Improving Conversation Engagement Through Data-Driven Agent Behavior Modification

  • Michael ProcterEmail author
  • Fuhua Lin
  • Robert Heller
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9673)


E-learning systems based on a conversational agent (CA) provide the basis of an intuitive, engaging interface for the student. The goal of this paper is to propose an agent-based framework for providing an improved interaction between students and CA-based e-learning applications. Our framework models both the student and the CA and uses agents to represent data sources for each. We describe an implementation of the framework based on BDI (Belief-Desire-Intention) architecture and results of initial testing.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Computing and Information SystemsAthabasca UniversityAthabascaCanada
  2. 2.Faculty of Humanities and Social SciencesAthabasca UniversityAthabascaCanada

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