RCN-UBE Incubator: Networking Systems Biologists with Community College Educator

RCN-UBE 孵化器：网络系统生物学家与社区大学教育工作者

• 批准号: 2019088
• 负责人: Jennifer Eklund
• 金额: $ 7.49万
• 依托单位: Institute for Systems Biology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-12-15 至 2022-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019088&HistoricalAwards=false
• 关键词: RCN; UBE; Incubator; Networking; Systems

This RCN-UBE project seeks to network community college educators and systems biologists to promote biological data literacy amongst community college students. The volume, velocity, and variety of biological data has increased dramatically. As a result, current and future careers in biology are now highly dependent on quantitative skills such as sophisticated mathematical modeling, “big data” analysis, and computer simulation. The implication for education is that all biology students need educational experiences that build biological data literacy. However, due to the rapidly evolving nature of skills needed to interact with increased volume, velocity and variety of data, many STEM educators lack contemporary data literacy skills. Even fewer have training on how to use data in the classroom in a way that is accessible to students and helps them build data literacy skills. This lack of training is more pronounced for community college faculty who do not regularly interact with researchers who develop and use these skills. This project pilots an approach that has the potential to significantly improve undergraduate STEM teaching and learning not only by increasing faculty comfort with systems biology approaches, but also by network participants directly engaging diverse undergraduates in cutting-edge methods in their introductory courses. This approach could serve as a model for future collaborations between research institutes and primarily undergraduate institutions that seek to increase minority recruitment, engagement, retention, and success along STEM pathways.This project will bring together systems biologists and community college faculty to engage in professional learning experiences that draw on the expertise of both populations. Community college faculty will engage in a week of deep learning of quantitative biology skills supported by the members of the network who are quantitative biology researchers. The full network will then create curricular resources that engage students in data literacy modules to complement classroom based undergraduate research and assist students in building the skills to interpret large multidimensional datasets founded in authentic research contexts. The network will partner to implement these resources in community college courses that serve a broad range of students including populations traditionally underrepresented in STEM fields. The project will improve the preparation of community college students by increasing achievement and learning of quantitative biology research methods and improve undergraduate biology learning environments by enhancing undergraduate faculty teaching of quantitative biology research methods. Further the project outcomes will generate instructional strategies and curricular resources founded in contemporary quantitative biology research and an expanded network of undergraduate biology faculty and scientists at research institutes engaging students in classroom-based quantitative biology research.This project is being jointly funded by the Directorate for Biological Sciences, Division of Biological Infrastructure, and the Directorate for Education and Human Resources, Division of Undergraduate Education as part of their efforts to address the challenges posed in Vision and Change in Undergraduate Biology Education: A Call to Action (http://visionandchange/finalreport/).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.

这个RCN-UBE项目旨在将社区学院教育工作者和系统生物学家联系起来，以促进社区学院学生的生物数据素养。生物数据的数量、速度和种类都在急剧增加。因此，目前和未来的生物学职业现在高度依赖于定量技能，如复杂的数学建模，“大数据”分析和计算机模拟。对教育的影响是，所有生物学学生都需要建立生物数据素养的教育经验。然而，由于与数量、速度和种类不断增加的数据进行交互所需的技能的快速发展，许多STEM教育工作者缺乏当代的数据素养技能。更少的人接受过如何在课堂上以学生可以访问的方式使用数据的培训，并帮助他们建立数据素养技能。这种缺乏培训的情况在社区大学教师中更为明显，他们不经常与开发和使用这些技能的研究人员互动。该项目试点的方法，有可能显着改善本科STEM教学和学习，不仅通过增加教师舒适度与系统生物学方法，而且通过网络参与者直接从事不同的本科生在他们的入门课程的尖端方法。 这种方法可以作为研究机构和主要本科院校之间未来合作的模式，旨在增加少数民族的招聘，参与，保留和成功沿着STEM pathways.This项目将汇集系统生物学家和社区学院教师从事专业学习经验，借鉴两个群体的专业知识。社区学院的教师将参与为期一周的定量生物学技能的深度学习，由定量生物学研究人员网络成员提供支持。然后，整个网络将创建课程资源，让学生参与数据素养模块，以补充基于课堂的本科研究，并帮助学生建立解释真实研究背景下建立的大型多维数据集的技能。该网络将合作在社区大学课程中实施这些资源，为广泛的学生提供服务，包括传统上在STEM领域代表性不足的人群。该项目将通过提高定量生物学研究方法的成就和学习来改善社区大学生的准备，并通过加强定量生物学研究方法的本科教师教学来改善本科生物学学习环境。此外，该项目的成果将产生基于当代定量生物学研究的教学策略和课程资源，以及研究机构的本科生物学教师和科学家的扩展网络，使学生参与基于课堂的定量生物学研究。该项目由生物科学理事会，生物基础设施司和教育与人力资源理事会共同资助，本科生教育部，作为他们努力解决在本科生生物学教育的愿景和变化所带来的挑战的一部分：行动呼吁（http：//visionandchange/finalreport/）。该奖项反映了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。