INFERENTIAL STATISTICAL ANALYSIS IN E-LEARNING UNIVERSITY EDUCATION IN LATIN AMERICA IN TIMES OF COVID-19

Abstract

Since the appearance of COVID-19, the teaching-learning processes in higher education have changed. This article shows a focus on university education and e-learning, performing a statistical analysis on university students in Ecuador, obtaining significant evidence that the use of ICTs improves academic performance in the subject of statistics. In the first case, two third semester courses are taken, the experimental group is made up of 23 students, to which e-learning is applied and an application developed in Scilab that shows the resolution process for descriptive and inferential statistics; while the control group is made up of 14 students, in which only e-learning and traditional teaching are used. In the second case, 2 courses are taken, the first is formed by 14 students and the second by 22 students, using e-learning and traditional teaching. First, the Shapiro Test is used to determine if the population has a normal distribution, then the Student’s T test is applied in the hypothesis test of difference of means to determine if academic performance is improved with the use of ICTs. Finally, for α = 0.05, it is verified that the developed application improves academic performance. Another important finding is that only using traditional teaching with e-learning does not significantly change academic performance.