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人工智能DeepSeek赋能跨学科实验教学——以原电池式湿度传感器的制备与应用为例

郑巍, 凌星月, 吴俊喆, 陆超   

  1. 苏州大学材料与化学化工学部, 江苏 苏州 215123
  • 收稿日期:2026-07-24 录用日期:2026-09-03
  • 通讯作者: 陆超 E-mail:chaolu@suda.edu.cn Chao Lu
  • 基金资助:
    江苏特聘教授(SR10900225)；国家自然科学基金(62404148)；姑苏创新创业领军人才(ZXL2023191)

DeepSeek enhances interdisciplinary laboratory teaching: a case study on the preparation and application of a primary batterytype humidity sensor

Wei Zheng, Xingyue Ling, Junzhe Wu, Chao Lu   

  1. College of Chemistry, Chemical Engineering and Materials Science, Soochow University, Suzhou 215123, Jiangsu Province, China
  • Received:2026-07-24 Accepted:2026-09-03
  • Contact: Chao Lu E-mail:chaolu@suda.edu.cn

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摘要： 顺应“人工智能+教育”深度融合的发展趋势，为有效突破传统实验教学在资源有限、原理抽象、数据分析滞后等方面的局限，本文以“原电池式湿度传感器的制备与应用”实验为例，系统探讨了生成式人工智能模型DeepSeek在跨学科实验教学中的赋能路径与实践价值。本文详细阐述了DeepSeek在智能教案设计、实验原理可视化呈现与实验数据高效分析三个关键教学环节的具体实施过程、操作方法与应用效果，并提出了针对性的应用建议与优化策略。为生成式人工智能与高校实验教学的深度融合、创新转型提供了可操作、可推广的实践范例，助力培养适应智能时代的复合型人才。

关键词: DeepSeek, 实验教学, 湿度传感器, 原理动画, Python

Abstract: In response to the growing trend of deep integration between artificial intelligence and education, and to effectively overcome the limitations of traditional laboratory teaching—such as constrained resources, abstract principles, and delayed data analysis—this study takes the experiment “Preparation and Application of a Primary Battery-Type Humidity Sensor” as a case study to systematically explore the pathways and practical value of the generative AI model DeepSeek in empowering interdisciplinary laboratory teaching. The study elaborates on the specific implementation processes, operational methods, and application outcomes of DeepSeek in three key teaching stages: intelligent lesson plan design, visualized presentation of experimental principles, and efficient analysis of experimental data. It also proposes targeted application recommendations and optimization strategies. This work provides an actionable and scalable practical example for the deep integration and innovative transformation of generative AI and university laboratory teaching, thereby supporting the cultivation of interdisciplinary talents equipped for the intelligent era.

Key words: DeepSeek, Laboratory teaching, Humidity sensor, Animated visualization, Python