Experiences in Implementing Constraint-Based Modeling in SQL-Tutor
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Estimating Problem Value in an Intelligent Tutoring System Using Bayesian Networks
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Constraint-Based Tutors: A Success Story
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WETAS: A Web-Based Authoring System for Constraint-Based ITS
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Automatic Problem Generation in Constraint-Based Tutors
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QUE: an expert system explanation facility that answers "why not" types of questions
Journal of Computing Sciences in Colleges
An expert system development environment for introductory AI course projects
Journal of Computing Sciences in Colleges
Model-based computer science curricula design
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A Comparison of Model-Tracing and Constraint-Based Intelligent Tutoring Paradigms
International Journal of Artificial Intelligence in Education
Constraint-based Modeling and Ambiguity
International Journal of Artificial Intelligence in Education
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A comparative analysis of cognitive tutoring and constraint-based modeling
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A scalable solution for adaptive problem sequencing and its evaluation
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
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Constraint-based models [7] represent the domain by describing states into which a solution may fall, and testing that solutions in a state are consistent with the problem being solved. Constraints have a relevance condition (which defines the state) and a satisfaction condition (which tests the integrity of the solution.) In this paper we present a purely pattern-based representation for constraints, and describe a method for using it to generate correct solutions based on students' incorrect answers. This method will be used to tailor feedback, by presenting the student with correct examples that most closely match their attempts.