The Collaborative Intelligent Mathematics Tutoring Agent Platform
This paper describes the development of a personalized intelligent tutoring agent (ITA) designed to improve the mathematics homework experience for students by catering to individual learning needs, providing instant access to explanatory videos, and conducting assessments that mimic human interaction. This paper explores how large language models can be integrated within an intelligent agent to solve mathematical problems and enhance mathematical reasoning, which can transform traditional approaches in mathematics education. Large-scale language models have the potential to improve personalised learning and problem-solving through AI-enabled tutoring agents. The system consists of two main components: homework process assistance and personalized homework tutoring. The effectiveness of this agent-based system was validated through rigorous testing, demonstrating its potential to significantly improve the quality and efficiency of mathematics education.
Authors
- Jun Shen (ORCID: https://orcid.org/0000-0002-9403-7140)
- Qian Zhao (ORCID: https://orcid.org/0000-0003-4000-1473)
- Fei Xie
- Meng Hao (ORCID: https://orcid.org/0000-0002-1545-1926)
- Xiaosong Wang (ORCID: https://orcid.org/0000-0002-3840-5658)
- Yi Luo (ORCID: https://orcid.org/0000-0002-4065-8937)
Institutions
- Shenyang University of Technology (CN)
- University of Wollongong (AU)
- Shandong Institute of Business and Technology (CN)
Publication Details
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1109/ica63002.2024.00041
- Citations
- 1
- Primary Topic
- Advanced Data Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.33