AI在化学海洋学教学中的赋能研究
Study on Empowering the Teaching of Chemical Oceanography by Artificial Intelligence
DOI: 10.12677/ces.2025.135313, PDF,   
作者: 宋贵生*, 张海彦, 杨 伟：天津大学海洋科学与技术学院，天津
关键词: 化学海洋学；人工智能；教学改革；Chemical Oceanography； Artificial Intelligence； Teaching Reform
摘要: 化学海洋学是海洋科学专业重要的核心课程之一，是一门理论基础与现场实践高度融合的学科。当下传统教材内容滞后、教学形式单一、经费和设备限制等问题制约了教学质量。人工智能(AI)技术的发展为化学海洋学教学提供了新的机遇，有助于打破传统瓶颈，深化海洋类课程教学改革，实现教育模式的创新。利用AI技术，可通过跨学科知识融合、提升数据处理能力和复合型思维培养为化学海洋学教学赋能，强化学生的实践能力。
Abstract: Chemical oceanography is one of the important core courses in Marine Science. It is a discipline that highly integrates theoretical foundations with practice. Currently, issues such as lagging traditional textbook content, monotonous teaching formats, funding and equipment constraints hinder the quality of teaching. The development of Artificial Intelligence (AI) technology provides new opportunities for chemical oceanography teaching, helping to break through traditional bottlenecks, deepen the teaching reform of marine courses, and realize innovations in educational models. By utilizing AI technology, we can empower chemical oceanography teaching through interdisciplinary knowledge integration, enhancement of data processing capabilities and the cultivation of composite thinking, thereby strengthening students’ practical abilities.
文章引用：宋贵生, 张海彦, 杨伟. AI在化学海洋学教学中的赋能研究[J]. 创新教育研究, 2025, 13(5): 91-96. https://doi.org/10.12677/ces.2025.135313

参考文献

[1] 杨伟, 陈儒, 宋贵生, 张海彦. 基于虚拟仿真技术开展海洋综合调查教育的教学设计研究[J]. 创新教育研究, 2023, 11(6): 1288-1294. [Google Scholar] [CrossRef] 
[2] Almasri, F. (2024) Exploring the Impact of Artificial Intelligence in Teaching and Learning of Science: A Systematic Review of Empirical Research. Research in Science Education, 54, 977-997. [Google Scholar] [CrossRef] 
[3] 乔静, 晏茂军, 赵云, 陈文强, 鲍红艳. 虚拟仿真技术在海洋科学实验教学中的应用[J]. 创新教育研究, 2023, 11(7): 2037-2044. [Google Scholar] [CrossRef] 
[4] Xu, W. and Ouyang, F. (2022) The Application of AI Technologies in STEM Education: A Systematic Review from 2011 to 2021. International Journal of STEM Education, 9, Article No. 59. [Google Scholar] [CrossRef] 
[5] Li, X. and Wang, F. (2022) Artificial Intelligence Oceanography. Springer.
[6] Dong, C., Xu, G., Han, G., Bethel, B.J., Xie, W. and Zhou, S. (2022) Recent Developments in Artificial Intelligence in Oceanography. Ocean-Land-Atmosphere Research, 2022, Article ID: 9870950. [Google Scholar] [CrossRef] 
[7] Zhao, C., Wang, K., Jiao, Q., Xu, X., Yi, Y., Li, P., et al. (2024) Machine Learning Models for Evaluating Biological Reactivity within Molecular Fingerprints of Dissolved Organic Matter over Time. Geophysical Research Letters, 51, 1-11. [Google Scholar] [CrossRef] 
[8] 胡耀强. 海洋化学仪器分析授课模式与内容探讨[J]. 广州化工, 2020, 48(17): 153-154, 183.
[9] 褚如心. 生成式人工智能赋能高等教育发展的应用、风险及破解之道[J]. 青年学报, 2024(4): 60-66.
[10] 牛茜如, 陈思, 李琰, 牟林. 学科交叉背景下应用海洋学课程教学改革与实践[J]. 高教学刊, 2024, 10(27): 11-16.
[11] 王蕾, 刘荣, 安鑫龙. 海洋科学专业课程思政体系构建探究[J]. 黑龙江水产, 2025, 44(1): 90-92.
[12] 汤博, 贾欣鑫, 邵秋丽, 宗芳伊. 课程思政融入《海洋化学》教学等探索与实践[J]. 广东化工, 2022, 49(4): 229-230.

为你推荐