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Investigating Students' Online Learning Behavior with a Learning Analytic Approach: Field Dependence/Independence vs. Holism/Serialism
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Yang, Tzu-Chi; Chen, Sherry Y. – Interactive Learning Environments, 2023
Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…
Descriptors: Student Behavior, Educational Technology, Electronic Learning, Cognitive Style
A Learning Analytics Approach to Investigating Pre-Service Teachers' Change of Concept of Engagement in the Flipped Classroom
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Sun, Fu-Rong; Hu, Hong-Zhen; Wan, Rong-Gen; Fu, Xiao; Wu, Shu-Jing – Interactive Learning Environments, 2022
To determine the impact of cognitive style on change of concept of engagement in the flipped classroom, a sequential analysis from the perspective of Bloom's Taxonomy was conducted to establish if significant differences existed between the learning achievements and engagement of students with different cognitive styles. The participants were…
Descriptors: Learning Analytics, Preservice Teachers, Educational Change, Learner Engagement
Social Learning Analytics for Determining Learning Styles in a Smart Classroom
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Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks