Online Education of a Music Flipped Classroom Based on Artificial Intelligence and Wireless Network

Peng, Yu; Wang, Xin

doi:10.1155/2022/9809296

Cited by 13 publications

(7 citation statements)

References 26 publications

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“…The higher education management system used the WSN technology to seamlessly perform activities and ensure proper communication in the smart campus system. The study in [27] used the concept of flipped classroom in music teaching with the support of two technologies, namely, artificial intelligence and wireless networking. The teachers and students were able to interact with each other using interactive devices supported by intelligent networking technologies.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Wireless Sensor Network and AI Application for Educational Technology Course

Luo

2023

Journal of Sensors

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Over the course of its long development, the modern educational technology curriculum has undergone several changes and amassed a lot of information. Theoretically speaking, the state places a strong priority on the use of IT in schools. Students majoring in education should take educational technology courses so that they can learn the characteristics and application techniques of core current information-based teaching media and incorporate them into their own lesson plans and classroom activities. This will help them meet the information needs of today’s classrooms as they evolve with the advent of educational modernization and availability of educational information. Thus, this research employs a wireless sensor network (WSN) to gather and send data on ed tech classes and then employs AI to assess those classes’ quality and guide real-time changes to how they are taught and complete the following tasks: (1) The development status of educational technology courses and WSN at home and abroad is introduced. (2) The application of WSN in teaching is introduced, the basic principle of GRU neural network and related optimization algorithms is expounded, and the quality evaluation system of educational technology courses is constructed. (3) The IPSO-Adam-GRU evaluation model improves the GRU neural network’s hyperparameters with the help of the improved PSO approach and Adam gradient descent. The model is fed test data for evaluation, and the findings are compared to those from an expert’s evaluation to determine how well the model performs. The results demonstrate that the model established for this article is superior to others since it provides a more accurate assessment.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Wireless Sensor Network and AI Application for Educational Technology Course

Luo

2023

Journal of Sensors

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“…The system is made intelligent by using a convolutional neural network, which provides automated course content categorization. The K-means method is contrasted with the suggested model [10].…”

Section: Related Workmentioning

confidence: 99%

The Application of Flipped Classroom Based on the Fias Analysis Model in the Online Teaching of Piano Art Instruction

Xueying Liu

2024

jes

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This research investigates the use of the Flipped Classroom (FC) approach, based on the Flanders Interaction Analysis System (FIAS) analysis model, in the online teaching of piano art instruction. The FIAS analysis model is used to analyze the key factors that influence the effectiveness of the flipped classroom approach. The study uses a mixed-methods research design, combining surveys and interviews with students and teachers to gather data on the effectiveness of the flipped classroom approach. The study used piano theory for analysing the interaction analysis. The results indicate that the FC approach, based on the FIAS analysis model, can significantly improve student engagement and learning outcomes in online piano art instruction. The study also identifies several challenges and limitations of the approach, such as the need for adequate preparation time and the need for students to have access to suitable technology and resources. In this study, we have used ANOVA method to analyse the data. Overall, the study provides insights into the potential benefits and challenges of the FC approach in online piano art instruction and offers recommendations for future research and practice.

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“…The integration of AI technology with music education has achieved satisfactory integration results after being put into practice in some schools. "Flipped Classroom" is a teaching model that combines offline teaching and online teaching [10]. In flipped classrooms, smart devices that combine AI technology are the communication bridge between educators and learners [10].…”

Section: Introductionmentioning

confidence: 99%

“…"Flipped Classroom" is a teaching model that combines offline teaching and online teaching [10]. In flipped classrooms, smart devices that combine AI technology are the communication bridge between educators and learners [10]. Additionally, the help of AI technology in music education is not only reflected in the interaction between teachers and students.…”

Section: Introductionmentioning

confidence: 99%

The Application of Artificial Intelligence Technology in Music Education

Luo

2024

LNEP

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Artificial intelligence (AI) is transforming the field of education by emulating human cognitive processes, boosting adaptability, and improving efficiency across various domains. This integration of AI with music education, which involves a rich tapestry of history, culture, theory, and instrument instruction, facilitates the efficient utilization of musical resources. The growing demand for AI-driven online education is reshaping the landscape of learning and music instruction, particularly in the realm of music education, where the amalgamation of AI technology heralds innovative teaching approaches. This article reviews three significant AI-driven approaches: the "Flipped Classroom", which redefines traditional teaching paradigms by seamlessly combining online and offline learning experiences; the "Music Learning System Based on the RBF Algorithm", employing intricate neural network structures and large-scale music samples for personalized music education; and the "Music Learning System Based on the SCMA Algorithm", which utilizes advanced multiuser detection algorithms for tailored learning experiences. Each method leverages AI techniques, including Convolutional Neural Networks (CNN) and sophisticated algorithms, to enhance content delivery, automate feature extraction, and differentiate individual student needs. These approaches collectively signify a paradigm shift in music education, fostering personalized, interactive, and efficient learning environments for diverse learners. This article proposes future developments that could revolutionize the landscape of AI in music education. The "Singing Teaching System" mentioned in the article creates open-access AI music education software accessible to non-music majors.

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Online Education of a Music Flipped Classroom Based on Artificial Intelligence and Wireless Network

Cited by 13 publications

References 26 publications

[Retracted] Wireless Sensor Network and AI Application for Educational Technology Course

[Retracted] Wireless Sensor Network and AI Application for Educational Technology Course

The Application of Flipped Classroom Based on the Fias Analysis Model in the Online Teaching of Piano Art Instruction

The Application of Artificial Intelligence Technology in Music Education

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