iModuleBuddy - a hybrid AI-based academic planning system

Abstract

iModuleBuddy is a study planner that helps postgraduate students create personalized study plans. It combines course recommendation with long-term planning and considers students’ professional background, career goals, and individual study preferences. The system integrates structured data from the ESCO ontology and course descriptions with vector-based similarity methods and retrieval-augmented generation (RAG). A key component is the JobRanking algorithm, which prioritizes courses based on the relevance of a student’s career history. The system uses a multi-agent architecture: one agent aligns professional experience with suitable courses, while another organizes these into a multi-semester plan. Based on user input, iModuleBuddy generates different study plans—career-focused, balanced, and preference-based—along with explanations of how the recommended courses contribute to career development. The system is currently under development, with the career-focused plan already implemented and the other variants in progress.