Adaptive Collaboration Support for the Web Amy Soller Institute for Defense Analyses, Alexandria,...

Adaptive Collaboration Support for the Web

Amy SollerInstitute for Defense Analyses, Alexandria, Virginia, U.S.A.

Jonathan GradyOctober 12, 2005

References

1. Soller, A. (2005). Adaptive Collaboration Support Technology. “The Adaptive Web: Methods and Strategies of Web Personalization”. Draft Chapter. Springer.

2. Boticario, J., Gaudioso, E., Catalina C. (2003). Towards personalised learning communities on the Web. In P. Dillenbourg, A. Eurolings, editor. Proceedings of the First European Conference on Computer-Supported Collaborative Learning, pages 115-122.

3. Constantino-González, M., Suthers, D. (2003). Automated Coaching of Collaboration based on Workspace Analysis: Evaluation and Implications for Future Learning Environments. Proceedings of the 36th Hawaii International Conference on the System Sciences 2003: 32.

Agenda

• Introduction

• Strategic Pairing and Group Modeling

• Online Knowledge Sharing & Discovery

• Collaboration Management Cycle

• Q & A Session

Background

• Many adaptive web techniques help individual users find and apply existing knowledge:– Content selection– Adaptive presentation– Navigation support

• What if the knowledge doesn’t exist?

Introduction

Background (cont.)

Introduction

Intelligent Collaborative Learning

Adaptive Group

Formation Adaptive Collaboration

Support

Virtual Students

(Adapted from Brusilovsky & Peylo, 2003)

Adaptive Collaboration Support

• Adaptive technologies that facilitate, mediate, & support:– Collaboration– Interaction– Knowledge Construction

• Coaches & Monitors

Introduction

Strategic Pairing & Group Modeling

Collaborative Filtering

• Recommend relevant items & services, or provide guidance to individuals based on user models.

• Generalize info among several user models and provide recommendations for the group as a whole.

• Find similarities => majority appeal


Building Group Models

• Group models store recommended content & user reactions to these recommendations

• Elements of group models:– Group performance– Group history– Individual member profiles (?)

• Goal is to create groups with dynamics for successful collaboration


Approaches to Pairing & Modeling

• 1st approach– User models are pre-processed– Groups constructed by selecting the most

compatible members• 2nd approach

– Facilitator analyzes group interaction after collaboration begins

– Dynamically facilitates group interaction, or modifies environment accordingly

– Logs user responses to interventions• Many systems use a combination of the approaches


Example: IMMEX

• Interactive MultiMedia Exercises (http://www.immex.ucla.edu/)

• Online version contains collaborative web navigation, synchronization, & structured chat

• Constructs user models and predicts future learning behavior


http://www.immex.ucla.edu/

Example: IMMEX


Example: IMMEX

• IMMEX aggregates user models to select optimal learning partners

• Approach: boosts predictive capabilities of user models through HMM.

• Initiates collaboration, recommends resources, mediates communication

• Continually monitors and predicts problem-solving strategies by group members.


Example: aLF + WebDL

• Boticario et al. (2003)• aLF – non-adaptive website designed

for collaborative education (similar to Courseweb)

• WebDL – analyzes user/group interactions; tailors services accordingly– Multi-agent user modeling– Advisor agent selects optimal response


Example: aLF + WebDL


Group Dynamics & Facilitation

• Chat sequence analysis: using HMM to predict effectiveness of interaction– Sentence openers: “I think...”, “Do you

know...”

• Targeted mouse control– Chiu (2004) – if users could not anticipate

when they would take control of the workspace, they became more actively involved in task-oriented dialog


Online Knowledge Sharing & Discovery

Knowledge Discovery

• Communities of Practice vs. Communities of Interest

• Shared workspaces vs. user goals– Public workspaces => persistent info– Private workspaces => transient info

• Social awareness & networking tools– Content, detail, language, time, context– Visualizations of social network


Example: LiveJournal


http://www.livejournal.com/

Example: iVisTo


Community Maintenance

• Environment must continue to foster collaboration

• Search Aids: metadata, structures, tools

• Moderators

• Cross-community discussion groups– Annotations of content– Voting on content relevance


Motivation & Participation

• Reward members for taking action– Peer reviews, reputation enhancers

• Trust relationships– Function of competence, risk, utility,

importance – Still relies heavily on personal judgment

• User & group models updated to reflect constructive feedback


Example: COLER

• Constantino-Gonzalez, Suthers (2003)


Example: COLER

• Focused on identifying competing solutions and participation level; no expert model

• Conducted five experiments with groups of 3 students

• 73% of generated advice was deemed “Worth saying” by expert

• Most students rated COLER’s collaboration support as helpful.


The Collaboration Management Cycle

Overview


• Framework for guiding distributed virtual group activity

Phases 1 & 2

• Collect (1) & Aggregate (2) online interactions

• Represent interactions in a standardized log format:– <time: 14:00>

<user: Tom><event: clickentity5>

<chat: “I’m going to...”>


Conceptualizing Interactions

• Depends on performance metric

• High-level variables are “collaboration” or “skill competency” evaluated– Simple statistics– Probabilistic models– Fuzzy logic


Phase 3

• Compare observed interaction with desired state (based on expert model)

• Must use the same computational representation as the observed interaction

• What if there are discrepancies?


Phase 4

• Mirroring tools– Self-reflection and self-mediation

• Metacognitive tools– Presents representations

of both actual and potential interactions

• Guiding Systems– Assess collaborations– Provide hints & coaches


Summary

• Adaptive Collaboration Support:– Models based on group interaction theories– Identify and form optimal groups– Facilitate and mediate collaboration among

group members (coach & monitor)– Continually log interactions, adapting

mediation and environment appropriately

Questions?

Adaptive Collaboration Support for the Web Amy Soller Institute for Defense Analyses, Alexandria,...

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