Ridit analysis reveals adaptive self-regulated learning behaviors in graduate students during online learning.
Self-regulated learning (SRL) has emerged as a central concern in educational research, particularly with the growing prevalence of online learning environments. This study applies Ridit analysis to examine the SRL behaviors of 49 graduate students, with a focus on their motivational beliefs and learning strategies in online contexts. The results indicate that online intrinsic motivation was the most positively endorsed dimension, while negative achievement emotions were the least. Overall, students demonstrated high levels of motivation and low levels of emotional resistance toward online learning. These findings suggest that learners generally exhibit adaptive SRL behaviors in response to online learning challenges. The study contributes to the development of more effective online instructional strategies and offers implications for future research on SRL in digital learning environments.
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Xu et al. (2025) studied this question.
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