The last few years have witnessed an upsurge in the number of studies using Machine and
Deep learning models to predict vital academic outcomes based on different kinds and …

Student persistence and retention in STEM disciplines is an important yet complex and multi-
dimensional issue confronting universities. Considering the rapid evolution of online …

The rapid growth of educational data creates the requirement to mine useful information
from learning behavior patterns. The development of data mining technology makes …

We analyze the correlation between different assets in the cryptocurrency market throughout
different phases, specifically bearish and bullish periods. Taking advantage of a fine-grained …

Studies examining students' learning behavior predominantly employed rich video data as
their main source of information due to the limited knowledge of computer vision and deep …

We employ graph-based methods to examine the connectedness between cryptocurrencies
of different market caps over time. By applying denoising and detrending techniques …

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 …

In this study, learning pathways are modelled by networks constructed from the log data of
student–LMS interactions. These networks capture the sequence of reviewing the learning …

Due to the growing demand for information technology skills, programming education has
received increasing attention. Predicting students' programming performance helps teachers …

Data mining approaches have been widely used to estimate student performance in online
education. Various Machine Learning (ML) based data mining techniques have been …