Learning Management System (LMS) can track student interactions with digital learning resources during an online learning activity. Learners with different goals, motivations and preferences may exhibit different behaviours when accessing these materials. These different behaviours may further affect their learning performance. The purpose of this…

This study aimed to develop a prediction model to classify students based on their academic procrastination tendencies, which were measured and classified as low and high using a self-report tool developed based on the students' assignment submission behaviours logged in the learning management system's database. The students' temporal learning…

On e-learning platforms, most e-learners didn't complete the course successfully. It means that reducing dropout is a critical problem for the sustainability of e-learning. This paper aims to establish a predictive model to describe e-learners' dropout behavior, which can help the commercial e-learning platforms to make appropriate interventions…

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…

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…

Purpose: This study aims to investigate factors that could predict the continued usage of e-learning systems, such as the learning management systems (LMS) at a Technical University in Ghana using machine learning algorithms. Design/methodology/approach: The proposed model for this study adopted a unified theory of acceptance and use of technology…

Digital advances in the learning space have changed the contours of student engagement as well as how it is measured. Learning management systems and other learning technologies now provide information about student behaviors with course materials in the form of learning analytics. In the context of a large, integrated and interdisciplinary Core…

Purpose: Through the lens of the information systems success model, self-determination theory, and TAM2, this study proposes and tests an integrative model to investigate students' satisfaction with the use of e-learning systems in higher education institutions in a developing country context. Design/methodology/approach: This study adopted a…

Developed to maximize learning performance, learning analytics dashboards (LAD) are becoming increasingly commonplace in education. An LAD's effectiveness depends on how it is used and varies according to users' academic levels. In this study, two LADs and a learning support system were used in a higher education course to support students'…

Procrastination is a significant problem in academia with some estimates suggesting that this occurs in as high as 70-90% of college students (Abdi Zarrin & Gracia, 2020) that manifests in numerous harmful ways including postponement of weekly reading assignments, delay in writing term papers, and inadequate preparation and beginning too late…

Purpose: This paper aims to investigate the relationship between the students' digital activities and their academic performance through two stages. In the first stage, students' digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the…

Students' and instructors' adoption of "e-learning management systems (e-LMSs)" is critical to their success in a "virtual learning environment." Students can use "e-learning" to obtain instructional materials to supplement "traditional classroom" instruction. This study intends to highlight the important…

The COVID-19 pandemic precipitated a global shift to fully remote learning via learning management systems (LMS). Despite this significant shift, there has been a paucity of research exploring how students of varying academic performance engage with online learning resources. This study investigates the utilization of LMS among students with…

Education is increasingly infiltrated by technology and datafication. This techno-data amplification is entangled with neoliberalism and the emphasis on calculation and measurement it brings, often through metrics. This article critically examines how metrics are shaping discipline practices in schools through ClassDojo, a popular platform for…

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…