Engaging Faculty and Students in Learning with OOI Data Explorations

将大量数据用于研究和教育增加了分析和综合科学理解的机会和挑战。越来越多的研究项目收集了大量数据，特别是海洋学项目，其中使用了先进技术，包括有线系统、自动滑翔机和复杂的浮标传感器系统，产生了巨大的数据集。例如，国家科学基金会的海洋观测站倡议(OOI)建立了观测和计算机基础设施，提供持续的海洋测量，以研究未来几十年的气候变异性、海洋环流、生态系统动力学、海气交换、海底过程和板块尺度地球动力学。这个海洋观测系统已经通过积累大量数据来解决关于复杂海洋过程的问题，从而提高了我们了解自然世界的能力。这种更广泛的数据访问也为地球科学教授提供了前所未有的机会，让本科生利用基于网络的技术，利用真实世界的数据集、模型和地球科学过程的模拟来体验数据。直接从数据中学习被证明是有利的，因为它挑战学习者构建意义，发展对一个主题或现象的更深层次的理解，鼓励学生探究，并在科学实践中发展技能。使用真实世界的数据也被证明有助于培养对科学的兴趣、动机和认同感。此外，分析数据和识别模式已成为工作场所和21世纪公民参与的核心劳动力技能。OOI提供了一个机会，将专业收集的、实时和接近实时的地球海洋数据、图像和视频带入正式和非正式的学习环境。该项目建立在先前创建网络基础设施的基础上，帮助教育工作者获得OOI数据。为了正确地集中开发教育工具，对海洋学界的做法和教学需求进行了两项前端评估研究。虽然73%的本科生教授表示他们在课堂上使用数据，但只有一小部分人使用学生的实时数据。最重要的是，决定有必要进一步探索如何有效地将数据整合到教学中，以及如何创建数据可视化工具，以帮助本科生教授满足21世纪科学技能和实践教学的要求。为了应对真实数据教学带来的挑战，并鼓励在本科课堂上使用OOI数据，该项目将设计和实施专业发展工作坊和一个微型助学金计划，以扩大OOI数据在本科教学中的使用。该项目通过重点分析海洋数据的课堂体验，进一步发展、扩大和实施提高本科生对地球科学的参与度的方法。PIS将雇用大约150名教职员工参加以OOI数据和数据可视化教学为重点的研讨会。将招聘来自社区学院的教师，主要是本科院校(PUI)、少数民族服务机构(MSI)、历史上的黑人学院和大学，以及来自研究实验室、更大的研究型大学的教师，以及一支教学专家团队。这个项目的目标是扩大教授社区，有效地利用OOI数据在他们的课堂上，最终创建一个以OOI为重点的实践社区，利用数据进行教学。该项目将为各种活动和讲习班提供支持，这些活动和讲习班将增加来自OOI用户社区各机构的教员的参与。教员将能够使用OOI数据产品通过在线数据活动让学生参与海洋学，并改进对本科生进行数据解释和分析的培训。数据探索将由合作的本科生教授开发，并提供给所有教育工作者使用。该项目将评估和评估将数据引入课堂和培训教师新方法的各种方法的有效性。该项目解决了NSF在2018-2022年战略计划中规定的优先事项-STEM劳动力：促进更有能力和多样化的研究劳动力的增长，并提高国家的科学和创新技能。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Using high volumes of data for research and education increases both opportunities and challenges to analyze and synthesize scientific understanding. A growing number of research programs collect high volumes of data, especially oceanography programs where the use of advanced technologies, including cabled systems, autonomous gliders, and sophisticated buoy sensor systems generate huge data sets. For example, the National Science Foundation's Ocean Observatories Initiative (OOI) has constructed observational and computer infrastructure that provides sustained ocean measurements to study climate variability, ocean circulation, ecosystem dynamics, air-sea exchange, seafloor processes, and plate-scale geodynamics for the coming decades. This ocean observing system is already advancing our ability to understand the natural world by accumulating large quantities of data to address questions about complex oceanographic processes. This expanded access to data also provides professors in the geosciences with unprecedented opportunities to engage undergraduate students in data experiences using real-world data sets, models, and simulations of geoscience processes using web-based technologies. Learning directly from data has been shown to be advantageous as it challenges learners to construct meaning and develop a deeper understanding of a topic or phenomenon, encourages student inquiry, and develops skills with the practices of science. Using real world data has also been shown to help develop interest in, motivation for, and identity with respect to science. Moreover, analyzing data and identifying patterns have become core workforce skills in the workplace and for civic engagement in the 21st century. The OOI offers an opportunity to bring professionally collected, real-time and near-real-time data, images, and video of the Earth's oceans into both formal and informal learning environments. This project builds on prior efforts to create cyberinfrastructure that helps make OOI data available to educators. In order to correctly focus development of educational tools, two front-end evaluation studies on the practices and teaching needs of the oceanographic community were conducted. While 73% of undergraduate professors said they use data in their classroom, only a small subset use real-time data with their students. Most importantly, it was determined that there is a need for further exploration into how to effectively integrate data into teaching and how to create data visualization tools that help undergraduate professors meet the demands of teaching 21st century science skills and practices. In order to meet the challenges posed by teaching with authentic data and to encourage the use of OOI data in undergraduate classrooms, this project will design and implement professional development workshops and a mini grant program to expand the use of OOI data in undergraduate teaching. This project further develops, scales up, and implements ways to improve undergraduate student engagement in the geosciences through classroom experiences focused on analyzing oceanographic data. The PIs will engage approximately 150 faculty in workshops focused on teaching with OOI data and data visualizations. Faculty from community colleges, Primarily Undergraduate Institutions (PUIs), Minority-Serving Institutions (MSIs), Historically Black Colleges & Universities will be recruited, as well as faculty from research laboratories, larger research universities, and a team of pedagogical experts. The goal of this project is to expand the community of professors effectively utilizing OOI data in their classrooms, eventually creating an OOI focused Community of Practice for teaching with data. The project will support a variety of activities and workshops that will increase the involvement of faculty members from a wide range of institutions in the OOI user community. The faculty will be able to use OOI data products to engage students in oceanography via online data activities and improve the training of undergraduate students in data interpretation and analysis. Data explorations will be developed by collaborating undergraduate professors and made available for all educators to use. The project will assess and evaluate the effectiveness of various methods for introducing data into the classroom and for training faculty members in the new methods.This project addresses NSF priorities as stated in the NSF Strategic Plan for 2018-2022, "Strategic Objective 2.2 - STEM Workforce: Foster the growth of a more capable and diverse research workforce and advance the scientific and innovation skills of the Nation."This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.