                           Online learning platforms
                                 SocialLearn
Theoretical Background


Social Learning Analytics are designed to
 support learning through social
 networks.
Theoretical Background
Motivated by Networked Learning Theory
drawing on the related concepts and tools of
  Social Network Analytics which provide
  complementary perspectives onto the
  structure of social networks
and Social Capital Theory, which provide
  complementary perspectives onto the
  content of such networks
Theoretical Background:
       Networked Learning


Networked Learning Theory tries to
   understand how people develop
   networks to support their learning.
Theoretical Background:
     Networked Learning

Networked learning focuses on the
 diversity of social relationships that
 people develop, the strategies they use
 to maintain them and the value this
 creates for learning.
Theoretical Background:
        Network Theory

Network Theory looks at the structure of
 networks, the interplay of the
 multiplexity and strength of ties within a
 network and the antecedents and
 consequences of the position of a
 person in a network
Theoretical Background:
         Social Capital

Social Capital Theory provides a lens to
 look more closely at the relational
 resources embedded in social ties and
 how actors interact to gain access to
 these resources
NAT Plugin for SocialLearn

The NAT plug-in for SocialLearn
 visualizes networks by identifying
 relationships between people who
 interact around the same learning
 topics.
NAT Plugin for SocialLearn
  Dealing with multiple levels at once

1. Theme’s – tag clouds – based on ‘sets’
   defined by content – overall online
   learning platform
2. Theme networks – visualization of the
   relation within a ‘set’ – ‘group’ level
3. Mutiplexity, strength and content of ties
4. Ego-networks – individual network
   relations per person
http://bit.ly/NAT-SocialLearn
Conclusion
• From an ego-perspective learners can see
  their own learning network to provoke
  learning-centric reflection by learners on how
  they use their peers for learning.
• Learners can use the plug-in as a (learning
  browser).
• Educators can use the plug-in to guide
  students in the development of networked
  learning competences and to gain insight into
  the ability of groups of students to learn
  collectively over time.
Conclusion
Educators can detect multiple (isolated)
  networks within the online learning
  environment, connect ideas and foster
  collaboration beyond existing boundaries.
For researchers, the analysis of learning ties
  and networks helps clarify how professionals
  engage in learning relationships, as well as
  the value of this engagement.
Future Research
• Learners perceptions of their learning networks, their
  (and mentors’) reactions to these visualizations.
• Multiplexity of ties
• Does the content of ties influence the structure of the
  learning network?
• Semantic Analysis on the tagcloud
• Dynamic analysis
• Do students find more peers to learn from using the
  NAT plug-in?
• Potential tool for conferences to find co-researchers
  to do interdisciplinary research?
More information?

Screencast of the NAT plugin in SocialLearn:
http://bit.ly/NAT-SocialLearn

The Network Awareness Tool:
Schreurs, B., & de Laat, M. (2012). Network Awareness Tool – Learning Analytics in the
       workplace: Detecting and Analyzing Informal Workplace Learning. Paper presented at
       LAK12: 2nd International Conference on Learning Analytics and Knowledge (30 April - 2
       May), Vancouver, Canada.


Email: bieke.schreurs@ou.nl

Special thanks to Prof. Simon Buckingham-Shum and Rebecca Ferguson from
          The Open University to make this internship possible through the
                                SocialLearn Project

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LAK13: Visualizing Social Learning Ties by Type and Topic: Rationale and Concept Demonstrator

  • 1. Visualizing Social Learning Ties by Type and Topic: Rationale and Concept Demonstrator Bieke Schreurs, Chris Teplovs, Rebecca Ferguson, Maarten de Laat and Simon Buckingham-Shum
  • 2. Interdisciplinary Collaboration Network Awareness Tool Networked learning Visualising Networks of teachers in the TEL workplace based on practice-based research Plugin for SocialLearn (Social) Learning Anaytics Online learning platforms SocialLearn
  • 3. Theoretical Background Social Learning Analytics are designed to support learning through social networks.
  • 4. Theoretical Background Motivated by Networked Learning Theory drawing on the related concepts and tools of Social Network Analytics which provide complementary perspectives onto the structure of social networks and Social Capital Theory, which provide complementary perspectives onto the content of such networks
  • 5. Theoretical Background: Networked Learning Networked Learning Theory tries to understand how people develop networks to support their learning.
  • 6. Theoretical Background: Networked Learning Networked learning focuses on the diversity of social relationships that people develop, the strategies they use to maintain them and the value this creates for learning.
  • 7. Theoretical Background: Network Theory Network Theory looks at the structure of networks, the interplay of the multiplexity and strength of ties within a network and the antecedents and consequences of the position of a person in a network
  • 8. Theoretical Background: Social Capital Social Capital Theory provides a lens to look more closely at the relational resources embedded in social ties and how actors interact to gain access to these resources
  • 9. NAT Plugin for SocialLearn The NAT plug-in for SocialLearn visualizes networks by identifying relationships between people who interact around the same learning topics.
  • 10. NAT Plugin for SocialLearn Dealing with multiple levels at once 1. Theme’s – tag clouds – based on ‘sets’ defined by content – overall online learning platform 2. Theme networks – visualization of the relation within a ‘set’ – ‘group’ level 3. Mutiplexity, strength and content of ties 4. Ego-networks – individual network relations per person
  • 12. Conclusion • From an ego-perspective learners can see their own learning network to provoke learning-centric reflection by learners on how they use their peers for learning. • Learners can use the plug-in as a (learning browser). • Educators can use the plug-in to guide students in the development of networked learning competences and to gain insight into the ability of groups of students to learn collectively over time.
  • 13. Conclusion Educators can detect multiple (isolated) networks within the online learning environment, connect ideas and foster collaboration beyond existing boundaries. For researchers, the analysis of learning ties and networks helps clarify how professionals engage in learning relationships, as well as the value of this engagement.
  • 14. Future Research • Learners perceptions of their learning networks, their (and mentors’) reactions to these visualizations. • Multiplexity of ties • Does the content of ties influence the structure of the learning network? • Semantic Analysis on the tagcloud • Dynamic analysis • Do students find more peers to learn from using the NAT plug-in? • Potential tool for conferences to find co-researchers to do interdisciplinary research?
  • 15. More information? Screencast of the NAT plugin in SocialLearn: http://bit.ly/NAT-SocialLearn The Network Awareness Tool: Schreurs, B., & de Laat, M. (2012). Network Awareness Tool – Learning Analytics in the workplace: Detecting and Analyzing Informal Workplace Learning. Paper presented at LAK12: 2nd International Conference on Learning Analytics and Knowledge (30 April - 2 May), Vancouver, Canada. Email: bieke.schreurs@ou.nl Special thanks to Prof. Simon Buckingham-Shum and Rebecca Ferguson from The Open University to make this internship possible through the SocialLearn Project