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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
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
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
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
Rotelli, Daniela; Monreale, Anna – Journal of Learning Analytics, 2023
The increased adoption of online learning environments has resulted in the availability of vast amounts of educational log data, which raises questions that could be answered by a thorough and accurate examination of students' online learning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensions that…
Descriptors: Learning Analytics, Learning Management Systems, Time on Task, Student Behavior
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
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)
Kasakowskij, Regina; Haake, Joerg M.; Seidel, Niels – International Educational Data Mining Society, 2023
Improving competence requires practicing, e.g. by solving tasks. The Self-Assessment task type is a new form of scalable online task providing immediate feedback, sample solution and iterative improvement within the newly developed SAFRAN plugin. Effective learning not only requires suitable tasks but also their meaningful usage within the…
Descriptors: Self Evaluation (Individuals), Student Behavior, College Students, Learning Processes
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
Mohd Fazil; Angelica Rísquez; Claire Halpin – Journal of Learning Analytics, 2024
Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…
Descriptors: Learning Analytics, Learning Management Systems, Learning Processes, Decision Making
Lars de Vreugd; Anouschka van Leeuwen; Renée Jansen; Marieke van der Schaaf – Journal of Learning Analytics, 2024
For university students, self-regulation of study behaviour is important. However, students are not always capable of effective self-regulation. Providing study behaviour information via a learning analytics dashboard (LAD) may support phases within self-regulated learning (SRL). However, it is unclear what information a LAD should provide, how to…
Descriptors: Learning Management Systems, Learning Analytics, Student Behavior, Behavior Patterns
Chi-Tung Chen; Chih-Ming Chen; Hsiao-Ting Tsai – Interactive Learning Environments, 2024
This study utilised the instant semantic analysis and feedback system (ISAFS) to assist learners in the online discussion learning activities of socio-scientific issues (SSIs) and to document their learning process behaviours for behavioural analyses. The aim was to understand the learners' discussion behaviours during the ISAFS assisted learning…
Descriptors: Behavior Patterns, Electronic Learning, Discussion, Instructional Effectiveness
Nguyen, Huu Thanh Minh – TESL-EJ, 2023
Understanding the IELTS washback on learning in English as a Foreign Language (EFL) in higher education contexts remains limited. To fill in this research gap, this study investigated washback effects of the International English Language Testing System (hereafter called IELTS) as an English language proficiency exit test for final-year English…
Descriptors: Testing Problems, English (Second Language), Second Language Learning, Second Language Instruction
Liu, Min; Li, Chenglu; Pan, Zilong; Pan, Xin – Interactive Learning Environments, 2023
More research is needed on how to best use analytics to support educational decisions and design effective learning environments. This study was to explore and mine the data captured by a digital educational game designed for middle school science to understand learners' behavioral patterns in using the game, and to use evidence-based findings to…
Descriptors: Computer Games, Educational Games, Instructional Design, Instructional Effectiveness
Jennie K. Grammer; Keye Xu; Agatha Lenartowicz – npj Science of Learning, 2021
Activities that are effective in supporting attention have the potential to increase opportunities for student learning. However, little is known about the impact of instructional contexts on student attention, in part due to limitations in our ability to measure attention in the classroom, typically based on behavioral observation and…
Descriptors: Correlation, Classroom Environment, Attention Control, Diagnostic Tests