Dynamic guidance for task-based exploratory learning

Authors:
James M. Thomas;R. Michael Young
Affiliations:
Digital Games Research Center, Department of Computer Science, North Carolina State University, Raleigh, NC;Digital Games Research Center, Department of Computer Science, North Carolina State University, Raleigh, NC
Venue:
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Year:
2011

Citing 4
Cited 0

The Behavior of Tutoring Systems

International Journal of Artificial Intelligence in Education
STRIPS: a new approach to the application of theorem proving to problem solving

IJCAI'71 Proceedings of the 2nd international joint conference on Artificial intelligence
Using Task-Based Modeling to Generate Scaffolding in Narrative-Guided Exploratory Learning Environments

Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Annie: Automated Generation of Adaptive Learner Guidance for Fun Serious Games

IEEE Transactions on Learning Technologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes the implementation and evaluation of a new system to guide exploratory learning in arbitrary task-based domains. The system employs a knowledge representation borrowed from the field of automated planning to represent both the exploratory environment and the student's model of the tasks in the environment.