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Learning Analytics of and in
Mediational Processes of
Collaborative Learning
Dan Suthers
Alyssa Friend Wise
Betrand Schnei...
The collection, analysis and reporting
of data traces related to learning in
order to understand, inform and
improve the p...
Rapidly growing interest in learning analytics by the
CSCL community
CSCL’15: 9 papers + 3 posters +
this invited sessions...
Generation of insight through computational
analytic methods
Informing of human action and decision
making (“closing the l...
One Schematic of Learning Analytics
Adapted from Tyne (2015)
Data Access,
Capture &
Management
Analysis &
Creation of
Insi...
Learning Analytics and CSCL
Fundamental shared concern with learning
processes and innovating to improve them
Analytics ca...
Focus of the Panel
Explore potential of learning analytics for generating understanding
of and participating in mediationa...
Mediation of Discussion Forum Activity by
“Messages”: A Learning Analytics Approach
Supported by the Social Sciences and H...
Origins of Online “Listening”
• From a social constructivist perspective, the goal of
online discussions is for learners t...
Distinct Characteristics of Listening Online
• Listeners (rather than speakers) determine timeline
by which messages and i...
Not Just the Messages, but their
Presentation also Mediates Interaction
11
Microanalytic Case Studies of Listening
Date Time Session Action Duration
(min)
Length
(words)
Message #
6/3/2011 23:46 1 ...
Common Online Listening Patterns
Pattern Characteristic Behaviors
Disregardful
Minimal attention to others’ posts (few pos...
Developing Metrics for the Patterns
14
Dimension Metric Definition
Listening
Breadth
% of posts viewed
Number of unique po...
Identifying Patterns with Metrics
Breadth Depth
Connections with Speaking
• Greater revisitation of others’ posts is
associated with richer responsiveness
• Greater liste...
Designing Learning Analytics to Mediate
Learner’s Interactions w/ Messages
Embedded Analytics
Designing Learning Analytics to Mediate
Learner’s Interactions w/ Messages
Extracted Analytics
Metric Your Data
(Week X)
C...
Summary
The E-Listening Project as a brief illustration of how:
1. Analytics helped uncover mediation of
discussion forum ...
Alyssa Friend Wise
Simon Fraser University
afw3@sfu.ca
@alywise
www.sfu.ca/~afw3/research/e-listening
Continue the conversation and bridge building…
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Learning Analytics and Mediation of Collaborative Learning Processes (CSCL 2015)

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My slides from the CSCL 2015 panel on learning analytics to support and mediate collaborative learning.

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Learning Analytics and Mediation of Collaborative Learning Processes (CSCL 2015)

  1. 1. Learning Analytics of and in Mediational Processes of Collaborative Learning Dan Suthers Alyssa Friend Wise Betrand Schneider David Williamson Shaffer H. Ulrich Hoppe George Siemens
  2. 2. The collection, analysis and reporting of data traces related to learning in order to understand, inform and improve the process, outcomes and/or environments in which it occurs Learning Analytics
  3. 3. Rapidly growing interest in learning analytics by the CSCL community CSCL’15: 9 papers + 3 posters + this invited sessions CSCL’13: No mention in program A rose by any other name… Intrigue Puzzlement Hesitancy Energy
  4. 4. Generation of insight through computational analytic methods Informing of human action and decision making (“closing the loop” in a tighter cycle) Development of indicators, models and data representations Some Critical Characteristics of Learning Analytics
  5. 5. One Schematic of Learning Analytics Adapted from Tyne (2015) Data Access, Capture & Management Analysis & Creation of Insight Processes that Impact Student Learning & Success
  6. 6. Learning Analytics and CSCL Fundamental shared concern with learning processes and innovating to improve them Analytics can help uncover mediation of social interactions by physical, digital + conceptual artifacts - Identify patterns in “big” or “deep” data As well, learning analytics themselves are material that can further mediate these interactions - Possibilities for data-informed practices
  7. 7. Focus of the Panel Explore potential of learning analytics for generating understanding of and participating in mediational processes in CSCL Session Structure Four illustrative examples of CSCL learning analytics projects Comments and questions to the panel by George Siemens, Founding President of SoLAR (Society for Learning Analytics Research) Extended discussion based on questions from the audience, live + via twitter #cscl2015 #learninganalytics
  8. 8. Mediation of Discussion Forum Activity by “Messages”: A Learning Analytics Approach Supported by the Social Sciences and Humanities Research Council of Canada CSCL 2015 ∙ Gothenburg, Sweden Alyssa Friend Wise Simon Fraser University  Vancouver, Canada With grateful thanks to the entire e-listening research team: Trisha, Hsiao, Farshid Marbouti, Jennifer Speer, Yuting Zhao, Simone Hausknecht & Nishan Perera
  9. 9. Origins of Online “Listening” • From a social constructivist perspective, the goal of online discussions is for learners to build understanding through dialoging with other. At a basic level this involves Externalizing one’s ideas by contributing msgs to an online discussion Taking in the externalizations of others by accessing existing msgs The messages are thus conceptual and interactional resources that mediate the process of discussing online
  10. 10. Distinct Characteristics of Listening Online • Listeners (rather than speakers) determine timeline by which messages and ideas are accessed • Large decision space – Frequency and length of log-in sessions – Which posts attended to, in what order, for how long – Revisit posts as many times as needed – Reply when ready, unlimited time to prepare
  11. 11. Not Just the Messages, but their Presentation also Mediates Interaction 11
  12. 12. Microanalytic Case Studies of Listening Date Time Session Action Duration (min) Length (words) Message # 6/3/2011 23:46 1 Read 44.43 413 447 6/3/2011 23:52 1 Read 1.73 60 455 6/4/2011 00:08 1 Scan 0.23 117 459 6/4/2011 00:09 1 Read 12.51 413 460 6/4/2011 23:49 2 Post 3.18 120 477 Dynamic Discussion Map: A record of the discussion to show the historical appearance of the discussion forum at any point in time Log-file Data of Student Actions So how do we study this?
  13. 13. Common Online Listening Patterns Pattern Characteristic Behaviors Disregardful Minimal attention to others’ posts (few posts viewed; short time viewing). Brief and relatively infrequent sessions of activity in discussions. Coverage Views a large proportion of others’ posts, but spends little time attending to them (often only scanning the contents). Short but frequent sessions of activity, focusing primarily on new posts. *May be socially-oriented or content-driven. Focused Views a limited number of others’ posts, but spends substantial time attending to them. Few extended sessions of activity in discussions. Thorough Views a large proportion of other’s posts; spends substantial time attending to many of them. Long overall time spent listening; considerable revisitiation of posts already read.
  14. 14. Developing Metrics for the Patterns 14 Dimension Metric Definition Listening Breadth % of posts viewed Number of unique posts that a student viewed divided by the total number of posts made by others. % of posts read Number of unique posts that a student read divided by the total number of posts made by others. Listening Depth % of real reads Number of times a student viewed other’s posts that were slower than 6.5 words per second, divided by the total number of views. Av. length of real reads Total time a student spent reading posts, divided by the number of reads. Listening Reflectivity # of reviews of own posts Number of times a student revisited posts that he/she had made previously in the discussion # of reviews of others posts Number of times a student revisited others’ posts that he/she had viewed previously in the discussion
  15. 15. Identifying Patterns with Metrics Breadth Depth
  16. 16. Connections with Speaking • Greater revisitation of others’ posts is associated with richer responsiveness • Greater listening depth (% of real reads) is associated with richer argumentation • Initially no relationship found between listening breadth and quality of speaking
  17. 17. Designing Learning Analytics to Mediate Learner’s Interactions w/ Messages Embedded Analytics
  18. 18. Designing Learning Analytics to Mediate Learner’s Interactions w/ Messages Extracted Analytics Metric Your Data (Week X) Class Average (Week X) % of posts read 72% 87% % of real reads 41% 66% Av. length of real reads 2.37m 4.12m #of reviews of own posts 22 13 #of reviews of others’ posts 8 112
  19. 19. Summary The E-Listening Project as a brief illustration of how: 1. Analytics helped uncover mediation of discussion forum activity by “messages” as conceptual / interactional resources 2. This information could then be used to create material that could further mediate these interactions
  20. 20. Alyssa Friend Wise Simon Fraser University afw3@sfu.ca @alywise www.sfu.ca/~afw3/research/e-listening
  21. 21. Continue the conversation and bridge building…

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