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Making social learning visible:
some provocations for Connected Learning Analytics
dashboard concepts
Simon Buckingham Shum
Professor of Learning Informatics
Director, Connected Intelligence Centre
@sbuckshum
cic.uts.edu.au
To nurture skillful social learners (prev talk)…
…invisible + ephemeral social processes need to
be made visible + persistent
…for which we need analytics to aggregate +
visualise data meaningfully
as proxies for social + personal learning
2
Bridging the data—meaning gulf
3
logs of user actions (xAPI triples)
meaningful, timely representations
how students and educators think about learning
(not necessarily the same thing)
Bridging the data—meaning gulf
4
logs of user actions (xAPI triples)
meaningful, timely representations
how students and educators think about learning
(not necessarily the same thing)
sensemaking	
  
ac+on/interven+on	
  
Bridging the data—meaning gulf
5
logs of user actions (xAPI triples)
meaningful, timely representations
how students and educators think about learning
(not necessarily the same thing)
Bloom’s	
  taxonomy,	
  etc	
  
Opera&on	
  ...	
  Wayfinding	
  …	
  Sensemaking	
  …	
  Innova&on	
  
All of the following are possible in
closed learning platforms
‘Technically straightforward’
to apply to an xAPI LRS?
But which are of most interest?
6
textchat + videoconf
replay + analytics
7
FlashMeeting (Open University’s Knowledge Media Institute)
8
http://flashmeeting.open.ac.uk
FlashMeeting (Open University’s Knowledge Media Institute)
9
http://flashmeeting.open.ac.uk
social network
analytics
10
Learning	
  
Technology	
  
KMi,	
  OU	
  
AI	
  &	
  
Argumenta&on	
  
Learning	
  
Disposi&ons	
  
Human-­‐Centred	
  	
  
Informa&cs	
  
Learning	
  
Analy&cs	
  
Seman&c	
  Scien&fic	
  	
  
Publishing	
  
Dialogue	
  /	
  Issue	
  /	
  
Argument	
  Mapping	
  
Social learning
analytics
— quantifying
“professional
identity”
Schreurs B, Teplovs C, Ferguson R, De Laat
M and Buckingham Shum S. (2013)
Visualizing Social Learning Ties by Type
and Topic: Rationale and Concept
Demonstrator. Proc. 3rd International
Conference on Learning Analytics &
Knowledge. Leuven, BE: ACM, 33-37. Open
Access Eprint: http://oro.open.ac.uk/36891
Adding topic and type of social tie to filter SN
Adding topic and type of social tie to filter SN
Schreurs B, Teplovs C, Ferguson R, De Laat
M and Buckingham Shum S. (2013)
Visualizing Social Learning Ties by Type
and Topic: Rationale and Concept
Demonstrator. Proc. 3rd International
Conference on Learning Analytics &
Knowledge. Leuven, BE: ACM, 33-37. Open
Access Eprint: http://oro.open.ac.uk/36891
discourse analytics
14
analytics that look beneath the
surface, and quantify linguistic
proxies for ‘deeper learning’
Beyond number / size / frequency
of posts; ‘hottest thread’
http://www.glennsasscer.com/wordpress/wp-content/uploads/2011/10/iceberg.jpg
Discourse analytics on webinar textchat
Ferguson, R. and Buckingham Shum, S., Learning analytics to identify exploratory dialogue within synchronous text chat. In: 1st
International Conference on Learning Analytics and Knowledge (Banff, Canada, 2011). ACM
Can we spot the
quality learning
conversations in a
2.5 hr webinar?
-60
-40
-20
0
20
40
60
80
9:28
9:32
9:36
9:40
9:41
9:46
9:50
9:53
9:56
10:00
10:05
10:07
10:07
10:09
10:13
10:17
10:23
10:27
10:31
10:35
10:40
10:45
10:52
10:55
11:04
11:08
11:11
11:17
11:20
11:24
11:26
11:28
11:31
11:32
11:35
11:36
11:38
11:39
11:41
11:44
11:46
11:48
11:52
11:54
12:00
12:03
12:04
12:05
Average Exploratory
Discourse analytics on webinar textchat
Sheffield, UK not as sunny
as yesterday - still warm
Greetings from Hong Kong
Morning from Wiltshire,
sunny here!
See you!
bye for now!
bye, and thank you
Bye all for now
Given a 2.5 hour webinar, where in the live
textchat were the most effective learning
conversations?
Not at the start and end of a webinar…
Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc.
3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
-60
-40
-20
0
20
40
60
80
9:28
9:32
9:36
9:40
9:41
9:46
9:50
9:53
9:56
10:00
10:05
10:07
10:07
10:09
10:13
10:17
10:23
10:27
10:31
10:35
10:40
10:45
10:52
10:55
11:04
11:08
11:11
11:17
11:20
11:24
11:26
11:28
11:31
11:32
11:35
11:36
11:38
11:39
11:41
11:44
11:46
11:48
11:52
11:54
12:00
12:03
12:04
12:05
Average Exploratory
Discourse analytics on webinar textchat
Given a 2.5 hour webinar, where in the live
textchat were the most effective learning
conversations?
Not at the start and end of a webinar
but if we zoom in on a peak…
Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc.
3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
Discourse analytics on webinar textchat
-100
0
100
9:28
9:40
9:50
10:00
10:07
10:17
10:31
10:45
11:04
11:17
11:26
11:32
11:38
11:44
11:52
12:03
Averag
Classified as
“exploratory
talk”
(more
substantive
for learning)
“non-
exploratory”
Given a 2.5 hour webinar, where in the live
textchat were the most effective learning
conversations?
Not at the start and end of a webinar
but if we zoom in on a peak…
Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc.
3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
writing analytics
20
Visualizations of writing cohesion
21
Whitelock, D., D. Field, J. T. E. Richardson, N. V. Labeke and S. Pulman (2014). Designing and Testing Visual Representations of Draft Essays for Higher
Education Students. 2nd International Workshop on Discourse-Centric Learning Analytics, Fourth International Conference on Learning Analytics and
Knowledge, Indianapolis, Indiana, USA. https://dcla14.files.wordpress.com/2014/03/dcla14_whitelock_etal.pdf
Rhetorical functions of metadiscourse
identified by the Xerox Incremental Parser (XIP)
BACKGROUND KNOWLEDGE
Recent studies indicate …
… the previously proposed …
… is universally accepted ...
NOVELTY
... new insights provide direct evidence ...
... we suggest a new ... approach ...
... results define a novel role ...
OPEN QUESTION
… little is known …
… role … has been elusive
Current data is insufficient …
GENERALIZING
... emerging as a promising approach
Our understanding ... has grown
exponentially ...
... growing recognition of the importance ...
CONTRASTING IDEAS
… unorthodox view resolves …
paradoxes …
In contrast with previous
hypotheses ...
... inconsistent with past
findings ...
SIGNIFICANCE
studies ... have provided important
advances
Knowledge ... is crucial for ... understanding
valuable information ... from studies
SURPRISE
We have recently observed ... surprisingly
We have identified ... unusual
The recent discovery ... suggests intriguing roles
SUMMARIZING
The goal of this study ...
Here, we show ...
Altogether, our results ... indicate
22
AWA: Academic Writing Analytics tool
23
AWA: Academic Writing Analytics tool
24
AWA: Academic Writing Analytics tool
25
dispositional
analytics
making dispositions visible, quantifiable, and improvable
26
“It’s more than knowledge and skills. For the
innovation economy, dispositions
come into play:
readiness to collaborate;
attention to multiple perspectives;
initiative;
persistence;
curiosity.”
Larry Rosenstock
High Tech High
San Diego
hightechhigh.org
LearningREimagined project: http://learning-reimagined.com
Larry Rosenstock: http://audioboo.fm/boos/1669375-50-seconds-of-larry-rosenstock-ceo-of-hightechhigh-on-how-he-would-re-imagine-learning
Knowledge, Skills & Dispositions
27
“It’s vital to know that … focusing on
learning is not smoke and
mirrors. It’s not just some clever idea
among the intelligentsia. It’s really important.
And it’s really, really important that we
can measure it, demonstrate it, and
develop a language for it.”
Mark Moorhouse
Matthew Moss High School,
Rochdale, UK
http://youtu.be/kayzkma1TIM — Learning Futures channel: http://bit.ly/lfmovies
MMHS website: http://www.mmhs.co.uk/learning
Measuring learning to learn
28
Deakin Crick, R., S. Huang, A. Ahmed Shafi and C. Goldspink (2015). Developing Resilient Agency in Learning: The Internal Structure of
Learning Power. British Journal of Educational Studies: Published online: 24 Mar 2015. http://dx.doi.org/10.1080/00071005.2015.1006574 29
Evidencing learning dispositions: CLARA survey
(Ruth Deakin Crick, UTS)
30
Structural Equation
Model underpinning
CLARA
Deakin Crick, R., S. Huang, A. Ahmed Shafi and C. Goldspink (2015).
Developing Resilient Agency in Learning: The Internal Structure of Learning
Power. British Journal of Educational Studies: Published online: 24 Mar 2015.
http://dx.doi.org/10.1080/00071005.2015.1006574
Mindful
Agency
Sense making
Creativity
CuriosityBelonging
Collaboration
Hope and
optimism
Immediate visual analytic generated by CLARA
(Individual and cohort profiles + detailed reports + spreadsheets enabling further analysis)
Rapid Visual Feedback to
Stimulate Self-Directed Change
A framework for a coaching conversation
+
Mindful Agency
Sense making
Creativity
CuriosityBelonging
Collaboration
Hope and
optimism
Behavioural analytics for learning dispositions?
Social network patterns,
teamwork effectiveness and
initiation of relationships?
Questioning, arguing and
search behaviours reveal
intrinsic curiosity and
epistemic commitments?
Tagging/sharing/blogging/social
patterns reveal how you see
connections between ideas?
32
From blog feeds (to xAPI?)
Mood View widget
Dashboard view
Teacher’s dashboard for EnquiryBlogger
a learning design
patterns tool?
37
CompendiumLD: for OU Learning Design
OU LDI Project led by Grainne Conole: http://compendiumld.open.ac.uk
(screenshots from
CLAtoolkit demo)
39
Harvesting social media activity as xAPI triples
40
Harvesting social media activity as xAPI triples
41
Facebook	
  
TwiOer	
  
Integrated	
  data	
  stream	
  
Harvesting social media
activity as xAPI triples
42

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Provocations for CLA Dashboard

  • 1. Making social learning visible: some provocations for Connected Learning Analytics dashboard concepts Simon Buckingham Shum Professor of Learning Informatics Director, Connected Intelligence Centre @sbuckshum cic.uts.edu.au
  • 2. To nurture skillful social learners (prev talk)… …invisible + ephemeral social processes need to be made visible + persistent …for which we need analytics to aggregate + visualise data meaningfully as proxies for social + personal learning 2
  • 3. Bridging the data—meaning gulf 3 logs of user actions (xAPI triples) meaningful, timely representations how students and educators think about learning (not necessarily the same thing)
  • 4. Bridging the data—meaning gulf 4 logs of user actions (xAPI triples) meaningful, timely representations how students and educators think about learning (not necessarily the same thing) sensemaking   ac+on/interven+on  
  • 5. Bridging the data—meaning gulf 5 logs of user actions (xAPI triples) meaningful, timely representations how students and educators think about learning (not necessarily the same thing) Bloom’s  taxonomy,  etc   Opera&on  ...  Wayfinding  …  Sensemaking  …  Innova&on  
  • 6. All of the following are possible in closed learning platforms ‘Technically straightforward’ to apply to an xAPI LRS? But which are of most interest? 6
  • 8. FlashMeeting (Open University’s Knowledge Media Institute) 8 http://flashmeeting.open.ac.uk
  • 9. FlashMeeting (Open University’s Knowledge Media Institute) 9 http://flashmeeting.open.ac.uk
  • 11. Learning   Technology   KMi,  OU   AI  &   Argumenta&on   Learning   Disposi&ons   Human-­‐Centred     Informa&cs   Learning   Analy&cs   Seman&c  Scien&fic     Publishing   Dialogue  /  Issue  /   Argument  Mapping   Social learning analytics — quantifying “professional identity”
  • 12. Schreurs B, Teplovs C, Ferguson R, De Laat M and Buckingham Shum S. (2013) Visualizing Social Learning Ties by Type and Topic: Rationale and Concept Demonstrator. Proc. 3rd International Conference on Learning Analytics & Knowledge. Leuven, BE: ACM, 33-37. Open Access Eprint: http://oro.open.ac.uk/36891 Adding topic and type of social tie to filter SN
  • 13. Adding topic and type of social tie to filter SN Schreurs B, Teplovs C, Ferguson R, De Laat M and Buckingham Shum S. (2013) Visualizing Social Learning Ties by Type and Topic: Rationale and Concept Demonstrator. Proc. 3rd International Conference on Learning Analytics & Knowledge. Leuven, BE: ACM, 33-37. Open Access Eprint: http://oro.open.ac.uk/36891
  • 15. analytics that look beneath the surface, and quantify linguistic proxies for ‘deeper learning’ Beyond number / size / frequency of posts; ‘hottest thread’ http://www.glennsasscer.com/wordpress/wp-content/uploads/2011/10/iceberg.jpg
  • 16. Discourse analytics on webinar textchat Ferguson, R. and Buckingham Shum, S., Learning analytics to identify exploratory dialogue within synchronous text chat. In: 1st International Conference on Learning Analytics and Knowledge (Banff, Canada, 2011). ACM Can we spot the quality learning conversations in a 2.5 hr webinar?
  • 17. -60 -40 -20 0 20 40 60 80 9:28 9:32 9:36 9:40 9:41 9:46 9:50 9:53 9:56 10:00 10:05 10:07 10:07 10:09 10:13 10:17 10:23 10:27 10:31 10:35 10:40 10:45 10:52 10:55 11:04 11:08 11:11 11:17 11:20 11:24 11:26 11:28 11:31 11:32 11:35 11:36 11:38 11:39 11:41 11:44 11:46 11:48 11:52 11:54 12:00 12:03 12:04 12:05 Average Exploratory Discourse analytics on webinar textchat Sheffield, UK not as sunny as yesterday - still warm Greetings from Hong Kong Morning from Wiltshire, sunny here! See you! bye for now! bye, and thank you Bye all for now Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Not at the start and end of a webinar… Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
  • 18. -60 -40 -20 0 20 40 60 80 9:28 9:32 9:36 9:40 9:41 9:46 9:50 9:53 9:56 10:00 10:05 10:07 10:07 10:09 10:13 10:17 10:23 10:27 10:31 10:35 10:40 10:45 10:52 10:55 11:04 11:08 11:11 11:17 11:20 11:24 11:26 11:28 11:31 11:32 11:35 11:36 11:38 11:39 11:41 11:44 11:46 11:48 11:52 11:54 12:00 12:03 12:04 12:05 Average Exploratory Discourse analytics on webinar textchat Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Not at the start and end of a webinar but if we zoom in on a peak… Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
  • 19. Discourse analytics on webinar textchat -100 0 100 9:28 9:40 9:50 10:00 10:07 10:17 10:31 10:45 11:04 11:17 11:26 11:32 11:38 11:44 11:52 12:03 Averag Classified as “exploratory talk” (more substantive for learning) “non- exploratory” Given a 2.5 hour webinar, where in the live textchat were the most effective learning conversations? Not at the start and end of a webinar but if we zoom in on a peak… Ferguson, R., Wei, Z., He, Y. and Buckingham Shum, S., An Evaluation of Learning Analytics to Identify Exploratory Dialogue in Online Discussions. In: Proc. 3rd International Conference on Learning Analytics & Knowledge (Leuven, BE, 8-12 April, 2013). ACM. http://oro.open.ac.uk/36664
  • 21. Visualizations of writing cohesion 21 Whitelock, D., D. Field, J. T. E. Richardson, N. V. Labeke and S. Pulman (2014). Designing and Testing Visual Representations of Draft Essays for Higher Education Students. 2nd International Workshop on Discourse-Centric Learning Analytics, Fourth International Conference on Learning Analytics and Knowledge, Indianapolis, Indiana, USA. https://dcla14.files.wordpress.com/2014/03/dcla14_whitelock_etal.pdf
  • 22. Rhetorical functions of metadiscourse identified by the Xerox Incremental Parser (XIP) BACKGROUND KNOWLEDGE Recent studies indicate … … the previously proposed … … is universally accepted ... NOVELTY ... new insights provide direct evidence ... ... we suggest a new ... approach ... ... results define a novel role ... OPEN QUESTION … little is known … … role … has been elusive Current data is insufficient … GENERALIZING ... emerging as a promising approach Our understanding ... has grown exponentially ... ... growing recognition of the importance ... CONTRASTING IDEAS … unorthodox view resolves … paradoxes … In contrast with previous hypotheses ... ... inconsistent with past findings ... SIGNIFICANCE studies ... have provided important advances Knowledge ... is crucial for ... understanding valuable information ... from studies SURPRISE We have recently observed ... surprisingly We have identified ... unusual The recent discovery ... suggests intriguing roles SUMMARIZING The goal of this study ... Here, we show ... Altogether, our results ... indicate 22
  • 23. AWA: Academic Writing Analytics tool 23
  • 24. AWA: Academic Writing Analytics tool 24
  • 25. AWA: Academic Writing Analytics tool 25
  • 26. dispositional analytics making dispositions visible, quantifiable, and improvable 26
  • 27. “It’s more than knowledge and skills. For the innovation economy, dispositions come into play: readiness to collaborate; attention to multiple perspectives; initiative; persistence; curiosity.” Larry Rosenstock High Tech High San Diego hightechhigh.org LearningREimagined project: http://learning-reimagined.com Larry Rosenstock: http://audioboo.fm/boos/1669375-50-seconds-of-larry-rosenstock-ceo-of-hightechhigh-on-how-he-would-re-imagine-learning Knowledge, Skills & Dispositions 27
  • 28. “It’s vital to know that … focusing on learning is not smoke and mirrors. It’s not just some clever idea among the intelligentsia. It’s really important. And it’s really, really important that we can measure it, demonstrate it, and develop a language for it.” Mark Moorhouse Matthew Moss High School, Rochdale, UK http://youtu.be/kayzkma1TIM — Learning Futures channel: http://bit.ly/lfmovies MMHS website: http://www.mmhs.co.uk/learning Measuring learning to learn 28
  • 29. Deakin Crick, R., S. Huang, A. Ahmed Shafi and C. Goldspink (2015). Developing Resilient Agency in Learning: The Internal Structure of Learning Power. British Journal of Educational Studies: Published online: 24 Mar 2015. http://dx.doi.org/10.1080/00071005.2015.1006574 29 Evidencing learning dispositions: CLARA survey (Ruth Deakin Crick, UTS)
  • 30. 30 Structural Equation Model underpinning CLARA Deakin Crick, R., S. Huang, A. Ahmed Shafi and C. Goldspink (2015). Developing Resilient Agency in Learning: The Internal Structure of Learning Power. British Journal of Educational Studies: Published online: 24 Mar 2015. http://dx.doi.org/10.1080/00071005.2015.1006574
  • 31. Mindful Agency Sense making Creativity CuriosityBelonging Collaboration Hope and optimism Immediate visual analytic generated by CLARA (Individual and cohort profiles + detailed reports + spreadsheets enabling further analysis) Rapid Visual Feedback to Stimulate Self-Directed Change A framework for a coaching conversation +
  • 32. Mindful Agency Sense making Creativity CuriosityBelonging Collaboration Hope and optimism Behavioural analytics for learning dispositions? Social network patterns, teamwork effectiveness and initiation of relationships? Questioning, arguing and search behaviours reveal intrinsic curiosity and epistemic commitments? Tagging/sharing/blogging/social patterns reveal how you see connections between ideas? 32
  • 33. From blog feeds (to xAPI?)
  • 36. Teacher’s dashboard for EnquiryBlogger
  • 38. CompendiumLD: for OU Learning Design OU LDI Project led by Grainne Conole: http://compendiumld.open.ac.uk
  • 40. Harvesting social media activity as xAPI triples 40
  • 41. Harvesting social media activity as xAPI triples 41 Facebook   TwiOer   Integrated  data  stream  
  • 42. Harvesting social media activity as xAPI triples 42