2. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 1 How Social Network Analysis can help to measure cohesion in collaborative distance-learning Christophe REFFAY Thierry CHANIER Laboratoire d’Informatique de Franche-Comté Besançon - France

3. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 2 Outline 1.Introduction 2.Experiment : Simuligne learning session 3.SNA computational models –Cliques –Clusters 4.Conclusion

4. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 3 The problem Distance: Interaction data Face-to-face: Visual & Oral indices

5. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 4 Our approach: Hypothesis CL works well in « Active » groups. Collaboration requires communication Questions synthesis from communication data appropriateness importance computability Representation

6. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 5 How SNA can help ? Social Network Analysis, based on: Group dynamics Social relationships models Graph theory

7. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 6 The central role of "Cohesion" Necessary for collaborative tasks Very important for social aspects Essential for motivation (no isolation)

8. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 7 Cohesion ? much more complex than… temperature, speed, or weight… …Less physical, and more human ! Cohesion is an attractive "force" between individuals

9. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 8 Cohesive subgroups SNA (Wasserman & Faust, 1994) : "Subsets of actors among whom there are relatively strong, direct, intense, frequent or positive ties"

10. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 9 Experiment : "Simuligne": distance learning course

11. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 10 Research context : the ICOGAD project partner leader partner Programme COGNITIQUE 2000 Research Ministry of France (53 K€) Simuligne : The training session ICOGAD Project Analysis of interaction tracks from SimuLigne Definition of needed indicators to follow a group Development of new tools to plug in LMS Simuligne : The training session

12. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 11 Pedagogical hypothesis To produce together

13. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 12 The learning context 100% at a distance French as foreign language Public : 40 adults –English speakers –Advanced level in French –Web litterate Groups of 10 + tutor + 2 NS LMS : WebCT 30 hours over 10 weeks

14. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 13 The Simuligne organisation Coordinator AquitaniaGalliaLugdunensisNarbonensis Learners Tutor

15. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 14 Simuligne Interaction data e-mail : 834 753 chars in 4 062 messages Forum : 879 015 chars in 2 686 messages Chat : 234 694 char. in 5 680 speach turns

16. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 15 Communication graphs Only read (opened) messages. (separately) on E-mail or Forum for a given period Gives the number of messages sent by A and read by B on the directed edge A->B

17. Gallia E-mails over the whole training period

18. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 17 The E-mail Graph matrix For Gallia over the whole training period

19. E-mails Gallia (without the tutor)

20. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 19 A forum graph (Gallia) … Not very useful information

21. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 20 Forum Matrix Not straightforward to use...

22. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 21 Our first try… Global index of cohesion (Group) –0 for no relation –Based on shared neighbours –1 for a fully connected graph Number of messages ignored Difficult to define evolution No information on individuals But:

23. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 22 Def. : A clique of level c is a set where all members are directly connected one to another with a value  c. Clique of level c (valued graph) Clique of level 10 15 10 1312 10 11 8 8 12 C = 10

24. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 23 Computing cliques of level-c Symetrisation of the adjaccency matrix Definition of the threshold (c) Selection of ties >= c=10 Gn1 Gn2 Gt Gl10Gl6 Gl4Gl2 Gl1 7 5 12 14 32 10 7 8

25. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 24 Computing cliques of level-c Each pair of members of the resulting subset exchanged at least 10 messages. Gn1 Gn2 Gt Gl10Gl6 Gl4Gl2 Gl1 This is a cohesive subset Property:

26. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 25 Result on Gallia for c=10

27. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 26 Comparing the 4 groups Aquitania Gallia Lugdunensis Gallia Narbonensis

28. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 27 Information given by Cliques A good picture of the group structure Highlights cohesive groups Highlights isolated individuals … for a given threashold c !

29. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 28 Hierarchical Clusters Initially : identity partition : N clusters Repeat Find the most communicant pair of clusters Fusion of the pair in one cluster Print communication level (k) N = N-1 Until (N=1)

30. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 29 Hierarchical Clusters for Gallia GALLIA G G G G G G G G G G l l l n l G l n l l l 1 Level 3 2 1 1 t 4 2 6 5 9 0 ----- - - - - - - - - - - - 167... XXX...... 108... XXXXX..... 83.. XXXXXXX..... 64.. XXXXXXXXX.... 52. XXXXXXXXXXX.... 42 XXXXXXXXXXXXX.... 29 XXXXXXXXXXXXXXX... 9 XXXXXXXXXXXXXXX XXXXX 5 XXXXXXXXXXXXXXXXXXXXX MaxMin

31. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 30 Discussion Cliques of level c gives: –precise communication structure (for a given c). –cohesive subsets –isolated individuals. Clusters: –show more about intensity –Easier to compare groups.

32. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 31 Technical Conclusion Cliques and clusters: complementary information Process 1.Clusters analysis on all groups 2.Then threshold c 3.Level-c cliques

33. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 32 Further work User friendly representations –Development –Experiment SNA multiplexity: integration of all com tools into one representation Exploration of SNA models

34. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 33 Questions ?

35. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 34 From data to social indices LMS data extraction relationship definitions (graphs) Apropriate model User friendly representation

36. E-mails of Aquitania during the whole training period

37. Aquitania (without the tutor)

38. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 37 (questions) Activity as a whole A LMS is an integration of many tools The designer can use them differently : –Communication (Forum, e-mail, Chat, …) –Production (texts, drawing, cards, etc…) –Tests (quizzes, auto-evaluation,…) –Reading, contents pages navigation, etc. One learner can participate to many courses To reckon cohesion only on forum is not sufficient in general, but a good starting point in “simuligne”

39. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 38

40. FRE 2661 CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier 39 Using the Cliques of level c Gn1 Gn2 Gt Gl10Gl6Gl5 Gl9 Gl4Gl3Gl2 Gl1 C=10