Ensuring fair access to quality education is essential for every education system to fully
realize every student's potential. Nowadays, machine learning (ML) is transforming …

The purpose of this study was to investigate the use of predictive video analytics in online
courses in the literature. A systematic literature review was performed based on a hybrid …

Traditional learning-based approaches to student modeling generalize poorly to
underrepresented student groups due to biases in data availability. In this paper, we …

In recent years, distance learning using learning management and e-book systems has
been actively conducted in higher education institutions and various other organizations. It is …

Student performance prediction is vital for identifying at-risk students and providing support
to help them succeed academically. In this paper, we propose a feature importance-based …

Conventional methods for student modeling, which involve predicting grades based on
measured activities, struggle to provide accurate results for minority/underrepresented …

Recent advances in artificial intelligence (AI) and crowdsourcing have shown success in
enhancing learning experiences and outcomes in online education. This paper studies a …

Describing and analysing learner behaviour using sequential data and analysis is becoming
more and more popular in Learning Analytics. Nevertheless, we found a variety of definitions …

Predictive learning outcomes' models for online students can provide useful information to
instructors to estimate students' final performance in the early stages of a course …

Abstract Massive Open Online Courses (MOOCs) have gradually become a dominant trend
in online education. However, due to the large number of learners participating in MOOCs …