This study empirically tested a model examining the effect of four e-learning quality dimensions, i.e., information quality, system quality, service quality, and instructor quality as well as students' self-efficacy on e-learning behaviour--satisfaction and continued intentions that further affect students' academic performance. The research model…

The outbreak of COVID-19 has caused significant disruption in all sectors and industries around the world. To tackle the spread of the novel coronavirus, the learning process and the modes of delivery had to be altered. Most courses are delivered traditionally with face-to-face or a blended approach through online learning platforms. In addition,…

The current study aimed to evaluate an online learning experience based on the music model of motivation in an educational technology post-graduate program in Oman. In order to understand the motivational perceptions of students regarding the instruction, a two-phase, sequential explanatory mixed method research design was conducted in this study.…

The adaptive learning environment provides learning support that suits individual characteristics of students, and the student model of the adaptive learning environment is the key element to promote individualized learning. This paper provides a systematic overview of the existing student models, consequently showing that the Elo rating system…

Contribution: Model-based learning improves systems thinking (ST) based on students' prior knowledge and gender. Relations were found between textual, visual, and mixed question types and student achievements. Background: ST is essential to judicious decision-making and problem-solving. Undergraduate students can be taught to apply better ST, and…

In the era of COVID-19 and right after the announcement of it as a pandemic and threat to humanity by the World Health Organization, most educational activities were globally forced to shut down their traditional teaching/learning activities. This is one of the biggest and most vital changes of educational settings which have led to migration to…

We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance modeling problem is a critical step for building adaptive online teaching systems. Specifically, we conduct a study of how to utilize various types and large amounts of log data from earlier…

Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…

Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…

The state of the art knowledge tracing approaches mostly model student knowledge using their performance in assessed learning resource types, such as quizzes, assignments, and exercises, and ignore the non-assessed learning resources. However, many student activities are non-assessed, such as watching video lectures, participating in a discussion…

This study aims to explore the difference between on-line and off-line teaching and comprehensively evaluate the of elearning system operation effect as both technology-mediated learning and an open information system. This study develops "process-situation-result" (PSR) network, a comprehensive learning system evaluation model. It…

The spread of the coronavirus (COVID-19) strongly affected educational management in Thailand. This gave rise to the problem of how to improve the quality of students of all ages through 100% online learning, be this in areas of knowledge, abilities, skills, and attitudes towards learning. Therefore, the Secretariat of the Education Council of…

Predicting student performance is crucial in higher education, as it facilitates course selection and the development of appropriate future study plans. The process of supporting the instructors and supervisors in monitoring students in order to upkeep them and combine training programs to get the best outcomes. It decreases the official warning…

Recently, machine learning (ML) has evolved and finds its application in higher education (HE) for various data analysis. Studies have shown that such an emerging field in educational technology provides meaningful insights into several dimensions of educational quality. An in-depth analysis of the application of ML could have a positive impact on…

We used the design-based research approach to test and refine a theoretically grounded goal-access-feedback-challenge-collaboration gamification model. The testbed was a 10-week, university-level e-learning design course offered in two consecutive semesters. In Study 1, we implemented the initial goal-access-feedback-challenge-collaboration model…