Factors shaping learners interactions in networked learning

Factors shaping learners’ interactions in networked learning context

Srećko Joksimovićs.joksimovic@ed.ac.uk

@s_joksimovic

Dragan Gaševićdragan.gasevic@ed.ac.uk

@dgasevic

Vitomir Kovanovićv.kovanovic@ed.ac.uk

@vkovanovic

C X- Open design- Learner centered- Use of social media- Distributed communication

- Fixed design- Focused on learner-content Interaction- Video lectures- Peer assessment

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cMOOC study context

Social capital

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cMOOC study context

Social capital

Social network analysis

Slide 4 of 23

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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

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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

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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

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

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

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

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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

****

**

**

**

**

*

**

**

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

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

Factors shaping learners’ interactions in networked learning context

Srećko Joksimovićs.joksimovic@ed.ac.uk

@s_joksimovic

Dragan Gaševićdragan.gasevic@ed.ac.uk

@dgasevic

Vitomir Kovanovićv.kovanovic@ed.ac.uk

@vkovanovic

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.