Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…

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…

In this study, we report on a Systematic Mapping Study (SMS) for the application of technology acceptance models to Moodle under the prism of latent variable modeling. Based on an automatic search including primary studies from journals, conferences, and book chapters during 2001 to 2019, 41 primary were selected. We aim to contribute to a better…

With the explosive growth of various applications on the Internet, higher education institutions have advocated distance learning courses, making research on online learning increasingly important. This study attempts to emphasize the characteristics of instruction in online learning systems, using the Theory of Planned Behavior. Two groups of…

To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…

This paper describes a neural network model that can be used to detect at- risk students failing a particular course using only grade book data from a learning management system. By analyzing data extracted from the learning management system at the end of week 5, the model can predict with an accuracy of 88% whether the student will pass or fail…

Learning Management Systems (LMS) have gained importance in the last few years; however, the emergence of COVID-19 disease made these systems indispensable for educational systems. In the post-pandemic scenario and blended learning contexts, this kind of information system is also becoming more critical as a support system. Therefore, this…

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…

Purpose: The aim of this study is to explore and establish the relationships between justice dimensions, expectation-confirmation model (ECM) and continuance intention and also to examine the mediating effect of learners' satisfaction and perceived usefulness toward continuance intentions of the university learning management system (LMS) within…

The research attempted to study the readiness and need for the Dual Vocational Education Model for the Diploma Program in Aviation of Khon Kaen Industrial and Community Education College and to create, experiment, and assess the program. The research was conducted from 2014 to 2018 with 60 teachers teaching in the college and 16 in the workplaces…

Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…

One of the main generic competencies in Higher Education is "Learning to Learn". The key component of this competence is the capacity for self-regulated learning (SRL). For this competence to be developed, peer feedback seems useful because it fosters evaluative judgement. Following the principles of peer feedback processes, an online…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

Various theories and models are used to understand the impact of technology in education. One of these models is the UTAUT-2 model. This model allows us to understand the acceptance and use of technology. In this study, students' intentions and behaviours related to using the UBYS system, which is used as a learning management system, were…

The objective of this research is to develop and study the outcomes of developing the Ubiquitous Buddhism Learning Ecosystem for Proactive Buddhism Propagation for Digital Citizenship. The sample group used in the research consists of nine individuals selected through targeted sampling, comprising experts in the design and development of learning…