Research on the Application of Large Language Models in Intelligent Tutoring System

DOI

10.2991/978-94-6463-823-3_97How to use a DOI?

Keywords

Large Language Models; Education; Intelligent tutoring systems; Artificial intelligence; Personalized learning

Abstract

With the breakthrough development of artificial intelligence technology, the Large Language Models centered on transformer architecture is implementing intelligent transformation for the education field by virtue of its deep semantic understanding and dynamic content generation and interaction capability. In this paper, I focus on the generation mechanism of the big source model, in order to analyze how the Large Language Models generates suitable teaching content for learners through the pre-training of its self-attention mechanism and the integration of massive data, this paper selects three typical cases of its intelligent tutoring system in educational scenarios, namely, MWPTutor (guiding the generation of content and interaction with the Large Language Models through the structural teaching framework), Sociedad Playground (guiding the generation of content and interaction with students through the structural teaching framework), and MWPTutor (guiding the generation of content and interaction with the Large Language Models). The cases are MWPTutor (guiding the Large Language Models to generate content and students through a structured teaching framework), Socratic Playground (enhancing students’ independent judgmental thinking through the form of follow-up questions), and Slide2Lecture (automatically converting PPT courseware into interactive lessons). Cases show that the Large Language Models is transforming traditional education into intelligent education by virtue of its excellent interactive capability, learning behavior analysis capability and resource generation capability, lowering the threshold of popularization of high-quality education while guaranteeing the quality of teaching and learning, which will reshape the global education ecosystem in the future.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Chenyao Xia
PY  - 2025
DA  - 2025/08/31
TI  - Research on the Application of Large Language Models in Intelligent Tutoring System
BT  - Proceedings of the 2025 3rd International Conference on Image, Algorithms, and Artificial Intelligence (ICIAAI 2025)
PB  - Atlantis Press
SP  - 993
EP  - 1003
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-823-3_97
DO  - 10.2991/978-94-6463-823-3_97
ID  - Xia2025
ER  -