Intelligent tutoring interoperability for the new web

Interoperability of systems based on knowledge is a very important element for reducing their development cost and enabling an easy-to-perform service enrichment. Intelligent tutoring systems (ITSs) may be described as distant learning systems, which base their work on the simulation of the “real” teacher in the learning and teaching process. ITSs base their interoperability on the interchange of domain knowledge, knowledge about learning and teaching process and knowledge about students. This paper describes DiSNeT, a distance learning system we designed based on the intelligent tutoring paradigm, on knowledge presentation using distributed semantic networks and on using agents in the learning and teaching process. We also present a methodology for ensuring interoperability between DiSNeT and other ITSs.

[1]  Shamus Paul Smith,et al.  Developing an authoring environment for procedural task tutoring systems : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Palmerston North, New Zealand , 1997 .

[2]  Tak-Wai Chan,et al.  Artificial Agents in Distance Learning , 1995 .

[3]  Laks V. S. Lakshmanan,et al.  XML Interoperability , 2003, WebDB.

[4]  Ashok Patel,et al.  Intelligent Tutoring Systems: Confluence of Information Science and Cognitive Science , 2001 .

[5]  Wouter Joosen,et al.  Customization of Component-based Object Request Brokers through dynamic reconfiguration , 2000, Proceedings 33rd International Conference on Technology of Object-Oriented Languages and Systems TOOLS 33.

[6]  Jeff Heflin,et al.  SHOE: A Knowledge Representation Language for Internet Applications , 1999 .

[7]  Claus Pahl,et al.  Adaptive E-learning content generation based on semantic web technology , 2005 .

[8]  Juha Puustjärvi,et al.  Using Web Services and Workflow Ontology in Multi- Agent Systems , 2002 .

[9]  M. David Merrill,et al.  Instructional transaction shells: responsibilities, methods, and parameters , 1992 .

[10]  Wolfgang Emmerich,et al.  Software engineering and middleware: a roadmap , 2000, ICSE '00.

[11]  Tom Murray,et al.  Authoring Intelligent Tutoring Systems: An analysis of the state of the art , 1999 .

[12]  Nicola Henze,et al.  An Assessment Framework for eLearning in the Semantic Web , 2004, LWA.

[13]  Nader Azarmi,et al.  Enhancing E-Communities with Agent-Based Systems , 2001, Computer.

[14]  R Barthel,et al.  Standardization in e-Learning. The "Sharable Content Object Reference Model (SCORM)” , 2004 .

[15]  Peter Dolog,et al.  The Personal Reader: Personalizing and Enriching Learning Resources Using Semantic Web Technologies , 2004, AH.

[16]  Ian Horrocks,et al.  OIL: An Ontology Infrastructure for the Semantic Web , 2001, IEEE Intell. Syst..

[17]  Pablo Castells,et al.  An Authoring Tool for Building Adaptive Learning Guidance Systems on the Web , 2001, Active Media Technology.

[18]  Ashraf A. Kassim,et al.  A WEB-BASED INTELLIGENT APPROACH TO TUTORING , 2001 .

[19]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[20]  Peter Fankhauser,et al.  An Integration Framework for CORBA Objects , 1999, Trans. SDPS.

[21]  Robert Jasper,et al.  A Framework for Understanding and Classifying Ontology Applications , 1999 .

[22]  Robert J. Gaizauskas,et al.  Using Edit Distance Algorithms to Compare Alternative Approaches to ITS Authoring , 2002, Intelligent Tutoring Systems.

[23]  Marcus Thint,et al.  Adaptive personal agents , 1998, Personal Technologies.

[24]  Wolfgang Emmerich,et al.  Distributed objects , 1999, Proceedings of the 1999 International Conference on Software Engineering (IEEE Cat. No.99CB37002).