Adaptive multi-agent architecture to track students' self-regulated learning

Intelligent Tutoring Systems (ITS) can be designed to improve learning and performance through Pedagogical Agents (PAs) that are designed to foster self-regulated learning through interactions and exchange of information with human learners. PAs are intelligent and follow rational behaviors, but to adaptively track students' progress, they need to be systematically and specifically designed. However, in order to follow a common goal, different self-regulatory systems have been designed that use PAs, but fail to provide an adaptive multi-agent architecture which provides such feature that agents adaptively track students' scaffolding. In this paper, we introduce a multi-agent framework designed for an agent-based ITS. We also define the agent architecture, multi-agent framework and communication mechanism.