Inferring user goals from personality and behavior in a causal model of user affect
Proceedings of the 8th international conference on Intelligent user interfaces
Informing the Detection of the Students' Motivational State: An Empirical Study
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Evaluating Bayesian networks' precision for detecting students' learning styles
Computers & Education
Controlling Transparency in an Online Learning Environment
VLHCC '07 Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing
Developing a generalizable detector of when students game the system
User Modeling and User-Adapted Interaction
eTeacher: Providing personalized assistance to e-learning students
Computers & Education
Modeling Students' Natural Language Explanations
UM '07 Proceedings of the 11th international conference on User Modeling
Affect and Usage Choices in Simulation Problem-Solving Environments
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Towards Predictive Modelling of Student Affect from Web-Based Interactions
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Motivationally Intelligent Systems: Diagnosis and Feedback
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
An Efficient Student Model Based on Student Performance and Metadata
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
A dynamic mixture model to detect student motivation and proficiency
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Affect-aware tutors: recognising and responding to student affect
International Journal of Learning Technology
Log file analysis for disengagement detection in e-Learning environments
User Modeling and User-Adapted Interaction
Educational Software Features that Encourage and Discourage “Gaming the System”
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Motivational Diagnosis in ITSs: Collaborative, Reflective Self-Report
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
User models for adaptive hypermedia and adaptive educational systems
The adaptive web
Building group recommendations in e-learning systems
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Adaptive e-learning using ECpAA rules, Bayesian models, and group profile and performance data
International Journal of Learning Technology
An analysis of students' gaming behaviors in an intelligent tutoring system: predictors and impacts
User Modeling and User-Adapted Interaction
Towards Systems That Care: A Conceptual Framework based on Motivation, Metacognition and Affect
International Journal of Artificial Intelligence in Education
Modeling mental workload using EEG features for intelligent systems
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Modeling engagement dynamics in spelling learning
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
The fine-grained impact of gaming (?) on learning
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
Building Intelligent Interactive Tutors: Student-centered strategies for revolutionizing e-learning
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Adapting to when students game an intelligent tutoring system
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Generalizing detection of gaming the system across a tutoring curriculum
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
International Journal of Artificial Intelligence in Education - Special issue on Best of ITS 2010
Enhancing the automatic generation of hints with expert seeding
International Journal of Artificial Intelligence in Education - Special issue on Best of ITS 2010
Building group recommendations in e-learning systems
Transactions on Computational Collective Intelligence VII
Cross-system validation of engagement prediction from log files
EC-TEL'07 Proceedings of the Second European conference on Technology Enhanced Learning: creating new learning experiences on a global scale
Towards a Framework for Modelling Engagement Dynamics in Multiple Learning Domains
International Journal of Artificial Intelligence in Education - Best of AIED 2011
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A student's goals and attitudes while interacting with a tutor are typically unseen and unknowable. However their outward behavior (e.g. problem-solving time, mistakes and help requests) is easily recorded and can reflect hidden affect status. This research evaluates the accuracy of a Bayesian Network to infer a student's hidden attitude toward learning, amount learned and perception of the system from log-data. The long term goal is to develop tutors that self-improve their student models and their teaching, dynamically can adapt pedagogical decisions about hints and help improve student's affective, intellectual and learning situation based on inferences about their goals and attitude.