EAGER: Evaluating the Accuracy of Digital Compass Measurements on Mobile Devices

移动的设备正在彻底改变地球科学家进行实地研究的方式，正在开发的新技术与前几代人使用的方法有很大不同。例如，许多智能手机和平板电脑中内置的硬件允许这些设备用作数字地质罗盘。数字测量的易用性和速度似乎代表了在野外使用模拟地质罗盘的明显优势。然而，初步调查表明，数字指南针应用程序可能无法提供专业野外地质学家所需的准确性。为了解决这些问题，本项目将统计评估使用数字罗盘在移动的设备上与模拟罗盘相比的方向测量的相对精度。该项目将产生影响所有使用地质罗盘进行定向测量的地球科学家的结果，因此，对地球科学学科的潜在影响是巨大的。该项目将利用学生的移动的设备，使他们成为现场数据的主要收集者。高级地质学课程的学生将使用模拟和数字罗盘进行方位测量，然后将其用于数字与模拟罗盘测量的相对准确度的统计评估。研究人员将评估其数据集中的统计变化，包括平台之间的变化，现场不同位置观察者测量的变化，以及同一表面重复测量的变化。将对现场数据集进行统计分析，如Fisher分布和Watson-Williams分析以及Bland-Altman检验。研究人员将评估测量类型和软件之间的差异程度和一致性限制;测量，平台和软件之间存在任何系统性变化趋势;以及评估收集的现场数据范围内测量的一致性。除了研究的实践方面，该项目还将通过本科生参与该项目来促进STEM（科学，技术，工程和数学）教育。

Mobile devices are revolutionizing how geoscientists approach field-based research, and new technologies are being developed that are significantly different from methods used by previous generations. For example, hardware built into many smart phones and tablets allow these devices to function as digital geologic compasses. The ease of use and speed of taking digital measurements seem to represent distinct advantages over using an analog geologic compass in the field. However, preliminary investigations suggest that digital compass apps may not provide the accuracy that a professional field geologist needs. To address these concerns, this project will statistically evaluate the relative accuracy of orientation measurements using digital compasses on mobile devices as compared with analog compasses. This project will produce results that impact all geoscientists that use geologic compasses to take orientation measurements, and as such, the potential impacts across geoscience disciplines are substantial. The project will tap into students' facility with mobile devices to make them the primary collectors of field data. Students in upper-level geology courses will take orientation measurements with both analog and digital compasses, which will then be used for statistical evaluations of the relative accuracy of digital vs. analog compass measurements. The researchers will assess statistical variation in their datasets to include variation between platforms, variation within measurements by observers on different locations in the field, and variation in repeated measurements on the same surface. Statistical analyses, such as Fisher distribution and Watson-Williams analyses, and Bland-Altman tests, will be applied to the field datasets. The researchers will assess the magnitude of the discrepancy and limits of agreement between types of measure and software; the existence of any systematic trends in variation across measurements, platforms, and software; as well as evaluate the consistency of measurement across the range of collected field data. In addition to the practical aspects of the research, the project will contribute to STEM (science, technology, engineering, and mathematics) education by the engagement of undergraduate students in the project.