Recent years have witnessed an increased interest in online education, both massive open
online courses (MOOCs) and small private online courses (SPOCs). This significant interest …

Predicting university student graduation is a beneficial tool for both students and institutions.
With the help of this predictive capacity, students may make well-informed decisions about …

Student dropout is a serious problem globally. It affects not only the individual who drops out
but also the former school, family, and society in general. With the current development of …

Data-driven predictive models are increasingly used in education to support students,
instructors, and administrators, which has raised concerns about the fairness of their …

Accompanied with the development of storage and processing capacity of modern
technology, educational data increases sharply. It is difficult for educational researchers to …

Featured Application The found model with the best values of the performance metrics,
found as the result of comparing several machine learning classifiers, can identify students …

The core of dropout prediction lies in the selection of predictive models and feature tables.
Machine learning models have been shown to predict student dropouts accurately. Because …

The student academic performance prediction is becoming an indispensable service in the
computer supported intelligent education system. But conventional machine learning-based …

Artificial intelligence (AI) is gaining demanding growth in the field of smart cities, agriculture,
food management, and weather forecasting due to the lack of computing power on sensing …

Self-regulated learning (SRL) can be defined as the ability of learners to act independently
and actively manage their own learning process. This skill becomes especially important in …