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Mohammed Jebbari; Bouchaib Cherradi; Soufiane Hamida; Abdelhadi Raihani – Education and Information Technologies, 2024
With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…
Descriptors: MOOCs, Algorithms, Computer Simulation, COVID-19
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Rovers, Sanne F. E.; Clarebout, Geraldine; Savelberg, Hans H. C. M.; de Bruin, Anique B. H.; van Merriënboer, Jeroen J. G. – Metacognition and Learning, 2019
Although self-regulated learning (SRL) is becoming increasingly important in modern educational contexts, disagreements exist regarding its measurement. One particularly important issue is whether self-reports represent valid ways to measure this process. Several researchers have advocated the use of behavioral indicators of SRL instead. An…
Descriptors: Metacognition, Measurement, Learning Strategies, Comparative Analysis
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Wang, Zheng; Zhu, Xinning; Huang, Junfei; Li, Xiang; Ji, Yang – International Educational Data Mining Society, 2018
Academic achievement of a student in college always has a far-reaching impact on his further development. With the rise of the ubiquitous sensing technology, students' digital footprints in campus can be collected to gain insights into their daily behaviours and predict their academic achievements. In this paper, we propose a framework named…
Descriptors: Academic Achievement, Prediction, Data Analysis, Student Behavior
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Lai, Song; Sun, Bo; Wu, Fati; Xiao, Rong – IEEE Transactions on Learning Technologies, 2020
Adaptive e-learning can be used to personalize learning environment for students to meet their individual demands. Individual differences depend on the students' personality traits. Numerous studies have indicated that understanding the role of personality in the learning process can facilitate learning. Hence, personality identification in…
Descriptors: Personality Traits, Electronic Learning, Individual Differences, Learning Processes
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Tiger, Jeffrey H.; Miller, Sarah J.; Mevers, Joanna Lomas; Mintz, Joslyn Cynkus; Scheithauer, Mindy C.; Alvarez, Jessica – Journal of Applied Behavior Analysis, 2013
School consultants who rely on direct observation typically conduct observational samples (e.g., 1 30-min observation per day) with the hopes that the sample is representative of performance during the remainder of the day, but the representativeness of these samples is unclear. In the current study, we recorded the problem behavior of 3 referred…
Descriptors: Classroom Environment, Classroom Techniques, Student Behavior, Observation
Lee, Woon Jee – ProQuest LLC, 2012
The purpose of this study was to explore the nature of students' mapping and discourse behaviors while constructing causal maps to articulate their understanding of a complex, ill-structured problem. In this study, six graduate-level students were assigned to one of three pair groups, and each pair used the causal mapping software program,…
Descriptors: Student Behavior, Graduate Students, Maps, Computer Uses in Education