创新创业理论研究与实践 ›› 2024, Vol. 7 ›› Issue (17): 43-47.

• 教学革新 • 上一篇    下一篇

项目式人工智能实验课程教学模式设计

周琼   

  1. 贵州商学院,贵州贵阳 550014
  • 出版日期:2024-09-10 发布日期:2024-11-28
  • 作者简介:周琼(1992—),女,贵州黔西人,硕士研究生,助教,研究方向:人工智能、医学图像数据挖掘。
  • 基金资助:
    贵州商学院2023年度教育教学研究与改革项目“OBE视阈下人工智能课程教学模式改革研究”(2023XJJG18); 贵州省教育厅自然科学研究—青年科技人才成长项目“基于深度学习的医学图像分类算法研究”(黔教合KY〔2022〕328)

Design of Teaching Mode for Project-Based Artificial Intelligence Experimental Courses

ZHOU Qiong   

  1. Guizhou University of Commerce, Guiyang Guizhou, 550014, China
  • Online:2024-09-10 Published:2024-11-28

摘要: 项目式人工智能实验课程教学模式以学生为中心,依据人工智能项目的开发流程,把实际生产的各环节引入课堂教学,利用课程算法设计符合实际生产场景的实验教学案例,探讨人工智能实验课程的教学内容、教学模式及考核机制。该文以AlexNet模型对脑部肿瘤医学图像的分类识别为例探讨项目式课程教学模式的设计过程,使用人工智能算法解决社会实际问题的实验案例不仅能有效激发学生的学习热情,也能培养学生独立解决实际问题的综合能力和自主学习能力。

关键词: 人工智能, 项目式教学, 考核机制, 创新实验, AlexNet, 医学图像

Abstract: The mode of project-based artificial intelligence experiment courses are student-centered. According to the development process of artificial intelligence projects, various stages of actual production will be incorporated into classroom teaching. To explore the teaching method, teaching content and assessment mechanism of innovative artificial intelligence experiment courses, the experimental teaching cases that meet the actual production scenario are designed by using the course algorithm. Taking AlexNet for brain tumor medical image classification and recognition as an example, this paper discusses the design process of project-based course teaching mode. The experimental cases of using artificial intelligence algorithm to solve social practical problems can not only effectively stimulate students'learning enthusiasm, but also cultivate students'comprehensive ability to solve practical problems independently and independent learning ability.

Key words: Artificial intelligence, Project-based teaching, Evaluation mechanism, Innovative experiment, AlexNet, Medical imaging

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