From the October-December 2013 issue
A Multiparadigm Intelligent Tutoring System for Robotic Arm Training
By Philippe Fournier-Viger, Roger Nkambou, Engelbert Mephu Nguifo, André Mayers, and Usef Faghihi
To assist learners during problem-solving activities, an intelligent tutoring system (ITS) has to be equipped with domain knowledge that can support appropriate tutoring services. Providing domain knowledge is usually done by adopting one of the following paradigms: building a cognitive model, specifying constraints, integrating an expert system, and using data mining algorithms to learn domain knowledge. However, for some ill-defined domains, each single paradigm may present some advantages and limitations in terms of the required resources for deploying it, and tutoring support that can be offered. To address this issue, we propose using a multiparadigm approach. In this paper, we explain how we have applied this idea in CanadarmTutor, an ITS for learning to operate the Canadarm2 robotic arm. To support tutoring services in this ill-defined domain, we have developed a multiparadigm model combining: 1) a cognitive model to cover well-defined parts of the task and spatial reasoning, 2) a data mining approach for automatically building a task model from user solutions for ill-defined parts of the task, and 3) a 3D path-planner to cover other parts of the task for which no user data are available. The multiparadigm version of CanadarmTutor allows providing a richer set of tutoring services than what could be offered with previous single paradigm versions of CanadarmTutor.
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IEEE Transactions on Learning Technologies is a joint publication of the IEEE Computer Society and the IEEE Education Society
IEEE Transactions on Learning Technologies is Indexed in ISI.
IEEE Transactions on Learning Technologies (TLT) is an archival journal published quarterly using a delayed open access publication model. TLT covers research on such topics as Innovative online learning systems, Intelligent tutors, Educational software applications and games, and Simulation systems for education and training.
Dr. Peter Brusilovsky
Dr. Mike Sharples