Collaborative Research: Using Tutorial-Based Active E-Learning to Broaden Participation and Enhance Scientific Computing Skills in a Seismology Context

协作研究：使用基于教程的主动电子学习来扩大地震学背景下的参与并增强科学计算技能

• 批准号: 2121342
• 负责人: Michael Hubenthal
• 金额: $ 3.75万
• 依托单位: Incorporated Research Institutions for Seismology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2121342&HistoricalAwards=false
• 关键词: Collaborative; Research; Using; Tutorial; Based

This project aims to serve the national interest by improving computational thinking and scientific computing skills of advanced undergraduate students. It will do so by developing a large-enrollment, asynchronous, open access, online computational workshop. Such training is important to ensure that future scientists develop the knowledge and skills they need to tackle computer- and data-intensive scientific problems of national importance, such as climate change. This project will provide more than 1200 advanced undergraduates with computational training in a seismological context. The training will build on and refine a pilot tutorial-based, active e-learning experience called the Seismology Skill Building Workshop. The project also aims to generate a more successful, inclusive, and satisfying online learning experience that can be exported to other STEM disciplines. Because the workshop offers advanced coursework online without fees or prerequisites, it is likely to increase the participation of diverse undergraduates and other learners in computing. In fact, based on data from the pilot workshop, this project will reach many students from communities that have been disproportionately impacted by the COVID-19 pandemic. Through its research efforts, the project intends to increase understanding about how diverse groups of students engage with and benefit from the tutorial-based active e-learning approach. By identifying workshop features that attract diverse audiences and promote retention, learning, and satisfaction, the project can also define a framework that other STEM communities can use to develop similar technical training efforts.A preliminary Seismology Skill Building Workshop was offered in 2020 by the Incorporated Research Institutions for Seismology, an NSF-funded university consortium that operates the seismology community data and equipment facility. The pilot workshop was launched in response to the COVID-19 pandemic and reached more than 700 students, many more than anticipated and with higher diversity than typical in-person computing courses. Through the pilot workshop, the project team identified challenges and gathered data about workshop effectiveness. This project will investigate the resulting research questions, which are important within and beyond seismology: 1) To what extent does this online scientific computing training model enhance participant learning and behavior? 2) What are the key influences on retention and performance for advanced undergraduates in the online scientific computing training model and can new interventions improve efficacy? 3) To what degree do the elements of the tutorial-based active e-learning approach contribute to learning? 4) How can the value of the Seismology Skill Building Workshop and its positioning within the seismology learning ecosystem be optimized to ensure sustainability? These questions will be addressed through a multi-year, mixed methods research investigation that includes development of instruments for summative assessment of computational thinking and programming within a disciplinary context, improved characterization of assignment question types to examine performance trends, and correlation analysis of participant activity and performance data. Expert reviews of the curriculum and community focus groups will be conducted to ensure sustainability of the Seismology Skill Building Workshop. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. This project is in the Engaged Student Learning track, through which the IUSE program supports the creation, exploration, and implementation of promising practices and tools.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.

该项目旨在通过提高高年级本科生的计算思维和科学计算技能来服务于国家利益。 它将通过开发一个大规模的、异步的、开放获取的在线计算研讨会来实现这一目标。这种培训对于确保未来的科学家掌握必要的知识和技能，以解决气候变化等具有国家重要性的计算机和数据密集型科学问题十分重要。该项目将为1200多名高年级本科生提供地震学方面的计算培训。 该培训将建立在一个名为“地震学技能建设讲习班”的试点辅导式积极电子学习经验的基础上，并对其进行完善。该项目还旨在产生一个更成功，更包容，更令人满意的在线学习体验，可以导出到其他STEM学科。由于研讨会提供先进的在线课程，没有费用或先决条件，它很可能会增加不同的本科生和其他学习者在计算的参与。 事实上，根据试点研讨会的数据，该项目将惠及许多来自受COVID-19大流行影响不成比例的社区的学生。 通过其研究工作，该项目打算增加了解不同群体的学生如何参与并受益于基于辅导的积极电子学习方法。通过确定吸引不同受众并促进保留，学习和满意度的研讨会功能，该项目还可以定义一个框架，其他STEM社区可以用来开发类似的技术培训工作。 该试点工作坊是为应对COVID-19疫情而推出的，共有700多名学生参加，比预期多得多，比典型的面对面计算课程更具多样性。 通过试点讲习班，项目小组确定了挑战，并收集了关于讲习班成效的数据。 这个项目将调查由此产生的研究问题，这是重要的内部和外部地震学：1）在多大程度上，这种在线科学计算培训模型提高参与者的学习和行为？2)在在线科学计算培训模式中，对高年级本科生的保留和表现有什么关键影响？新的干预措施能否提高效果？3)基于辅导的主动电子学习方法的要素在多大程度上有助于学习？4)如何优化地震学技能建设研讨会的价值及其在地震学学习生态系统中的定位，以确保可持续性？这些问题将通过一个多年的，混合方法的研究调查，其中包括开发的工具，计算思维和编程的总结性评估的学科背景下，改进表征的分配问题类型，以检查性能趋势，并参与者的活动和性能数据的相关性分析。将对课程和社区焦点小组进行专家审查，以确保地震学技能建设讲习班的可持续性。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。 该项目是在学生学习的轨道，通过该IUSE计划支持创建，探索和实施有前途的做法和工具。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。