Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
This publication covers papers presented at AIED2009, part of an ongoing series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. The conference provides opportunities for the cross-fertilization of techniques from many fields that make up this interdisciplinary research area, including: artificial intelligence, computer science, cognitive and learning sciences, education, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which AIED systems have been designed and evaluated. AIED2009 focuses on the theme "Building learning systems that care: from knowledge representation to affective modelling". The key research question is how to tackle the complex issues related to building learning systems that care, ranging from representing knowledge and context to modelling social, cognitive, metacognitive, and affective dimensions. This requires multidisciplinary research that links theory and technology from artificial intelligence, cognitive science, and computer science with theory and practice from education and the social sciences.
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Affect Metacognition and Motivation
Intelligent Games and Exploratory Learning Environments
Natural Language Processing
Knowledge Representation and Ontological Modeling
Learning Process and Modeling
Modeling Learners and Learning Processes
Collaboration Social Dimensions and Communities
IllDefined Domains and SocioCultural Dimensions
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2009 The authors activities adaptive affective agent algorithm analysis annotated answer approach Artificial Intelligence assessment authors and IOS automatically AutoTutor Cognitive Tutor collaborative learning components concepts correlation data mining developed diagram discussion domain e-learning Ecolab emotions evaluation example experiment feedback Figure goals Hidden Markov Models instruction Intelligence in Education Intelligent Tutoring Systems interaction interface International Conference IOS Press Journal Keywords knowledge Koedinger Latent Semantic Analysis learning environments machine learning metacognitive method misconceptions motivation off-task behavior ontology open learner model participants pedagogical performance post-test pretest problem solving procedural knowledge Proceedings questions representation responses rights reserved scaffolding scenarios Science scores self-regulated learning semantic session simulation skills social solution specific strategies student model Sudoku task teachers Technology theory topic tutorial dialogue types University University of Memphis