how social network analysis can help to measure cohesion in collaborative distance-learning

1

FRE 2661

CSCL Conference, Bergen, june 2003C. Reffay, T. Chanier

How Social Network Analysis

can help to

measure cohesion in collaborative distance-learning

Christophe REFFAYThierry CHANIER

Laboratoire d’Informatique de Franche-Comté Besançon - France

2

FRE 2661


Outline

1. Introduction

2. Experiment : Simuligne learning session

3. SNA computational models

– Cliques

– Clusters

4. Conclusion

3

FRE 2661


The problem

Distance:

Interaction data

Face-to-face:

Visual & Oral indices

4

FRE 2661


Our approach:

Hypothesis

• CL works well in « Active » groups.

• Collaboration requires communication

Questions• synthesis from

communication data • appropriateness• importance • computability

• Representation

5

FRE 2661


How SNA can help ?

Social Network Analysis, based on:

• Group dynamics

• Social relationships models

• Graph theory

6

FRE 2661


The central role of "Cohesion"

• Necessary for collaborative tasks

• Very important for social aspects

• Essential for motivation (no isolation)

7

FRE 2661


Cohesion ?

much more complex than… temperature, speed, or weight…

…Less physical, and more human !

Cohesion is an attractive "force" between individuals

8

FRE 2661


Cohesive subgroups

SNA (Wasserman & Faust, 1994) :

"Subsets of actors among whom there are relatively

strong, direct, intense, frequent or positive ties"

9

FRE 2661


Experiment : "Simuligne": distance learning course

10

FRE 2661


Research context : the ICOGAD project

Laboratoire dePsychologie de Nancy

(France)

partner

Laboratoire d'Informatiquede Franche-Comté

(France)

leader

Department ofLanguages - Open

University (UK)

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

11

FRE 2661


Pedagogical hypothesis

To produce together

12

FRE 2661


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

13

FRE 2661


The Simuligne organisationCoordinator

Aquitania Gallia Lugdunensis Narbonensis

Learners Learners Learners Learners

Tutor Tutor Tutor Tutor

14

FRE 2661


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

15

FRE 2661


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

Gallia E-mails over the whole training period

17

FRE 2661


The E-mail Graph matrix

For Gallia over the whole training period

E-mails Gallia (without the tutor)

19

FRE 2661


A forum graph (Gallia)

… Not very useful information

20

FRE 2661


Forum Matrix

Gt Gl1 Gl2 Gn1 Gl3 Gl4 Gl5 Gn2 Gl6 Gl9 Gl10Gt 107 107 99 106 90 107 26 106 107 25 27Gl1 60 60 52 59 45 60 7 59 60 11 9Gl2 27 27 27 24 24 27 5 25 27 3 4Gn1 36 36 33 36 29 36 6 36 36 5 7Gl3 18 18 18 18 15 18 1 18 18 3 1Gl4 48 48 42 47 38 48 8 47 48 9 8Gl5 7 7 6 7 4 7 5 7 7 4 6Gn2 30 30 27 28 25 30 5 28 30 4 5Gl6 14 15 14 14 11 15 3 14 15 3 3Gl9 9 9 7 9 6 9 5 9 9 5 7Gl10 5 5 3 5 4 5 3 5 5 2 2

Not straightforward to use...

21

FRE 2661


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:

22

FRE 2661


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

13 12

101111

8

8

12

C = 10

23

FRE 2661


Computing cliques of level-c

• Symetrisation of the adjaccency matrix

• Definition of the threshold (c)

• Selection of ties >= c=10Gn1Gn2

Gt

Gl10

Gl6

Gl4

Gl2

Gl1

7

512

1432

10

10

7 8

24

FRE 2661


Computing cliques of level-c

Each pair of members of the resulting subset exchanged at least 10 messages. Gn1Gn2

Gt

Gl10

Gl6

Gl4

Gl2

Gl1This is a cohesive subset

Property:

25

FRE 2661


Result on Gallia for c=10

26

FRE 2661


Comparing the 4 groups

Aquitania

Gallia

Lugdunensis

Gallia

Narbonensis

27

FRE 2661


Information given by Cliques

• A good picture of the group structure

• Highlights cohesive groups

• Highlights isolated individuals

… for a given threashold c !

28

FRE 2661


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)

29

FRE 2661


Hierarchical Clusters for GalliaGALLIA G G G G G G G G G G l l l n l G l n l l l 1Level 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

Max

Min

30

FRE 2661


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.

31

FRE 2661


Technical Conclusion

• Cliques and clusters: complementary information

• Process1. Clusters analysis on all groups

2. Then threshold c

3. Level-c cliques

32

FRE 2661


Further work

• User friendly representations

– Development

– Experiment

• SNA multiplexity: integration of all com

tools into one representation

• Exploration of SNA models

33

FRE 2661


Questions ?

34

FRE 2661


From data to social indices

• LMS data extraction

• relationship definitions (graphs)

• Apropriate model

• User friendly representation

E-mails of Aquitania during the whole training period

Aquitania (without the tutor)

37

FRE 2661


(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”

38

FRE 2661


39

FRE 2661


Using the Cliques of level c

Gn1Gn2

Gt

Gl10

Gl6

Gl5 Gl9

Gl4

Gl3

Gl2

Gl1 C=10

how social network analysis can help to measure cohesion in collaborative distance-learning

Documents