Psychological Predictors of Successful Online Student Learning
The report is devoted to the study of psychological predictors of successful online learning. The relevance of the study is due to the need to study psychological predictors of student success in order to build an optimal organization of the educational process. In the course of the study, the analysis of literature sources on the problems of not only defining the concept of online learning, but also identifying the characteristics of predictors as a phenomenon and their changes with the transition to online learning was carried out. The results of an empirical study of the relationship of psychological characteristics of students' personality, which act as predictors of success with their online learning results, are presented. Characteristics of self-organization, motivation and personality traits were selected as predictors. The study was conducted on the basis of the Ural Federal University, the sample was formed from students of the 1st year of study – 271 people, mostly representing the Ural Humanitarian Institute. The study took into account the results of academic performance in the subjects of the Natural Science picture of the world - a model of fully online learning, and History – a model of mixed learning. As a result of regression analysis, several statistically significant predictors of success in online learning were identified. Success is influenced by the degree of ability to independently organize their educational activities, the manifestation of a responsible attitude to the performance of tasks and courses. Executive personality helps to overcome differences in formats, creating conditions for effective activity. Motivation acts as a marker of a student's interest in the educational process in different formats.
Keywords: online learning, psychological predictors of successful learning, learning success, psychological predictors
Article type: theses
For citation: Lebedeva M.A., Maltsev A.V. Psychological Predictors of Successful Online Student Learning. Digital Humanities and Technology in Education (DHTE 2023),, pp. 753–767.
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