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…

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…

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'…

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…

Purpose: Since there is lack of studies in determine factors that affecting enjoyment sentiment when using online learning system, this study aims to explore the antecedents of perceived online learning enjoyment by using extended technology acceptance model (TAM) and its effect on behavioral intentions (BIN) among higher education institutions…

A review of the literature shows that much academic effort has been expended studying information system usage and information technology adoption. However, these theories/models based on psychological research are not specific to the virtual reality context and may not fully capture the nature of virtual reality-based learning system (VR-BLS)…

This empirical study uses a random forest algorithm to examine the factors that influence learners' persistence in online learning at a prominent Korean institution. The data were collected from students who began their studies in Spring 2021, and encompassed a range of variables including individual attributes, academic engagement, academic…

A mobile learning management system (mobile LMS) facilitates the interaction between lecturers and students to transfer knowledge flexibly. With the high possibility of universities adopting a mobile LMS into their learning systems, predicting student acceptance of mobile LMS is critical. Based on an extension of the unified theory of acceptance…

Learning Analytics Dashboards (LADs) are gaining popularity as a platform for providing students with insights into their learning behaviour patterns in online environments. Existing LAD studies are mainly centred on displaying students' online behaviours with simplistic descriptive insights. Only a few studies have integrated predictive…