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…

Poor academic performance remains among the most concerning educational issues, especially in higher education and online learning. To address the concern, institutions like the University of Southeastern Philippines (USeP) leverage educational data mining (EDM) techniques to generate relevant information from learning management systems (LMS)…

The sustainable development of Internet education platforms has not been a research focus due to the continuous renewal of artificial intelligence, big data, and policies across different countries and regions. To address this gap, this paper utilizes bibliometric analysis and visualization tools to analyze the development of online education…

E-learning readiness (ELR) is critical for implementing digital education strategies, particularly in developing countries where online learning faces unique challenges. This study aims to provide a concise and actionable framework for assessing and predicting ELR in Algerian universities by combining the ADKAR model with advanced machine learning…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…

Purpose: This paper aims to investigate the relationship between the students' digital activities and their academic performance through two stages. In the first stage, students' digital activities were studied and clustered based on the attributes of their activity log of learning management system (LMS) data set. In the second stage, the…

Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…

Purpose: This paper aims to describe the statistical arguments produced by third-grade students (8-9 years old) and to identify the teaching support for collective argumentation in a lesson based on data comparison. A Lesson Study Group researched and planned the lesson around a problem from the official mathematics textbook.…

The current study provides an integrated comprehensive analysis of mediation-moderation models to understand 567 tourism and hospitality students' viewpoints by exploring multidisciplinary contributions relevant to the big data and new technology application bodies of literature. The results show that self-efficacy was the primary motivation…

This study reviews the journal publications of artificial intelligence-supported online learning (AIoL) in the Web of Science (WOS) database from 1997 to 2019 taking into account the contributing countries/areas, leading journals, highly cited papers, authors, research areas, research topics, roles of AIoL, and adopted artificial intelligence (AI)…

As Canadian post-secondary institutions emerge from the pandemic restrictions, they are in a historically unique position to assess how online education has both facilitated and hindered learning, and how the effects might be greater for some. In this study, open-ended comments from the Canadian Digital Learning Research Association 2022 Spring…

Aim/Purpose: To gain insight into the opinions and reviews of Malaysian university students regarding e-learning systems, thereby improving the quality and services of these systems and resolving any problems, concerns, and issues that may exist within the institution. Background: This exploratory study examines the students' perceptions of…

Online learning systems allow learners to freely access learning contents and record their interactions throughout their engagement with the content. By using data mining techniques on the student log data of those systems, it is possible to examine learning behavior and reveal navigation patterns through learning contents. This study was aimed at…

As a requirement of our era, digital competence and e-learning have become basic competencies. The importance of these concepts has become clearer in medical education, especially with the COVID-19 pandemic. This period also triggered the transformation in education with technology. This study aimed to examine the relationship between medical…

The dataset includes data from 1699 higher education students from two Slovenian universities. Among those participants were also 56 students with special educational needs (SEN). Students were enrolled in all study fields and levels. The study aimed to measure the use of online learning resources (OLRs) among higher education students and…