A New Mathematical Metric for Inclusive Excellence in Teaching Applied Before and During the COVID-19 Era

Abstract

In this paper a novel metric for evaluating inclusive excellence in teaching is introduced and applied to students' performance in classes before and during the COVID-19 era. The novel metric, named the Inclusive Excellence Ratio (IER), is designed to simultaneously reflect the two desirable characteristics embraced by inclusive excellence teaching: strong student performance and low variation in performance across all students. The computation of the IER given student test score data is simple and straightforward: it is the statistical sample mean divided by the sample standard deviation. Consequently, the IER is high when the students' test scores are high and variance is low, suggesting it may provide a useful quantitative measure for those educational innovators seeking to experiment with new, effective teaching methodologies that boost inclusive excellence. The IER is applied to evaluate a posteriori student performance taken from cumulative aggregate data from the University of California, Irvine (UCI) undergraduate math finance classes involving 378 students over two academic years (2018 to 2020), spanning five quarters before and one quarter during the COVID-19 era of remote teaching at UCI. Conclusions are drawn and discussed comparing the quality of in-person teaching environments to remote teaching environments.