Factors shaping learners interactions in networked learning
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Transcript of Factors shaping learners interactions in networked learning
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Factors shaping learners’ interactions in networked learning context
Srećko Joksimović[email protected]
@s_joksimovic
Dragan Gašević[email protected]
@dgasevic
Vitomir Kovanović[email protected]
@vkovanovic
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C X- Open design- Learner centered- Use of social media- Distributed communication
- Fixed design- Focused on learner-content Interaction- Video lectures- Peer assessment
2023-04-15 Slide 2 of 23
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cMOOC study context
Social capital
Slide 3 of 23
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cMOOC study context
Social capital
Social network analysis
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cMOOC study context
Information exchange
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cMOOC study context
• Language and the quality of social ties are mutually dependent.
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xMOOC study context
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cMOOC study approachCCK11 (12 weeks)
CCK12 (12 weeks)Week1
Learner 1
Learner 2
Learner N
Week2
Learner 1
Learner N
…
SNA
Degree centralityEigenvalue centralityBetweenness centralityCloseness centrality
Coh-Metrix
NarrativitySyntactic SimplicityWord ConcretenessReferential CohesionDeep Cohesion
MLM
<<extract>
>
<<extract>>
<<analyze>>
<<an
alyz
e>>
<<measure>>
<<measure>>
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1755 posts
2483 posts
1473 posts
61 posts
2266 posts
624 posts
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xMOOC study approach
Slide 9 of 23
NGIx (8 weeks)SNA
Degree centralityEigenvalue centralityBetweenness centralityCloseness centrality
<<extract>>
<<analyze>> <<measure>>
Learner 1
Learner 2
…
Learner N
Coh-Metrix<<
anal
yze>
>
<<extract>> NarrativitySyntactic SimplicityWord ConcretenessReferential CohesionDeep Cohesion<<measure>>
MLMActive learners
All learners
Grades
MLMActive learners
All learners
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SNA metricsDegree Centrality
Closeness Centrality
Betweenness Centrality
Eigenvalue Centrality
Slide 10 of 23
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Linguistic properties• Narrativity
• Deep cohesion
• Referential cohesion
• Syntactic simplicity
• Word concreteness
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Statistical analyses
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Dependent Independent Random
cMOOC and xMOOC cMOOC and xMOOC cMOOC
Degree centrality Narrativity Learner within a course
Eigenvalue centrality Deep Cohesion Course slope
Betweenness centrality Referential Cohesion
Closeness centrality Syntax Simplicity xMOOC
xMOOC Word Concreteness Learner
Final grade cMOOC Word count
Media
Time
Activity
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Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.08 -0.06 -0.04 -0.02 0 0.02 0.04 0.06
Degree models
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.1 -0.05 0 0.05 0.1
*
*
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.1 0 0.1 0.2 0.3 0.4 0.5
All learners Active learners
**
*
**
**
*
***
**
cMOOC
xMOOC
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Betweenness models
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.05 0 0.05 0.1
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.1 0 0.1 0.2 0.3 0.4 0.5
All learners Active learners
*
***
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.05-0.04-0.03-0.02-0.01 0 0.01 0.02 0.03
*
*
cMOOC
xMOOC
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Closeness models
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4
All learnersActive learners
**
**
**
*
**
**
cMOOC
xMOOC
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.03 -0.02 -0.01 0 0.01 0.02
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cMOOC Eigenvalue model
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.08 -0.06 -0.04 -0.02 0 0.02 0.04
***
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Low referential cohesion Higher eigenvalue centrality
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Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Week 7
Week 8
Week 9
Week 10
Week 11
Week 12
00.10.20.30.40.50.60.70.80.9
1
cMOOC Contextual factors
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Media Twitter vs. Facebook vs. Blogs
Differ in their affordances
Time Negative association?
Activity More active -> more likely to grow
influence
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xMOOC Performance models
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.25 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1
Slide 18 of 23
Syntax Simplicity
Deep Cohesion
Referential Cohesion
Word Concreteness
Narrativity
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6
All learners Active learners
****
**
**
**
**
*
**
**
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What do we know…?
• Contextual, as well as linguistic and discourse features of written artefacts, are important determinants of learning in a cMOOC environment.
• cMOOC: Course participants who tend to use more narrative and informal style, nevertheless still manage to maintain a deeper cohesive structure in their communication will have more ties.
• xMOOC: – Better performance – more expository style discourse– Higher centrality – more narrative style, with less overlap between
words and ideas
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So what…?• Practice
– Effective use of language to communicate and share knowledge – Sharing novel information, using concrete and coherently
structured language– Traditional academic performance vs. social centrality
• Research– Are learners able to develop all the necessary skills to learn in
distributed settings?– Changes in linguistic features as indicators of learning progress
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What we are missing?
• cMOOC– temporal dimension– 72 undirected weighted graphs
• xMOOC– cross-sectional analysis– limited set of interactions
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What we are missing?
L1
L2
L3
FB post - fi
TW post - ti
L4Blog post - bi
TW post - tj
SM post - smn
post
comment
like
comment
post
mention
retweet
post
post
post
commentreference fa
vorit
e
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What we are missing?
L2Temporal properties:- Linguistic and discourse features – t1- Linguistic and discourse features – t2- …- Linguistic and discourse features – tn
Overall- GPA- Previous activities- Demographics
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Further research• (Temporal) Exponential Random Graph
Models– Mathematical vs. Statistical model
Henry and Dietz (2011)2023-04-15 Slide 24 of 23
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Factors shaping learners’ interactions in networked learning context
Srećko Joksimović[email protected]
@s_joksimovic
Dragan Gašević[email protected]
@dgasevic
Vitomir Kovanović[email protected]
@vkovanovic
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References• Joksimović, S., Dowell, N. M., Skrypnyk, O., Kovanović, V., Gašević, D., Dawson, S., Graesser,
A.C. - Exploring the Development of Social Capital in cMOOC through Language and Discourse, Journal of Educational Data Mining, 2015 (submitted).
• Dowell, N. M., Skrypnyk, O., Joksimović, S., Graesser, A. C., Dawson, S., Gašević, D., Hennis, T. A., de Vries, P., Kovanović, V. – Modeling Learners’ Social Centrality and Performance through Language and Discourse, The 8th International Conference on Educational Data Mining, Madrid, Spain, 26-29 June, 2015 (accepted).
• Henry, A. D., Dietz, T. - Information, networks, and the complexity of trust in commons governance. International Journal of the Commons, [S.l.], v. 5, n. 2, p. 188-212, sep. 2011. ISSN 1875-0281. Available at: <http://www.thecommonsjournal.org/index.php/ijc/article/view/312/231>. Date accessed: 17 May. 2015.