Application of PLS SEM in Evaluations of Mathematics Statistics II Course Online Learning

Abstract

The impact of the COVID-19 pandemic on the education sector includes the learning system that cannot be conducted directly (offline). With the change in the learning system, it is necessary to evaluate whether the implemented online learning system can run well and provide results as expected. The level of student satisfaction is one of the factors that can be used to evaluate online learning. This study analyzed the student satisfaction level with online learning for the Mathematics Statistics II course at the Mathematics Department of Andalas University, related to service quality by lecture and the level of student understanding. Data analysis was conducted using causal modeling, namely Partial Least Square Structural Equations Modeling (PLS-SEM). By using The PLS-SEM, it is known that there is a significant and positive effect of service quality on student satisfaction in the Mathematics Statistics II course. In addition, the service quality also affects the understanding level significantly and positively. However, the level of student understanding has no significant effect on the level of student satisfaction. The coefficient of determination (R2) from the structural model of student satisfaction toward the Mathematics Statistics II course online learning is 0.774. This value indicates that the resulting model is good because it has relatively high accuracy.