The rapid development of higher education in China has significantly advanced physical education within universities, contributing to students' comprehensive development and national health improvement. However, the expansion of university enrollment has introduced challenges such as a decrease in per capita sports resources and declines in…

This research works on creating a hybrid Knowledge Recommendation System (KRS) for an Entrepreneurship Course using the Knowledge Graph (KG) and Clustering Technologies (CTs). The system aims at improving students' learning experience by providing relevant learning materials and even focusing on learner preferences. These results are already part…

In order to study the big data of college students' employment, this paper takes the big data of college students' employment as the premise, analyzes the current employment data by establishing a DBN model, and puts forward relevant management measures, aiming to provide scientific basis for the management of graduates' employment data. The…

The attention time of students studying in MOOC (Massive Open Online Courses) classroom was analyzed to optimize and further improve their performance. On this basis, a student class model based on convolutional neural networks (CNN) feature extraction was proposed. Through Pr (Adobe Premiere) technology, students' class videos were processed by…

This paper investigates a flipped classroom teaching model that integrates deep learning into the design of college physical education instruction. By adjusting the time schedule inside and outside the classroom, the model shifts the focus of teaching to students, and the teacher's role changes from knowledge transmitter to learning guide. The…

To target improving the physical fitness for female college students and to meet the individualized needs of different subgroups. A total of 6987 female college students from a teacher training college were assessed for physical fitness. Their fitness indices were analyzed using K-means clustering and GBDT regression algorithms. Based on physical…

In recent years, with the economic development of various countries, education has also made great leaps, and piano teaching has been popularized and promoted in various universities. Pianos are also put into use in universities through normal channels. According to the survey, there are certain drawbacks in the teaching process of piano, which…

Applying multimedia technology to college music teaching can directly present some abstract knowledge to students. This not only breaks the limitation of traditional teaching time and space, but also enriches the teaching content and improves the teaching quality. Therefore, it is very important to change the teaching concept, actively practice…

In the evolving landscape of vocal pedagogy, ttehe integration of computer-assisted technologies represents a transformative shift from traditional master-apprentice models. This study investigates the efficacy of computer-assisted vocal training methods compared to conventional approaches, focusing on improvements in pitch accuracy, vocal range…

As cloud computing, big data, and AI advance, teachers increasingly leverage "cloud" technology for flexible and intelligent teaching. The "cloud classroom" is a growing trend, especially for instrumental music education. This paper examines the pros and cons of cloud-based instrumental music teaching, exploring how to adapt…

With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…

In order to promote the growth of contemporary music and the reform of music, this article designs an improved collaborative filtering (CF) algorithm to solve the problem of sparse matrix in traditional recommendation algorithms. The data matrix is dimensionally reduced to find the nearest neighbor, so as to realize personalized recommendation of…

This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a…

Relying on the nation's first judicial big data research base for people's courts in Southeast University, Southeast University Law School has set up a training direction for graduate students in legal big data and artificial intelligence, and explored the "three-dimensional, small-scale, wide-ranging, and large-scale ecology." The…

The latest advancements in AI are reshaping the way we learn foreign languages through listening comprehension. However, the empirical studies on how artificial intelligence in English listening teaching can effectively improve EFL learners' listening proficiency are still limited. To address this gap, this study aims to investigate the role of…