Beyond the backchannel: Leveraging Twitter to enact learning processes

Drew Paulin University of British Columbia @drewpaulin Caroline Haythornthwaite University of British Columbia @hthwaite Rafa Absar Clarkson University @RafaAbsar

Sarah Gilbert University of British Columbia @_sgilbert_ Anatoliy Gruzd Ryerson University @gruzd

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#pLASMA Project on Learning Analytics in the Social Media Age http://tiny.cc/SMLabPlasma

•  PIs: Anatoliy Gruzd & Caroline Haythornthwaite

•  Studying learning processes in social media.

•  Analysis of social media texts and networks.

•  Is social media beneficial to teaching and learning?

•  How do social media networks influence educational

models?

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pLASMA

Intro

SNA & Learning

Twitter & Learning

Twitter Tools

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Session 2 Preview

@drewpaulin @_sgilbert_ | #pLASMA #iconf15

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https://socialmediaandsociety.com/

CFP STILL OPEN – WIP AND POSTERS

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How do you think connections in the Twitter backchannel at conferences foster learning?

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pLASMA

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SNA & Learning

Twitter

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Twitter & Learning

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@drewpaulin @_sgilbert_ | #pLASMA #iconf15

Session plans Why Twitter and learning at conferences? What are we doing today?

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pLASMA

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SNA & Learning

Twitter

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Twitter & Learning

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@drewpaulin @_sgilbert_ | #pLASMA #iconf15

Learning and social networks How might learning happen in Twitter?

–  Social Learning (Bandura, 1977; 1986). Observing others’ behaviour, adopting/adapting.

–  Modelling (Haythornthwaite, Kazmer, Robins and Shoemaker, 2000). New learners look to more experienced learners to understand how to ‘be’ online in a learning context.

–  (…sort of a) Zone of Proximal Development (Vygotsky, 1978). Interacting with more knowledgeable others (MKOs).

–  Connectivism (Siemens, 2005). Access to good information sources, focus on connecting information together towards sensemaking.

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pLASMA

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SNA & Learning

Twitter

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Twitter & Learning

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@drewpaulin @_sgilbert_ | #pLASMA #iconf15

Social network analysis Centrality measures 1.  Betweenness:

•  how often a node falls along the shortest path between 2 other nodes.

•  high betweenness = information control

2.  Eigenvector: •  How well-connected/central a node is in terms of

the overall network

3.  Prestige: •  The number of ties a node has. •  In-degree – prestige & popularity •  Out-degree – influence & activity.

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Have you used Twitter in any formal or informal learning environments? If so, how?

Data collection for Twitter SNA / text analysis 1.  TAGS (Twitter Archiving Google Sheet – Martin Hawksey)

–  https://tags.hawksey.info/ –  Collect tweets to an archive using Google Sheets. –  Creates network sociograms (TAGSExplorer). –  Creates searchable archive interface (TAGS Archive).

2.  Netlytic (Anatoliy Gruzd) –  https://netlytic.org –  Web-based text and SN analysis tool suite. –  Datasets: Twitter, FB, Instagram, YouTube, Text, RSS, etc.

10 @drewpaulin @_sgilbert_ | #pLASMA #iconf15

pLASMA

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SNA & Learning

Twitter

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Useful Twitter tools – getting started  

Most twitter activity is live-tweeting summaries, but… •  #ICYMI - (in case you missed it)

sharing relevant resources/examples. •  #WDYT – (what do you think?)

posing questions, generating discussions/collaboration.

Examples: •  #LAK14 – creating a dataset, collaboration. •  #hcsmca – question driven discussion.

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pLASMA

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Practical applications of Twitter for learning: Beyond the backchannel  

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Roles Count

SM health content providers 110 Unaffiliated individual users 89 Communicators - not specifically health related 74

Communicators - Health related 59 Healthcare professionals 50 Health institutions 31 Advocacy 30 Students 16 Educators, professors 13 Researchers 10 Government and health policy makers 4

#hcsmca  

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#hcsmca  

Say hello to your tablemates! 1.  What are your names? Where are you from? Why are

you at iConference 2015?

2.  Do you follow conference hashtags when you are not attending a conference?

3.  What was the most interesting hashtag you’ve followed recently? Why?

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Group activity  

What does this cMOOC Twitter SN diagram tell us about class participation?

15 #CCK11  Class  Tweets  (Node  size=“Outdegree”)  

What does this visualization NOT tell us? What other info is needed to make sense of it?

16 #CCK11  Class  Tweets  (Node  size=“Outdegree”)  

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pLASMA

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#iconf15 #pLASMA #  

How can we leverage Twitter to facilitate learning?

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Summary

What resonated most in your group discussions? What are you interested in exploring further?

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Next session (Thursday @ 4pm) Our plans 1.  Previous work – Conference Twitter network

research •  #LAK14 •  #Congress2013

2.  Conference tweeter roles

3.  Explore #iconf15 Twitter networks