A Group Learning Management Method for Intelligent Tutoring Systems

In this paper we propose a group management specification and execution method that seeks a compromise between simple course design and complex adaptive group interaction. This is achieved through an authoring method that proposes predefined scenarios to the author. These scenarios already include complex learning interaction protocols in which student and group models use and update are automatically included. The method adopts ontologies to represent domain and student models, and object Petri nets to specify the group interaction protocols. During execution, the method is supported by a multi-agent architecture.

[1]  Fuhua Lin.  Designing Distributed Learning Environments With Intelligent Software Agents , 2004 .

[2]  Victor R. Lesser,et al.  Quantitative Organizational Models for Large-Scale Agent Systems , 2004, MMAS.

[3]  Chihab Hanachi,et al.  Protocol Moderators as Active Middle-Agents in Multi-Agent Systems , 2004, Autonomous Agents and Multi-Agent Systems.

[4]  Niels Pinkwart,et al.  Conducting situated learning in a collaborative virtual environment , 2006 .

[5]  Javier Vázquez-Salceda,et al.  OMNI: Introducing Social Structure, Norms and Ontologies into Agent Organizations , 2004, PROMAS.

[6]  Janette Cardoso,et al.  A method for modelling adaptive interactions in Intelligent Tutoring Systems , 2007 .

[7]  Mark K. Singley,et al.  Deploying Intelligent Tutors on the Web: An Architecture and an Example , 1999 .

[8]  M. Wooldridge,et al.  Organisational Abstractions for the Analysis and Design of Multi-Agent Systems , 2000 .

[9]  Peter Brusilovsky,et al.  Adaptive Hypermedia: From Intelligent Tutoring Systems to Web-Based Education , 2000, Intelligent Tutoring Systems.

[10]  Carlos Angel Iglesias,et al.  A Survey of Agent-Oriented Methodologies , 1998, ATAL.

[11]  Lars Bollen,et al.  Collaboration and Cognitive Tutoring: Integration, Empirical Results, and Future Directions , 2005, AIED.

[12]  Jacqueline Bourdeau,et al.  Using Ontological Engineering to Overcome Common AI-ED Problems , 2000 .

[13]  Edilson Ferneda,et al.  Mathema: A Learning Environment Based on a Multi-Agent Architecture , 1995, SBIA.

[14]  Yun Peng,et al.  Modeling agent conversations with colored petri nets , 1999 .

[15]  Guilherme Bittencourt,et al.  MATHTUTOR : A MULTI-AGENT INTELLIGENT TUTORING SYSTEMS , .

[16]  Julian Padget,et al.  Formalizing a Language for Institutions and Norms , 2001, ATAL.

[17]  Olivier Boissier,et al.  Modeling Organization in MAS: A Comparison of Models , 2005 .

[18]  Claude Frasson,et al.  LANCA: A Distance Learning Architecture Based on Networked Cognitive Agents , 1998, Intelligent Tutoring Systems.

[19]  Daniel D. Suthers,et al.  Coaching Web-based Collaborative Learning based on Problem Solution Differences and Participation , 2003, Int. J. Artif. Intell. Educ..

[20]  Pedro Cuesta,et al.  A Framework for Evaluation of Agent Oriented Methodologies ? , 2003 .

[21]  Claude Frasson,et al.  WHITE RABBIT - Matchmaking of User Profiles Based on Discussion Analysis Using Intelligent Agents , 2000, Intelligent Tutoring Systems.

[22]  Carlo Strapparava,et al.  Adaptive Hypermedia and Adaptive Web-Based Systems, 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008. Proceedings , 2008, AH.

[23]  Marian H. Nodine,et al.  A Metamodel for Agents, Roles, and Groups , 2004, AOSE.

[24]  Barbara Wasson,et al.  Intelligent Agents Supporting Distributed Collaborative Learning , 2005 .

[25]  Jacques Ferber,et al.  From Agents to Organizations: An Organizational View of Multi-agent Systems , 2003, AOSE.

[26]  Janette Cardoso,et al.  MathTutor: A Multi-Agent Intelligent Tutoring System , 2004, AIAI.

[27]  Carlos José Pereira de Lucena,et al.  A UML based approach for modeling and implementing multi-agent systems , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..