Improving Study Planning with an Agent-based System

This paper presents a system for designing and updating a personalized study plan in a collaborative environment. Unlike existing systems, which are mainly interested in storing the study plan, this system based on learning agents is able to suggest a study plan and if needed, identify potentially problematic choices in the future, thus bringing dynamics in to the system. By collaborating with other agents in a multi-agent environment, the chances of finding a mutually beneficial result is improved. A prototype of the system for creating study plans is available. Initial empirical results show that after a short learning period, the system is able to form a study plan which requires minimal attention from the students.