Applying Multiple Regression to Evaluate Academic Performance of Students in E-Learning

The educational system is no longer conceivable without the use of progressive electronic learning technologies. LMS Moodle, as the main tool of e-learning, provides great opportunities for evaluating students' academic performance: designing and creating electronic tests in courses with the possibility of automatic assessment, displaying learning results, tracking the activity of students in the e-learning environment. The problem of students' academic failure is one of the most urgent in pedagogy. Monitoring of academic performance should be systematic and take into account various factors. Academic performance is a complex phenomenon because it involves the interrelationship of multiple factors, which means it should be evaluated using multivariate methods, such as multiple regression. This paper focuses on the application of multiple regression to evaluate students' academic performance in e-learning. This study analyzed the academic performance of students as a function of the learners' knowledge level prior to taking the e-course and the time spent by the student in the e-course. Analysis and evaluation of the result of students' performance allow to reveal the cause-and-effect relationships of their successes or failures, to build further ways to improve the quality of students’ knowledge, their individual educational trajectories, to adjust further activities in the framework of e-learning. #CSOC1120