Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…

In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…

Purpose: Although E-learning has been in use for over two decades, running parallel to traditional learning systems, it has gained increased attention due to its vital role in universities in the wake of the COVID-19 pandemic. The primary challenge within E-learning pertains to the maintenance of sustainable effectiveness and the assurance of…

Despite the importance of physics practical work in higher education, its implementation is often hampered by various constraints and problems. Technology, such as learning management systems (LMS) and mobile learning, can offer solutions to some of these problems and enrich students' learning experiences. Therefore, this research proposes a model…

This study aims to adapt and extend the DeLone and McLean Information System (IS) success model in the context of an online English as a Foreign Language (EFL) higher education foundation program. The objective is to enhance teaching, learning, and knowledge-sharing experiences within a virtual community of practice (vCoP). The research involved…

Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…

Blended learning sets solid foundations for the utilization of educational technology in authentic student learning experiences within traditional educational contexts as well as in distance education. The author introduces an integrated and distributed model of blended learning, utilizing educational technology for authentic student learning…

One of the main generic competencies in Higher Education is "Learning to Learn". The key component of this competence is the capacity for self-regulated learning (SRL). For this competence to be developed, peer feedback seems useful because it fosters evaluative judgement. Following the principles of peer feedback processes, an online…

Online learning continues to grow at unprecedented rates. K-12 had more than 275,000 students enrolled in full-time virtual schools in 2011--2012 and over 2 million participating in at least one online course. Despite this growth, there is little research on model formation and model validation for online learning. Two research-based models were…

The goal of learning analytics is to optimize learning and the environments in which it occurs. Since 2011, when learning analytics was defined as a separate and distinct area of academic inquiry, the literature has identified a need for research that presents evidence of effective learning analytics, as well as, learning analytics research that…

Even before the pandemic, the college/university business model was under scrutiny. With rising tuition costs outpacing living wages, and student debt burdens crippling students, institutions of higher learning were grappling with how to evolve. The COVID-19 pandemic introduced an abundance of obstacles that colleges had to face head on, but they…