Investigation of Self-Regulated Online Learning According to Demographic Variables and Their Relationship to Learning Approaches

Year 2023, , 804 - 817, 28.12.2023

Işıl Sönmez

https://doi.org/10.51535/tell.1304278

Abstract

Self-regulation in online learning environments is of great importance in terms of ensuring effective learning since it makes the learner autonomous. In this context, the research aims to compare the self-regulated online learning of education faculty students according to certain variables and to reveal the relationship between their self-regulated online learning and learning approaches. The research is conducted using a correlational research design. Firstly, the general view of students' self-regulated online learning and learning approaches was determined. After that, self-regulated online learning averages were compared according to their gender and academic averages, and finally, the relationship between self-regulated online learning and learning approaches was presented. The study group of the research, which continues their education through distance education due to the pandemic in the 2021-2022 academic year; consisted of a total of 376 students who studied in different departments of the education faculty of Necmettin Erbakan University in Konya. The research findings demonstrate the fact that students' self-regulated online learning corresponds to an above-average value and their self-regulated online learning differs according to their gender and academic achievement. Moreover, there is a moderately positive correlation between the deep learning approach and self-regulated online learning skills, and a low negative correlation between the superficial learning approach and self-regulated online learning skills.

Keywords

self regulated learning, learning approaches, online learning, deep learning, superficial learning

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