This paper focuses on the problem of personalized federated learning (FL) with the schema
of contrastive learning (CL), which is to implement collaborative pattern classification by …

The student academic performance prediction is becoming an indispensable service in the
computer supported intelligent education system. But conventional machine learning-based …

Predicting student academic performance is a critical area of education research. Machine
learning (ML) algorithms have gained significant popularity in recent years. The capability to …

Predicting students' performance is one of the most important issue in educational data
mining. In order to investigate the state‐of‐the‐art research development in predicting …

Acquiring big-size datasets to raise the performance of deep models has become one of the
most critical problems in representation learning (RL) techniques, which is the core potential …

Predicting students' performance is one of the most important issues in educational data
mining. In this study, a method for representing students' partial sequence of learning …

Abstract Automated Machine Learning-based systems' integration into a wide range of tasks
has expanded as a result of their performance and speed. Although there are numerous …

The dual-channel assumption of the cognitive theory of multimedia learning suggests that
importing a large amount of information through a single (visual or audio) channel overloads …

Knowledge tracing (KT) models students' mastery level of knowledge concepts based on
their responses to the questions in the past and predicts the probability that they correctly …

Based on student's cognitive structure, the cognitive diagnostic models (CDMs) can reveal
the potential relationships among the student's knowledge level, test item features and the …