RCN-UBE Incubator: REAL (R in Education and Assessment of Learning)

RCN-UBE 孵化器：REAL（教育和学习评估中的 R）

• 批准号: 2018592
• 负责人: Robert Erdmann
• 金额: $ 7.49万
• 依托单位: University of Minnesota-Twin Cities
• 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: 2020-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018592&HistoricalAwards=false
• 关键词: RCN; UBE; Incubator; REAL; Education

Knowing how to use math and computing skills effectively has become essential to working in science, particularly for biologists in recent years. However, because of the rapid pace of change in biological and computing technologies, many faculty members find themselves teaching skills which are also new to them or that they had to learn independently. In this project, the research team seeks to develop a network of researchers and educators who will collaborate to increase their own computing and statistical skills, while also developing "best practices" of how to teach these skills to students. Using the programming language R, a free and open source coding language that is increasingly used in the biological sciences, the R in Education and Assessment of Learning (REAL) network will establish an inclusive, sustainable community of biology educators and biology education researchers who will both teach and use R for the betterment of biology research and education nationwide. The REAL network aims to support the training of biology researchers in quantitative and computational methods; foster collaborations for the development, sharing and assessment of educational modules for quantitative skills and of R-code for biology education researchers; and to catalyze the development of common standards and best practices for the training of undergraduates and graduate students in quantitative and computational skills. The network’s central activity involves training an initial cohort of beginners in R to develop, assess and disseminate biology classroom modules to teach quantitative skills using R and/or develop and test R code scripts and packages tailored specifically for biology education research. REAL trainees will develop novel educational modules to infuse effective, up-to-date quantitative skills into the biology curriculum, rigorously assess the impact of their teaching, and make significant contributions to education research both at the interface of biology and computing and at the edges of current statistical practice. The REAL Network will increase the number of biology faculty with the skills to effectively teach quantitative and computational skills to biology undergraduates, contributing to a new generation of biologists ready to tackle the research and data analysis challenges posed by the development of novel high-throughput technologies. In addition, these faculty will also be better equipped to rigorously assess the educational outcomes of their students, leading to improved teaching practices and allowing for the development of common standards and best practices unique to the training of biologists in quantitative methods.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.

了解如何有效地使用数学和计算技能对于从事科学工作至关重要，尤其是近年来生物学家。但是，由于生物学和计算技术的变化速度迅速，许多教职员工发现自己的教学技能对他们来说也是新的，或者他们必须独立学习。在这个项目中，研究团队试图建立一个研究人员和教育工作者网络，他们将合作以提高自己的计算和统计技能，同时还开发了如何向学生讲授这些技能的“最佳实践”。使用编程语言R，一种越来越多地在生物科学中使用的免费和开源编码语言，学习和学习评估（REAL）网络的R将建立一个包容性，可持续的生物学教育和生物学教育研究人员社区，他们将教授和使用R来改善全国生物学研究和教育。真正的网络旨在支持生物学研究人员在定量和计算方法方面的培训。促进与生物学教育研究人员开发，共享和评估教育模块的开发，共享和评估；并促进开发普通标准和最佳实践，以培训本科生和研究生的定量和计算技能。该网络的主要活动涉及培训R中最初的R中的初学者队列，以开发，评估和传播生物学课堂模块，以使用R和/或开发和测试R代码脚本以及专门针对生物学教育研究量身定制的R Code脚本和包装来教授定量技能。 REAL trainees will develop novel educational modules to infuse effective, up-to-date quantitative skills into the biology curriculum, rigorously assess the impact of their teaching, and make significant contributions to education research both at the interface of biology and computing and at the edges of The REAL Network will increase the number of biology faculty with the skills to effectively teach quantitative and computational skills to biology undergraduates, contributing to a new generation of biologists ready to应对新型高通量技术的发展所带来的研究和数据分析挑战。此外，这些教师还将更好地精力评估学生的教育成果，从而改善了教学实践，并允许制定普通标准和最佳实践，以及在定量方法中培训生物学家在生物学家中培训的独特所独有的。该项目由生物科学，教育和人类的局部局部研究局局共同资助。本科生物学教育的愿景和变化所带来的挑战：行动呼吁（http：//ivisionandchange/finalReport/）。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的审查标准通过评估而被视为珍贵的。