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Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
Saleh Alhazbi; Afnan Al-ali; Aliya Tabassum; Abdulla Al-Ali; Ahmed Al-Emadi; Tamer Khattab; Mahmood A. Hasan – Journal of Computer Assisted Learning, 2024
Background: Measuring students' self-regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self-report questionnaires and think aloud protocols have been used to measure self-regulated learning skills (SRL). However, these methods are…
Descriptors: Learning Analytics, Independent Study, Higher Education, College Students
Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Sonja Kleter; Uwe Matzat; Rianne Conijn – IEEE Transactions on Learning Technologies, 2024
Much of learning analytics research has focused on factors influencing model generalizability of predictive models for academic performance. The degree of model generalizability across courses may depend on aspects, such as the similarity of the course setup, course material, the student cohort, or the teacher. Which of these contextual factors…
Descriptors: Prediction, Models, Academic Achievement, Learning Analytics
Maloney, Suzanne; Axelsen, Megan; Galligan, Linda; Turner, Joanna; Redmond, Petrea; Brown, Alice; Basson, Marita; Lawrence, Jill – Online Learning, 2022
Driven by the increased availability of Learning Management System data, this study explored its value and sought understanding of student behaviour through the information contained in activity level log data. Specifically, this study examined analytics data to understand students' engagement with online videos. Learning analytics data from the…
Descriptors: Learning Analytics, Video Technology, Learning Management Systems, Comparative Analysis
Wan, Han; Zhong, Zihao; Tang, Lina; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2023
Small private online courses (SPOCs) have influenced teaching and learning in China's higher education. Learning management systems (LMSs) are important components in SPOCs. They can collect various data related to student behavior and support pedagogical interventions. This research used feature engineering and nearest neighbor smoothing models…
Descriptors: Online Courses, Learning Management Systems, Higher Education, Student Behavior
Watanabe, Hiroyuki; Goda, Yoshiko; Shimada, Atsushi; Yamada, Masanori – International Association for Development of the Information Society, 2021
Learning assistance is an essential part of higher education. Tutors, the core of the assistance staff, need to have learning assistance skills. If the potential for these skills can be identified when selecting tutors, the training method will be more efficient. Also, learning assistance skills are thought to be related to learning skills.…
Descriptors: Learning Analytics, Higher Education, Tutors, Learning Processes
Shabnam Ara S. J.; Tanuja R. – Journal of Education and e-Learning Research, 2024
Understanding the factors that influence students' results in hybrid learning environments is becoming increasingly important in today's educational environment. The goal of this research is to examine factors that influence students' academic performance as well as their level of participation in blended learning environments. A comprehensive…
Descriptors: Academic Achievement, Blended Learning, Learning Analytics, Technology Education