This research designed an improved collaborative filtering algorithm to be responsible for music recommendation tasks in the online music teaching platform. This algorithm integrates the user's social trust into the similarity calculation formula. Then, the algorithm uses behavioral feature data driven by preferences, music tags, and popularity as…

This article introduces a novel method that integrates collaborative filtering into the naive Bayes model to enhance predicting student academic performance. The combined approach leverages collaborative user behavior analysis and probabilistic modeling, showing promising results in improved prediction precision. Collaborative Filtering explores…

Predictive models play a pivotal role in education by aiding learning, teaching, and assessment processes. However, they have the potential to perpetuate educational inequalities through algorithmic biases. This paper investigates how behavioral differences across demographic groups of different sizes propagate through the student success modeling…

The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…