Instructional planning using focus of attention

  • Xueming Huang
  • Gordon I. McCalla
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 608)


An instructional planner needs to revise both the student model and the instructional plan itself as its perceptions of the student change during the interaction with the student. Artificial intelligence provides a variety of reason maintenance systems (RMSs) whose job is to carry out such revisions. Unfortunately, traditional RMSs cannot be used directly in real time instructional planning because they are typically quite slow. To overcome this problem, we propose a new RMS, called the attention-shifting belief revision system (ABRS), that works efficiently by focusing only on the parts of the student model and the instructional plan that are relevant to the current subgoal(s) of the planner. The planner identifies current goals and relevant beliefs in the student model. The ABRS then ensures that these goals and beliefs are kept in focus and that their consistency is maintained. An example shows that instructional planning using the ABRS is just as effective as using traditional RMSs, but is considerably more efficient.


Work Memory Belief Revision Plan Operation Base Belief Intelligent Tutoring System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Xueming Huang
    • 1
  • Gordon I. McCalla
    • 2
  1. 1.Knowledge Systems Laboratory Institute for Information TechnologyNational Research Council CanadaOttawaCanada
  2. 2.ARIES Laboratory Department of Computational ScienceUniversity of SaskatchewanSaskatoonCanada

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