Headnote
ABSTRACT
Objective:.The main aim is to explore the relationship between computer-mediated teaching strategies and the incorporation of MIR verification software to achieve more interactive learning outcomes for the a sustainable development.
Theoretical Framework: This article outlines the development process of the verification software and tests its validity. Theories related to the effective sharing of digital music resources include generative theories of interaction. The study hypothesizes and examines the reliability of educational tools based on Music Information Retrieval (MIR).
Method: The methodology contains two components. First, the author presents a model for a MIR and sharing verification system. It utilizes Java, an object-oriented programming language, for the backend. It employs JavaScript in conjunction with the Vue framework for the front end, ensuring a clear separation between the two layers. Second, the author collected data through questionnaires administered to 21 students to evaluate the effectiveness and functionality of the beta version of the software in music lessons.
Results and Discussion: The result highlights the open-loop format of verification software in music education for the Sustainable Development Goals. The findings indicate that the MIR system could provide new value to enhance the achievement of the sustainable development in music education.
Research Implications: The findings indicate that the sharing verification software creates a technology-enhanced environment that promotes a structured educational experience and increases student motivation.
Originality/Value: This study reveals a significant new value of the MIR system that connects teachers and students, enabling qualified users to edit, verify, and ensure database accuracy.
Keywords: MIR, Sharing Verification, Music Software, Digital Music Education, Intelligent Software
RESUMO
Objetivo: O principal objetivo é explorar a relação entre as estratégias de ensino mediadas por computador e a incorporação do software de verificação MIR para alcançar resultados de aprendizagem mais interativos para um desenvolvimento sustentável.
Referencial Teórico: Este artigo descreve o processo de desenvolvimento do software de verificação e testa sua validade. As teorias relacionadas ao compartilhamento eficaz de recursos musicais digitais incluem teorias generativas de interação. O estudo formula hipóteses e examina a confiabilidade das ferramentas educacionais baseadas na Recuperação de Informação Musical (MIR).
Método: A metodologia contém dois componentes. Primeiro, o autor apresenta um modelo para um sistema de verificação e compartilhamento baseado em MIR. Ele utiliza Java, uma linguagem de programação orientada a objetos, para o backend. No front-end, emprega JavaScript em conjunto com o framework Vue, garantindo uma separação clara entre as duas camadas. Segundo, o autor coletou dados por meio de questionários aplicados a 21 estudantes para avaliar a eficácia e funcionalidade da versão beta do software nas aulas de música.
Resultados e Discussão: Este estudo revela um novo e significativo valor do sistema MIR, que conecta professores e alunos, permitindo que usuários qualificados editem, verifiquem e garantam a precisão do banco de dados. Implicações da Pesquisa: Os resultados indicam que o software de verificação de compartilhamento cria um ambiente aprimorado pela tecnologia, que promove uma experiência educacional estruturada e aumenta a motivação dos alunos.
Originalidade/Valor: Este estudo revela um novo e significativo valor do sistema MIR, que conecta professores e alunos, permitindo que usuários qualificados editem, verifiquem e garantam a precisão do banco de dados.
Palavras-chave: Recuperação de Informação Musical, Verificação de Compartilhamento, Software Musical, Educação Musical Digital, Software Inteligente
RESUMEN
Objetivo: El objetivo principal es explorar la relación entre las estrategias de enseñanza mediadas por computadora y la incorporación del software de verificación MIR para lograr resultados de aprendizaje más interactivos para un desarrollo sostenible.
Marco Teórico: Este artículo describe el proceso de desarrollo del software de verificación y prueba su validez. Las teorías relacionadas con el intercambio efectivo de recursos musicales digitales incluyen teorías generativas de interacción. El estudio formula hipótesis y examina la fiabilidad de las herramientas educativas basadas en la Recuperación de Información Musical (MIR).
Método: La metodología contiene dos componentes. Primero, el autor presenta un modelo para un sistema de verificación y compartición basado en MIR. Utiliza Java, un lenguaje de programación orientado a objetos, para el backend. Para el frontend, emplea JavaScript junto con el framework Vue, asegurando una separación clara entre las dos capas. Segundo, el autor recopiló datos a través de cuestionarios administrados a 21 estudiantes para evaluar la efectividad y funcionalidad de la versión beta del software en las clases de música.
Resultados y Discusión: El resultado resalta el formato de bucle abierto del software de verificación en la educación musical para los Objetivos de Desarrollo Sostenible. Los hallazgos indican que el sistema MIR podría aportar un nuevo valor para mejorar el logro del desarrollo sostenible en la educación musical.
Implicaciones de la Investigación: Los hallazgos indican que el software de verificación de compartición crea un entorno mejorado por la tecnología que promueve una experiencia educativa estructurada y aumenta la motivación de los estudiantes.
Originalidad/Valor: Este estudio revela un nuevo y significativo valor del sistema MIR, que conecta a profesores y estudiantes, permitiendo que usuarios calificados editen, verifiquen y garanticen la precisión de la base de datos.
Palabras clave: Recuperación de Información Musical, Verificación de Compartición, Software Musical, Educación Musical Digital, Software Inteligente.
1 INTRODUCTION
The Music Information Retrieval (MIR) system 1s a vital search engine for music databases. It helps users identify songs and music, verify different versions, and can even be used for copyright purposes. The system is designed to analyze and extract valuable data from music, covering aspects such as melody, rhythm, genre, harmony, and audio features like tempo and pitch. It utilizes techniques from various fields, including signal processing, machine learning, and musicology.
Despite its potential, there has been limited scholarly attention paid to the application of Music Information Retrieval (MIR) in music education. This article aims to explore how MIR can enhance learner self-motivation and interests, leading to personalized learning experiences. Music education has always played a crucial role in developing students' musical literacy. However, traditional teaching methods are often constrained by factors such as time, space, resources, teacher guidance, and students' self-practice. As individual differences among students increase, teachers' time and energy become insufficient to address the personalized needs of each student.
The emergence of the MIR system may help to resolve this issue. The author proposes that MIR software can provide students with customized learning experiences, transforming the music education model and expanding the music market through user experiences. The integration of technology offers more opportunities for music learners, facilitating better interaction between teachers and students, and promoting the dissemination and learning of music. To test this assumption, this study developed verification software for an experiment to analyze its effects.
2 THEORETICAL FRAMEWORK
The MIR systemis currently primarily utilized in streaming services for extracting audio features and classifying content for digital libraries and music discovery platforms. This article investigates its potential educational applications, beyond merely serving as a search tool. The suggestion to integrate sharing verification software into music education arises from the recognition that modern technology is essential for promoting equity and accessibility in music education. This technology can help bridge the development gap between urban and rural areas and rejuvenate music education in rural communities. Additionally, the user-friendly design of smart practice software makes achieving lifelong music learning goals more attainable.
A comprehensive review of recent research articles on music intelligence software reveals that developing music retrieval systems is an ongoing process marked by continuous iteration and improvement. Over the past five years, scholars have examined the implications of Al-driven personalized education in music teaching, highlighting both the benefits and potential challenges faced by educators and students. Data collected from sources such as the Journal of New Music Research, IEEE Transactions on Audio, Speech, and Language Processing, and the International Society for Music Information Retrieval (ISMIR) Conference Proceedings indicate that music information retrieval (MIR) has evolved from initial manual classification and tagging to modern automated and intelligent retrieval methods.
Giovanni Gabbolini and Derek Bridge recently published a comprehensive review of over 20 years of research in Music Information Retrieval (MIR) focused on music playlists in their 2024 article titled "Surveying More Than Two Decades of Music Information Retrieval Research on Playlists." This extensive body of work encompasses approximately 300 papers that investigate various topics, including algorithms for automatic playlist generation and continuation, manual playlist creation, tagging, and captioning. The study also emphasizes the significant shift from physical media to music streaming and its influence on how playlists are constructed and curated.
Additionally, in 2024, scholar Vignesh Subramanian addressed the use of deep learning techniques in MIR in his article "Music Information Retrieval Using Deep Learning Techniques." He particularly focused on convolutional neural networks, recurrent neural networks, and transformers as they relate to various MIR tasks, including emotion recognition and content-based retrieval. A comparison between traditional machine learning methods and deep learning techniques is also discussed to showcase deep learning's dominance in complex MIR problems. Yu Chen, Bowen Liu, et al. proposed an end-to-end deep learning framework for the direct use of audio signals without relying on manually engineered features. The results show the hybrid recommendation system that improves personalization by integrating audiobased features with collaborative filtering methods (Chen et al., 2022).
Another research article highlighting the interaction between users and system is explored in the article "Multimodal Music Recommendation with Audio, Lyrics, and User Feedback", in which the authors present a multimodal music recommendation system that combines user feedback with other music features to enhance the accuracy of the recommendations (Simonetta, 2019).
Notably, Stuart Reeves' generative theories of interactions (Stuard, 2008) is one of the early basis of focus on the creation of interactive systems that adapt to users' behaviors and preferences, increasing committment and learning progress. Drawing insights from empirical studies on human behavior, more and more scholars established key concepts and principles for the design of interactive systems.
Contemporary theories and applications underscore the dynamic evolution of HCI in music education, focusing on creating more interactive, intuitive, and personalized learning experiences. These theories such as multimedia learning theory (Richard Mayer, 2001), usability Heuristics (Jacob Nielsen, 1994), and constructive learning theory (Lev Vigotsky,1978) from the adaptive learning systems imply that multimodal functions of information processing establish cross-modal retrieval and human-computer interaction in searching practices. Based on the currently existing research, the hypothesis in this study is assumped that the real-time feedback of the software and the learner's recognitions mutually enhanced the effectiveness of software and diverse learners' accomondation. Particularly, the purpose of the framwork is to investigate whether the equity, accessibility, and inclusion of the MIR can be assured in the application of music education. Therefore, this study intended to explore the application of MIR software in music education for sustainable development and test the effect of the proposed strategy.
3 METHODOLOGY
The methodology of this study falls into two sections. The first part outlines the procedures employed to establish the software, including the requirement analysis, design of model, sample selection, data collection, and editing methods. The interactive educational toolkit of the sharing verification software not only retrieves and processes musical data but also facilitates the sharing of information, with a strong emphasis on accuracy. The second part falls into the test and examination of the software ethical considerations, and limitations of the study. Its detailed and transparent description is essential to guarantee the replicability and reliability of the results, in addition to providing a solid basis for the interpretation and generalization of the findings. The second part is the satisfication survey that inquire 21 participants selected from the music college to examine the effect of model of software. The evaluation came out consequently.
Figure 1 provides the map of place where the software was desined, built up and evaluated.
The development purpose of the software is to facilitate user music information retrieval, sharing, and verification. In order to establish a modle of the verifivcation software, for the first step, the autor identified the target audience, focus groups in the field of the Chinese folk music classified by composing periods, regions of publication, the types of lable, and the styles of music. After determing the users and the overall structure of the software, the data flow, functional and non-fuctional requirements can be decided and formalized the ideas by a cateory as shown in Figure 2:
To select a proper proramming tool and language, Java and HTML are utilized. The runtime hardware envirnment is based on Intel Core 17-6700K, 8 GB RAM, and 900GB storage. The development hardware environment is establised by AMD Ryzen 9 1950X, 32GB RAM, and 700GB storage that used Windows OS operating system. The development environment tools are MyEclipse and Visual Studio Code. Linux Lite is applied as software runtime platform and operating system. MySQL 5.7, Spring MVC plays as software runtime support environment. The system leverages cloud computing technology. Technology Stack lays on the backend is developed using the Java object-oriented programming language. The frontend is built with JavaScript and the Vue framework, achieving a complete separation between the frontend and backend. The following figures illustrate interface and functions of software. This software can collect data generated by the application in real time, optimize it, and record operations instantly. This software was designed to possess multiple functional characteristics, and applications that was developed using MyEclipse and Visual Studio Code, with support from MySQL 5.7 and Spring MVC, all operated on Linux Lite. With a robust feature for regular data backups, this system allows previous data to be restored at any time, thereby mitigating the risk of data loss in case of a disaster. Part of the open coding source is attached in the Appendix.
Figure 3 indicates the page of [Music information Details] and the input items. After clicking the [Details] button, users will be directed to the music information details page, where they can view information such as the ID, music name, music type, music duration, music link, music tags, creation time, update time, and status.
Part of the open source code is listed below:
(ProQuest: ... denotes formula omited.)
After building up the beta version of the software, the author divided 21 students into 4 groups and requested each group to collect 300 historical folk songs originated from 22 various provinces of China, labeling the compositional period, duration of time, type of text, and the music styles. According to the classification, they categorized and uploaded the songs to the background. When the beta version is established, the teacher requested the same groups of people to search the target 1200 songs and tested the software's platform and gave feedback in the survey.
The metod utilized in this part is questionarie from the selected 21 college students. The author designed a survey that inquire the satisfaction of percentae. Figure 4 displays the number and level of samples.
Each student tested beta version of the sharing verification software, and the filled out the questionarie.
4 RESULTS AND DISCUSSIONS
According to data collected from a survey, the sharing verification software has provided valuable insights into rethinking the intrinsic value of music education. It emphasizes the need for more personalized and scientifically-informed teaching plans. The author illustrated the satisfication and the key relevant aspects as shown by Table 1 and Table 2.
Observing from the test, students were benefited from the software's provision of realtime digital feedback and personalized learning experience, which have enhanced the students" concentration. Additionally, this software transformed the delivery of music education, greatly enhanced students' practice and the records enabled educators to track students' manipulations. From this step, a teacher can know what students input and verify the information. lts interactive design also stimulates users' motivation to learn music knowledge, making lessons more engaging and reducing monotony. This approach encourages students to participate actively in their learning. On the other hand, while the verification software offers substantial automated technical support, it cannot completely replace teachers. Educators can leverage the data analysis provided by the software to create more effective teaching plans, fostering healthy interactions with students and enhancing their relationships.
This collaboration allows music education to extend beyond traditional classroom settings, enabling individuals of different levels of students to learn music knowledge in a collaborative manner. However, it is important to note that the research has limitations due to the size and capacity of the testing samples. To fully understand the comprehensive impact of music-sharing verification software, long-term observation and additional user feedback are essential. Consequently, this study has its limitations, and a more thorough evaluation of the software merits further exploration in the future.
5 CONCLUSION
According to this test, the impact of digital education on society is not entirely positive. The convienience of online resources and the availability of digital learning require music teachers to adapt their traditional teaching methods and improve their educational competencies. While softwares offer convenience, they also create employment pressures for music professionals. Music teachers need to recognize that extensive knowledge or precise learning feedback can now be supplemented or even replaced by technology. As a result, the ability to guide students' development, inspire their artistic creativity, and nurture a wellrounded musical aesthetic has become a higher skill requirement for traditional music instructors. From this viewpoint, intelligent practice or learning software has transformed the music market structure by increasing the number of potential music learners, while also altering the career development paths for traditional music professionals. Therefore, it is essential to explore both the advantages and disadvantages of smart practice software and to analyze the future structure of the music learning environment within the context of the current music ecosystem.
ACKNOWLEDGEMENTS
I would like to express my sincere gratitude to the students who participated in the survey. Their involvement was essential to the success of this research. I also appreciate the technical support provided by Zhaoging Artnesting Music Digital Technology Co., Ltd. The resources they offered were extremely helpful and played a crucial role in completing this research project successfully.
References
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