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Direct linkGonzalo Martinez-Munoz; Miguel Angel Alvarez-Rodriguez; Estrella Pulido-Canabate – IEEE Transactions on Education, 2024
In this article, student video visualization profiles are analyzed with two objectives: 1) to identify difficult sections in videos and 2) to predict student performance based on their video visualization profiles. For identifying critical sections in videos two novel indicators are proposed. The first one is designed to measure the complexity of…
Descriptors: Video Technology, Visualization, Electronic Learning, Profiles
Xiao-Fan Lin; Seng Yue Wong; Wei Zhou; Weipeng Shen; Wenyi Li; Chin-Chung Tsai – International Journal of Science and Mathematics Education, 2024
Research evidence indicated that a specific type of augmented reality-assisted (AR-assisted) science learning design or support might not suit or be effective for all students because students' cognitive load might differ according to their experiences and individual characteristics. Thus, this study aimed to identify undergraduate students'…
Descriptors: Computer Simulation, Cognitive Processes, Difficulty Level, Foreign Countries
