高等药学教育研究 ›› 2025, Vol. 43 ›› Issue (2): 69-80.

• 学科与课程建设 • 上一篇    下一篇

生成式人工智能在课程教学中的实践与思考——以药学类专业物理学课程为例

  

  1. 沈阳药科大学 医疗器械学院,辽宁 本溪 117004
  • 收稿日期:2024-04-27 出版日期:2025-06-25 发布日期:2025-07-07
  • 通讯作者: 支壮志
  • 作者简介:
    孙言(1987-),男(汉族),辽宁沈阳人,讲师,主要从事物理学、电工与电子学课程教学及创新方法应用实践等工作,Tel. 15840254376, E-mail sunyan0612@163.com;
  • 基金资助:
    创新方法工作专项(2020IM030100)

Practice and reflection on generative artificial intelligence in course teachingA case study of the physics course for pharmacy-related majors

  1. School of Medical Devices, Shenyang Pharmaceutical University, Benxi 117004, China
  • Received:2024-04-27 Online:2025-06-25 Published:2025-07-07

摘要:

随着人工智能技术的快速发展,生成式人工智能(AI)在教育领域的应用日益广泛。本研究以药学类专业物理学课程为例,探讨了生成式AI技术,特别是大型语言模型,在课程教学中的实践应用。笔者首先概述了生成式AI技术的发展现状及其在教育领域的应用优势,并结合药学类专业物理学的特点,提出了将AI工具应用于课前准备、课中和课后教学环节的策略。以ChatGPT和智谱清言为例,展示了AI工具在生成教学材料、辅助课堂讨论、提供个性化辅导、批改作业等方面的应用实践,并分析了其带来的积极影响。同时,也指出了AI技术应用中存在的挑战,如:内容准确性、隐私保护等,并提出了相应的对策和建议。最后,展望了生成式AI技术在教育领域的未来发展趋势,强调了其在提升教学质量和学生学习体验方面的巨大潜力。本研究为智慧教育中生成式AI的应用提供了理论参考和实践指导。

关键词: 生成式AI, 物理教学, 智谱清言, ChatGPT, 个性化学习

Abstract:

With the rapid development of artificial intelligence technology, generative AI is being increasingly applied in the field of education. Taking the physics course for pharmacy majors as an example, this study explores the practical application of generative AI technology, especially large language models, in course teaching. The article first outlines the development status of generative AI technology and its advantages in education. Combining the characteristics of physics for pharmacy majors, the article proposes strategies for applying AI tools in the pre-class preparation, in-class teaching, and post-class learning stages. Using ChatGPT and ZhipuQingyan as examples, this paper demonstrates the practical application of AI tools in generating teaching materials, assisting classroom discussion, providing personalized tutoring, and grading assignments, and analyzes their positive impacts. At the same time, the article also points out the challenges such as content accuracy and privacy protection, and puts forward corresponding countermeasures and suggestions. Finally, the article looks forward to the future development trend of generative AI in education, emphasizing its great potential in improving teaching quality and students' learning experience. This study provides theoretical reference and practical guidance for the application of generative AI in smart education.

Key words: generative AI, physics teaching, ZhipuQingyan, ChatGPT, personalized learning

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