The research presented links theory and technology from artificial intelligence, cognitive science, and computer science with theory and practice from education and social science to bring a wide range of tools to bear on the task of creating systems to help people learn.
The 13th International Conference on Artificial Intelligence in Education (AIED 2007) is in an ongoing series of biennial international conferences for top quality research in cognitive science and intelligent systems for educational computing applications.
The conference thus provides opportunities for the cross-fertilization of information and ideas from researchers in the many fields that make up this interdisciplinary research area, including: artificial intelligence, other areas of computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which AIED systems have been designed and built.
TOPICS
The technical program focuses on research linking theory and technology from artificial intelligence, cognitive science, and computer science with theory and practice from education and social science. Areas of interest include, but are not limited to: Socially informed design: Social dimensions of learning. Social-historical-cultural contexts. Learning and identity. Motivation and engagement in learning. Informal learning environments. Collaborative and group learning: Group learning environments. Networked learning communities. Analysis and modeling of group interactions. Design principles for collaborative learning environments. Communities of learners. Communities of practice. Learning systems platforms and architectures: Web based learning platforms. Metadata standards for learning objects and materials. Document management for learning applications. Authoring tools and assessment tools. Modeling and representation: Models of learners, facilitators, tasks and problem-solving processes. Knowledge representation and ontologies. Discourse representation and analysis. Intelligent tutoring and scaffolding: Adaptive environments (web-based and others). Pedagogical agents. Cognitive diagnosis. Instructional planning. Motivational diagnosis and feedback. Data mining and machine learning. Interaction design and novel interfaces: Ubiquitous computing/mixed reality learning environments. Virtual and 3D learning and training environments. Multi-modal interfaces for learning. Educational multimedia systems. Special application fields: Language learning. Mathematics and science education. Industrial, medical and other applications.Methods, tools and techniques for effective evaluation of cognitive, meta-cognitive and affective issues. The design and modeling of learning contexts and their impact on learning. The development of systems that encompass multiple learning contexts, including mobile learning applications