Multi-agent system for computer science and engineering education - Meleško, Jaroslav; Kurilovas, Eugenijus; Krikun, Irina (Lietuvos matematikos rinkinys, 2017)
The paper aims to analyse application trends of intelligent multi-agent systems to personalise learning. First of all, systematic literature review was performed. Based on the systematic review analysis, the main trends on applying multi-agent systems to personalise learning were identified. Second, main requirements and components for an educational multi-agent system were formulated. Third, based on these components a model of intelligent personalized system is proposed. The system employs five intelligent agents: (1) learning styles identification software agent, (2) learner profile creation software agent, (3) pedagogical suitability software agent, (4) optimal learning units/scenarios creation software agent, and (5) learning analytics/educational data mining software agent.
Keywords: educational data mining; learning analytics; learning personalisation; systematic literature review; personalised recommendations