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      실시간 온라인 학습에서의 유형화 연구 :학습자와 환경 요인에 대한 상호작용을 중심으로 = Classification on synchronous online learning: Focusing on the interaction between learners and environmental factors

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      https://www.riss.kr/link?id=A109488132

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      This study examines the intricate interplay between learners’ individual factors (self-regulated learning) and environmental factors (teaching presence) through the framework of Bandura’s reciprocal determinism. The study participants comprised a convenience sample of 351 undergraduate and graduate students from a metropolitan four-year university. The data were analyzed using SPSS, and the results were obtained at a .05 level of significance. First, three types of learner characteristics were identified through the K-means analysis (Learner & Instructor-led, Learner-led, and Learner-enhancement-needed). Second, the characteristics of each cluster were examined. No significant differences were observed in demographic characteristics (gender, grade level, or primary online learning platform) across clusters. However, significant differences were observed between the clusters regarding the level of learning activity and learning outcomes (flow, perceived achievement, and learning satisfaction). Cluster 1, “Learner & Instructor-led” exhibited relatively elevated levels of both learning activities and learning outcomes. Based on the findings of this study, which considers the intricate interaction between individuals and their environment, we propose the characteristics of learning styles and educational support in synchronous online learning.
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      This study examines the intricate interplay between learners’ individual factors (self-regulated learning) and environmental factors (teaching presence) through the framework of Bandura’s reciprocal determinism. The study participants comprised a ...

      This study examines the intricate interplay between learners’ individual factors (self-regulated learning) and environmental factors (teaching presence) through the framework of Bandura’s reciprocal determinism. The study participants comprised a convenience sample of 351 undergraduate and graduate students from a metropolitan four-year university. The data were analyzed using SPSS, and the results were obtained at a .05 level of significance. First, three types of learner characteristics were identified through the K-means analysis (Learner & Instructor-led, Learner-led, and Learner-enhancement-needed). Second, the characteristics of each cluster were examined. No significant differences were observed in demographic characteristics (gender, grade level, or primary online learning platform) across clusters. However, significant differences were observed between the clusters regarding the level of learning activity and learning outcomes (flow, perceived achievement, and learning satisfaction). Cluster 1, “Learner & Instructor-led” exhibited relatively elevated levels of both learning activities and learning outcomes. Based on the findings of this study, which considers the intricate interaction between individuals and their environment, we propose the characteristics of learning styles and educational support in synchronous online learning.

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