A Decision-Theoretic Approach to Scientific Inquiry Exploratory Learning Environment

  • Choo-Yee Ting
  • M. Reza Beik Zadeh
  • Yen-Kuan Chong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4053)


Although existing computer-based scientific inquiry learning environments have proven to benefit learners, effectively inferring and intervening within these learning environments remain an open issue. To tackle this challenge, this article will firstly address the issue on learning model by proposing Scientific Inquiry Exploratory Learning Model. Secondly, aiming at effective modeling and intervening under uncertainty in modeling learner’s exploratory behaviours, decision-theoretic approach is integrated into INQPRO. This approach allows INQPRO to compute a probabilistic assessment on learner’s scientific inquiry skills (Hypothesis Generation and Variables Identification), domain knowledge, and subsequently provides tailored hints. This article ends with an investigation on the accuracy of proposed learner model by performing a model walk-through with human expert and field trial evaluation with a total number of 30 human students.


Variable Identification Intelligent Tutor System Query Node Inquiry Learning Environment Decision Network 
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 2006

Authors and Affiliations

  • Choo-Yee Ting
    • 1
  • M. Reza Beik Zadeh
    • 2
  • Yen-Kuan Chong
    • 3
  1. 1.Faculty of Information Technology 
  2. 2.Faculty of Engineering 
  3. 3.Center for Multimedia Education and Application DevelopmentMultimedia UniversityCyberjayaMalaysia

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