LLM-powered Multi-agent Framework for Goal-oriented Learning in Intelligent Tutoring System

TL;DR

This paper introduces GenMentor, an LLM-powered multi-agent framework for goal-oriented, personalized learning in Intelligent Tutoring Systems, improving targeted education through dynamic goal mapping, optimized learning paths, and tailored content.

Contribution

The paper presents a novel framework that integrates LLMs with multi-agent systems to enhance goal-oriented learning in ITS, including goal mapping, adaptive scheduling, and personalized content generation.

Findings

GenMentor effectively maps learner goals to skills.

It optimizes learning paths based on dynamic learner profiles.

Human studies show improved personalization and goal alignment.

Abstract

Intelligent Tutoring Systems (ITSs) have revolutionized education by offering personalized learning experiences. However, as goal-oriented learning, which emphasizes efficiently achieving specific objectives, becomes increasingly important in professional contexts, existing ITSs often struggle to deliver this type of targeted learning experience. In this paper, we propose GenMentor, an LLM-powered multi-agent framework designed to deliver goal-oriented, personalized learning within ITS. GenMentor begins by accurately mapping learners' goals to required skills using a fine-tuned LLM trained on a custom goal-to-skill dataset. After identifying the skill gap, it schedules an efficient learning path using an evolving optimization approach, driven by a comprehensive and dynamic profile of learners' multifaceted status. Additionally, GenMentor tailors learning content with an exploration-drafting-integration mechanism to align with individual learner needs. Extensive automated and human evaluations demonstrate GenMentor's effectiveness in learning guidance and content quality. Furthermore, we have deployed it in practice and also implemented it as an application. Practical human study with professional learners further highlights its effectiveness in goal alignment and resource targeting, leading to enhanced personalization. Supplementary resources are available at https://github.com/GeminiLight/gen-mentor.