MOOC learners come from different backgrounds, and they have various motivations and intentions for taking online courses. This study examines learner intentions with subsequent behaviors and the reasons for the intention-behavior gap in MOOCs. A total of four MOOCs from BilgeIs MOOC Portal was used in this study. This quantitative study with a…

A data-driven model where individual learning behavior is a linear combination of certain stylized learning patterns scaled by learners' affinities is proposed. The absorption of stylized behavior through the affinities constitutes "building blocks" in the model. Non-negative matrix factorization is employed to extract common learning…

The imbalance in student-teacher ratio and the diversity of student population pose challenges to MOOC's quality of instructor support. An understanding of student profiles, such as who they are and how they behave, is critical to improving personalized support of MOOC learning environments. While past studies have explored different types of…

The full implementation of MOOCs in online education offers new opportunities for integrating multidisciplinary and comprehensive STEM education. It facilitates the alignment between online learning content and learning behaviors. However, it also presents new challenges, such as a high rate of STEM dropouts. Many learners struggle to establish…

Procrastination is one of the issues affecting more than half of the student population and is known to impact them negatively. It is also one of the major reasons for failure and dropout. Therefore, several studies have been conducted in this domain to understand when and why students procrastinate. The existing studies use self-reported…

In recent years, online education has been given more and more attention with the widespread use of the internet. The teaching procedure divides space and makes time for online learning; though teachers cannot control the learners accurately, the state of education calculates learners' learning situation. This paper explains that the discourse…

With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…

One of the recognized ways to enhance teaching and learning is having insights into the behavior patterns of students. Studies that explore behavior patterns in online self-directed learning (OSDL) are scant though. In addition, the focus is lacking on how high-achieving (HA) students' behavior patterns affect the academic performance of…

Since the COVID pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major drop in the learner's performance and his/her dissatisfaction with the learning experience. This may be due to several reasons, including the insensitivity of the virtual learning environment to the…

Previous research has produced contrasting findings regarding the influence of social networking on academic performance. Many have found negative relationships but some have also demonstrated a positive effect for social networking on academic performance. Still others report no links between social networking and academic performance.…

The learning style of a learner is an important parameter in his learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments to increase learners' performance. Thus, it is important to be able to automatically determine learning styles of learners in an e-learning…