A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Reusing Web Learning Portfolios by Case-Based Reasoning Technology to Scaffold Problem Solving
ICCE '02 Proceedings of the International Conference on Computers in Education
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Issues and Methods for Evaluating Learner-Centered Scaffolding
ICALT '01 Proceedings of the IEEE International Conference on Advanced Learning Technologies
Mutual disambiguation of 3D multimodal interaction in augmented and virtual reality
Proceedings of the 5th international conference on Multimodal interfaces
Workflow Management: Models, Methods, and Systems
Workflow Management: Models, Methods, and Systems
A multimodal learning interface for sketch, speak and point creation of a schedule chart
Proceedings of the 6th international conference on Multimodal interfaces
An Agent-Supported Multimodal Scaffolding Infrastructure
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
Toward an Affect-Sensitive AutoTutor
IEEE Intelligent Systems
Adaptive and Intelligent Web-based Educational Systems
International Journal of Artificial Intelligence in Education
International Journal of Artificial Intelligence in Education
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Creating a performance-oriented e-learning environment: A design science approach
Information and Management
Current status, opportunities and challenges of augmented reality in education
Computers & Education
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Training individuals from diverse backgrounds and in changing environments requires customized training approaches that align with the individual learning styles and ever-evolving organizational needs. Scaffolding is a well-established instructional approach that facilitates learning by incrementally removing training aids as the learner progresses. By combining multiple training aids (i.e. multimodal interfaces), a trainer, either human or virtual, must make real-time decisions about which aids to remove throughout the training scenario. A significant problem occurs in implementing scaffolding techniques since the speed and choice of removing training aids must be strongly correlated to the individual traits of a specific trainee. We detail an agent-based infrastructure that supports the customization of scaffolding routines as triggered by the performance of the trainee. The motivation for this agent-based approach is for integration into a training environment that leverages augmented reality (AR) technologies. Initial experiments using the simulated environment have compared the proposed adaptive approach with traditional static training routines. Results show that the proposed approach increases the trainees' task familiarity and speed with negligible introduction of errors.