AI赋能教师开发轻量化实验预习资源——以“高锰酸钾标定”为例

doi:10.12461/PKU.DXHX202608019

大学化学

AI赋能教师开发轻量化实验预习资源——以“高锰酸钾标定”为例

陈青, 谢湖均, 韩晓祥, 潘伟春, 张卫斌

浙江工商大学食品与生物工程学院, 浙江杭州 310018

收稿日期:2026-08-05 录用日期:2026-09-28
通讯作者: 陈青 E-mail:qingchenyu001@163.com Qing Chen
基金资助:
浙江省2025年本科省级教学改革项目(JGCG2025129)，浙江省“十四五” 第二批本科省级教学改革项目(JGBA2024831)，浙江工商大学校级教学改革项目(1110XJ0520121-04)

AI-empowered teacher-developed lightweight pre-lab resources: a case on the standardization of potassium permanganate

Qing Chen, Hujun Xie, Xiaoxiang Han, Weichun Pan, Weibin Zhang

School of Food Science and Technology, Zhejiang Gongshang University, Hangzhou 310018, Zhejiang Province, China

Received:2026-08-05 Accepted:2026-09-28
Contact: Qing Chen E-mail:qingchenyu001@163.com

1. DXHX202608019-SI.zip(568KB)

摘要/Abstract

摘要： 虚拟仿真实验是解决化学实验课“预习难”的重要工具，但传统开发模式的高门槛使普通教师难以自主建设符合教学需求的资源。本文以“高锰酸钾标准溶液的标定”实验为例，介绍了不具备编程技能的教师借助人工智能大模型(DeepSeek)自主开发轻量化互动式实验预习资源的实践过程。该模式具有技术门槛低、开发周期短、迭代成本低的特点，为普通教师自主建设交互式实验教学资源提供了可复制的路径参考。

关键词: 人工智能, 交互式, 实验预习, 无机及分析化学实验, 教学资源

Abstract: Virtual simulation experiments serve as an important tool for addressing the issue of inadequate pre-lab preparation in chemistry laboratory courses. However, the high barriers of traditional development models prevent ordinary teachers from independently creating resources that meet their teaching needs. Using the standardization of potassium permanganate standard solution as a case study, this paper describes the practical process through which a chemistry teacher without programming skills independently developed a lightweight interactive pre-lab resource with the assistance of the large language model DeepSeek. This model is characterized by low technical barriers, a short development cycle, and low iteration costs, providing a replicable pathway for ordinary teachers to independently develop interactive experimental teaching resources.

Key words: Artificial intelligence, Interactive, Pre-lab preparation, Inorganic and analytical chemistry laboratory, Teaching resource

陈青, 谢湖均, 韩晓祥, 潘伟春, 张卫斌. AI赋能教师开发轻量化实验预习资源——以“高锰酸钾标定”为例[J]. 大学化学, 2026, (): 2608019.

Qing Chen, Hujun Xie, Xiaoxiang Han, Weichun Pan, Weibin Zhang. AI-empowered teacher-developed lightweight pre-lab resources: a case on the standardization of potassium permanganate[J]. University Chemistry, 2026, (): 2608019.

链接本文: https://www.dxhx.pku.edu.cn/CN/10.12461/PKU.DXHX202608019

https://www.dxhx.pku.edu.cn/CN/Y2026/V/I/2608019

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