ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Constraint-Based Tutors: A Success Story
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Evaluating Spatial Representations and Skills in a Simulator-Based Tutoring System
IEEE Transactions on Learning Technologies
Mechanisms for human spatial competence
SC'06 Proceedings of the 2006 international conference on Spatial Cognition V: reasoning, action, interaction
The cognitive tutor authoring tools (CTAT): preliminary evaluation of efficiency gains
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
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To build an intelligent tutoring system, a key task is to define an expertise model that can support appropriate tutoring services. However, for some ill-defined domains, classical approaches for representing expertise do not work well. To address this issue, we illustrate in this paper a novel approach which is to combine several approaches into a hybrid model to support tutoring services in procedural and ill-defined domains. We illustrate this idea in a tutoring system for operating Canadarm2, a robotic arm installed on the international space station. To support tutoring services in this ill-defined domain, we have developed a model combining three approaches: (1) a data mining approach for automatically building a task model from user solutions, (2) a cognitive model to cover well-defined parts of the task and spatial reasoning, (3) and a 3D path-planner to cover all other aspects of the task. Experimental results show that the hybrid model allows providing assistance to learners that is much richer than what could be offered by each individual approach.