The phenotype of erroneous actions
International Journal of Man-Machine Studies
Modelling the Knowledge-Based Components of a Learning Environment within the Task/Method Paradigm
ITS '98 Proceedings of the 4th International Conference on Intelligent Tutoring Systems
Accounting for context in plan recognition, with application to traffic monitoring
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Automatic system for the detection and analysis of errors to support the personalized feedback
Expert Systems with Applications: An International Journal
Human factors affecting decision in virtual operator reasoning
BI'09 Proceedings of the 2009 international conference on Brain informatics
An expert system manipulating knowledge to help human learners into virtual environment
Expert Systems with Applications: An International Journal
Proposing the underlying causes that lead to the trainee's erroneous actions to the trainer
EC-TEL'07 Proceedings of the Second European conference on Technology Enhanced Learning: creating new learning experiences on a global scale
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When a tutoring system aims to provide learners with accurate and appropriate help and assistance, it needs to know what goals the learner is currently trying to achieve, what plans he is implementing and what errors he is making. That is, it must do both plan recognition and error detection. In this paper, we propose a generic framework which supports two main issues (i) the detection of learner's unexpected behavior by using the Hollnagel classification of erroneous actions and (ii) a recognition process based on a task model METISSE that we propose. This model, which is used to describe the tasks the learner has to do according to pedagogical goals, allows learner's unexpected behavior to be detected. The solutions proposed are generic because not dependent on the domain task, and they do not relate to a particular device.