Visualizing Social Learning Ties

by Type and Topic:

Rationale and Concept DemonstratorBieke Schreurs, Chris Teplovs, Rebecca Ferguson,

Maarten de Laat and Simon Buckingham-Shum

Interdisciplinary Collaboration

(Social) Learning Anaytics

Online learning platforms SocialLearn

Networked learning of teachers in the workplace based onpractice-based

research

Visualising NetworksTEL

Network Awareness Tool

Plugin for 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