
 
achievement level of the activity, etc. Alerts are sent 
when something abnormal occurs. 
4 ACCOMPLISHMENTS AND 
FUTURE WORK 
We have chosen to deploy the system on the Madkit 
multi-agents platform because it is intended for the 
development and the execution of multi-agents 
systems and more particularly those based on 
organizational criteria.  
The MaSE methodology and the deployment of 
communication mechanisms on the Madkit platform 
allowed us to test the feasibility of the multi-agent 
system for the observation of the learning system 
and to validate our conceptual approach. 
Several issues remain to be explored and 
implemented. This includes the development of 
mechanisms to make the device more autonomous 
and proactive. Thus, the environment would be able 
to prevent the teacher and the students when a group 
has a bursting risk or is in a position of educational 
failure. Collecting interaction traces of different 
users does this. 
Analysis of these traces is used to provide four 
types of assessments: 
•  A group level assessment: status related to the 
implementation of educational activities and to its 
members’ status (present, absent, inactive). The 
group supervisor agent that resides on the server 
carries out this assessment. 
•  A student level assessment: assessing his/her 
productivity related to the realization of the 
pedagogical activities, his/her sociability that 
indicates his/her communication level with other 
members of the group. An inactive user connects to 
the platform only to read messages.  
•  An activity level assessment: indicating the level 
of achievement of an activity by the group. 
•  A teacher level assessment: evaluating the 
predictive pedagogical scenario compared to the 
effective scenario. This agent will interact with the 
evaluation module of the MACADDAM studio. 
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