A model for reasoning about persistence and causation
Computational Intelligence
The effectiveness of games for educational purposes: a review of recent research
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Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
Inferring user goals from personality and behavior in a causal model of user affect
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Evaluating an Animated Pedagogical Agent
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Limitations of Student Control: Do Students Know When They Need Help?
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TACOP: a cognitive agent for a naval training simulation environment
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A focused learning environment for Eclipse
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Making dead history come alive through mobile game-play
CHI '07 Extended Abstracts on Human Factors in Computing Systems
Socializing Pedagogical Agents for Personalization in Virtual Learning Environments
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A multifactor approach to student model evaluation
User Modeling and User-Adapted Interaction
Sudoku access: a sudoku game for people with motor disabilities
Proceedings of the 10th international ACM SIGACCESS conference on Computers and accessibility
The common sense-based educational quiz game framework "What is it?"
Proceedings of the VIII Brazilian Symposium on Human Factors in Computing Systems
Cross-Cultural Evaluation of Politeness in Tactics for Pedagogical Agents
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Modelling Learning in an Educational Game
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
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Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Empirically building and evaluating a probabilistic model of user affect
User Modeling and User-Adapted Interaction
Modeling User Affect from Causes and Effects
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Evaluating Adaptive Feedback in an Educational Computer Game
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Adaptive Feedback in an Educational Game for Number Factorization
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Bringing tabletop technologies to kindergarten children
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Re-experiencing history in archaeological parks by playing a mobile augmented reality game
OTM'07 Proceedings of the 2007 OTM confederated international conference on On the move to meaningful internet systems - Volume Part I
Detecting and modeling play behavior using sensor-embedded rock-climbing equipment
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Multiple agent roles in an adaptive virtual classroom environment
IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
Developing a template-based edutainment system
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Innovative integrated architecture for educational games: challenges and merits
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HPCS'09 Proceedings of the 23rd international conference on High Performance Computing Systems and Applications
Data-Driven refinement of a probabilistic model of user affect
UM'05 Proceedings of the 10th international conference on User Modeling
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Expert Systems with Applications: An International Journal
The effects of adaptive sequencing algorithms on player engagement within an online game
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
AEGS'11 Proceedings of the 2011 international conference on Agents for Educational Games and Simulations
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International Journal of Distance Education Technologies
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Electronic educational games can be highly entertaining, but studies have shown that they do not always trigger learning. To enhance the effectiveness of educational games, we propose intelligent pedagogical agents that can provide individualized instruction integrated with the entertaining nature of the games. In this paper, we describe one such agent, that we have developed for Prime Climb, an educational game on number factorization. The Prime Climb agent relies on a probabilistic student model to generate tailored interventions aimed at helping students learn number factorization through the game. After describing the functioning of the agent and the underlying student model, we report the results of an empirical study that we performed to test the agent's effectiveness.