A model for reasoning about persistence and causation
Computational Intelligence
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
DT Tutor: A Decision-Theoretic, Dynamic Approach for Optimal Selection of Tutorial Actions
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Fearnot!: an experiment in emergent narrative
Lecture Notes in Computer Science
Creating Rapport with Virtual Agents
IVA '07 Proceedings of the 7th international conference on Intelligent Virtual Agents
Assessing Aptitude for Learning with a Serious Game for Foreign Language and Culture
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Optimizing story-based learning: an investigation of student narrative profiles
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part II
Integrating learning and engagement in narrative-centered learning environments
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part II
Narrative-Centered tutorial planning for inquiry-based learning environments
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Real-Time narrative-centered tutorial planning for story-based learning
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
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Interactive narrative-centered learning environments offer significant potential for scaffolding guided discovery learning in rich virtual storyworlds while creating engaging and pedagogically effective experiences. Within these environments students actively participate in problem-solving activities. A significant challenge posed by narrative-centered learning environments is devising accurate models of narrative-centered tutorial decision making to craft customized story-based learning experiences for students. A promising approach is developing empirically driven models of narrative-centered tutorial decision-making. In this work, a dynamic Bayesian network has been designed to make narrative-centered tutorial decisions. The network parameters were learned from a corpus collected in a Wizard-of-Oz study in which narrative and tutorial planning activities were performed by humans. The performance of the resulting model was evaluated with respect to predictive accuracy and yields encouraging results.