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Showing 1 to 15 of 43 results Save | Export
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Yirong Guo; Yifan Song; Jianpeng Guo – Education and Information Technologies, 2025
The digital transformation in education and the widespread use of mobile devices have blurred the boundaries between students' learning and entertainment, increasing the prevalence of cyberloafing among college students. To address the inconsistent effects of cyberloafing on academic achievement, this study proposed a curvilinear relationship…
Descriptors: Academic Achievement, College Students, Time Management, Cognitive Ability
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Liu, Yan; Deng, Lisa; Lin, Lin; Gu, Xiaoqing – Interactive Learning Environments, 2023
With the rapid development of mobile devices and web-based technologies, it becomes common for students to switch between different tasks during study time. However, it remains unclear how the transition between on-task and off-task states happens and how digital devices affect the process. This study examines college students' independent study…
Descriptors: Independent Study, Student Behavior, Behavior Patterns, Time on Task
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Shan Li; Xiaoshan Huang; Gaoxia Zhu; Hanxiang Du; Tianlong Zhong; Chenyu Hou; Juan Zheng – Journal of Computer Assisted Learning, 2024
Background: Social annotation has emerged as a promising educational technology that fosters collaborative reading and discussion of digital resources among learners. While the positive impact of social annotation on students' learning process and performance is widely acknowledged, students' behavioural patterns in social annotation are…
Descriptors: Undergraduate Students, Cooperative Learning, Reading Strategies, Group Activities
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Xu Du; Lizhao Zhang; Jui-Long Hung; Hao Li; Hengtao Tang; Miao Dai – Journal of Computing in Higher Education, 2024
This study aims to track college students' on-task rate during the teaching process and to analyze the influence of instructional strategies on on-task rate through the aspects of observable and internal engagement indicators. Thirty-six undergraduate students at a higher education institution in China participated in the study. Students'…
Descriptors: Teaching Methods, Attention Control, Brain Hemisphere Functions, Diagnostic Tests
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Aleksandra Maslennikova; Daniela Rotelli; Anna Monreale – Journal of Learning Analytics, 2023
Students organize and manage their own learning time, choosing when, what, and how to study due to the flexibility of online learning. Each person has unique learning habits that define their behaviours and distinguish them from others. To investigate the temporal behaviour of students in online learning environments, we seek to identify suitable…
Descriptors: Learning Analytics, Online Courses, Time Management, Self Management
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Zhang, Mo; Guo, Hongwen; Liu, Xiang – International Educational Data Mining Society, 2021
We present an empirical study on the use of keystroke analytics to capture and understand how writers manage their time and make inferences on how they allocate their cognitive resources during essay writing. The results suggest three distinct longitudinal patterns of writing process that describe how writers approach an essay task in a writing…
Descriptors: Keyboarding (Data Entry), Learning Analytics, Data Collection, Cognitive Processes
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Xu, Cuiqin; Xia, Jun – Computer Assisted Language Learning, 2021
The last two decades have witnessed a quick shift from pen-and-paper writing to computer keyboard writing. Corresponding to this shift in the writing medium are vigorous research efforts to understand new features of writing in computer keyboard settings. Using Inputlog7.0, this study investigated the writing process of 60 Chinese English as a…
Descriptors: Scaffolding (Teaching Technique), Writing Processes, Writing Skills, English (Second Language)
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Chevalier, Nicolas – Child Development, 2018
Cognitive effort is costly and this cost likely influences the activities in which children engage. Yet, little is known about how school-age children perceive cognitive effort. The subjective value of cognitive effort, that is, how valuable or costly effort is perceived, was investigated in seventy-three 7- to 12-year-olds using an effort…
Descriptors: Child Development, Children, Difficulty Level, Learner Engagement
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Chen, Zhongzhou; Xu, Mengyu; Garrido, Geoffrey; Gunthrie, Matthew W. – Physical Review Physics Education Research, 2020
This study examines whether including more contextual information in data analysis could improve our ability to identify the relation between students' online learning behavior and overall performance in an introductory physics course. We created four linear regression models correlating students' pass-fail events in a sequence of online learning…
Descriptors: Correlation, Electronic Learning, Performance Factors, Learning Analytics
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da Costa, Bruno G. G.; da Silva, Kelly S.; Bandeira, Alexsandra S.; Martins, Cilene R.; Vieira, Jéssika A. J.; Petroski, Edio L. – Journal of School Health, 2019
Background: Sedentary behavior (SB) is related to unhealthy outcomes and is performed in many contexts, including school. The aim of this study was to identify sociodemographic, biological, and psychosocial correlates of SB performed at school in a sample of adolescents. Methods: Adolescents provided information regarding sex, age, socioeconomic…
Descriptors: Foreign Countries, Physical Activity Level, Health Behavior, Child Health
Wu, Yi-Chieh; Liao, Wen-Hung; Chi, Ming-Te; Li, Tsai-Yen – International Association for Development of the Information Society, 2016
In response to the recent trend in maker movement, teachers are learning 3D techniques actively and bringing 3D printing into the classroom to enhance variety and creativity in designing lectures. This study investigates the usage pattern of a 3D modeling software, Qmodel Creator, which is targeted at K-12 students. User logs containing…
Descriptors: Courseware, Use Studies, Technology Uses in Education, Computer Software
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Palazzo, David J.; Lee, Young-Jin; Warnakulasooriya, Rasil; Pritchard, David E. – Physical Review Special Topics - Physics Education Research, 2010
Submissions to an online homework tutor were analyzed to determine whether they were copied. The fraction of copied submissions increased rapidly over the semester, as each weekly deadline approached and for problems later in each assignment. The majority of students, who copied less than 10% of their problems, worked steadily over the three days…
Descriptors: Homework, Duplication, Cheating, Physics
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Brower-Breitwieser, Carrie M.; Miltenberger, Raymond G.; Gross, Amy; Fuqua, R. Wayne; Breitwieser, Justin – International Journal of Behavioral Consultation and Therapy, 2008
The present study used a concurrent operants preference assessment to evaluate preference for two instructional approaches commonly used with children diagnosed with autism, Applied Behavior Analysis (ABA) and the Treatment and Education of Autistic and Communication Handicapped Children (TEACCH). Results showed that the three children with autism…
Descriptors: Autism, Intervention, Time on Task, Teaching Methods
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Preiss, David D. – Learning and Individual Differences, 2009
I investigated the instructional pattern for the teaching of language at the elementary school level in Chile. The data were obtained from analyzing videos filmed for a teaching assessment system implemented by the Chilean Government. The system identified four levels of teacher competence. I treated these levels of competence as an independent…
Descriptors: National Programs, Foreign Countries, Time on Task, Teaching Methods
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Krupski, Antoinette – Exceptional Children, 1985
Learning disabled and nondisabled (N=22) children were individually observed in their classroom. Results indicated that normal youngsters spent about 80 percent of observed time on-task regardless of task demands. Learning disabled youngsters varied in their on-task behavior as a function of task demands. (Author/CL)
Descriptors: Attention, Behavior Patterns, Learning Disabilities, Time on Task
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