The Autotutor 3 Architecture: A Software Architecture for an Expandable, High-Availability ITS

Providing high quality of service over the Internet to a variety of clients while simultaneously providing good pedagogy and extensibility for content creators and developers are key issues in the design of the computational architecture of an intelligent tutoring system (ITS). In this paper, we describe an ITS architecture that attempts to address both issues using a distributed hub-and-spoke metaphor similar to that of the DARPA Galaxy Communicator. This architecture is described in the context of the natural language ITS that uses it, AutoTutor 3.

[1]  Arthur C. Graesser,et al.  Perceived Characteristics and Pedagogical Efficacy of Animated Conversational Agents , 2002, Intelligent Tutoring Systems.

[2]  Arthur C. Graesser,et al.  Intelligent Tutoring Systems with Conversational Dialogue , 2001, AI Mag..

[3]  Pamela W. Jordan.  Tools for Authoring Tutorial Dialogue Knowledge , 2001 .

[4]  Allan Kuchinsky,et al.  Integrating user-perceived quality into Web server design , 2000, Comput. Networks.

[5]  Arthur C. Graesser,et al.  Human or Computer? AutoTutor in a Bystander Turing Test , 2002, Intelligent Tutoring Systems.

[6]  James C. Lester,et al.  Animated Pedagogical Agents: Face-to-Face Interaction in Interactive Learning Environments , 2000 .

[7]  Arthur C. Graesser,et al.  Utterance Classification in AutoTutor , 2003, HLT-NAACL 2003.

[8]  Shaaron Ainsworth,et al.  EVALUATING THE EFFECTIVENESS AND EFFICIENCY OF THE REDEEM INTELLIGENT TUTORING SYSTEM AUTHORING TOOL , 2002 .

[9]  David E. Culler,et al.  SEDA: an architecture for well-conditioned, scalable internet services , 2001, SOSP.

[10]  Chen-Lin C. Kulik,et al.  Educational Outcomes of Tutoring: A Meta-analysis of Findings , 1982 .

[11]  Vincent Aleven,et al.  An effective metacognitive strategy: learning by doing and explaining with a computer-based Cognitive Tutor , 2002, Cogn. Sci..

[12]  Joseph P. Magliano,et al.  Collaborative dialogue patterns in naturalistic one-to-one tutoring , 1995 .

[13]  Arthur C. Graesser,et al.  Why/AutoTutor: A Test of Learning Gains from a Physics Tutor with Natural Language Dialog , 2003 .

[14]  Carolyn Penstein Rosé,et al.  Fading and Deepening: The Next Steps for Andes and other Model-Tracing Tutors , 2000, Intelligent Tutoring Systems.

[15]  Kurt VanLehn,et al.  A model of the self-explanation effect. , 1992 .

[16]  Albert T. Corbett,et al.  Cognitive Computer Tutors: Solving the Two-Sigma Problem , 2001, User Modeling.

[17]  Heather H. Mitchell,et al.  AutoTutor: A tutor with dialogue in natural language , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[18]  M. Angela Sasse,et al.  It ain't what you charge, it's the way that you do it: a user perspective of network QoS and pricing , 1999, Integrated Network Management VI. Distributed Management for the Networked Millennium. Proceedings of the Sixth IFIP/IEEE International Symposium on Integrated Network Management. (Cat. No.99EX302).