Reflections on the Teaching Reform of Polymer Chemistry: Towards Intelligent and Data-driven Approaches

XIE Dan; CHEN Feng-qing; JIANG Bai-yu; XIAO You-hua; LIU Li-na; DAI Jin-feng

doi:10.14028/j.cnki.1003-3726.2025.24.315

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Reflections on the Teaching Reform of Polymer Chemistry: Towards Intelligent and Data-driven Approaches

更新时间：2025-04-29

- Reflections on the Teaching Reform of Polymer Chemistry: Towards Intelligent and Data-driven Approaches
- Polymer Bulletin Vol. 38, Issue 5, Pages: 837-843(2025)
- 作者机构：
  
  浙江农林大学化学与材料工程学院，杭州 311300
- 作者简介：
- 基金信息：
- DOI：10.14028/j.cnki.1003-3726.2025.24.315
  CLC：
- Received：17 October 2024，
  
  Accepted：2025-02-08，
  
  Published Online：07 March 2025，
  
  Published：20 May 2025
- 稿件说明：
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谢丹, 陈风青, 姜柏羽, 肖友华, 刘丽娜, 戴进峰. 基于知识图谱与AI赋能高分子化学的数智化教学思考. 高分子通报, 2025, 38(5), 837–843.

Xie, D.; Chen, F. Q.; Jiang, B. Y.; Xiao, Y. H.; Liu, L. N.; Dai, J. F. Reflections on the teaching reform of polymer chemistry: towards intelligent and data-driven approaches. Polym. Bull. (in Chinese), 2025, 38(5), 837–843.
谢丹, 陈风青, 姜柏羽, 肖友华, 刘丽娜, 戴进峰. 基于知识图谱与AI赋能高分子化学的数智化教学思考. 高分子通报, 2025, 38(5), 837–843. DOI： 10.14028/j.cnki.1003-3726.2025.24.315.

Xie, D.; Chen, F. Q.; Jiang, B. Y.; Xiao, Y. H.; Liu, L. N.; Dai, J. F. Reflections on the teaching reform of polymer chemistry: towards intelligent and data-driven approaches. Polym. Bull. (in Chinese), 2025, 38(5), 837–843. DOI： 10.14028/j.cnki.1003-3726.2025.24.315.

摘要

随着人工智能(AI)技术的发展和深入应用，探索人工智能支持教学和专业发展的需求日益迫切，深入实施AI赋能教育已成为教育数智化改革的一个重要方向。高分子化学课程作为高分子材料与工程专业的核心课程，利用知识图谱以智能化和数字化的方式展开教学，能够弥补传统授课模式中存在的因特教学缺失、理论和实践脱节、教学方式及评价体系单一等不足，对促进高分子化学课程的教学改革和进一步提升培养人才的质量具有积极的意义。

Abstract

With the development and deeper application of artificial intelligence (AI) technology

there is an increasing demand to explore AI-supported teaching and professional development. The in-depth implementation of AI-enabled education has become an important direction in the digital and intelligent transformation of education. As a core course in polymer materials and engineering

polymer chemistry can benefit from the use of knowledge graphs to teach intelligently and digitally. This approach addresses shortcomings of traditional teaching models

such as insufficient interactive teaching

a disconnect between theory and practice

and a limited variety of teaching methods and evaluation systems. This holds significant value for promoting the reform of polymer chemistry teaching and further enhancing the quality of talent cultivation.

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references

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