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A Comparison of the Academic Performance of Rising Scholars with Other Student Demographic Groupings before and during the COVID Pandemic

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2022 ASABE Annual International Meeting  2200205.(doi:10.13031/aim.202200205)
Authors:   Grace L. Baldwin, Virginia Booth Womack, Sarah E. LaRose, Carol S. Stwalley, Robert M. Stwalley, III
Keywords:   academic performance, COVID, NSF S-STEM, support networks, socioeconomic status

Abstract. The Purdue University Rising Scholars program was established in 2016 by a NSF grant designed to examine the effect of adult mentor support networks on student performance. The first students began classes in the fall of 2017, and their performance and many aspects of the program have been reported in the literature. Unfortunately, during this same time period, the COVID-19 pandemic moved across the globe and dramatically changed collegiate education. The effects of the pandemic in education will be felt for some time following the eventual demise of the virus. Because of this NSF grant period, the research team was uniquely positioned with matched pair sets of matriculating students from the Rising Scholars program, engineering, and exploratory studies. This paper will compare the performance of these students and the general student population for GPA and retention between the pre-COVID period (< spring of 2020) and the COVID period (spring 2020 onward). It is commonly perceived among collegiate instructors that student performance has suffered during the pandemic. The Rising Scholar demographic has the potential to have increased adverse effects from the pandemic disruption, but they also have an established adult mentor support network. The researchers have looked at differential performance outcomes between the various groups and exposed a tendency toward diminished performance with thinner networked students. Sample sizes were too small for the evaluation of any meaningful statistical tests.

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