数智时代地理数据科学课程“轻量级模拟实验”设计与实践

Design and Practice of “Lightweight Simulation Experiments” for Geography Data Analysis Courses in the Digital and Intelligent Era

  • 摘要: 在数智时代和对地观测技术蓬勃发展背景下,地理时空大数据的迅速积累与地理学思想方法、技术模型的不断创新,共同推动了地理学理论和地理产业发展。地理数据科学课程承担着培养地理学创新性人才计算思维的重任。然而,目前该系列课程的实验设计存在三大问题:难度梯度不合理、实践动手能力培养不足、学科交叉性薄弱。在地理时空大数据与人工智能深度耦合的数智化背景下,传统地理数据科学课程的实验设计问题进一步凸显,具体表现为实验数据维度单薄、技能训练链断裂与学科交叉薄弱三重困境。本文创新性地提出基于物联网传感矩阵的轻量级模拟实验模式,通过构建地理环境多要素(光、温、湿、风)的实时数据采集系统,借助Arduino开发框架实现“传感端-云端-算法端”全流程训练,通过集成AI工具(如神经网络、分类模型)实现地理要素的智能预测与异常检测,强化了AI技术与地理数据的深度融合。这一模式为地理数据科学的实践教学提供可供参考的技术范例,不仅强化了地理学科数智化转型的技术支撑,也为高校地理学相关课程的优化与创新提供理论依据,助力提升地理学创新人才的培养水平。

     

    Abstract: In the era of digital intelligence and the booming development of Earth observation technologies, the rapid accumulation of geo-spatiotemporal big data, coupled with the continuous deepening of geographical thought methods and technical models, jointly constitute the core driving force for the theoretical development of geography and innovation in the geography industry. In the face of this era of transformation, promoting the digital and intelligent transformation of education and cultivating composite talents with computational thinking, digital literacy, and intelligent computing skills has become a historic mission and valuable opportunity entrusted to universities in the new era. Geography data analysis courses in higher education bear the responsibility of nurturing computational thinking among innovative geography talents. Among these, the experimental design component of such courses is particularly crucial, imposing high requirements on instructors to rigorously conceive, meticulously design, and repeatedly explore. In response to the constraining factors currently faced in the experimental design of this series of courses, such as unreasonable difficulty gradients, challenges in developing students' practical abilities, and poor interdisciplinary integration, this study innovatively proposes a "lightweight simulation experiment" course design model. By introducing convenient IoT sensor devices and leveraging cloud platforms and other technological means, the aim is to comprehensively optimize course experimental design from multiple aspects, including stimulating students' interest in learning, cultivating their practical abilities, promoting interdisciplinary thinking, and improving quantitative assessment dimensions of the course. This study will contribute to an in-depth analysis of the difficulties and breakthrough paths in the current teaching development of geography data analysis courses, providing strong support for the high-quality development of related geography courses in Chinese universities and enhancing the level of cultivating innovative geography talents.

     

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