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…

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…

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…

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…

Online-only course design has to balance students' needs to experience (1) competence and (2) autonomy as it may affect their motivation. Lecture units can provide structured guidance by being made accessible in a fixed order, or support students' autonomy by providing free access to all lecture units. Online-only courses with lecture units…

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…

This predictive-causal study determined the factors affecting students' Behavioral Intention (BI) and Actual Use (AU) of Canvas Learning Management System (LMS) and Zoom for both synchronous and asynchronous classes in a private higher education institution in the Philippines adopting Technology Acceptance Mode (TAM). After surveying 496 students,…

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…

This paper presents the first experiences of the use of an online open-source repository with programming exercises. The repository is independent of any specific teaching approach. Students can search for and select an exercise that trains the programming concepts that they want to train and that only uses the programming concepts they already…

Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…

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…

One of the biggest challenges for online learning is upholding academic integrity in online assessments. In particular, institutions and faculties attach importance to exam security and academic dishonesty in the online learning process. The aim of this study was to compare the test-taking behaviors and academic achievements of students in…