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Multi-user Virtual Environment to aid Collaborative Learning and Transfer of Scientific Knowledge and Inquiry Skills
Name: Nader HannaStudent ID: 42259541Supervisor: Prof. Deborah Richards
ITEC810 End of Semester Workshop- 2012
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Agenda
Introduction What is Activity Theory? The Aim of the Study The Focus of the Study Literature Review about on Using AT in Designing Collaborative
environment Literature Review About the Approaches of Agent Collaboration.
Agent-to-agent Collaboration One-way Human-agent Collaboration Two-way Human Agent Collaboration
Proposed Framework of Multi-agent Collaborative Virtual Learning (MACVILLE)
Proposed Collaborative Agent Architecture Challenges Conclusion
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Introduction
Why collaborative learning? Classroom learning improves significantly when students participate in
collaborative learning [Johnson and Johnson, 1999].
Why virtual environment? Using virtual environment increases the involvement of the students in learning
activity.
What is Intelligent agent? A software agent that has some intelligence and autonomous in its environment , it
takes decisions by itself.
What is BDI agent reasoning model? Belief-Desire-Intention model, agent has knowledge about his environment, plans
to achieve and methods to achieve these plans
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What is Activity Theory? Activity Theory (AT) is a theoretical framework for analyzing human practices in a
given context. It is used to arrange the collaborative learning.
1. Subject: Members of the learning group
2. Object: Experiences, Knowledge , Products,…
3. Community: learning group, system, society ,…
4. Tools: plans, spoken language, ICT applications, devices ,…
5. Rules: practices, collaboration, negotiation ,…
6. division of labor:learners, tutors, supervisors, virtual agents Subject uses Tools to interact with Object. Community uses Division of Effort to interact with
Object, and uses Rules to interact with Subject.
Subject Object
CommunityRules Division of Effort
Tools
Outcome
Structure of Activity theory
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The aim of the study
The aim of this study is to design, implement, and test a collaborative multi-agent multi-user virtual learning environment.
The collaborative environment will include 3 levels of collaboration:1. Human-human collaboration in physical world.2. Human-agent collaboration in virtual world.3. Human-human collaboration in virtual world.
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The virtual environment
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Levels of collaboration
1 2 3 40
5
10
15
20
25
30
WK1WK2WK3
Human-human physical collaboration
Human-agent virtual collaboration
1
2
8
Levels of collaboration (cont.)
3 Human-human virtual collaboration
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The Focus of the Study
Collaborative Learning
Learning Scientific
Conclusion
Agent Reasoning
Model
Activity Theory
We target
this part
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Literature Review on Using AT in Designing Collaborative Environment
Miao [1] presents a conceptual framework for the design of virtual problem-based learning environments in the light of activity theory.
Gifford and Enyedy [2] propose a framework called Activity Centered Design (ACD). Their proposed framework is based on three main concepts of AT.
Liang et al. [3] further build on the six steps to define components and their relationships for collaborative network learning.
Norris and Wong [4] use AT to identify any difficulties that users may have when navigating through QuickTime Virtual Reality Environments (QTVR).
Zurita and Nussbaum [5] identified six steps to propose a conceptual framework for mobile Computer Supported Collaborative Learning (MCSCL) activities.
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Literature Review on the approaches of agent collaboration
We determined 3 possible categories of agent collaboration:
1. Agent-agent Collaboration…interacting agents in a dynamic environment using techniques such as Tuple-Spaces, Group Computation and Roles.
2. One-way Human-agent Collaboration…where agent behave as a mediator or facilitator to human-human collaborative activities.
3. Two-way Human-agent Collaboration…where agent directly interacts with human actions.
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Agent-to-agent collaboration
use of a shared/global model between agents to achieve the determined goal.
Agent Collaboration Approaches:
Tuple-spaces provide a multi-agent-like architecture, where agents can collaborate through writing, reading or removing tuples in the space.
Group Computation a way to program group based activities .
Activity Theory is a framework to design the mediated interaction that may happen between agents.
Roles are used to define common interactions between agents in virtual environments.
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One-way human-agent collaboration
actions performed by the human with assistance from the agent.
Aguilar et al. [6] Agent could assist the group during the execution stage of a Team Training Strategy
Yacine and Tahar [7] the role of the agent could be a mediator where the agent’s role is to facilitate the collaboration between users and give feedback
Zhang et al. [8, 9]The role of the mediator agent could be to facilitate the communication of a user with other users
Luin et al. [10] the agent could collaborate with the user by answering the user’s questions while navigating into a virtual world
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Two-way human agent collaboration
the actions of both the human and agent interleave and depend on each other.
Miller et al [11] Humans and/or agents could be are working together to achieve a goal
Lesh et al. [12] plan recognition algorithm in order to reduce communication during collaboration between a human and an agent
Miao et al. [13] Agent could behave and modify his behaviour according to human actions, for example to train learners to handle abnormal situations while driving cars
Hedfi et al. [14] Collaboration between human and agent could take the form of negotiation in design something
Fan and Yen [15] To make a teamwork between human and agent, agent may need estimate its human partner’s cognitive load
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Learner Companion
Learner Colleague
AgentCollaborative Virtual World
Learner-agent group
Learner-learner physical group
Learner-learner online group
-Interaction-Guidance-Discussion-Role taking
Face-to-face communication
-Interaction-Guidance
Virtualcommunication
Online
communication
-Debating-Negotiating
Conclusion Making
Social Interaction
Collect evidences
Write report
3D character graphic
3D character animation
-BDI-Co-Operation-Social
Agent reasoning model
Network Protocol
Database
Communication
Text
Awareness
Voice
Target Determining
Roles Specifying
Progression
Role playing
Virtual Collaborative
Collaboration
Discussion
Guidance
Decision-making
Roleplaying
KnowledgeSharing
NoteTaking
Conclusion Making
Decision Justifying
Idea Defending
Questioning
Comparing
Conclusion Making
Decision Updating
Negotiation
Proposed framework of Multi-agent collaborative virtual learning (MACVILLE)
Subject Object
CommunityRules Division of Effort
Tools
Outcome
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Proposed collaborative agent architecture
S
itu
atio
n
Goal Setting
Planning
Situation Understanding
Learning
Cognitive Processes
Plan Executing/Adopting
Information Retrieval
Knowledge Integration
Knowledge/ Memory
Memory and its Processes
The Intelligent and Cognitive processes
Situation Understanding
Learner Realizing
Partner Progress Evaluating
Action and Communication
Social and Collaborative Processes
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The Intelligent and Cognitive processes
The memory or the knowledge base is where the agents store information, knowledge and experience.
two processes related to the memory: Knowledge Integration to add a new experience to the stored knowledge, and Information Retrieval to get the appropriate piece of information
Information Retrieval
Knowledge Integration
Knowledge/ Memory
Memory and its Processes
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The Intelligent and Cognitive processes (cont.)
Cognitive processes gives the agent the ability to perform the tasks and change in its environment.
Situation Understanding…using inputs from the environment to understand where is the agent?
Goal Setting…using inputs from the environment and the human learner to determine what the agent going to collaborate with the user.
Planning…the ability to have a different plans for each task.
Executing/Adopting…adopt the plans to perform the task according to the changes in the environment.
Learning…new rules may be added to knowledge base for future usage.
Goal Setting
Planning
Situation Understanding
Learning
Cognitive Processes
Plan Executing/Adopting
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Social and Collaborative Processes
Social and Collaborative Processes…
Situation Understanding…understanding what is the social situation the agent going to handle.
Learner Realizing…understanding who is the human team member, and what is the role of human in the collaboration activity.
Partner Progress Evaluating…working in a teamwork needs the members to feel the need to others help.
Action and Communication …instructions exchanged between human and agent.
Situation Understanding
Learner Realizing
Partner Progress Evaluating
Action and Communication
Social and Collaborative Processes
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Challenges Conceptual and design challenges may include:
1. Determining the factors that control human collaboration and determine successful teamwork.
2. The difficulties in capturing and measuring the levels and nature of collaboration that take place between human and agent.
Implementation challenges may include:
1. Creating, selecting or adapting an appropriate implementation framework to extend the [BDI] reasoning model of the agent.
2. Integrating the framework of agent reasoning with a 3D game engine already in use (unity3D).
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Conclusion There are different approaches for agent collaboration in 3D virtual environment.
Activity Theory is a framework used to manage collaborative learning in physical classroom, and could be use in virtual collaborative environment .
Two-way human-agent collaboration needs the agent to be fully aware of the environment, the task to be achieved, the plan to be done and the partner.
BDI model of agent reasoning give the agent the ability to think in doing required task regardless to participation from other actor.
Collaboration between human user and agent needs the agent to go beyond BDI model.
22
References
1. Miao, Y.: An Activity Theoretical Approach to a Virtual Problem Based Learning Environment. In: the 2000 International Conference on Information in the 21 Century: Emerging Technologies and New Challenges, pp. 647-654. (2000)
2. Gifford, B.R., Enyedy, N.D.: Activity Centered Design: Towards a Theoretical Framework for CSCL. In: Roschelle, C.H.J. (ed.) Proceedings of the 1999 conference on Computer support for collaborative learning, pp. 22-37. International Society of the Learning Sciences, Palo Alto, California (1999)
3. Liang, X., Wang, R., Bai, G.: A Multi-Agent System Based on Activity Theory for Collaborative Network Learning. In: First International Workshop on Education Technology and Computer Science (ETCS '09), pp. 392-397. (2009)
4. Norris, B.E., Wong, B.L.W.: Activity Breakdowns in QuickTime Virtual Reality Environments. Proceedings of the First Australasian User Interface Conference (AUIC '00), pp. 67 - 72. IEEE Computer Society, Canberra, ACT (2000)
5. Zurita, G., Nussbaum, M.: A Conceptual Framework Based on Activity Theory for Mobile CSCL. British Journal of Educational Technology 38,211-235 (2007)
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References (cont.)
6. Aguilar, R.A., Antonio, A.d., Imbert, R.: An Intelligent Collaborative Virtual Environment for Team Training -- A Preliminary Report. In: 15th International Conference on Computing (CIC '06), pp. 236-239. (2006)
7. Yacine, L., Tahar, B.: Supporting Collaboration in Agent-Based Collaborative Learning System (SACA ). In: Information and Communication Technologies ( ICTTA '06 ), pp. 2843-2848. (2006)
8. Zhang, C., Xi, J., Yang, X.: An Architecture for Intelligent Collaborative Systems Based on Multi-agent In: 12th International Conference on Computer Supported Cooperative Work in Design (CSCWD '08), pp. 367 - 372. (2008)
9. Zhang, P., Li, X.: The Framework of Multi Intelligent Agent Based on Collaborative Design. In: International Conference on Future BioMedical Information Engineering ( FBIE '09), pp. 513 - 517. (2009)
10. Luin, J.v., Akker, R.o.d., Nijholt, A.: A Dialogue Agent for Navigation Support in Virtual Reality. In: extended abstracts on Conference on Human Factors in Computing Systems (CHI '01), pp. 117-118. ACM, (2001)
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References (cont.)
11. Miller, M.S., Yin, J., Volz, R.A., Ioerger, T.R., Yen, J.: Training Teams with Collaborative Agents. In: Proceedings of the 5th International Conference on Intelligent Tutoring Systems, pp. 63-72. Springer-Verlag, 745826 (2000)
12. Lesh, N., Rich, C., Sidner, C.L.: Using plan recognition in human-computer collaboration. In: Proceedings of the seventh international conference on User modeling, pp. 23-32. Springer-Verlag New York, Inc., 317331 (1999)
13. Miao, Y., Hoppe, U., Pinkwart, N.: Naughty Agents Can Be Helpful: Training Drivers to Handle DangerousSituations in Virtual Reality. In: Sixth International Conference on Advanced Learning Technologies (ICALT '06), pp. 735-739. (2006)
14. Hedfi, R., Ito, T., Fujita, K.: Towards Collective Collaborative Design: An Implementation of Agent-Mediated Collaborative 3D Products Design System. In: 2010 International Symposium on Collaborative Technologies and Systems (CTS), pp. 314-321. (2010)
15. Fan, X., Yen, J.: Realistic cognitive load modeling for enhancing shared mental models in human-agent collaboration. In: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems, pp. 1-8. ACM, 1329197 (2007)