发表机构
Faculty of Physics and Engineering, Rochester Community and Technical College（罗切斯特社区技术学院物理与工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究将工程引入物理实验，利用智能手机和曲柄滑块机构，通过数据采集与视频分析，将实验测量与几何模型预测对比，激发工程专业学生的兴趣。
AI 中文摘要
许多选修微积分基础物理课程的学生正在攻读工程学位。与工程直接相关、并运用所学物理知识进行分析的实验室活动，能够激发学生的兴趣，并提供与现实世界的联系。如果设备价格低廉且部分由学生自建，则效果更佳。此外，我们希望使用智能手机作为数据采集设备。智能手机已成为物理教育的重要工具，因为它们通过内置传感器提供了一种便捷且廉价的数据采集方式。Physics Toolbox和phyphox等几款免费应用程序促进了基于传感器的数据采集和分析，使得无需昂贵设备即可开展有意义的实验室活动。我们选择使用一个简单的曲柄滑块机构进行活动。曲柄滑块将旋转运动转换为直线运动，在内燃机和压缩机等设备中有常见应用。教育研究表明，曲柄滑块机构及相关机械装置为引入工程概念、将理论模型与实际应用联系起来提供了有效情境。在我们的实施中，一个旋转电机驱动一个圆盘，圆盘通过连杆连接到沿气轨运动的滑块上。学生利用智能手机数据采集和视频分析来研究由此产生的运动。随后将实验测量结果与根据系统几何关系推导出的数学模型预测进行比较。
英文摘要
Many of the students enrolled in the calculus-based physics sequence are pursuing engineering degrees. Lab activities that have a direct connection to engineering, analyzed with the physics they have been studying, can grab students' interest and provide a real-world connection. All the better if the equipment is inexpensive and partly self-built. In addition, we wanted to use smartphones as data collection devices. Smartphones have become valuable tools for physics education because they provide an accessible and inexpensive means of experimental data acquisition through their built-in sensors. Several free applications, such as Physics Toolbox and phyphox, facilitate sensor-based data collection and analysis, making it possible to perform meaningful laboratory activities without expensive equipment. We chose to use a simple crank-slider mechanism for our activity. The crank-slider converts rotary motion into linear motion and has common applications in such things as internal combustion engines and compressors. Educational studies have shown that slider-crank mechanisms and related mechanical devices provide effective contexts for introducing engineering concepts and connecting theoretical models with practical applications. In our implementation, a rotary motor drives a disk connected by a rod to a cart moving along an air track. Students investigate the resulting motion using smartphone data acquisition and video analysis. Experimental measurements are then compared with the predictions of a mathematical model derived from the geometry of the system.
