A Reconfigurable Architecture for Building Intelligent Learning Environments

  • Authors:

  • Joseph G. Linn;James Segedy;Hogyeong Jeong;Benjamin Podgursky;Gautam Biswas

  • Affiliations:

  • Dept. of EECS/ISIS, Vanderbilt University, Nashville, TN. USA;Dept. of EECS/ISIS, Vanderbilt University, Nashville, TN. USA;Dept. of EECS/ISIS, Vanderbilt University, Nashville, TN. USA;Dept. of EECS/ISIS, Vanderbilt University, Nashville, TN. USA;Dept. of EECS/ISIS, Vanderbilt University, Nashville, TN. USA

  • Venue:
  • Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
  • Year:
  • 2009

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Abstract

This paper describes our initial efforts at implementing a new Choice-Adaptive Intelligent Learning Environment (CAILE) that combines multi-agent adaptive technologies and service architectures to provide a framework for designing extendible and reconfigurable learning environments. We describe the core components of the CAILE architecture, learning tasks that establish a situated context for learning, and a set of customizable agents that support student learning. We employ software engineering metrics to evaluate the system, and illustrate the reconfigurable and extensible properties of our design and implementation.