野外观测及采样与室内实验分析能力是海洋工程与技术专业学生从事科学研究必备重要技能,也是培养方案对本科生培养提出的关键要求。本研究以海岸水质遥感智能探测实验课程为案例,探讨将野外与室内实验相结合的教学模式,旨在提升学生野...野外观测及采样与室内实验分析能力是海洋工程与技术专业学生从事科学研究必备重要技能,也是培养方案对本科生培养提出的关键要求。本研究以海岸水质遥感智能探测实验课程为案例,探讨将野外与室内实验相结合的教学模式,旨在提升学生野外获取实验样品与室内样品处理分析综合能力。在该教学模式中,学生通过采集野外水样和获取遥感数据,在实验室进行水质测量和光谱分析,最终利用遥感数据处理软件进行数据处理和分析。这一过程强化了学生的实践操作能力、创新思维和综合分析能力。该模式在提高学生的理论与实践结合能力方面进行了创新性的尝试,可为其他工程类专业课程的教学改革提供参考。Field observation, sample collection and laboratory experiment skills are crucial for students majoring in ocean engineering and technology when engaging in scientific research, and they are key requirements in undergraduate training programs. “Remote Sensing Coastal Water Quality Intelligent Detection Experiment” course is designed as a case study to explore a teaching pattern that integrates field and laboratory experiments, aimed at enhancing students’ abilities in water samples collection in the field and sample analysis in the laboratory. In the course, students firstly collect water samples and obtain remote sensing data in the field, then return to the laboratory for water quality measurement and spectroscopic analysis, and finally use software for data processing and analysis to retrieve the spatial distribution of water quality from remote sensing data. This entire process could strengthen students’ practical operational skills, innovative thinking, and comprehensive analytical abilities. This course represents an innovative attempt to enhance students’ ability to integrate theory and practice, and can provide a reference for courses in other engineering disciplines.展开更多
文摘野外观测及采样与室内实验分析能力是海洋工程与技术专业学生从事科学研究必备重要技能,也是培养方案对本科生培养提出的关键要求。本研究以海岸水质遥感智能探测实验课程为案例,探讨将野外与室内实验相结合的教学模式,旨在提升学生野外获取实验样品与室内样品处理分析综合能力。在该教学模式中,学生通过采集野外水样和获取遥感数据,在实验室进行水质测量和光谱分析,最终利用遥感数据处理软件进行数据处理和分析。这一过程强化了学生的实践操作能力、创新思维和综合分析能力。该模式在提高学生的理论与实践结合能力方面进行了创新性的尝试,可为其他工程类专业课程的教学改革提供参考。Field observation, sample collection and laboratory experiment skills are crucial for students majoring in ocean engineering and technology when engaging in scientific research, and they are key requirements in undergraduate training programs. “Remote Sensing Coastal Water Quality Intelligent Detection Experiment” course is designed as a case study to explore a teaching pattern that integrates field and laboratory experiments, aimed at enhancing students’ abilities in water samples collection in the field and sample analysis in the laboratory. In the course, students firstly collect water samples and obtain remote sensing data in the field, then return to the laboratory for water quality measurement and spectroscopic analysis, and finally use software for data processing and analysis to retrieve the spatial distribution of water quality from remote sensing data. This entire process could strengthen students’ practical operational skills, innovative thinking, and comprehensive analytical abilities. This course represents an innovative attempt to enhance students’ ability to integrate theory and practice, and can provide a reference for courses in other engineering disciplines.
