AI-Powered Math Tutoring: Platform for Personalized and Adaptive Education

TL;DR

This paper introduces a multi-agent AI tutoring platform for mathematics that offers personalized, structured, and tool-assisted learning experiences, addressing limitations of reactive AI systems and enhancing educational effectiveness.

Contribution

It presents a novel modular platform combining pedagogical agents, adaptive feedback, and knowledge retrieval to improve AI-driven math education.

Findings

Enables students to identify and target weaknesses effectively

Supports unlimited personalized exercises for practice

Facilitates structured, exam-revision, and deep learning processes

Abstract

The growing ubiquity of artificial intelligence (AI), in particular large language models (LLMs), has profoundly altered the way in which learners gain knowledge and interact with learning material, with many claiming that AI positively influences their learning achievements. Despite this advancement, current AI tutoring systems face limitations associated with their reactive nature, often providing direct answers without encouraging deep reflection or incorporating structured pedagogical tools and strategies. This limitation is most apparent in the field of mathematics, in which AI tutoring systems remain underdeveloped. This research addresses the question: How can AI tutoring systems move beyond providing reactive assistance to enable structured, individualized, and tool-assisted learning experiences? We introduce a novel multi-agent AI tutoring platform that combines adaptive and personalized feedback, structured course generation, and textbook knowledge retrieval to enable modular, tool-assisted learning processes. This system allows students to learn new topics while identifying and targeting their weaknesses, revise for exams effectively, and practice on an unlimited number of personalized exercises. This article contributes to the field of artificial intelligence in education by introducing a novel platform that brings together pedagogical agents and AI-driven components, augmenting the field with modular and effective systems for teaching mathematics.