Comparing University Students’ Performance in the Statistical Processing and Visualization of Laboratory Data before, during and after the COVID-19 Pandemic

Abstract

The face-to-face education system around the world unexpectedly collapsed in March 2020 due to the COVID-19 pandemic. The priority education process became remote education and activities related to self-study and self-education. This paper investigates how university students’ performance has been influenced by remote learning during the lockdown period. Academic performance is evaluated by measuring the time required to complete specific homework in statistical data processing. Comparisons of performance are made for before, during and after the pandemic period. This study examines a population of third-year university students majoring in Materials Science and Engineering. The students were asked to complete a specific homework requiring the processing and evaluation of random laboratory data using analytical software. The delivery times of the completed homework before, during and after the lockdown period are compared. It has been found that although the students had to spend more time on their task during the pandemic, their relative performance remained unchanged and was comparable to that of pre-pandemic. After the end of the lockdown period, an increase in academic performance was noted. Our results suggest that the sudden transition to remote education may have been beneficial for the long-term performance of a group of selected university students in data processing and evaluation. The findings support the idea that teachers and their institutions should be willing to use a variety of teaching methods. The inclusion of remote learning methods in university instruction is encouraged.