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

Authors
Jaros_aw A. Chudziak,
Adam Kostka
Date
Publisher
arXiv
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.
Study at a glance
  • Question: How can AI math tutors provide structured, personalized learning instead of just giving direct answers?
  • Setting and data: Not stated in the abstract
  • Method: Development and description of a new AI tutoring platform
Why it matters

Current AI tutoring systems are often reactive, providing direct answers without encouraging deep reflection or incorporating structured pedagogical strategies. This limitation is most apparent in mathematics, where AI tutoring systems remain underdeveloped.

Key findings
  • In mathematics, a new AI tutoring platform combines personalized feedback, structured course generation, and textbook content to provide individualized student learning.
  • The system allows students to learn new mathematical topics while actively identifying and targeting their specific areas of weakness.
  • The platform enables students to study effectively for exams by providing an unlimited supply of personalized practice exercises.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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