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…

Although self-regulated learning (SRL) plays an important role in supporting online learning performance, the lack of student self-regulation skills poses a persistent problem to many educators. Recommender systems have the potential to promote SRL by delivering personalized feedback and tailoring learning strategies to meet individual learners'…

Online learning has developed rapidly and billions of learners have participated in various courses. However, the high dropout rate is universal and learning performance is not satisfactory. Fortunately, learners have posted a large number of reviews which express their feedback opinions. The fine-grained aspects and opinions existing in reviews…

The large scale expansion of online courses has led to the crisis of course quality issues. In this study, we first established an evaluation index system for online courses using factor analysis, encompassing three key constructs: course resource construction, course implementation, and teaching effectiveness. Subsequently, we employed factor…

Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

Technology Enabled Learning (TEL) has a major impact on the learning adaptability of the learners. During the COVID-19 pandemic, there has been a drastic change in the learning methodology. The adaptability of learners from the various domains, levels and age has been a significant component of research in context to education. In this paper, the…

The application of computer technology has revolutionized and promoted the traditional mode of piano teaching. Nowadays, many companies and institutions have begun to apply computer technology to online piano teaching. This paper analyzes the difficulties faced by students in piano teaching and the development of piano assistant practice and…

At present, the construction of online courses is an important content in the process of educational informatization. At present, there are two problems in the construction of online courses: from the teaching point of view, the design of teaching activities and teaching processes in online courses is not enough, and the teaching effect is not…

Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against some students and possible harmful long-term…

This report describes the use of electroencephalography (EEG) to collect online learners' physiological information. Recent technological advancements allow the unobtrusive collection of live neurosignals while learners are engaged in online activities. In the context of multimodal learning analytics, we discuss the potential use of this new…

This study discusses the use of an online learning recommendation system as a smart solution related to changing the face-to-face learning process to online. This study uses user-based collaborative filtering, item-based collaborative filtering, and hybrid collaborative filtering. This research was conducted in two stages using the KNN machine…

The test results show that the fast Fourier process with multiple time superposition and a dimension length of 40 is most beneficial to the accuracy of the model. The loss curve value of the convolutional recurrent network model (CRN) is much lower than the other three models. The music tone recognition model learns better. The accuracy rate value…

Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…

The early detection of students' academic performance or final grades helps instructors prepare their online courses. In the Open University Learning Analytics Dataset, I found many online students clicked the course materials before the first day of class. This study aims to investigate how data mining models can use this student interaction data…