In this paper, we review algorithmic bias in education, discussing the causes of that bias and
reviewing the empirical literature on the specific ways that algorithmic bias is known to have …

The ability to predict student performance in a course or program creates opportunities to
improve educational outcomes. With effective performance prediction approaches …

Several challenges are associated with e‐learning systems, the most significant of which is
the lack of student motivation in various course activities and for various course materials. In …

The student's performance prediction is an important research topic because it can help
teachers prevent students from dropping out before final exams and identify students that …

Predictive analytics methods in education are seeing widespread use and are producing
increasingly accurate predictions of students' outcomes. With the increased use of predictive …

Algorithm discrimination becomes a serious problem. Its far-reaching implications have
attracted the interest of many studies in a variety of disciplines, including computer science …

Machine Learning (ML) techniques have been increasingly adopted to support various
activities in education, including being applied in important contexts such as college …

Este artículo profundiza en el impacto de la Inteligencia Artificial (IA) en la educación,
explorando tanto su potencial transformador como los riesgos asociados. A medida que las …

In recent years, the use of analytics and data mining–methodologies that extract useful and
actionable information from large datasets–has become commonplace in science (ie Jing et …

While machine learning (ML) has been extensively used in Massive Open Online Courses
(MOOCs) to predict whether learners are at risk of dropping-out or failing, very few work has …