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…

With the rapid development of information technology, the internet has emerged as a pivotal driving force in reshaping higher education paradigms. This paper delves into clustering algorithms and proposes an enhanced version, exploring how this enhanced clustering algorithm can be applied to blended teaching of digital electronic technology…

Understanding how students engage with feedback is often reduced to a study of feedback messages that sheds little light on effects. Using the emerging notion of feedback encounters as an analytical lens, this study examines what characterizes productive feedback encounters when learning online. Drawing from a cross-national digital ethnographic…

Although e-learning is considered one of the leading teaching methods in higher education, both learners and instructors face significant challenges owing to reduced social interaction compared with traditional classroom learning. In this study, we explore the leveraging of recent developments in generative artificial intelligence (AI) and create…

This study focused on postsecondary students who participated in solely online educational programs. The study sought to determine if there was a correlation between student personality traits and their ability to persist in online programs. In addition, this study revealed if a certain personality profile, based on the dominant trait, correlated…

Purpose: Online education enables location-independent learning, potentially providing university students with more flexible study programs and reducing traffic-related CO2 emissions. This paper aims to examine whether online education can contribute to university-related sustainable everyday mobility, with particular consideration given to…

Purpose: The purpose of this study is to set up an evaluation model to predict massive open online courses (MOOC) learning performance by analyzing MOOC learners' online learning behaviors, and comparing three algorithms -- multiple linear regression (MLR), multilayer perceptron (MLP) and classification and regression tree (CART).…

Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…

Objective: College students tend to have lower body image than other groups, in part because of comparisons they make with peers. The closing of college campuses due to the onset of the COVID-19 pandemic disrupted the ability to compare; thus, we investigate how the transition to and from virtual-learning influenced body image. Participants:…

Background: The growth of online education has provided flexibility and access to a wide range of courses. However, the self-paced and often isolated nature of these courses has been associated with increased dropout and failure rates. Researchers employed machine learning approaches to identify at-risk students, but multiple issues have not been…

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…

Purpose: This research aims to look at how students feel about taking online learning (OL) while studying in higher education institutions (HEIs) using an extended technology acceptance model (TAM). The study looked into the factors that influence students' decisions to use OL, which helps meet their individual needs beyond the confines of the…

Aim/Purpose: The study aims to supplement existing knowledge of information systems by presenting empirical data on the factors influencing the intentions of doctoral students to learn through online platforms. Background: E-learning platforms have become popular among students and professionals over the past decade. However, the intentions of the…

The COVID-19 pandemic precipitated a global shift to fully remote learning via learning management systems (LMS). Despite this significant shift, there has been a paucity of research exploring how students of varying academic performance engage with online learning resources. This study investigates the utilization of LMS among students with…

With the expanding realm of online education in Indonesia, determining factors influencing university students' participation in distinct modes of virtual learning is crucial to developing more effective digital pedagogy. This research aims to scrutinize factors affecting Indonesian EFL (English as a Foreign Language) university students' low…