大学化学 >> 2025, Vol. 40 >> Issue (5): 244-251.doi: 10.12461/PKU.DXHX202406035

教学研究与改革 上一篇    下一篇

将理论和实践深度融合的研究性教学模式全过程探索——以“白醋总酸含量的测定”自主设计方案为例

王利平, 王焕锋, 李玉玲, 李领川, 李晓静, 陈会锋, 姬博文, 王琳娜   

  1. 郑州工程技术学院食品与化工学院, 郑州 450044
  • 收稿日期:2024-06-11 修回日期:2024-09-02 发布日期:2025-05-21
  • 通讯作者: 王利平 E-mail:hdwlp@163.com
  • 基金资助:
    2022年河南省教育厅本科高校研究性教学改革研究与实践项目(教高[2023]36号,2022SYJXLX121,2022SYJXLX122);2024年度河南省教育教学改革项目(教高[2024]146号,2024SJGLX0566,2024SJGLX0569);2024年度郑州工程技术学院教育教学改革研究与实践项目(本科高等教育类)(郑工行办[2024]2号,ZGJG202405A);2022年河南省教育厅本科高校研究性教学示范课程(教高[2023]36号,127);河南省青年骨干教师培养计划(教办高[2023]440号,2023GGJS183)

Exploring the Full Process of a Research-Based Teaching Model through the Deep Integration of Theory and Practice: A Case Study of the Self-Designed Scheme for “Determination of Total Acid Content in White Vinegar”

Liping Wang, Huanfeng Wang, Yuling Li, Lingchuan Li, Xiaojing Li, Huifeng Chen, Bowen Ji, Linna Wang   

  1. College of Food and Chemical, Zhengzhou University of Technology, Zhengzhou 450044, China
  • Received:2024-06-11 Revised:2024-09-02 Published:2025-05-21
  • Contact: Liping Wang E-mail:hdwlp@163.com

摘要: 借助研究手段,将理论与实践课程内容深度融合,对我校大学一年级学生的分析化学课程进行了多维度研究性教学模式改革。此模式有效提升了学生的主动学习能力,培养了他们处理信息和解决实际问题能力,促进了从浅层学习向深度学习的转变。希望为化学基础知识不系统,研究能力薄弱的低年级学生进行研究性教学提供些许参考。

关键词: 研究性教学, 深度学习, 课堂改革

Abstract: This study employs research-based methods to deeply integrate theoretical knowledge with practical applications, leading to a multi-dimensional reform of the research-based teaching model in the analytical chemistry course for first-year undergraduate students at our university. This approach has been shown to effectively enhance students' active learning capabilities, foster their skills in information processing and problem-solving, and facilitate the transition from surface learning to deep learning. The findings aim to offer insights for implementing research-based teaching strategies for lower-year students with limited systematic knowledge of chemistry and underdeveloped research skills.

Key words: Research-based teaching, Deep learning, Classroom reform