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…

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…

This research addresses the pressing need for innovative educational frameworks that foster creativity and innovation in online learning environments. The study develops and validates a comprehensive model integrating STEAM education, micro-learning principles, and augmented reality (AR) technology within massive open online courses (MOOCs).…

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…

Online learning communities play a crucial role in delivering high-quality courses to a large number of learners. However, to maintain an economically sustainable and constantly evolving online learning ecosystem, it is essential to create a virtuous cycle from knowledge production to knowledge consumption by charging learners to incentivize…

Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…

This study advances the emerging research on shared metacognition through the lens of the community of inquiry framework. It seeks components and utterances of the community of inquiry and shared metacognition in online collaborative learning environments to bring an instructional design model to the fore. A three-cycle design-based research…

The aim of research is to reveal the effect of a training program based on the TAWOCK model for teaching computational thinking skills on teaching self-efficacy among computer teachers. It used the quasi-experimental approach, with a pre-test and post-test design with a control group. An electronic training program based on the TAWOCK model was…

This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an "interest" parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. Controlled experiments, spanning diverse online platforms, validate the ARM model's…