The utilization of reinforcement learning (RL) within the field of education holds the potential
to bring about a significant shift in the way students approach and engage with learning and …

Abstract Educational Data Mining is an emerging discipline which seeks to develop methods
to explore large amounts of data from educational settings, in order to understand students' …

In recent years, there has been increasing interest in using the methods of educational data
mining (EDM) and learning analytics (LA) to study and measure learner cognition. In this …

Pedagogical agents are typically designed to take on a single role: either as a tutor who
guides and instructs the student, or as a tutee that learns from the student to reinforce what …

Student performance, student progress and student potential are critical for measuring
learning results, selecting learning materials and learning activities. However, existing work …

Many models in computer education and assessment take into account difficulty. However,
despite the positive results of models that take difficulty in to account, knowledge tracing is …

Intelligent tutoring systems adapt the curriculum to the needs of the individual student.
Therefore, an accurate representation and prediction of student knowledge is essential …

Increasing widespread use of educational technologies is producing vast amounts of data.
Such data can be used to help advance our understanding of student learning and enable …

In this paper, a new method for handling the Multi-Input Multi-Output Student Academic
Performance Prediction (MIMO SAPP) problem is proposed. The MIMO SAPP aims to predict …

Research shows that middle school is an important juncture for a student where he or she
starts to be conscious about academic achievement and thinks about college attendance. It …