Factors shaping learners interactions in networked learning

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  1. 1. Factors shaping learners interactions in networked learning context Sreko Joksimovi s.joksimovic@ed.ac.uk @s_joksimovic Dragan Gaevi dragan.gasevic@ed.ac.uk @dgasevic Vitomir Kovanovi v.kovanovic@ed.ac.uk @vkovanovic
  2. 2. C X- Open design - Learner centered - Use of social media - Distributed communication - Fixed design - Focused on learner-content Interaction - Video lectures - Peer assessment 2015-06-16 Slide 2 of 23
  3. 3. cMOOC study context 2015-06-16 Social capital Slide 3 of 23
  4. 4. cMOOC study context 2015-06-16 Social capital Social network analysis Slide 4 of 23
  5. 5. cMOOC study context 2015-06-16 Information exchange Slide 5 of 23
  6. 6. cMOOC study context 2015-06-16 Language and the quality of social ties are mutually dependent. Slide 6 of 23
  7. 7. xMOOC study context 2015-06-16 Slide 7 of 23
  8. 8. cMOOC study approach 2015-06-16 CCK11 (12 weeks) CCK12 (12 weeks) Week 1 Learner 1 Learner 2 Learner N Week 2 Learner 1 Learner N SNA Degree centrality Eigenvalue centrality Betweenness centrality Closeness centrality Coh-Metrix Narrativity Syntactic Simplicity Word Concreteness Referential Cohesion Deep Cohesion MLM Slide 8 of 23 1755 posts 2483 posts 1473 posts 61 posts 2266 posts 624 posts
  9. 9. xMOOC study approach 2015-06-16 Slide 9 of 23 NGIx (8 weeks) SNA Degree centrality Eigenvalue centrality Betweenness centrality Closeness centrality Learner 1 Learner 2 Learner N Coh-Metrix Narrativity Syntactic Simplicity Word Concreteness Referential Cohesion Deep Cohesion MLM Active learners All learners Grades MLM Active learners All learners
  10. 10. SNA metrics 2015-06-16 Degree Centrality Closeness Centrality Betweenness Centrality Eigenvalue Centrality Slide 10 of 23
  11. 11. Linguistic properties 2015-06-16 Narrativity Deep cohesion Referential cohesion Syntactic simplicity Word concreteness Slide 11 of 23
  12. 12. Statistical analyses 2015-06-16 Slide 12 of 17 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
  13. 13. -0.1 -0.05 0 0.05 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity Degree models -0.1 -0.05 0 0.05 0.1 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity * * -0.2 0 0.2 0.4 0.6 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity All learners Active learners ** * ** ** * *** ** cMOOC xMOOC
  14. 14. Betweenness models -0.05 0 0.05 0.1 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity -0.2 0 0.2 0.4 0.6 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity All learners Active learners * *** -0.06 -0.04 -0.02 0 0.02 0.04 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity * * cMOOC xMOOC
  15. 15. Closeness models -0.2 -0.1 0 0.1 0.2 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity -0.4 -0.2 0 0.2 0.4 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity All learners Active learners ** ** ** * ** ** cMOOC xMOOC -0.03 -0.02 -0.01 0 0.01 0.02 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity
  16. 16. cMOOC Eigenvalue model 2015-06-16 -0.08 -0.06 -0.04 -0.02 0 0.02 0.04 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity *** Slide 16 of 23 Low referential cohesion Higher eigenvalue centrality
  17. 17. 0 0.2 0.4 0.6 0.8 1 Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11 Week 12 cMOOC Contextual factors 2015-06-16 Slide 17 of 23 Media Twitter vs. Facebook vs. Blogs Differ in their affordances Time Negative association? Activity More active -> more likely to grow influence
  18. 18. xMOOC Performance models 2015-06-16 -0.3 -0.2 -0.1 0 0.1 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity Slide 18 of 23 -1 -0.5 0 0.5 Syntax Simplicity Deep Cohesion Referential Cohesion Word Concreteness Narrativity All learners Active learners **** ** ** ** ** * ** **
  19. 19. 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 2015-06-16 Slide 19 of 23
  20. 20. 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 2015-06-16 Slide 20 of 23
  21. 21. What we are missing? cMOOC temporal dimension 72 undirected weighted graphs xMOOC cross-sectional analysis limited set of interactions 2015-06-16 Slide 21 of 23
  22. 22. What we are missing? L1 L2 L3 FB post - fi TW post - ti L4 Blog post - bi TW post - tj SM post - smn post
  23. 23. What we are missing? L2 Temporal properties: - Linguistic and discourse features t1 - Linguistic and discourse features t2 - - Linguistic and discourse features tn Overall - GPA - Previous activities - Demographics 2015-06-16 Slide 23 of 23
  24. 24. Further research (Temporal) Exponential Random Graph Models Mathematical vs. Statistical model Henry and Dietz (2011) 2015-06-16 Slide 24 of 23
  25. 25. Factors shaping learners interactions in networked learning context Sreko Joksimovi s.joksimovic@ed.ac.uk @s_joksimovic Dragan Gaevi dragan.gasevic@ed.ac.uk @dgasevic Vitomir Kovanovi v.kovanovic@ed.ac.uk @vkovanovic
  26. 26. References Joksimovi, S., Dowell, N. M., Skrypnyk, O., Kovanovi, V., Gaevi, 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., Joksimovi, S., Graesser, A. C., Dawson, S., Gaevi, D., Hennis, T. A., de Vries, P., Kovanovi, 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: . Date accessed: 17 May. 2015.