The goal of this study was to create a model for predicting the factors that influence
graduates' decisions to continue their studies at the master's level within the same institution …

Predicting student dropout is a crucial task in online education. Traditionally, each
educational entity (institution, university, faculty, department, etc.) creates and uses its own …

Introduction As artificial intelligence (AI) technology becomes more widespread in the
classroom environment, educators have relied on data-driven machine learning (ML) …

Featured Application The student performance data stored in the micro-learning platform
Priscilla, specially developed to improve IT students' knowledge, is analyzed using learning …

Data Mining (DM) is method for determining hidden patterns and relationships within large
datasets using statistical and computational methods [1]. It includes obtaining meaningful …

In the context of the COVID-19 global pandemic, highly intense and frequent online teaching
has leapt to be one of the dominant learning patterns and become an ordinary situation in …

An educational institution's primary objective is to create a learning environment that
enhances student academic success by mitigating academic failure and promoting higher …

Predicting student performance is crucial for both preventing failure and enabling
personalized teaching-and-learning strategies. The digitalization of educational institutions …

Assessment is a crucial part of education. Traditional marking is a source of inconsistencies
and unconscious bias, placing a high cognitive load on the assessors. An approach to …

This paper describes a project carried out between the University and a course provider
company, where an early dropout prediction system has been developed in fully online …