Assessing and promoting computer-supported collaborative learning

Assessing and promoting computer-supported collaborative learning

Anne Meier University of Freiburg, Institute of

Psychology

[email protected]

• Introduction to CSCL (computer-supported collaborative learning)

• Assessing CSCL learning processes

• Supporting CSCL learning processes

• Example study: adaptive support for knowledge co-construction

Overview

The CSCL community

• a short history of CSCL…• “seeds” in the 1980s, e.g. 1989 NATO-sponsored workshop

“computer-supported collaborative learning” (Maratea, Italy)• since 1995: bi-annual CSCL conferences• since 2003: CSCL community part of International Society

of the Learning Sciences (ISLS)

• own journal: International Journal of CSCL (ijCSCL) published by Springer since 2006

• highly interdisciplinary community

Introduction to CSCL

• CSCL researchers study:• How people can learn together with the help of computers (Stahl,

Koschmann, & Suthers, 2007)• How technology can facilitate the sharing and creation of knowledge

and expertise through peer interaction and group learning processes (Restra & Laferrière, 2007)

advantages/strengths

challenges/pitfalls

What is your experience with (computer-supported) collaborative learning?

• Neo-Piagetian perspective• learning = cognitive restructuring• resolving socio-cognitive conflict arising from peer collaboration

• Cognitive elaboration perspective• learning = elaboration and integration of knowledge• very important: constructing explanations

• Neo-Vygotskian perspective• learning = appropriation, internalization• knowledge co-construction; scaffolding and fading

• Situated learning perspective• learning = increasingly “central” participation in a community of

practice• distributed cognition: persons, tools, symbols, artefacts,…

What makes collaborative learning effective?

See for example: Cohen, 1994; Dillenbourg et al., 1995; Fischer, 2002; Webb & Palincsar, 1996)

• Motivational process loss (e.g. Salomon & Globerson, 1989)

• Free-rider effect (“social loafing”)• Sucker effect

• Production blocking• having to wait for others to finish their turn• e.g. in brainstorming (Diehl & Stroebe, 1987)

• Biased information sampling (e.g. Brodbeck et al., 2007; Stasser & Titus, 1985))

• neglecting individuals’ unique knowledge• striving for consensus rather than understanding

Putting people in a (computer-supported) group does not mean that they will collaborate well!

Pitfalls of collaborative learning


• Assessing CSCL learning processes What characterizes “good” computer-supported collaborative learning?



Overview

Cognitive, social, and affective aspects of collaboration quality in CSCL

Communication (Clark & Brennan, 1991)

• Grounding• adapting utterances to the amount of shared knowledge/ perspective/

experience• establishing referential identity (e.g. of objects in a shared whiteboard,

of previous messages/ contributions)• establishing a shared terminology

• Conversation management • initiating conversations• managing turn-taking• ensuring that contributions are taken up

For additional literature/ references, please see Meier, Spada, & Rummel, 2007


Joint information-processing

• Elaborative information-processing• eliciting and providing elaborated explanations• using the partner as a resource• elaborating on partners’ contributions

• Argumentative information-processing• constructing justified arguments and counterarguments• engaging in a critical discussion: avoiding an illusion of consensus


Coordination (explicit or tacit) (e.g. Malone & Crowstone, 1994)

• Task division• identifying interdependent subtasks• blending individual and collaborative work

• Time management• agreeing on a realistic time schedule• monitoring the remaining time during the work process

• Resource management• handling the available tools efficiently• agreeing on who may use a technical feature at what time


Relationship management

• maintaining equal participation• symmetric or complementary, depending on role structure

• solving conflicts constructively• epistemic vs. social conflicts


Motivation

• individual task orientation• keeping up a high level of expended effort• volitional processes: focusing attention, exerting motivation control

• mutual self-regulation• mutual encouragement• monitoring performance and giving feedback

Example: Collaboration quality rating-scheme

• Development• sample from study on interdisciplinary collaboration: students of

psychology and medicine solving complex patient cases (Rummel & Spada, 2005)

Meier, A., Spada, H. & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2 , 63-86.


Control Room

Experimental Room I Experimental Room II


• Development• sample from study on interdisciplinary collaboration: students of

psychology and medicine solving complex patient case (Rummel & Spada, 2005)

• data- and theory-driven analyses 5 aspects/ 9 dimensions• for each dimension:

• collaboration “standard” defined and illustrated in rating handbook• collaboration quality rated on 5-point scales


Means: Pattern 1 (task division)

00,5

11,5

22,5

33,5

Control Script Scriptplus

Model Modelplus

Means: Pattern 2 (individual task orientation, medical student)

00,5

11,5

22,5

33,5

Control Script Scriptplus

Model Modelplus

model / script > controlmodel-plus > modelInformation pooling

Task divisionTime managementTechnical coordination

model > control > scriptmodel-plus > modelIndividual task orientation

Quality of joint solution(Rummel, Spada, & Hauser, 2009)

Rummel

rummele


• adaptation to new CSCL setting (Synergo) (Voyiatzaki et al., 2008)• descriptive framework valid in this setting as well• But: changed operationalization of dimensions and re-anchoring of scales

necessary

….. work in progress:providing adaptive feedback to students based on ratings of their collaboration quality(Meier, Voyiatzaki, Kahrimanis, Rummel, Spada, Avouris, 2008)



• Supporting CSCL learning processes How can beneficial collaboration processes be facilitated?


Overview

Supporting CSCL learning processes

• Earlier approaches: support “around” collaboration

• Collaboration scripts: support during collaboration

• Adaptivity: from fixed to flexible support


• Earlier approaches: support “around” collaboration• Support prior to collaboration, e.g. training for strategic questioning

(King, 1991)• Support after collaboration, e.g. group processing approaches (Yager,

Johnson, Johnson, & Snider, 1986)



after: Diziol & Rummel, accepted



• Collaboration scripts: support during collaboration• provide specific instructions about task-related interaction (Kollar et al.,

2006)• Sequencing work phases• Distributing roles• Specifying activities

goal: enhance cognitive, meta-cognitive and social learning processes



Collaboration Scripts

Jigsawdistribution of knowledge

(e.g. expert groups & teams)exchange of information

Conflictconflicting opinions

(e.g. pro & contra-roles)argumentation

Reciprocalcognitive & metacognitive tasks

(e.g. recaller & detector)mutual regulation

Split Where Interaction Should Happen (SWISH) (Dillenbourg & Jermann, 2007)

Schema Split Compensation




• Adaptivity: from fixed scripts to flexible support• Danger of “overscripting” collaboration (Dillenbourg, 2002); instead:

taking into account students’ prior knowledge and “internal collaboration scripts”

• realizing flexible, adaptive support:• “Wizard of Oz” studies• adaptive feedback based on automated analyses of interaction (e.g.

Dönmez et al, 2005)






Overview

Example: Supporting Collaborative Inferences

F - I - R - E !

Figure from: Bauer, K., & Hesse, F. (2006). Von Kopf zu Kopf. [From head to head]. Gerhirn und Geist [Brain & Mind], 5/2006, 34-39.


Wolfgang‘s fingerprints are on

the gun.

Wolfgang showed the guns to his guests in the

afternoon.

A B


Wolfgang‘s fingerprints are on

the gun.

Wolfgang showed the guns to his guests in the

afternoon.

A B


Wolfgang left his fingerprints on the weapon when he showed it to his guests.

A B

Information distribution Inference type

Person A Person B

collaborative

individual

shared


Inference drawing frequency

0.49

0.65

0.79

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

collaborative individual shared

***

Meier & Spada, 2007


Why is it so difficult to draw collaborative inferences?

1. individual group member holds “unconnected” information• seen as less relevant and therefore less likely to be brought up during

discussion (Fraidin, 2004)

2. inference must be drawn on the basis of newly learned information and recalled information• people tend to focus on old rather than new information (Wittenbaum, Hubbel &

Zuckermann, 1999)• recall vulnerable to disruptions in group discussion (Finlay, Hitch & Meudell,

2000)

Training Experiment: train collaboration strategies for• drawing inferences• pooling “unconnected” information• taking up new information


No Training(n=9 )

Training Task(n=9)

Training Task+ Text (n=9)

Training Task + Text + Tutoring (n=9)

Training phase

read text on collaboration strategies

Training task (medical diagnosis):individual reading phase

discussion & solution ...with inference tutoring tool

collaborative reflection

Testing phase

Test task (murder mystery)

Meier & Spada, 2008

disease information

patient information

inference

1

2

3

4

5

6

7

8

...

New Information!

ANJA has matching information.


disease information

patient information

inference

1

2

3

4

5

6

7

8

...

Well done!

You have drawn an important inference!



No Training(n=9 )

Training Task(n=9)

Training Task+ Text (n=9)

Training Task + Text + Tutoring (n=9)

Training phase

read text on collaboration strategies

Training task (medical diagnosis):individual reading phase

discussion & solution ...with inference tutoring tool

collaborative reflection

Testing phase

Test task (murder mystery)

Meier & Spada, 2008


Inference drawing frequency

0

0.2

0.4

0.6

0.8

1

No_Training TrainingTask

TrainingTask + Text

TrainingTask + Text

+ Tutor

collaborative individual shared

**

**

performance during testing (without tutoring tool)

Meier & Spada, 2008

In a nutshell…

• Introduction to CSCL (computer-supported collaborative learning)• diverse perspectives on collaborative learning within field of CSCL• successful collaboration does not occur spontaneously!

• Assessing CSCL learning processes• focus here was on processes, rather than outcomes or preconditions• many relevant aspects: communication, information-processing,

coordination, relationship management, motivation

• Supporting CSCL learning processes• collaboration scripts: (computer-)support during collaboration• moving towards more flexible, more adaptive support

• Example study: adaptive support for knowledge co-construction• collaborative inferences are important but difficult• adaptive support yields best training results

Many thanks to the CoEmCo-Team:Hans Spada, Nikol Rummel

Dejana Diziol, Sabine HauserEva Zerpies, Malte Jansen

This work was funded byThis work was funded by

Thank you for your attention!

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References / Readings


Meier, A., Spada, H. & Rummel, N. (2007). A rating scheme for assessing the quality of computer-supported collaboration processes. International Journal of Computer-Supported Collaborative Learning, 2 , 63-86.

CommunicationSustaining mutual understanding

Dialog management

Joint information processingInformation pooling

Reaching consensus

Coordination

Task division

Time management

Technical coordination

Relationship management Reciprocal interaction

Motivation Individual task orientation

Outcomes of collaborative learning

When are groups better than individuals? insights from social psychology (Kraut, 2003)

• Aggregation: combining the unique resources of individual group members• Making use of members’ complementary knowledge, perspectives, skills etc.• e.g. a cross-functional marketing team making strategic decisions based on

members’ complementary expertise

• Synergy: going beyond the resources contributed by group members• building on each others’ contributions, creating innovative ideas & solutions• e.g. a product-design team developing a new product

“assembly bonus” however: groups tend to neglect members’ unique knowledge and focus

instead on shared knowledge (Stasser & Titus, 1985)

Measuring the success of computer-supported collaborative learning

• Individual learning• types of knowledge and skills

• conceptual vs. procedural• skills: domain, collaboration, self-regulation, computer-literacy

• level of evaluation: subjective evaluation - retention – transfer

• Group-level learning• transactive memory, shared mental models facilitates future collaboration in the same group

• Interpersonal and motivational outcomes• trust, liking, friendships,…• self- and group-efficacy• interest motivation for future collaboration

Measuring the success of computer-supported collaborative learning

• What characterizes “success” in the TEL-environment you study? How do you assess it?

Assessing collaboration quality

cognitive, social, and affective processes

process gain:

assembly bonus, synergy effects

process loss:

motivation and coordination problems

group size & composition

task type

technical & informational

resources

goal structure

Group learning, e.g. transactive memory, shared mental models

Individual learning- domain knowledge and problem-solving skills- collaboration skills- technical skills

Interpersonal & motivational outcomes, e.g. trust, liking, self-efficacy, group-efficacy

institutional context

Input