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…

As universities around the world have begun to use learning management systems (LMSs), more learning data have become available to gain deeper insights into students' learning processes and make data-driven decisions to improve student learning. With the availability of rich data extracted from the LMS, researchers have turned much of their…

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…

This research piece has the following goals: (1) to create a curriculum for creating a competency-based learning management system based on the economically motivated approach (BCG Model) by utilizing the proactive learning management concept for students practice teaching professional experience, (2) to assess the success of the curriculum in…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

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…

Purpose: Although E-learning has been in use for over two decades, running parallel to traditional learning systems, it has gained increased attention due to its vital role in universities in the wake of the COVID-19 pandemic. The primary challenge within E-learning pertains to the maintenance of sustainable effectiveness and the assurance of…

This dissertation in practice investigated and addressed the issue of low faculty engagement with instructional design support (IDS) office support services at a regional comprehensive university in the United States. The Performance Improvement/Human Performance Technology (PI/HPT) model used in this study is a practitioner-based performance…

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…

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…

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…

The learning management system (LMS) is claimed to be a crucial strategy for creating successful e-learning and teaching methods, enhancing students' learning satisfaction and achieving academic outcomes. Although the Indonesia Open University has implemented e-learning innovation through LMS in higher education, it has not gained popularity.…

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…