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Berkan Celik; Kursat Cagiltay – Education and Information Technologies, 2024
MOOC learners come from different backgrounds, and they have various motivations and intentions for taking online courses. This study examines learner intentions with subsequent behaviors and the reasons for the intention-behavior gap in MOOCs. A total of four MOOCs from BilgeIs MOOC Portal was used in this study. This quantitative study with a…
Descriptors: Students, MOOCs, Intention, Student Behavior
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Hengtao Tang; Yeye Tang; Miao Dai; Xu Du; Jui-Long Hung; Hao Li – TechTrends: Linking Research and Practice to Improve Learning, 2024
Blended learning, integrating online and in-person components, has been increasingly adopted in higher education to enhance students' learning experience and outcomes. While the advantages of blended learning are well-evidenced, research has primarily focused on the online pre-learning component, neglecting the significance of in-class activities.…
Descriptors: Blended Learning, Behavior Patterns, Learning Processes, Learning
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Osipenko, Maria – Education and Information Technologies, 2022
A data-driven model where individual learning behavior is a linear combination of certain stylized learning patterns scaled by learners' affinities is proposed. The absorption of stylized behavior through the affinities constitutes "building blocks" in the model. Non-negative matrix factorization is employed to extract common learning…
Descriptors: Behavior Patterns, Models, Undergraduate Students, Preferences
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Esteban Villalobos; Isabel Hilliger; Carlos Gonzalez; Sergio Celis; Mar Pérez-Sanagustín; Julien Broisin – Journal of Learning Analytics, 2024
Researchers in learning analytics have created indicators with learners' trace data as a proxy for studying learner behaviour in a college course. Student Approaches to Learning (SAL) is one of the theories used to explain these behaviours, distinguishing between deep, surface, and organized study. In Latin America, researchers have demonstrated…
Descriptors: Learning Analytics, Academic Achievement, Role Theory, Learning Processes
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Biedermann, Daniel; Ciordas-Hertel, George-Petru; Winter, Marc; Mordel, Julia; Drachsler, Hendrik – Journal of Learning Analytics, 2023
Learners use digital media during learning for a variety of reasons. Sometimes media use can be considered "on-task," e.g., to perform research or to collaborate with peers. In other cases, media use is "off-task," meaning that learners use content unrelated to their current learning task. Given the well-known problems with…
Descriptors: Learning Processes, Learning Analytics, Information Technology, Behavior Patterns
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Hui Shi; Yihang Zhou; Vanessa P. Dennen; Jaesung Hur – Education and Information Technologies, 2024
The imbalance in student-teacher ratio and the diversity of student population pose challenges to MOOC's quality of instructor support. An understanding of student profiles, such as who they are and how they behave, is critical to improving personalized support of MOOC learning environments. While past studies have explored different types of…
Descriptors: MOOCs, Behavior Patterns, Student Behavior, Cluster Grouping
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Xiaona Xia; Wanxue Qi – Education and Information Technologies, 2024
The full implementation of MOOCs in online education offers new opportunities for integrating multidisciplinary and comprehensive STEM education. It facilitates the alignment between online learning content and learning behaviors. However, it also presents new challenges, such as a high rate of STEM dropouts. Many learners struggle to establish…
Descriptors: Graphs, MOOCs, STEM Education, Learning Processes
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Rose Sebastian; Anandita Krishnamachari; Andrew McCartney – Journal of Education for Teaching: International Research and Pedagogy, 2024
Consultation evenings, also known as parent-teacher conferences, are important opportunities for teachers to strengthen their relationships with caregivers. Many teachers, however, are unprepared, having had few opportunities to build skills and participate in real consultations during teacher training. To provide student teachers with more…
Descriptors: Student Teachers, Parent Teacher Conferences, Simulation, Behavior Patterns
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Li, Xiaoyin; Clarke, Nickeisha; Kim, Su-Young; Ray, Anne E.; Walters, Scott T.; Mun, Eun-Young – Journal of American College Health, 2022
Objective: To examine race, gender, and alcohol use level as moderators of the association between protective behavioral strategies (PBS) and alcohol-related problems. Participants: A sample of 12,011 participants who reported recent drinking (87.7% White, 61% Women) from Project INTEGRATE, a study that combined individual participant data (IPD)…
Descriptors: Alcohol Abuse, Drinking, Student Behavior, Race
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Melvin Prince; Emma Wang – Journal of Further and Higher Education, 2024
Past studies of academic dishonesty typically have been grounded in the theory of planned behaviour. Key predictors of academic dishonesty variables under this framework generally have been attitudes towards academic dishonesty, the impact of peer pressure to engage in such acts, and individual perceptions of related acts. However, planned…
Descriptors: Integrity, Cheating, Ethics, Student Behavior
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Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
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Liu, Sannyuya; Kang, Lingyun; Liu, Zhi; Fang, Jing; Yang, Zongkai; Sun, Jianwen; Wang, Meiyi; Hu, Mengwei – Interactive Learning Environments, 2023
Computer-supported collaborative concept mapping (CSCCM) integrates technology and concept mapping to support students' knowledge understanding, and much research on the behavioral patterns involved in CSCCM activities has been conducted. However, there is limited understanding of the differences in knowledge understanding and behavioral patterns…
Descriptors: Computer Assisted Instruction, Concept Mapping, Student Attitudes, College Students
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Yun Tang; Zhengfan Li; Guoyi Wang; Xiangen Hu – Interactive Learning Environments, 2023
To better understand the self-regulated learning process in online learning environments, this research applied a data mining method, the two-layer hidden Markov model (TL-HMM), to explore the patterns of learning activities. We analyzed 25,818 entries of behavior log data from an intelligent tutoring system. Results indicated that students with…
Descriptors: Electronic Learning, Learning Activities, Self Management, Intelligent Tutoring Systems
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Kang, Jina; Liu, Min – Technology, Knowledge and Learning, 2022
An open-ended serious game can engage students' scientific problem-solving processes. However, understanding how students learn higher-order thinking skills through solving a problem in an open-ended game system is a challenge. The complex game systems may make learning more difficult for students with different characteristics such as an at-risk…
Descriptors: Student Behavior, Behavior Patterns, Navigation, Educational Games
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Dorea-Bandeira, Ingrid; Oliveira, Vanessa Gusmão de; Araújo-Pereira, Mariana; Andrade, Bruno Bezerril; Nazar, André Nogueira; Quintanilha, Luiz Fernando; Avena, Katia de Miranda – Problems of Education in the 21st Century, 2022
Academic misconduct during medical school is common, with multifactorial causes, and can negatively impact the training and professional performance of future physicians. This study investigated factors linked to academic misconducts among medical students during their training. It is a transversal, quantitative, and analytical study that assessed…
Descriptors: Foreign Countries, Medical Students, Student Attitudes, Perception
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