AN JIANGYU, ZHAO DAN, PEI JIAGE
Media College, Yanching Institute of Technology, Langfang, CN
Renaissance 2024, 3(04); https://doi.org/10.70548/ra142141
Submission received: 8 June 2024 / Revised: 11 August 2024 / Accepted: 3 November 2024 / Published: 22 November 2024
Abstract: This paper aims to deeply explore the application situation, impacts, as well as the challenges and coping strategies faced by artificial intelligence in the higher education of Chinese traditional musical instruments. By analyzing the current situation of traditional musical instrument education, it elaborates on the necessity of the application of artificial intelligence, and introduces in detail the specific application modes of artificial intelligence in aspects such as teaching resource management, intelligent teaching assistance, creation of virtual teaching environments, and teaching evaluation. It also analyzes the application effects in combination with practical cases. Meanwhile, it discusses the multiple challenges in aspects such as technology, concepts, data security, and funds during the application process, and puts forward corresponding coping strategies. The research shows that artificial intelligence has brought innovative opportunities and development impetus to the education of Chinese traditional musical instruments. Reasonable application helps to improve teaching quality and promote cultural inheritance, but various challenges need to be properly addressed to achieve sustainable development.
Keywords: Artificial Intelligence; Education of Chinese Traditional Musical Instruments; Teaching Application
1. Introduction
Chinese traditional musical instruments carry profound historical and cultural connotations and are indispensable treasures in the art treasury of the Chinese nation. They play a unique role in shaping the national aesthetic taste and inheriting the essence of culture. However, with the changes of the times, the education of Chinese traditional musical instruments has encountered numerous challenges. On the one hand, educational resources are unevenly distributed among different regions and schools. High-quality teacher resources, teaching materials, and teaching facilities are often concentrated in a few developed regions and key schools, which limits the development opportunities of a wider range of learners. Moreover, the teaching methods are relatively backward, mainly relying on one-way lecturing, lacking interaction and personalization, and thus it is difficult to meet the diverse learning needs. On the other hand, influenced by popular culture, the audience base for traditional musical instruments is shrinking, there is a break in the inheritance of talents, and the inheritance of traditional musical instrument culture is facing a severe test. Meanwhile, artificial intelligence technology has been developing rapidly on a global scale and has shown great application potential in multiple fields, and the education field is no exception. With its powerful data processing capabilities, intelligent analysis, and simulated interaction functions, artificial intelligence has provided new ideas and tools for improving teaching methods and enhancing teaching quality. Against such a background, it is of great practical significance and far-reaching influence to explore the application of artificial intelligence in the higher education of Chinese traditional musical instruments.
2.An Overview of the Development of Higher Education for Chinese Traditional Musical Instruments
2.1 Positive Aspects of Development
The majors and curriculum systems have been gradually enriched: Many institutions of higher learning have offered a wide variety of majors and courses on traditional musical instruments, covering multiple instruments such as the erhu, guzheng, pipa, suona, and guqin. Besides performance, the professional directions also include traditional musical instrument education, theoretical research, instrument making and restoration, etc., which have provided ways for the professional and diversified development of traditional musical instruments. The course content not only includes the training of instrument performance skills but also incorporates theoretical courses on the historical culture, performance theories, and aesthetic appreciation of traditional musical instruments, helping students to understand traditional musical instruments in a more comprehensive and in-depth manner.
The teaching staff has been continuously strengthened: Colleges and universities have introduced and cultivated a group of traditional musical instrument teachers with high professional proficiency and rich teaching experience. Some institutions have also invited renowned traditional musical instrument performers and experts as visiting professors or part-time teachers. They have brought cutting-edge performance techniques, artistic concepts, and industry trends to students, thus improving the teaching quality and professional level.
Practical teaching has been increasingly emphasized: Colleges and universities actively provide practical platforms for students and organize on-campus concerts, off-campus performances, and participation in professional competitions and other activities. Through practice, students can combine theoretical knowledge with performance skills, improving their performance level and stage presence. Some colleges and universities have established cooperative relationships with professional art troupes and performance agencies, providing students with internship and employment opportunities, enabling them to better understand the industry demands and development trends and enhancing their professional competitiveness.
Frequent disciplinary exchanges and cooperation: Academic exchange activities have been carried out among domestic colleges and universities, such as holding seminars on traditional musical instrument education, academic lectures, and teacher exchanges, which have promoted the sharing of teaching experiences and the improvement of teaching methods. International exchanges and cooperation have also been increasing day by day. Students have the opportunity to participate in international music and cultural exchange activities, learn foreign music education concepts and performance techniques, and at the same time showcase the charm of Chinese traditional musical instruments to the world.
The social attention to traditional musical instrument education has increased: With the emphasis on traditional culture, all sectors of society have been paying increasing attention to higher education on traditional musical instruments. Enterprises, social organizations, etc. have strengthened their support for traditional musical instrument education, providing more resources and opportunities for the development of traditional musical instrument education in colleges and universities.
2.2 Existing Problems
The teaching models and methods need to be innovated: The teaching models of traditional musical instruments in some colleges and universities are rather traditional, mainly focusing on teachers’ demonstrations and students’ imitations, lacking innovation and interactivity. In terms of teaching methods, too much emphasis is placed on skill training, while the cultivation of students’ creativity, expressiveness, and musical accomplishment is neglected.
The curriculum settings are unbalanced: Professional skill courses account for a relatively large proportion in the curriculum settings, while cultural courses and interdisciplinary courses related to traditional musical instruments are relatively few, resulting in students’ knowledge structures being not comprehensive enough and their abilities to understand and interpret traditional musical instruments being limited.
The distribution of educational resources is uneven: There are significant differences in the educational resources for traditional musical instruments among different regions and institutions. Economically developed regions and key institutions have obvious advantages in terms of teaching staff, teaching facilities, and practical opportunities, while some colleges and universities in economically underdeveloped regions and ordinary institutions are faced with the problem of resource shortages.
Students’ employment is facing challenges: The employment channels for graduates majoring in traditional musical instruments are relatively narrow. Besides working in professional art troupes, music colleges, and other units, there are relatively few other employment opportunities. Meanwhile, there is a certain mismatch between the demand for traditional musical instrument performance talents in the job market and the number and professional level of graduates.
There is a contradiction between the inheritance and innovation of traditional musical instruments: In the teaching and development process of traditional musical instruments, how to innovate on the basis of inheriting traditional techniques and culture is an urgent problem to be solved. Some students pursue excessive proficiency in techniques and novelty in performance forms during the learning process, while neglecting the cultural connotations and spiritual values of traditional musical instruments.
3 An Overview of Artificial Intelligence Technology and Its Application Advantages in the Education Field
3.1 Definition and Core Technologies of Artificial Intelligence
Artificial intelligence (AI) is a scientific technology dedicated to simulating, expanding, and extending human intelligence. It constructs intelligent systems that enable machines to perform human-like intelligent behaviors such as learning, reasoning, perception, and decision-making.
The core technologies of AI include: Machine learning (ML) – which encompasses supervised learning, unsupervised learning, and reinforcement learning methods; Deep learning (DL) – based on neural networks. Among them, the convolutional neural network (CNN) performs excellently in image recognition, and the recurrent neural network (RNN) and its variant, the long short-term memory network (LSTM), are suitable for processing sequential data; Natural language processing (NLP) – which realizes functions such as language understanding, generation, and machine translation; Computer vision (CV) – including image recognition, object detection, video analysis, etc. It can capture playing movements in real time, analyze the normality of postures and fingering techniques, and provide intuitive feedback for teaching.
3.2 General Application Advantages of Artificial Intelligence in the Education Field
Personalized learning support: Artificial intelligence systems collect and analyze a large amount of learning data such as students’ learning duration and performance in answering questions, gain insights into their learning characteristics, the degree of knowledge mastery, and interest preferences, and then customize personalized learning plans accordingly and recommend learning content that matches their levels and interests, so as to teach students in accordance with their aptitude and improve the efficiency and effectiveness of learning.
Intelligent teaching assistance functions: In teaching, artificial intelligence acts as an intelligent assistant. It monitors students’ learning states and performances in real time, analyzes facial expressions and the degree of concentration in their eyes in the classroom to judge their attention, and provides feedback on the progress of knowledge mastery and existing problems based on the audio and video data of exercises. Then it gives guidance in the forms of voice, text, etc., assists teachers in precise teaching, reduces their burdens, and enhances the pertinence and effectiveness of teaching.
Optimization and integration of teaching resources: With the help of big data analysis and intelligent retrieval technologies, artificial intelligence collects, screens, classifies, and integrates a vast amount of educational resources, constructs an easily retrievable resource database, and accurately pushes teaching videos, courseware, and other resources of various disciplines according to the different needs of teachers and students. It breaks the limitations of time and space, facilitates the access to high-quality resources, broadens the horizons of teaching and learning, and promotes the dissemination and sharing of knowledge.
Exploration of innovative teaching models: Technologies related to artificial intelligence such as VR and AR create immersive and highly interactive new teaching environments. For example, VR can be used to enable students to learn historical knowledge by being placed in historical scenes, or AR can be used to superimpose virtual elements to assist learning, which can stimulate students’ learning interests and creativity, change monotonous teaching methods, and increase students’ participation and investment in learning.
4. Specific Application Modes of Artificial Intelligence in Higher Education of Chinese Traditional Musical Instruments
4.1 Application in Teaching Resource Management and Recommendation
4.1.1 Resource Collection and Integration
With the help of artificial intelligence techniques such as web crawler technology and big data analysis, various teaching resources on Chinese traditional musical instruments available on the Internet and stored offline can be comprehensively collected. These resources cover multiple types, including musical scores, performance audio and video materials, teaching courseware, instrument-making process materials, and introductions to historical and cultural backgrounds. Subsequently, meticulous classification and integration are carried out according to multiple dimensions, such as the types of musical instruments (e.g., guzheng, erhu, pipa, etc.), performance difficulty levels (beginner, intermediate, advanced), cultural genres (e.g., Jiangnan Sizhu, Guangdong music, etc.), and historical periods, so as to build a traditional musical instrument teaching resource database that is rich in content, well-structured, and easy to retrieve. For example, for the guzheng, the performance videos of pieces of different genres and different difficulty levels can be classified separately, facilitating teachers and students to quickly search and use them according to specific needs.
4.1.2 Personalized Resource Recommendation
Based on students’ individual characteristics (such as age, learning stage, mastered skills, hobbies, etc.) and learning behavior data (such as browsing records, practice duration, past learning feedback, etc.), intelligent recommendation algorithms are applied to achieve precise and personalized teaching resource recommendations. For example, for beginners with zero foundation, the system will recommend teaching resources such as explanations of basic music theory knowledge and performance demonstrations of simple introductory pieces to help them quickly establish a preliminary understanding of traditional musical instruments and basic performance abilities. For students who have a certain foundation and are interested in a particular instrument genre, such as learners who are interested in the gaohu performance of the Guangdong music genre, the system will recommend materials such as appreciation of classic pieces of this genre, analyses of unique performance techniques, and introductions to relevant cultural backgrounds, so as to meet their needs for further in-depth learning, improve the effectiveness of resource utilization, and help students enhance their traditional musical instrument performance levels in a more targeted manner.
4.2 Application of Intelligent Teaching Aids
Monitoring and Feedback on Performance Techniques: Intelligent teaching aids are developed by using computer vision technology to identify the movements of performers’ fingering, bowing, hand gestures, etc., and combining audio recognition technology to analyze audio features such as intonation, rhythm, and timbre during performance. When students practice traditional musical instruments, these tools can monitor their performance in real time and conduct comparative analysis on the collected data with the standard performance models.
For example, when a student plays the pipa, if there are mistakes in fingering or the rhythm is not accurately grasped, the system will immediately detect them and point out the specific problems to the student in the form of voice or text prompts (such as “The order of the right-hand finger-rolling technique is incorrect. Please pluck the strings in the order of the index finger, middle finger, ring finger, little finger, and thumb one by one.” “The rhythm of this measure is too fast. You should play it according to the rhythm of one and a half beats, half a beat, and one beat.” etc.), and also provide targeted improvement suggestions to help students quickly correct mistakes and improve their performance levels. It’s just like equipping each student with an “intelligent practice accompanist” who is always online, professional, and meticulous, thus improving the efficiency and quality of students’ independent practice.
Assistance in Learning Music Theory Knowledge: An intelligent music theory Q&A system is created by using natural language processing technology. Students can ask questions about music theory knowledge in the form of text or voice. Whether the questions are about note values, beat patterns, or chord compositions, etc., the system can accurately understand the questions and give detailed answers in an easy-to-understand and simple way. In addition, interactive learning modules such as mini-games for learning music theory knowledge and level-breaking exercises are designed by using intelligent interactive programs.
For example, a “Connect the Notes” game is designed to let students strengthen their memory by matching different notes and their values. Or music theory knowledge level-breaking exercises are set up, where deeper knowledge content is unlocked after passing each level. Through this interesting interactive form, students can better understand and remember music theory knowledge, enhance the learning effect, increase their enthusiasm and initiative for learning music theory, and make the originally boring music theory learning become more vivid and interesting.
4.3 Application of Creating Virtual Teaching Environments
Virtual Simulation of Performance Scenarios: Virtual reality (VR) and augmented reality (AR) technologies are used to create highly realistic virtual performance scenarios of traditional musical instruments, simulating performance occasions with different cultural backgrounds, historical periods, and regional characteristics. For example, in the case of ancient court performances, students can immerse themselves in the solemn atmosphere of playing traditional musical instruments together with other court musicians in the magnificent palaces and understand the ways of cooperation among the instruments. Or for folk temple fair performances, they can experience the lively and cheerful performance situations where they interact closely with the public. They can also experience performances on traditional festivals of ethnic minorities and appreciate the unique ethnic customs and the unique charm of traditional musical instruments in those settings. Through immersive experiences, students can better understand the artistic charm, cultural connotations of traditional musical instrument performances in different occasions, as well as the key points of cooperation with other instruments, improve their performance experiences and artistic perception abilities. Meanwhile, it also provides a vivid display form for the dissemination of traditional musical instrument culture, attracting more people to pay attention to and understand traditional musical instrument culture.
Virtual Experience of Instrument-making Processes: Technologies related to artificial intelligence such as 3D modeling and virtual operation are utilized to reproduce the specific operation processes of traditional musical instruments in each production link, from material selection, cutting, component manufacturing to assembly and debugging, and create a platform for students’ virtual operation experiences. For example, in the production of the guzheng, students can personally participate in selecting suitable wood on the virtual platform, observe how craftsmen process the wood into components such as the body of the zither, tuning pegs, and bridges, and then assemble and debug them according to the steps. They can understand the fine craftsmanship requirements of each link and the cultural inheritance value behind them. Through such virtual experiences, students’ all-round awareness and love for traditional musical instruments can be cultivated, making up for the difficulties in the inheritance of instrument-making techniques caused by factors such as limited production sites, materials, and the small number of veteran craftsmen in reality, opening up new ways for the inheritance of traditional instrument-making techniques, and attracting more young people to pay attention to and participate in the inheritance of traditional instrument-making techniques.
4.4 Application in Teaching Evaluation and Learning Trajectory Tracking
Construction of a Multi-dimensional Teaching Evaluation System:
With the help of artificial intelligence’s data collection and analysis capabilities, various types of data in students’ learning process are collected from multiple dimensions, such as performance skills, mastery of music theory knowledge, artistic expressiveness, improvement of cultural literacy, and learning attitude. For example, performance skills are evaluated by analyzing intonation, rhythm stability, and timbre control in students’ performance audio; the degree of mastery of music theory knowledge is judged according to the test scores of music theory knowledge and the situations of asking and answering questions in the Q&A system; artistic expressiveness is considered from aspects such as emotional investment during performance and the tacit cooperation with accompaniment or ensemble; the improvement of cultural literacy is measured through students’ understanding of the historical and cultural background knowledge of musical instruments and their enthusiasm for participating in cultural inheritance activities; learning attitude is reflected by learning duration, practice frequency, and behaviors of actively exploring new knowledge. Based on these multi-dimensional data, a scientific, reasonable, comprehensive, and objective teaching evaluation system for traditional musical instruments is established. This changes the previous single and subjective evaluation methods. Through quantitative analysis and comprehensive consideration, students’ learning achievements can be measured more accurately, providing a powerful basis for teachers to adjust teaching strategies and for students to improve learning methods, and promoting the continuous improvement of teaching quality.
Dynamic Tracking and Prediction of Learning Trajectories:
By recording in real time the detailed trajectory data of students’ learning behaviors, time investment, and changes in knowledge mastery during the learning process of traditional musical instruments, and using data analysis and machine learning algorithms to explore the patterns behind the data. For example, by analyzing the changes in students’ learning progress of various pieces and performance techniques at different stages, their learning strengths and weaknesses can be identified. If it is found that a student spends a long time practicing a specific performance technique but improves slowly, this can be judged as a weak point; if a student masters a certain style of pieces quickly and can show unique understanding and expressiveness, that is where his or her strength lies. Based on these analysis results, potential learning difficulties and bottlenecks that students may face can be predicted in advance. For example, when a student is about to learn pieces with a large increase in difficulty, the system can estimate that he or she may encounter problems in rhythm control or emotional expression, and send timely reminders to teachers and students. Teachers can then adjust teaching strategies accordingly, arrange targeted special exercises or additional tutoring for students; students can also plan their learning paths in advance and take the initiative to strengthen the learning of weak links, thus realizing the refined management of the learning process, helping students better plan their learning paths, and improving the effectiveness and continuity of learning.
5.Case Analysis of the Application of Artificial Intelligence in Higher Education of Chinese Traditional Musical Instruments
5.1Personalized Recommendation and Customization of Course Content
The traditional musical instrument education course platforms in some colleges and universities utilize artificial intelligence technology to provide students with personalized learning content recommendations based on data such as students’ learning history, practice performance, and interest preferences. For example, the “Virtual Teaching and Research Section of Music Major (Music Artificial Intelligence Direction)” of the Central Conservatory of Music analyzes students’ music learning data relying on artificial intelligence technology and recommends traditional musical instrument course content suitable for their levels and interests to students, including pieces in specific styles, performance technique tutorials, etc. For students who are good at playing the erhu and are interested in music in the Jiangnan style, the system may recommend classic erhu pieces in the Jiangnan style such as “The Moon Reflected on the Second Spring” and push the related performance technique explanation videos and practice materials.
Such personalized recommendations can enhance students’ learning enthusiasm and initiative, enabling them to conduct more targeted learning, helping them to delve deeper into the fields they are interested in, and improving learning efficiency and learning outcomes.
5.2Application of Intelligent Auxiliary Teaching Tools
5.2.1 Intelligent Practice Companion Tools
Case: The intelligent recognition and error correction system of the Yiguzheng Intelligent Music Classroom is a good example. In the guzheng teaching in colleges and universities, this system can accurately record students’ learning process and provide real-time feedback on the accuracy of students’ plucking of each string. The recognition rate of single notes of the guzheng can reach as high as 98%, and the recognition rate of pieces in the courseware is as high as 95%. When students are practicing guzheng pieces, the system can promptly detect the performance errors of students, such as intonation deviation and unstable rhythm, and give real-time guidance and suggestions to help students correct mistakes and improve their performance levels.
Effect: The intelligent practice companion tools provide students with a learning environment where they can get feedback and guidance at any time, breaking the limitation in traditional teaching that students can only get teachers’ guidance in the classroom, enabling students to practice more efficiently.
5.2.2 Virtual Teaching Assistants
Case: In the artificial intelligence virtual teaching platform created by the School of Music at Nanjing Normal University, virtual teaching assistants can simulate the guidance of professional teachers. During the process of learning traditional musical instruments, students can ask questions to the virtual teaching assistants and obtain answers regarding performance techniques, understanding of pieces, music theories, and other aspects. For example, when a student is learning pipa performance and doesn’t understand a certain complex fingering technique, the virtual teaching assistant can provide detailed explanations and demonstrations for the student in various forms such as text, pictures, and videos.
Effect: Virtual teaching assistants provide convenient learning support for students. Students can acquire knowledge and guidance anytime and anywhere, which reduces the teaching burden on teachers. Meanwhile, it also improves the coverage and accessibility of teaching.
5.2.3 Optimization, Integration and Management of Teaching Resources
Case: The music libraries or teaching resource platforms in many colleges and universities use artificial intelligence technology to manage and integrate a vast amount of traditional musical instrument education resources. For example, the music resource database of the China Conservatory of Music, through the big data analysis and intelligent retrieval technology of artificial intelligence, classifies and organizes different types of traditional musical instrument teaching videos, academic papers, musical scores and other resources, and makes precise pushes according to the needs of teachers and students. When teachers are preparing lessons and input keywords such as “guzheng teaching” and “advanced pieces”, the system can quickly retrieve relevant high-quality teaching resources, including teaching videos of famous guzheng performers and academic research papers on guzheng performance techniques.
Effect: This not only facilitates the access of teachers and students to teaching resources and improves the utilization rate of resources but also provides rich materials and references for the research and teaching of traditional musical instrument education, which helps to promote the development and innovation of traditional musical instrument education.
5.2.4 Intelligentization of Performance Evaluation and Assessment
Case: Some colleges and universities have introduced artificial intelligence evaluation systems in the teaching assessments of traditional musical instruments. For example, in the erhu performance assessments of students at the Shanghai Conservatory of Music, artificial intelligence technology is used to conduct multi-dimensional evaluations of students’ performances. The system can analyze aspects such as students’ performance intonation, rhythm, timbre, and expressiveness, and compare them with professional performance standards to give objective evaluation results and suggestions. Meanwhile, the system can also generate detailed evaluation reports to help students and teachers understand the students’ strengths and weaknesses so as to formulate the next learning plans.
Effect: The intelligent performance evaluation and assessment has improved the objectivity and accuracy of the evaluation, reduced the influence of human factors, enabled students to understand their own performance levels and existing problems more clearly, provided a scientific basis for teachers’ teaching, and is helpful for improving teaching quality and students’ performance levels.
5.2.5 Assistance for Music Creation and Innovation
Case: In the music creation courses of traditional musical instruments in colleges and universities, artificial intelligence music creation assistance systems are widely applied. For example, when students at the Sichuan Conservatory of Music are creating works that combine traditional musical instruments with modern music, they use the artificial intelligence music creation assistance system. This system can automatically generate accompaniments or harmonies that match the elements such as melodies, rhythms, and styles input by students, providing inspiration and support for students’ music creation. When a student is creating a modern music piece with the bamboo flute as the main instrument, the system can automatically generate a suitable electronic music accompaniment according to the bamboo flute melody created by the student, making the work richer and more diverse.
Effect: The artificial intelligence music creation assistance system has inspired students’ creative inspiration, improved their music creation and innovation abilities, enabling students to create traditional musical instrument music works with individuality and creativity more easily.
5.3Implications and Significance for Reference
The Principle of Matching between Technology Selection and Teaching Needs: Whether it is educational institutions or online platforms, when introducing artificial intelligence applications, they should fully consider their own teaching objectives and the actual needs of students and users, and choose the corresponding technological means that match them. For example, for teaching links that focus on performance technique training, accurate audio and video recognition technology is more crucial; while for imparting cultural knowledge and cultivating interests, personalized resource recommendation and the creation of virtual teaching environments can play a greater role.
The Issue of Teachers’ and Students’ Adaptability that Needs Attention during the Application Promotion Process: Importance should be attached to the training and guidance for teachers and students to help them become familiar with and master the usage methods of artificial intelligence application tools, understand their advantages and values in teaching, and avoid hindering the promotion of applications due to non-adaptation or misunderstandings. Meanwhile, feedback should be collected in a timely manner during the application process to continuously optimize the application design and improve user experience.
Optimizing Application Strategies According to the Characteristics of Different Educational Entities: Educational institutions should focus on closely integrating artificial intelligence applications with the discipline construction and talent cultivation system within the school, and give play to their synergistic role in professional teaching and cultural inheritance; online platforms should be oriented by market demands, continuously expand application functions, improve service quality, meet the personalized learning needs of different users, and expand the coverage and influence of traditional instrument education.
In conclusion, these cases fully demonstrate the positive effects of the application of artificial intelligence in all aspects of traditional instrument education in higher education institutions in China, providing us with many implications in terms of optimizing teaching models, improving teaching quality, cultivating students’ comprehensive abilities, and inheriting and innovating traditional instrument culture. In the future, we should actively explore how to better utilize the advantages of artificial intelligence, while paying attention to and dealing with possible problems, so that it can play a greater value in the field of traditional instrument education and help the traditional instrument culture shine more brightly in the new era.
6.Challenges Faced by the Application of Artificial Intelligence in Higher Education of Chinese Traditional Musical Instruments and Corresponding Coping Strategies
6.1Challenges Faced
6.1.1 Technical Challenges
Problems Regarding Recognition Accuracy: The timbre and performance techniques of traditional musical instruments are complex. Affected by factors such as the instruments themselves, performers, and the environment, there are significant differences in intonation, rhythm, and movements during performances, which pose great difficulties for artificial intelligence audio and image recognition technologies. For example, when multiple instruments play together, their sounds are intertwined, making it difficult to accurately identify each instrument and the performance situation of each performer. This easily leads to deviations in monitoring results, affects the feedback effect of teaching auxiliary tools, and fails to provide precise guidance for students.
Limitations in the Fidelity and Interactivity of Virtual Environments: Although VR and AR technologies can create virtual teaching environments, when simulating the performance scenes of traditional musical instruments, there is still room for improvement in terms of the detail restoration, sense of reality, and interactive functions. For instance, it is difficult to simulate physical feedback such as the touch of instruments and air flow in virtual environments, and the forms of interaction between students and other elements are limited, which cannot fully meet the requirements of immersive teaching experiences and thus weaken the role in enhancing learning effects.
Insufficient Compatibility and Stability of Systems: Artificial intelligence education application systems need to run on multiple hardware devices and software platforms. Currently, there are compatibility issues, which may lead to abnormal functions and abnormal screen displays. When used for a long time or on a large scale, they are also prone to lagging and crashing, causing inconvenience to teaching applications and affecting the normal teaching order.
6.1.2 Educational Concept Challenges
Difficulties in Teachers’ Concept Transformation: Some traditional musical instrument teachers have long been accustomed to traditional teaching methods and lack understanding and trust in emerging artificial intelligence technologies. They worry about being replaced by technology, thus developing a sense of resistance. In addition, some teachers believe that traditional teaching methods are already sufficient to meet teaching needs and lack enthusiasm for learning and adopting new artificial intelligence teaching tools and models. To a large extent, this has hindered the popularization and application of artificial intelligence in traditional musical instrument education, making it difficult for advanced technologies to fully play their roles in classroom teaching.
Students’ Over-Dependence Problem: In the process of using artificial intelligence-assisted learning, some students may rely too much on intelligent teaching tools and lack the awareness of independent thinking and active exploration. They are accustomed to passively accepting the guidance and suggestions given by the system while ignoring their own perception of music, the study of performance skills, and the cultivation of practical abilities. In the long run, this is not conducive to students’ truly mastering traditional musical instrument performance skills, nor is it conducive to improving their artistic accomplishment and innovation ability.
6.1.3 Challenges in Data Security and Privacy
Risks in Data Collection and Management: Artificial intelligence applications involve a lot of personal learning data of students, such as performance videos and audio recordings. There are risks in the processes of collection, storage, and transmission. If data management is not proper, for example, in the event of hacker attacks or network interception, data leakage and illegal acquisition may occur, which will violate privacy and trigger security issues, thus affecting the sustainable development of applications.
Privacy Protection Issues: When using student data for analysis and application, it is crucial to ensure that privacy is not violated. For example, when data is shared with third parties for teaching and research purposes, strict control over principles such as legality, compliance, and obtaining students’ consent is required. Meanwhile, how to anonymize data to protect privacy to the greatest extent while ensuring data availability is also a difficult problem that urgently needs to be solved.
6.1.4 Challenges in Funds and Resources
Input Cost Issues: To carry out the application of artificial intelligence in traditional musical instrument education, a large amount of funds are required for the research and development of intelligent teaching systems, the purchase of hardware equipment, teacher training, etc. However, some educational institutions or colleges and universities have limited budgets and it is difficult for them to afford the high costs, which restricts the expansion and in-depth development of the applications and leads to the failure of some potential application models to be implemented.
Difficulty in Resource Integration: It is challenging to integrate scattered traditional musical instrument teaching resources and connect them with artificial intelligence applications to achieve efficient utilization. The formats and qualities of resources vary greatly, and a large amount of manpower and material resources need to be invested in screening, sorting, and digital processing. Moreover, there are resource barriers among various institutions and colleges and universities, and it is not easy to coordinate the participation of multiple parties, which affects the resource foundation of the applications.
6.2Coping Strategies
6.2.1Technological Conquest and Optimization
Strengthening Research and Development Cooperation: Encourage universities, scientific research institutions and enterprises to strengthen cooperation among industry, academia and research, and conduct joint research to tackle the technological difficulties existing in the application scenarios of traditional musical instrument education. For example, universities and scientific research institutions, relying on their profound academic research strength, conduct in-depth studies on the acoustic characteristics and movement patterns of traditional musical instrument performances, providing theoretical support for enterprises. Enterprises, on the other hand, utilize their own technological research and development and engineering practice capabilities, invest more human and material resources to improve the accuracy of audio and image recognition, perfect the fidelity and interactivity of virtual environments, and enhance the compatibility and stability of systems. Through the complementary advantages of all parties, the acceleration of technological breakthroughs and product optimization can be achieved.
Continuous Technological Iteration: Establish a technological feedback mechanism to collect the technological problems discovered by teachers and students during the actual use process and promptly feed them back to the research and development team. Based on the feedback information, the research and development team continuously optimizes and upgrades the artificial intelligence application technologies, such as regularly updating algorithm models, fixing software bugs, and improving hardware performance, so as to better meet teaching needs and continuously improve user experience.
6.2.2Transformation and Guidance of Educational Concepts
Teacher Training and Incentives: Organize training activities specifically targeting traditional musical instrument teachers on artificial intelligence knowledge and skills, such as holding training courses, seminars, and workshops. Invite experts to give technical explanations and share cases, enabling teachers to understand the advantages and application methods of artificial intelligence in teaching and master the usage skills of relevant tools. Meanwhile, establish an incentive mechanism to give certain rewards to teachers who actively adopt artificial intelligence in teaching. For example, give them priority in professional title evaluation and teaching achievement selection, encouraging teachers to change their concepts, take the initiative to integrate new technologies into teaching, and organically combine artificial intelligence with traditional teaching methods to achieve better teaching effects.
Student Education and Guidance: Teachers should pay attention to guiding students to correctly use artificial intelligence-assisted learning tools during the teaching process and cultivate students’ independent thinking and active practical abilities. For example, after students receive feedback and suggestions from intelligent teaching tools, teachers can guide students to further analyze the causes of the problems, encourage them to try different solutions, and verify and improve through their own practice, so that students understand that intelligent tools are just auxiliary means and their own efforts and exploration are the keys to learning traditional musical instruments well.
6.2.3Data Security and Privacy Protection
Improving Systems and Regulations: The state and relevant departments should improve data security management regulations, clarify the norms and responsibilities for all aspects of artificial intelligence applications in the education field, and build a solid defense line for data security and privacy protection. For example, it should be stipulated that data is collected in accordance with the principle of minimization, the scope of use is restricted, and consent from students or their guardians is required for sharing, and third parties should sign confidentiality agreements to ensure that data circulation is legal, compliant, and controllable.
Technical Protection and Management: Use data encryption technology to encrypt student data throughout the entire process so that it exists in ciphertext to prevent leakage. With the help of access control technology, set access levels and limit scopes according to the permissions of user roles. Meanwhile, establish a data management team to conduct regular inspections and evaluations, screen for potential security risks, and comprehensively safeguard data security and privacy.
6.2.4Measures for Fund and Resource Guarantee
Diversified Fund Raising
The government should increase its support**: The government should attach importance to the value of artificial intelligence in traditional musical instrument education and set up special funds to finance relevant institutions and colleges and universities to carry out research and development on artificial intelligence teaching applications, purchase hardware, and conduct teacher training. For example, allocate funds to help remote schools equip themselves with intelligent teaching hardware, so as to narrow the gap in educational resources.
Attract the participation of social capital: Encourage enterprises to invest funds through donations, cooperative education, investment in research and development, etc., and broaden the channels. For example, musical instrument manufacturing enterprises can cooperate with educational institutions to develop courses and provide funds, while technology enterprises can contribute with technology investment and equipment donations to ensure an adequate supply of funds.
Resource Sharing and Co-construction
Build a unified resource platform: Led by the education administrative department or industry associations, build a sharing platform to integrate high-quality resources from all parties, formulate access and application standards, facilitate teachers and students to search and use resources, and improve the utilization rate of resources.
Promote cooperation among schools and between institutions: Strengthen cooperation and exchanges among schools, between educational institutions and social art groups, establish a sharing mechanism, encourage the sharing of resources and complementary advantages, jointly promote the combination of traditional musical instrument education resources and artificial intelligence applications, and facilitate overall development.
7.Conclusions
Through in-depth research on the application of artificial intelligence in the education of Chinese traditional musical instruments, it can be clearly observed that the application of artificial intelligence in this particular field has already reaped certain positive achievements and has also demonstrated broad prospects for further development.
When it comes to the current situation of its application, artificial intelligence has been applied in multiple crucial teaching links. For instance, it plays an important role in teaching resource management, where it can efficiently organize, categorize, and recommend a vast array of teaching materials related to traditional musical instruments. In terms of intelligent teaching assistance, it is capable of providing students with timely feedback and guidance during their learning process, just like an intelligent tutor by their side. When creating virtual teaching environments, it enables students to have immersive learning experiences as if they were in real performance scenes or classrooms. Moreover, in teaching evaluation, it can offer objective and comprehensive assessments from various aspects, helping teachers and students better understand the learning outcomes. Thanks to these applications in different aspects, a diverse range of application patterns have thus been formed.
From the perspective of application effects, the application of artificial intelligence is beneficial in resolving some of the existing problems in traditional musical instrument education. Take the uneven distribution of teaching resources as an example. With the help of artificial intelligence, relevant resources can be better distributed and recommended to different regions and individuals according to their actual needs, so as to make up for the gaps in resource allocation. In terms of the lack of innovation in teaching methods, artificial intelligence brings in new ways of teaching and learning, such as virtual reality-based learning experiences and personalized learning paths, which inject fresh vitality into the traditional teaching model. Regarding the shortage of inheritance talents, by attracting more students with its innovative and interesting teaching approaches and providing more targeted training, it can contribute to cultivating a larger number of talented individuals who are willing to inherit and carry forward the traditional musical instrument culture. And for the problem of incomplete teaching evaluation, artificial intelligence can collect and analyze data from multiple dimensions to form a more comprehensive and objective evaluation system, enabling a more accurate understanding of students’ learning situations. However, during the application process, it is inevitable to face challenges in multiple aspects. Technically speaking, issues like the accuracy of recognition in complex musical instrument performances, the fidelity and interactivity limitations of virtual environments, as well as the compatibility and stability problems of systems all pose difficulties for the smooth application of artificial intelligence. In terms of educational concepts, some teachers, who have been accustomed to traditional teaching methods for a long time, find it hard to change their mindsets. They may lack sufficient understanding and trust in artificial intelligence technologies, and even worry about being replaced by these technologies, resulting in resistance to their application. Meanwhile, students might overly rely on intelligent teaching tools and neglect their own independent thinking and practical abilities. When it comes to data security and privacy, risks exist in the collection, storage, and transmission of students’ personal learning data, such as performance videos and audio recordings. There are also concerns about how to ensure privacy protection while using these data for analysis and application. In addition, in terms of funds and resources, the high costs involved in research and development, hardware purchase, and teacher training put a heavy financial burden on many educational institutions and schools, and the integration of scattered teaching resources also faces numerous difficulties.
Currently, the integration of artificial intelligence and the education of Chinese traditional musical instruments is still in a stage of continuous exploration and development. It requires the joint efforts of all parties, including educational institutions, teachers, students, technology companies, and relevant government departments, to address these challenges. Only in this way can a better integration effect be achieved, thereby promoting the innovative development of traditional musical instrument education.
With the continuous progress of science and technology, the application of artificial intelligence technology in the future education of Chinese traditional musical instruments is expected to develop in a more intelligent, personalized, and immersive direction. It is believed that through continuous technological innovation, concept renewal, and collaborative cooperation in the future, traditional musical instrument education can be elevated to a new level. This will enable this artistic treasure of the Chinese nation to shine even more brightly in the new era, cultivating more outstanding talents who are not only proficient in the performance skills of traditional musical instruments but also have a deep understanding of their cultural connotations, and ultimately realizing the sustainable inheritance and development of traditional musical instrument culture.
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