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In this paper we present our approach in the field of Intelligent Tutoring System (ITS), in fact the risk of dropping out for learners have emerged as crucial issues to be solved. So it is necessary to ensure an individualized and continuous learner's follow-up during learning process. Several research effort has been spent on the development of ITS. However the available literature does not generally concentrate on the individual realtime continuous follow up of learners. Our contribution in this field is to design and implement a computer system able to initiate learning and provide an individualized monitoring of learners. This approach involves 1) the use of Dynamic Case Based Reasoning to retrieve the past experiences that are similar to the learners' traces (traces in progress), and 2) the use of Multi-Agents System. Our Work focuses on the use of the learner traces. When interacting with the platform, every learner leaves his/her traces in the machine. The traces are stored in database, this operation enriches collective past experiences. Via monitoring, comparing and analyzing these traces, the system keeps a constant intelligent watch on the platform, and therefore it detects the difficulties hindering progress, and it avoids possible dropping out. The system can support any learning subject.
Zouhair et al. (Wed,) studied this question.