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

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

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.