The aim of this paper is to survey recent research publications that use Soft Computing
methods to answer education-related problems based on the analysis of educational data …

Student success is essential for improving the higher education system student outcome.
One way to measure student success is by predicting students' performance based on their …

Undersampling is a widely used resampling technique for imbalanced data. As traditional
undersampling techniques, typically making majority and minority classes in imbalanced …

This paper introduces a novel approach to identify at-risk students with a focus on output
interpretability through analyzing learning activities at a finer granularity on a weekly basis …

In recent years, many research studies have focused on personalized e-learning. One of the
most crucial parts of any learning environment is having a learning style that focuses on …

This paper investigates the symptoms of failure in public corporations with multiple
hospitality businesses and examines whether a new case-based deep-layer predictive …

Online learning environments became popular in recent years. Due to high attrition rates,
the problem of student dropouts became of immense importance for course designers, and …

Studies on the prediction of student success in distance learning have explored mainly
demographics factors and student interactions with the virtual learning environments …

Procrastination, the irrational delay of tasks, is a common occurrence in online learning.
Potential negative consequences include a higher risk of drop-outs, increased stress, and …

Understanding the research landscape of any domain is of primary importance at all stages
of a concept's evolution. Research in the domain of analytics has increased exponentially in …