The paper describes the research of causal relationships between the factors of technological, organizational, environmental, and personal contexts and their influence on the development of learning intentions in potential students. Its purpose was to develop a mechanism for designing a public online educational resource platform based on the…

The pedagogy aspect of education has been the key factor influencing the effectiveness and quality of e-learning platforms. However, there is a lack of systematic review with an emphasis on the pedagogical aspect when it comes to e-learning in higher education. This research aims to systematically review seven major databases to identify the…

This study aimed to evaluate structural models and measurement models of student satisfaction in online learning. This was a quantitative study using a survey research design. Structural model testing was done by examining the relationship between several variables. The variables in question were the learning management system (LMS), admin…

The recommendation is an active area of scientific research; it is also a challenging and fundamental problem in online education. However, classical recommender systems usually suffer from item cold-start issues. Besides, unlike other fields like e-commerce or entertainment, e-learning recommendations must ensure that learners have the adequate…

This systematic review sheds light on the role of ontologies in predicting achievement among online learners, in order to promote their academic success. In particular, it looks at the available literature on predicting online learners' performance through ontological machine-learning techniques and, using a systematic approach, identifies the…

MOOC platforms provide a means of communication through forums, allowing learners to express their difficulties and challenges while studying various courses. Within these forums, some posts require urgent attention from instructors. Failing to respond promptly to these posts can contribute to higher dropout rates and lower course completion…

Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…

There is a growing need to empirically evaluate the quality of online instructional interventions at scale. In response, some online learning platforms have begun to implement rapid A/B testing of instructional interventions. In these scenarios, students participate in series of randomized experiments that evaluate problem-level interventions in…

The adaptation of traditional systems to service-oriented architectures is very frequent, due to the increase in technologies for this type of architecture. This has led to the construction of frameworks or methodologies for adapting computational projects to service-oriented architecture (SOA) technology. In this work, a framework for adaptation…

Churn in e-learning refers to learners who gradually perform less and become lethargic and may potentially drop out from the course. Churn prediction is a highly sensitive and critical task in an e-learning system because inaccurate predictions might cause undesired consequences. A lot of approaches proposed in the literature analyzed and modeled…

Prior research on the "Community of Inquiry" (CoI) framework has a limited amount of work which uses structural techniques to confirm the factorial structure of the CoI. The current study investigates the structural relationships among the three elements of the CoI framework (cognitive presence, teaching presence, and social presence),…

Tutoring promotes student achievement, academic independence, and the reduction of anxiety. While ample studies support tutoring for enhancing student success, few address how to evaluate tutoring. This quandary led to research in building and testing a meta-model that identified the hallmarks of one-on-one high-quality online tutoring.…

In e-learning environments, most adaptive systems do not consider the learner's emotional state when recommending activities for learning difficulties, blockages, or demotivation. In this paper, we propose a new approach of emotion-based adaptation in e-learning environments. The system will allow recommendation resources/activities to motivate…

The development of technology-based learning cannot replace the teacher's role as an educator, but the teacher who does not want to learn technology, the teacher will be replaced. During the COVID-19 pandemic and the digital era of technology, it provides opportunities for teachers to develop creative ideas in the use of online learning media.…

The models of E-learning Readiness (ELR) are basically designed to understand the process of obtaining the basic information necessary for measuring ELR among participants. They help organizations to identify the requirements for designing, developing and implementing E-learning. These models not only help the organizations to identify the degree…