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Lili Aunimo; Janne Kauttonen; Marko Vahtola; Salla Huttunen – Journal of Computing in Higher Education, 2025
Institutions of higher education possess large amounts of learning-related data in their student registers and learning management systems (LMS). This data can be mined to gain insights into study paths, study styles and possible bottlenecks on the study paths. In this study, we focused on creating a predictive model for study completion time…
Descriptors: Data Collection, Learning Management Systems, Study Habits, Time on Task
Anuradha Peramunugamage; Uditha W. Ratnayake; Shironica P. Karunanayaka; Ellen Francine Barbosa; William Simão de Deus; Chulantha L. Jayawardena; R. K. J. de Silva – Journal of Learning for Development, 2025
Interactions among students in online learning environments are difficult to monitor but can be crucial for their academic performance. Moodle is one of the best and most popular online learning platforms, where its log records can reveal important information on students' engagement and the respective performance. This study examines the degree…
Descriptors: Cooperative Learning, Interaction, Electronic Learning, Learning Management Systems
Imhof, Christof; Comsa, Ioan-Sorin; Hlosta, Martin; Parsaeifard, Behnam; Moser, Ivan; Bergamin, Per – IEEE Transactions on Learning Technologies, 2023
Procrastination, the irrational delay of tasks, is a common occurrence in online learning. Potential negative consequences include a higher risk of drop-outs, increased stress, and reduced mood. Due to the rise of learning management systems (LMS) and learning analytics (LA), indicators of such behavior can be detected, enabling predictions of…
Descriptors: Prediction, Time Management, Electronic Learning, Artificial Intelligence
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
Alam, Md. I.; Malone, Lauren; Nadolny, Larysa; Brown, Michael; Cervato, Cinzia – Journal of Computer Assisted Learning, 2023
Background: The substantial growth in gamification research has connected gamified learning to enhanced engagement, improved performance, and greater motivation. Similar to gamification, personalized learning analytics dashboards can enhance student engagement. Objectives: This study explores the student experiences and academic achievements using…
Descriptors: Academic Achievement, Game Based Learning, Introductory Courses, STEM Education
Chamizo-Gonzalez, Julian; Cano-Montero, Elisa Isabel; Urquia-Grande, Elena; Muñoz-Colomina, Clara Isabel – International Journal of Information and Learning Technology, 2015
Purpose: The purpose of this paper are twofold. First, to disclose whether accounting students who participate more in online activities proposed by the teacher achieve better learning outcomes. Second, to identify which virtual learning activities achieve improved outcomes. Design/methodology/approach: Data mining is a computer-based tool devoted…
Descriptors: Outcomes of Education, Accounting, Learning Analytics, Teaching Methods

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