Automatic symbolic traffic scene analysis using belief networks
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
Implementation of motivational tactics in tutoring systems
Journal of Artificial Intelligence in Education
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Simulation Approaches to General Probabilistic Inference on Belief Networks
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
A Belief Net Backbone for Student Modelling
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Two-Phase Updating of Student Models Based on Dynamic Belief Networks
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
Human Problem Solving
Why is diagnosis using belief networks insensitive to imprecision in probabilities?
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
Inferring user goals from personality and behavior in a causal model of user affect
Proceedings of the 8th international conference on Intelligent user interfaces
Media-on-Demand for Agent-Based Collaborative Tutoring Systems on the Web
PCM '02 Proceedings of the Third IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Probabilistic Student Modelling to Improve Exploratory Behaviour
User Modeling and User-Adapted Interaction
Temporal Relevance in Dynamic Decision Networks with Sparse Evidence
Applied Intelligence
U-director: a decision-theoretic narrative planning architecture for storytelling environments
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A student-oriented physics e-tutorial system
ICCOMP'05 Proceedings of the 9th WSEAS International Conference on Computers
Preference-based decision making for personalised access to Learning Resources
International Journal of Autonomous and Adaptive Communications Systems
Looking Ahead to Select Tutorial Actions: A Decision-Theoretic Approach
International Journal of Artificial Intelligence in Education
Affect-aware tutors: recognising and responding to student affect
International Journal of Learning Technology
Evaluating an affective student model for intelligent learning environments
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
Modeling narrative-centered tutorial decision making in guided discovery learning
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Affective support in narrative-centered learning environments
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Using similarity to infer meta-cognitive behaviors during analogical problem solving
UM'05 Proceedings of the 10th international conference on User Modeling
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Scaffolding problem solving with annotated, worked-out examples to promote deep learning
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
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DT Tutor uses a decision-theoretic approach to select tutorial actions for coached problem solving that are optimal given the tutor's beliefs and objectives. It employs a model of learning to predict the possible outcomes of each action, weighs the utility of each outcome by the tutor's belief that it will occur, and selects the action with highest expected utility. For each tutor and student action, an updated student model is added to a dynamic decision network to reflect the changing student state. The tutor considers multiple objectives, including the student's problem-related knowledge, focus of attention, independence, and morale, as well as action relevance and dialog coherence. Evaluation in a calculus domain shows that DT Tutor can select rational and interesting tutorial actions for real-world-sized problems in satisfactory response time. The tutor does not yet have a suitable user interface, so it has not been evaluated with human students.