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

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  • 1. Visualizing Social Learning Ties by Type and Topic:Rationale and Concept DemonstratorBieke Schreurs, Chris Teplovs, Rebecca Ferguson, Maarten de Laat and Simon Buckingham-Shum
  • 2. Interdisciplinary Collaboration Network Awareness ToolNetworked learning Visualising Networksof teachers in the TELworkplace based onpractice-basedresearch Plugin for SocialLearn (Social) Learning Anaytics Online learning platforms SocialLearn
  • 3. Theoretical BackgroundSocial Learning Analytics are designed to support learning through social networks.
  • 4. Theoretical BackgroundMotivated by Networked Learning Theorydrawing on the related concepts and tools of Social Network Analytics which provide complementary perspectives onto the structure of social networksand Social Capital Theory, which provide complementary perspectives onto the content of such networks
  • 5. Theoretical Background: Networked LearningNetworked Learning Theory tries to understand how people develop networks to support their learning.
  • 6. Theoretical Background: Networked LearningNetworked 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 TheoryNetwork 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 CapitalSocial 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 SocialLearnThe 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 once1. Theme’s – tag clouds – based on ‘sets’ defined by content – overall online learning platform2. Theme networks – visualization of the relation within a ‘set’ – ‘group’ level3. Mutiplexity, strength and content of ties4. Ego-networks – individual network relations per person
  • 11. http://bit.ly/NAT-SocialLearn
  • 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. ConclusionEducators 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-SocialLearnThe 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.nlSpecial 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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