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人工智能驱动的传感器与检测技术课程教学改革

Teaching Reform of Sensor and Detection Technology Driven by Artificial Intelligence

  • 摘要: 针对传统传感器与检测技术课程知识滞后、实践浅层化等问题,本研究提出人工智能驱动的传感器课程教学改革。内容上,构建“基础理论—AI融合模块—动态案例库”三级体系,将深度学习、数字孪生等人工智能技术融入传感器核心教学点,支撑教学案例库动态更新。实践环节采用“虚拟仿真→半实物调试→系统集成验证”三阶段模式,评价机制创新“知识—能力—素养”三维体系,引入AI辅助分析实验报告逻辑。实践表明,课程教学改革有效提升了学生系统级问题解决能力。

     

    Abstract: In response to the problems of outdated knowledge and shallow practice in traditional sensor and detection technology courses, this study proposes reform of sensor course driven by artificial intelligence. In terms of content, a three-level system of “basic theory—AI fusion module—dynamic case library” is constructed, integrating artificial intelligence technologies such as deep learning and digital twins into the core teaching points of sensors to support dynamic updates of the teaching case library. The practical stage adopts a three-stage mode of “virtual simulation → semi physical debugging → system integration verification”. The evaluation mechanism has been innovated with a three-dimensional framework of “knowledge— ability— quality”, and AI-assisted analysis of experimental report logic has been introduced. The practice has shown that the curriculum teaching reform has effectively enhanced students’ systematic problem-solving abilities.

     

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