Abstract

SHELEKHOVA, Ludmila; ALIYEVA, Margarita; BAKIZHEVA, Saida  and  KALASHNIKOVA, Svetlana. Efficiency of e-learning for mathematics students during quarantine. Conrado [online]. 2023, vol.19, n.91, pp. 427-433.  Epub Apr 30, 2023. ISSN 1990-8644.

The paper examines the opportunities to use e-learning technologies to improve the efficiency of the learning process based on the example of implementing online training courses and mathematical disciplines on the Moodle platform. The study finds that the laws of grade distribution in mathematical disciplines significantly vary between traditional and online learning. In traditional training, the law of distribution can be considered close to normal, in e-learning, the law of distribution should be defined as bimodal. In other words, students in the academic group should be split into two subgroups based on the results of e-learning: one of students who started learning better and the other - of those who went the opposite way. Student's t-test demonstrates that the average grades of the two subgroups in e-learning differ with a 95% reliability. This indicates that the academic group should be viewed as consisting of two sets with dissimilar characteristics. Analysis of the efficiency of the implementation of e-learning demonstrates the promise of using this method in the study of mathematical disciplines. Further development of e-learning should focus on the development of individual and personalized approaches to training that promote the activization of the learning process for all students.

Keywords : E-learning; Independent work; Personalized learning system; Content level; Interactive level; Learning efficiency.

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