Your SlideShare is downloading. ×
Introducing #pLASMA: project on Learning Analytics in the Social Media Age
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Introducing #pLASMA: project on Learning Analytics in the Social Media Age

1,577

Published on

Presentation at LAK14

Presentation at LAK14

Published in: Education
0 Comments
4 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
1,577
On Slideshare
0
From Embeds
0
Number of Embeds
7
Actions
Shares
0
Downloads
0
Comments
0
Likes
4
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Caroline Haythornthwaite @hthwaite Rafa Absar @rafaabsar Drew Paulin @drewpaulin Anatoliy Gruzd @gruzd project on Learning Analytics in the Social Media Age #pLASMA
  • 2. #pLASMA 2 ¡  Social Science and Humanities Research Grant (SSHRC) ¡  Research Team: ¡  Anatoliy Gruzd & Caroline Haythornthwaite (PIs) ¡  Drew Paulin, Rafa Absar, Mick Huggett, George Siemens ¡  Primary purpose: ¡  To determine and evaluate measures that can help educators manage their use of social media for teaching and learning through the use of automated analysis of social media texts and networks Project on Learning Analytics in the Social Media Age (#pLASMA)
  • 3. #pLASMA 3 Project on Learning Analytics in the Social Media Age (#pLASMA) ¡  Examine facets such as ¡  common patterns of exchange ¡  development of shared language and understanding ¡  emergence of roles and positions ¡  Primary approach ¡  Automated analysis of social media texts and networks ¡  Who talks to whom about what and via which (social) media? ¡  Research goal is to discover ¡  What forms of social connection – conversational structures of communication between people in a network – reveal learning, learning practices, learning roles, etc.
  • 4. Outline #pLASMA 4 •  Background / Social Network Perspective (Caroline) •  #hcsmca Case Study – a Twitter Community (Caroline) •  #pLASMA Survey (Drew) •  #pLASMA MOOCs Data (Rafa) •  Network Visualizations & Netlytic.org (Anatoliy) •  Interactive Exercise: Collaborative Analysis of a MOOC Network Visualization (Anatoliy & Caroline) •  Tweet using #LAK14 #pLASMA
  • 5. Background Questions about Online Interaction ¡  How do people work, learn and socialize together at a distance and through computer media? ¡  How do social network patterns of interaction support information and knowledge sharing? ¡  What relations and network dynamics create outcomes perceived by individuals as ‘belonging to a community’? ¡  What relations and dynamics create networks that persist regardless of individual membership? ¡  Can we see evidence of learning happening online through analysis of online conversation? Computer Mediated Communication Social Networks + Computer Networks Information flow, learning, social support Community online Group behavior Socio-technical systems Web 2.0 Participatory Culture #pLASMA 5
  • 6. Background: Social Network Perspective ¡  Actors such as people, groups or organizations, tied by relations that form networks, analyzed and displayed as graphs Social Network Analysis (SNA) The Building Blocks •  Actors, Relations, Ties, Networks SNA as an approach, method and vocabulary for addressing community formation and maintenance #pLASMA 6
  • 7. Outline #pLASMA 7 •  Background / Social Network Perspective (Caroline) •  #hcsmca Case Study – a Twitter Community (Caroline) •  #pLASMA Survey (Drew) •  #pLASMA MOOCs Data (Rafa) •  Network Visualizations & Netlytic.org (Anatoliy) •  Interactive Exercise: Collaborative Analysis of a MOOC Network Visualization (Anatoliy & Caroline) •  Tweet using #LAK14 #pLASMA
  • 8. #pLASMA 8 ¡  Health Care Social Media Canada ¡  Research Questions ¡  ‘#hcsmca is a vibrant community of people interested in exploring social innovation in health care. We share and learn, and together we are making health care more open and connected’ ¡  ‘#hcsmca hosts a tweet chat every Wednesday at 1 pm ET. The last Wednesday of the month is our monthly evening chat at 9 pm ET.’ ¡  What attributes distinguish this community ¡  What accounts for its relative longevity? ¡  What is the role of the founder? And of group members? ¡  Who contributes to this network? ¡  Does this differ by actor professions or roles? #hcsmca Case Study: a Twitter Community http://cyhealthcommunications.wordpress.com/hcsmca-2/
  • 9. #pLASMA 9 #hcsmca Case Study: Data Collection ¡ Public Twitter messages that mentioned the hashtag/keyword #hcsmca ¡ One month of data Nov. 12-Dec. 13, 2012 ¡ 3,871 tweets ¡ 486 unique posters NB. Data as illustration of network perspective ¡ Network data ¡  Tie based on who mentions and/or replies to whom ¡ Name networks ¡  Analysis technique for finding names is based on text mining of messages algorithm (Gruzd) ¡  Software: Netlytic http://netlytic.org ¡ Analysis and Visualization ¡  ORA and NetDraw
  • 10. #pLASMA 10#hcsmca Case Study: Revealing the Network ¡  Asking network questions to address relationships and structures ¡  How are members of the network connected? ¡  How does the structure of a network affect resource flow among group members? ¡  When do resources reach members of the network? ¡  Network properties and structures ¡  Density, cohesion, centrality, path length ¡  Core and periphery ¡  Cliques, clusters, components #hcsmca Twitter Communication Network (one month, Nov-Dec 2012) Tie = mentions or replies in messages
  • 11. #pLASMA 11Analyzing Dynamics Network Evolution Network Dissolution Group Rhythms Examples from an online learning environment (Haythornthwaite)
  • 12. #pLASMA 12#hcsmca Case Study: Group Rhythms ¡ Each week a discussion, Nov. 21th discussion generating most comments ¡ Topics Nov 21 ¡  Healthcare blogs should we or shouldn’t we, what have we learned, what are the benefits? ¡  Are healthcare blogs a useful tool for education and knowledge transfer?
  • 13. #pLASMA 13 Learning from Networks ¡ Using networks to interpret, analyze and design for community, with community A professional development network for a school (de Laat, 2010) Used to show participants how their networks are connected
  • 14. *Roles are assigned manually 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 Node size = In-Degree Centrality #hcsmca Case Study: Twitter Communication Network #pLASMA 14
  • 15. #pLASMA 15#hcsmca Case Study: Twitter Communication Network Nodes are automatically grouped based on their roles No apparent clustering among people in the same role (many cross- group ties)
  • 16. Summary of #hcsmca case ¡  How can a group of individuals who meet online, through the lean medium of Twitter, and the constraints of a 140 character posting, sustain and be considered a community? ¡  Strong core of active participants ¡  Attention to others as shown with measures of prestige and influence -- key players recognized through mentions and retweeting. ¡  Conversation is not fragmented – as shown by the one major component connecting all participants ¡  Weekly discussions that boost interaction and provide a dependable rhythm to interaction patterns, and a (virtual) site to return to each week. #pLASMA 16
  • 17. Outline #pLASMA 17 •  Background / Social Network Perspective (Caroline) •  #hcsmca Case Study – a Twitter Community (Caroline) •  #pLASMA Survey (Drew) •  #pLASMA MOOCs Data (Rafa) •  Network Visualizations & Netlytic.org (Anatoliy) •  Interactive Exercise: Collaborative Analysis of a MOOC Network Visualization (Anatoliy & Caroline) •  Tweet using #LAK14 #pLASMA
  • 18. #pLASMA 18#pLASMA Survey ¡  General lack of knowledge in this area ¡  Existing research provides overview (ex: Moran, Seaman, & Tinti-Kane, 2012) ¡  Media used, statistical information, demographics of instructors ¡  Introduces barriers to integration, attitudes towards social media ¡  Limitations of existing data ¡  US focus ¡  What media are used, but not much detail on how they are used Moran, M., Seaman, J., & Tinti-Kane, H. (2012). Teaching, Learning, and Sharing: How today’s higher education faculty use social media. Retrieved from http://www.pearsonlearningsolutions.com/higher- education/social-media-survey.php
  • 19. #pLASMA 19 #pLASMA Survey: Focus and Aims ¡  Overview of social media use in higher education ¡  Global reach ¡  Differences across regions and cultures ¡  Focus on HOW social media is used in higher education ¡  Details on learning activities built around social media (Cases) ¡  Alignment with learning objectives ¡  Formal assessment: Metrics and criteria used ¡  An understanding of the landscape of integration support ¡  Institutional context ¡  Pedagogical support (learning design resources available) ¡  Technological support
  • 20. #pLASMA 20Social Media and Learning Survey Please participate in our online survey (You could win 1 of 3 iPad Minis!) http://tinyurl.com/SMLearningSurvey
  • 21. Outline #pLASMA 21 •  Background / Social Network Perspective (Caroline) •  #hcsmca Case Study – a Twitter Community (Caroline) •  #pLASMA Survey (Drew) •  #pLASMA MOOCs Data (Rafa) •  Network Visualizations & Netlytic.org (Anatoliy) •  Interactive Exercise: Collaborative Analysis of a MOOC Network Visualization (Anatoliy & Caroline) •  Tweet using #LAK14 #pLASMA
  • 22. #pLASMA 22 #pLASMA MOOCs Data ¡ Athabasca University Courses ¡  CCK11: Connectivism and Connective Knowledge ¡  Change11: Change 2011 ¡  PLENK10: Personal Learning Environments Networks and Knowledge ¡ Not restricted to any one platform ¡  “Throughout this ‘course’ participants will use a variety of technologies, for example, blogs, Second Life, RSS Readers, UStream, etc.”
  • 23. #pLASMA 23 #pLASMA MOOCs Data: Sample course page
  • 24. #pLASMA 24#pLASMA MOOCs Data: Data Structure Daily Newsletters Blog posts Comments Discussion threads Twitter posts Retweets
  • 25. #pLASMA 25#pLASMA MOOCs Data: Overview CCK11 Change11 PLENK10 Blogs 812 2486 719 Discussion Threads 68 87 Comments 306 134 Tweets 1722 5665 2121
  • 26. #pLASMA 26 #pLASMA MOOCs Data: Average size of messages for CCK11 CCK11 Avg character count Avg word count Blogs 332.3 54.2 Discussion Threads 541.8 90.8 Comments 837.6 138.9 Tweets 113.9 14.4
  • 27. #pLASMA 27#pLASMA MOOCs Data: Challenges ¡ Data-related Issues ¡  Some posts contain mostly images/videos or are live seminars ¡  Unreachable links, e.g. expired blog links ¡ Participant-related issues ¡  Some posts are not in English (e.g. Spanish, Swedish) ¡  Participants sometimes miss live sessions that happen at “bad” local times (e.g. 4 am) ¡  Identity resolution: ¡  How to identify a single identity across platforms? ¡  How to identify two or more people with the same alias?
  • 28. Outline #pLASMA 28 •  Background / Social Network Perspective (Caroline) •  #hcsmca Case Study – a Twitter Community (Caroline) •  #pLASMA Survey (Drew) •  #pLASMA MOOCs Data (Rafa) •  Network Visualizations & Netlytic.org (Anatoliy) •  Interactive Exercise: Collaborative Analysis of a MOOC Network Visualization (Anatoliy & Caroline) •  Tweet using #LAK14 #pLASMA
  • 29. #pLASMA 29Network Visualizations & Netlytic.org a cloud-based analytic tool for automated text analysis & discovery of social networks from online communication Networks Stats Content
  • 30. Network Visualizations & Netlytic.org Social Network Analysis (SNA) • Nodes = Group Members • Edges /Ties (lines) = Relations#pLASMA 30
  • 31. http://www.theguardian.com/world/2014/feb/18/ ukraine-police-storm-kiev-protest-camp-live- updates#start-of-comments Sample Online Network Visualizations 31 Tweetsabout
  • 32. 2012 Olympics in London#pLASMA 32 Sample Visualization
  • 33. #tarsand Twitter Community#pLASMA 33 Sample Visualization
  • 34. #1b1t Twitter Book Club#pLASMA 34 Sample Visualization
  • 35. Outline #pLASMA 35 •  Background / Social Network Perspective (Caroline) •  #hcsmca Case Study – a Twitter Community (Caroline) •  #pLASMA Survey (Drew) •  #pLASMA MOOCs Data (Rafa) •  Network Visualizations & Netlytic.org (Anatoliy) •  Interactive Exercise: Collaborative Analysis of a MOOC Network Visualization (Anatoliy & Caroline) •  Tweet using #LAK14 #pLASMA
  • 36. #pLASMA 36Integrating Social Media: A collaborative exercise ¡ Hashtags: #LAK14, #pLASMA ¡ Network visualizations ¡ Collaborative analysis, focused discussion questions ¡ Tweet your responses ¡ Discussion ¡ Summary posted later today (Storify)
  • 37. #pLASMA 37 #CCK11 Class Tweets (Node size=“Indegree”)
  • 38. #pLASMA 38 #CCK11 Class Tweets (Node size=“Outdegree”)
  • 39. #pLASMA #CCK11 Class Tweets (Node size=“Outdegree”) Question 1 - #LAK14 #pLASMA What does this visualization tell us from an instructor’s perspective?
  • 40. #pLASMA #CCK11 Class Tweets (Node size=“Outdegree”) Question 2 - #LAK14 #pLASMA What does this visualization tell us from a student’s perspective?
  • 41. #pLASMA #CCK11 Class Tweets (Node size=“Outdegree”) Question 3 - #LAK14 #pLASMA What does this visualization not tell us?
  • 42. h"p://SocialMediaAndSociety.com              
  • 43. #pLASMA 43Social Media and Learning Survey Please participate in our online survey (You could win 1 of 3 iPad Minis!) http://tinyurl.com/SMLearningSurvey
  • 44. Caroline Haythornthwaite @hthwaite Rafa Absar @rafaabsar Drew Paulin @drewpaulin Anatoliy Gruzd @gruzd project on Learning Analytics in the Social Media Age #pLASMA

×