Exploration Teaching Models in the “Composite Materials” Course Supported by AI Technology

CHAI Juan; XIA Yan; GUO Zheng-hong; YAN Hong-qiang; FANG Zheng-ping

doi:10.14028/j.cnki.1003-3726.2026.26.166

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Exploration Teaching Models in the “Composite Materials” Course Supported by AI Technology

更新时间：2026-10-10

- Exploration Teaching Models in the “Composite Materials” Course Supported by AI Technology
- Polymer Bulletin (2026)
- 作者机构：
  
  浙大宁波理工学院材料科学与工程学院　宁波 315100
- 作者简介：
- 基金信息：
- DOI：10.14028/j.cnki.1003-3726.2026.26.166
  CLC：
- Received：03 April 2026，
  
  Accepted：17 June 2026，
- 稿件说明：
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柴娟, 夏衍, 郭正虹, 闫红强, 方征平. AI技术支撑下“复合材料”课程中的教学模式探索. 高分子通报, doi: 10.14028/j.cnki.1003-3726.2026.26.166

Chai, J.; Xia, Y.; Guo, Z. H.; Yan, H. Q.; Fang, Z. P. Exploration of teaching models in the “Composite Materials” course empowered by AI. Polym. Bull. (in Chinese), doi: 10.14028/j.cnki.1003-3726.2026.26.166
柴娟, 夏衍, 郭正虹, 闫红强, 方征平. AI技术支撑下“复合材料”课程中的教学模式探索. 高分子通报, doi: 10.14028/j.cnki.1003-3726.2026.26.166 DOI：

Chai, J.; Xia, Y.; Guo, Z. H.; Yan, H. Q.; Fang, Z. P. Exploration of teaching models in the “Composite Materials” course empowered by AI. Polym. Bull. (in Chinese), doi: 10.14028/j.cnki.1003-3726.2026.26.166 DOI：

摘要

随着人工智能(AI)技术的飞速发展，高等教育正面临着前所未有的变革机遇。“复合材料”作为材料科学与工程领域的核心课程，具有学科交叉性强、理论抽象、工程实践导向显著等特点，传统教学模式在解决学生“理解难、设计难、实践难”问题上存在局限性。本研究探讨了AI技术在“复合材料”课程教学中的赋能路径，构建了“虚实结合、人机协同、数据驱动”的新型教学模式。通过引入AI助教、生成式AI辅助设计、虚拟仿真实验平台及智能评价系统，有效提升了学生的自主学习能力、工程创新能力及复杂工程问题解决能力，为新材料领域的高素质人才培养提供了新思路。

Abstract

With the rapid development of artificial intelligence (AI) technology

higher education is facing unprecedented opportunities for transformation. As a core course in the field of materials science and engineering

“Composites” features strong interdisciplinarity

theoretical abstraction

and a significant engineering practice orientation. Traditional teaching methods have limitations in addressing students’ difficulties in understanding

designing

and practicing. This study explores the enabling paths of AI technology in the teaching of the “Composite Materials” course and constructs a new teaching model characterized by “virtual-real integration

human-machine collaboration

and data-driven approaches”. By introducing AI teaching assistants

generative AI-assisted design

virtual simulation experiment platforms

and intelligent evaluation systems

it effectively enhances students’ autonomous learning ability

engineering innovation ability

and problem-solving skills for complex engineering issues

providing new ideas for the cultivation of high-quality talents in the field of new materials.

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references

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