NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 5 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Yangyang Luo; Xibin Han; Chaoyang Zhang – Asia Pacific Education Review, 2024
Learning outcomes can be predicted with machine learning algorithms that assess students' online behavior data. However, there have been few generalized predictive models for a large number of blended courses in different disciplines and in different cohorts. In this study, we examined learning outcomes in terms of learning data in all of the…
Descriptors: Prediction, Learning Management Systems, Blended Learning, Classification
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Yue; Jiang, Qiang; Xiong, Weiyan; Zhao, Wei – Education and Information Technologies, 2023
One of the recognized ways to enhance teaching and learning is having insights into the behavior patterns of students. Studies that explore behavior patterns in online self-directed learning (OSDL) are scant though. In addition, the focus is lacking on how high-achieving (HA) students' behavior patterns affect the academic performance of…
Descriptors: Student Behavior, Behavior Patterns, Electronic Learning, Online Courses
Peer reviewed Peer reviewed
Direct linkDirect link
Nan Yang; Patrizia Ghislandi – Higher Education: The International Journal of Higher Education Research, 2024
The two main trends in the development of higher education worldwide are universal access and digital transformation. These trends are bringing about an increase in class sizes and the growth of online higher education. Previous studies indicated that both the large-class setting and online delivery threaten the quality, and the exploration of…
Descriptors: Foreign Countries, Required Courses, Educational Quality, Teaching Methods