AbstractAs technology becomes an integral part of educational content and methodology, its research significance continues to grow, particularly in the relationship between music and technology. The primary aim of this study is to quantify and analyze academic research outcomes concerning the use of technology in music education. The selected sample is drawn from the WoS core database, encompassing academic achievements from 1991 to 2024. Various bibliometric software tools and three major laws were employed for the analysis, examining publication distribution, relevant journals and authors, research countries, keywords, and current and future research themes. Presently, research is mainly focused on four themes: technology integration and interaction, adaptive learning and creative teaching methods, educational frameworks and performance, and the diverse inclusion of children and adolescents. Looking ahead, the two frontier hot topics in this field are remote and online education, and innovation in higher education and educational models. This study aims to contribute to the comprehensive bibliometric analysis literature on the use of technology in music education.
IntroductionMusic education encompasses a broad range of definitions, not limited to the learning and teaching of music but also including the use of music in other educational disciplines (Jorgensen, 2008). The application of technology in music education has significantly increased, becoming a focal area of educational research. Innovations such as virtual reality (VR), artificial intelligence (AI), and digital music tools have revolutionized traditional methods of music teaching and learning. Countries worldwide are now committed to integrating technology into education. Physical technological devices are incorporated into classrooms at various educational stages, and the use of these technologies is listed as a key skill for people (Consejo Europeo, 2018). This integration signifies the inclusion of various technologies into music education, applied to different teaching subjects.Over the past 30 years, the field of music education has undergone a profound transformation driven by rapid technological advancements (Savage, 2007). The weight of research on technology as content and methodology in educational disciplines has steadily increased (Serrano, 2017), leading to a consensus on the importance of its role in shaping modern pedagogical practices (Marín-Suelves et al., 2022). As personal computing emerged, internet-based learning platforms rose, and mobile devices were integrated into educational settings (Crawford, 2013). Scholars analyze how these technologies evolved from rudimentary classroom applications to sophisticated, user-friendly tools that promote creativity, collaboration, and inclusivity. In more recent years, the momentum of technology in music education has become even more pronounced. Global digital platforms now enable cross-cultural collaboration, enriching students’ exposure to a variety of musical traditions and techniques (Guo et al., 2024). Concurrently, the COVID-19 pandemic catalyzed significant breakthroughs, as remote teaching heightened the demand for innovative digital solutions (Hash, 2021; Schiavio et al., 2021). Correspondingly, research on these technological applications surged, underscoring their capacity to transform the music classroom, refine assessment methods, and adapt curriculum designs (Merrick, 2024). This 30-year window also reflects a growing body of literature suitable for robust bibliometric analysis, revealing how policy changes, research trends, and pedagogical shifts have reshaped music education worldwide.Early bibliometric studies (Romera, 1992) highlighted this growing trend, and subsequent inquiries demonstrated how music and technology began to intertwine in educational teaching (Giráldez, 2013). Building on this trajectory, scholars utilized literature reviews (Jorquera, 2017), national perspectives (Gustems and Calderón, 2014), and macro-level discipline analyses (Sánchez-Marroquí and Vicente-Nicolás, 2024) to illustrate how digital tools, software, and online platforms expanded learners’ musical horizons while fostering accessibility and inclusivity (Crawford, 2013).However, comprehensive citation measurement analysis of technology applications in music education is still insufficient. Most related studies still focus on short-term effects or more general scopes, and systematic analysis of the long-term impact of technology in music education is relatively lacking. (Marín-Suelves et al., 2022). This limitation hinders the academic community’s comprehensive understanding of the role of technology in music education, especially the understanding of research teams and cutting-edge research directions.To fill this gap, it is necessary to systematically explore the evolution and long-term trends of technological applications in music education. Therefore, this paper uses the WoS core database and bibliometric analysis methods to graphically illustrate the evolution and impact of technology in music education. This study aims to provide a clear understanding of the development trajectory in this field, analyze and review the existing literature to gain insights into research hotspots and trends, and provide references for relevant research and practical applications (Yang and Liu, 2022). Bibliometric research on technology-enabled music education is of significant importance. It will help educators and policymakers make informed decisions to enhance the effectiveness of music education through technology.This study addresses the following three research questions:
What is the distribution of major publications, national institutions, and research outcomes in technology-enabled music education research over the past 30 years?
What are the research hotspots in technology-enabled music education over the past 30 years?
What are the overall frontier developments in technology-enabled music education research over the past 30 years?
Literature reviewA brief discussion of this definition is typically most effective near the end of the Introduction or at the beginning of the Literature Review, especially where the article transitions into the scope and conceptual framework of the study. Placing the definition after introducing the central topic of music education ensures that readers understand how the paper conceptualizes “technology” before delving into specific research questions, theoretical underpinnings, or bibliometric analysis.Technology-enabled music education is closely related to other disciplines and presents diverse research trends, including methods (Devaney, 2023), creativity (Mielke and Andrews, 2023), technology (Uludag and Satir, 2023), COVID-19 (Merrick and Joseph, 2023), curriculum (Mercado, Draut (2024)), and teacher education (Humberstone et al., (2024)).Technology-enabled music education at various levelsThe integration of technology into music education at different stages has specific applications. In early childhood education, software is primarily designed for training purposes, while in elementary education, entertainment technology is prioritized. Higher education employs technology for blended learning environments (both online and offline). Comparatively, elementary school teachers are more inclined to integrate technology into music education than early childhood educators (Atabek and Burak, 2020). Teacher training is a critical factor (Väkevä, 2017), and practical experience in combining music and technology is also underway (Ortiz Molina et al., 2021). However, whether at the national level or the international level (Domínguez-Lloria and Pino-Juste, 2020), there are still some issues with the practice of integrating technology into music education.Challenges and innovations in music education technologyCurrent issues in music education primarily revolve around the demand for hybrid learning environments. This emphasizes the critical role of technology integration in hybrid education environments. The evident gap between technological advances and their integration into music education suggests that the educational potential of these technologies has not been fully realized. Nonetheless, technology offers numerous teaching advantages, enhancing not only teaching methods but also student accessibility and engagement. The integration of VR and AI, for example, redefines the teaching and learning experience in arts education (Yu et al., 2023). These technologies promote deeper personalized learning. Similarly, intelligent composition and augmented reality performances show significant improvements compared to traditional teaching methods (Yu et al., 2023).当前音乐教育的问题主要围绕着对混合学习环境的需求（Cheng 等人，2022 年）。这强调了技术整合在混合教育环境中的关键作用。技术进步与技术融入音乐教育之间的明显差距表明，这些技术的教育潜力尚未得到充分发挥。尽管如此，技术仍具有众多教学优势，不仅能增强教学方法，还能提高学生的可及性和参与度。例如，虚拟现实和人工智能的整合重新定义了艺术教育中的教学体验（Yu et al.）这些技术促进了更深入的个性化学习。同样，与传统教学方法相比，智能作文和增强现实表演也有显著改善（Yu 等，2023 年）。Application of bibliometric analysis in music educationWith the digital development of disciplines, the academic literature in the fields of technology and music education has increased significantly. Bibliometric analysis plays an important role in these areas (Marín-Suelves et al., 2022). Bibliometrics has proven effective for academic research in education (Romera, 1992), such as through bibliometric reviews (Jorquera, 2017), national research focusing on Spain (Gustems and Calderón, 2014), or comprehensive studies of the entire music education discipline (Sánchez-Marroquí and Vicente-Nicolás, 2024). Bibliometrics can identify trends and thematic focuses within academic fields, which is crucial for understanding the evolution and impact within these areas, highlighting research in specific subfields, and guiding future research trends. This is also significant for educational research and policy-making.The review of previous research indicates that studies on the application of technology in education mostly focus on short-term benefits, lacking comprehensive bibliometric analysis of long-term trends and detailed impacts. However, bibliometric research on technology in music education is essential, providing educators and policymakers with a research framework to improve teaching methods, increase student engagement, and enhance learning outcomes (Yu et al., 2023). Therefore, this paper uses bibliometric analysis to study the application of technology in music education, aiming to highlight future research trends in this field.Research designResearch methodsTo achieve the goals of this study, appropriate bibliometric analysis methods and techniques were selected (Donthu et al., 2021; Lin & Yu, 2023; Ma 2024; Wang et al. 2024a; J. Chen, et al., 2022). The focus was on analyzing research subjects such as authors, institutions, and countries, as well as clustering themes and future trends based on keywords. Using the three main bibliometric analysis—Price’s Law, Bradford’s Law, and Lotka’s Law—helped deeply understand the distribution and concentration of research activities in the field of technology in music education (de Solla Price (1963); Bradford, 1934; Lotka, 1926). The specific steps and screening methods are shown in Table 1.Table 1 The data collection and analysis protocol.Full size tableResearch toolsIn this study, three bibliometric tools—Bibliometrix, VOSviewer, and CiteSpace—were utilized to gain a comprehensive view of research on technology-enabled music education (Jing et al. 2024a). First, Bibliometrix was employed to assess scientific productivity and collaboration patterns by analyzing publication counts, citations, and author networks. Its integrated functions allowed us to quickly identify which authors, institutions, and countries are most active, as well as calculate key indices (e.g., annual publication growth, citation impact) and highlight notable research collaborations (Aria and Cuccurullo, 2017).Next, VOSviewer provided powerful clustering and visualization capabilities for exploring co-occurrence networks of keywords, authors, and references (Jing et al., 2024b). By measuring the strength of connections among nodes, VOSviewer generates easy-to-read maps where similar or closely related items form distinct clusters. These clusters reveal major themes within the field, showing at a glance how topics interrelate and which areas are drawing the most attention (Van Eck and Waltman, 2010).Finally, CiteSpace offered burst detection and timeline analysis to uncover emerging topics and trace their evolution over time. Burst detection identifies sudden increases in the usage of specific keywords or references, indicating rising research frontiers (Shang et al., 2024). The timeline visualization feature arranges these clusters chronologically, allowing us to see how certain themes gain or lose prominence. Collectively, these three tools offer a synergistic method for evaluating productivity, mapping intellectual structures, and identifying the field’s most dynamic research directions.Data sourcesThe data for this study were retrieved from the Web of Science core collection on January 16, 2024, including the Social Sciences Citation Index (SSCI), Science Citation Index (SCI), Emerging Sources Citation Index (ESCI), and Arts and Humanities Citation Index (A&HCI). Although ESCI journals are listed as data sources, they do not always meet the same rigorous standards as SSCI or SCI journals, so we retain these records for data integrity. These databases were chosen because they include high-quality peer-reviewed journals widely recognized in the academic community (Shang et al. 2024; Chen, et al. 2024; Lin & Yu, 2024). The search was based on the topics “technology” and “music education,” resulting in 1196 relevant documents. To ensure data accuracy and relevance, conference papers, retracted papers, and unrelated documents were excluded, resulting in 825 papers meeting the research criteria. Each article was individually reviewed to confirm its relevance to the research criteria. The data were stored in plain text format, including full records and citation references for subsequent analysis.Data analysisIn this study, we first collected and filtered 825 articles on technology-enabled music education from multiple WoS databases. The data were then exported in a standardized format and analyzed using three complementary bibliometric approaches (Table 1).Bibliometrix was employed to evaluate productivity and collaboration patterns. We generated quantitative indicators such as annual publication growth, total citations per year, and author collaboration indices, enabling a macro-level overview of the research landscape. Next, VOSviewer was used to visualize co-occurrence networks among keywords, authors, and references. By grouping items with stronger interconnections into clusters, we could quickly identify and interpret key research themes. The resulting network maps highlighted how different areas of technology in music education intersect. Finally, CiteSpace facilitated the detection of emerging topics and temporal trends. Through its burst detection function, we identified keywords and references that witnessed sharp rises in citation frequency over specific time slices. Additionally, CiteSpace’s timeline analysis helped illustrate how various clusters have evolved, revealing pivotal shifts in research emphasis and indicating the possible directions of future studies.Collectively, these tools provided a rigorous, multi-dimensional view of the data, uncovering core journals, leading authors, and thematic clusters, as well as uncovering frontier research topics driving innovation in technology-supported music education. An overview is shown in Fig. 1.Fig. 1Overview of research on technology applications in music education.Full size imageResultsFigure 2 shows the bibliometric overview of using technology in music education. From 1991, when the first relevant article was retrieved by WoS, to 2024, research output has increased by 12.07% per year, highlighting the growing importance of technology in this field. A total of 825 documents were published by 1836 authors, averaging 2.44 co-authors per paper, indicating strong collaboration. The international co-authorship rate is 13.03%, showing notable cross-national research efforts. These documents cover 2550 different keywords, reflecting a wide range of research topics. With a total of 28,471 references, these data show that research on technology in music education is a growing field with extensive international collaboration and diverse research themes, holding significant academic influence.Fig. 2Frequency of scientific publications related to technology in music education.Full size imagePublication strength: quantity and quality of journalsThe trend of publications on technology applications in music education can be divided into two phases: slow growth and significant growth (Fig. 2).Slow growth (1991–2018)The annual number of studies did not exceed 20 articles, but the number of publications steadily increased, reflecting initial academic interest in the intersection of technology and music education.Significant growth (2019–2022)Since 2019, the number of research articles has skyrocketed, peaking at 187 articles in 2022, driven by the global COVID-19 pandemic, which pushed music education towards online or digital teaching, consistent with previous studies (Li et al., 2021). There is a slight decrease in 2023, but it should be noted that this may be due to the typical lag in indexing some journals published on an annual basis, and not necessarily a real decrease in research activity.From 1991 to 2024, research on the application of technology in music education was published in 392 journals. According to Bradford’s Law, we calculated the core journals in this field (Fig. 3). Based on citation counts, the top ten journals were ranked (Table 2).Fig. 3Areas of scientific productivity of journals (core sources by Bradford’s Law: 392 journals and 825 articles).Full size imageTable 2 Top ten most-cited journals.Full size tableIn the field of technology-enabled music education, the International Journal of Music Education published the most articles, with 33 papers, but its average citation rate and impact factor are low (0.6). In contrast, Music Education Research has an average citation count of 16.34 per article, indicating significant influence in this field. Judging by the impact factor, Music Education Research is identified as a core authoritative journal in music technology and education. Notably, Frontiers in Psychology and Soft Computing are journals in psychology and computer science, respectively, reflecting the interdisciplinary research trend in music education.Research strength: core authors, institutions, and countriesTable 3 shows the top ten authors in the field of technology application in music education by publication volume. The analysis focuses on the top three authors: Gorbunova Irina B., Biasutti Michele, and Calderon-Garrido Diego.Table 3 WoS top ten core journals with the highest published paper amount.Full size tableIrina B. Gorbunova is the most prolific author in this field, with 18 articles and 35 citations. Her research mainly integrates technology into music education through theoretical frameworks and inclusive education. For example, Gorbunova uses mathematical and computer technologies to analyze music structure and creativity, advancing theoretical musicology and practical education. She developed software specifically for visually impaired students, demonstrating the potential of technology to enhance educational accessibility and outcomes (Gorbunova and Zalivadny, 2020).Michele Biasutti ranks second in productivity, focusing on the transformative use of digital tools in music education, particularly during the COVID-19 pandemic, using information and communication technology (ICT) for remote teaching to enhance teacher–student interaction. Through a constructivist approach, he enhances professional skills (Biasutti et al., 2023). Biasutti has a high citation count (199 citations from 7 articles), but he notes that the long-term impact of ICT on student outcomes and teacher effectiveness requires further exploration (Biasutti et al., 2019; Seddon and Biasutti, 2008).Diego Calderon-Garrido focuses on the training of music teachers, including digital competencies and adaptation strategies during the COVID-19 pandemic. His research reveals that music teachers turn to meditation activities in the face of resource constraints, advocating comprehensive digital training, though its effectiveness in different educational environments needs further exploration (Calderon-Garrido, Gustems-Carnicer (2021)).From Fig. 4, it can be seen that in the early 1990s, the primary research countries were only Australia and Germany. Around 2004, more countries began to participate in the research. Currently, research in this field involves dozens of countries.Fig. 4Evolution of the country-region share of relevant research between 1991 and 2024 (country-region based on the affiliation of the first author).Full size imageTable 4 shows that China leads in the number of publications in this field, accounting for ~35% of the total. Chinese research mainly focuses on exploring and applying digital music technology in classroom environments, such as combining text, images, animations, and music to enhance the teaching and learning process. Emphasis is placed on the role of multimedia technology in enriching classroom content, diversifying teaching methods, and improving the efficiency and effectiveness of music education. However, Chinese research often focuses solely on the functional use of technology, with less emphasis on educational outcomes.Table 4 Ranking by country by number of published papers.Full size tableThe USA ranks second with ~29% of the total publications. American research explores the use of advanced technology and multimedia tools, focusing on the evolution and practice of AI in music education, such as comparing traditional and AI-enhanced educational methods. AI addresses the limitations of traditional teaching and enhances personalized learning experiences (Chen et al., 2024; Yu et al., 2023; Wang et al., 2024b; Wang et al., 2025; Jin et al., 2025). Although American research highlights the significant potential of these technologies, it sometimes overlooks the impact of different educational and cultural backgrounds (Waddell and Williamon, 2019).Spain ranks third, accounting for ~19% of the total publications, focusing on integrating social media and online resources to improve accessibility and participation in music learning (Crawford, 2013). For example, the project “Music X” uses web 2.0 technology to provide a platform for music education for students in rural and remote areas, emphasizing educational inclusivity (Crawford, 2013). However, Spanish research’s over-reliance on these platforms may affect the quality and sustainability of education outcomes (Sastre et al., 2013).Figure 5 shows that international collaborations are frequent in the field of technology applications in music education, with extensive collaboration networks between China, the USA, Spain, and the UK, indicating the broadness and importance of global scientific cooperation. Notably, there is a high level of cooperation between China and the USA, possibly due to shared interests and resource sharing in technology and music education research (Lee and Nguyen, 2021). Additionally, regional cooperation in Europe is significant, particularly among Spain, the UK, Norway, Finland, and Ukraine, which not only enhances regional research levels but also promotes the application of technology in music education.Fig. 5National collaboration network.Full size imageFigure 6 indicates a significant increase in publication volume in recent years, especially in 2022, reflecting rapid growth in this field. Asian countries like China, Japan, and South Korea, also have substantial publication volumes. In Italy, researchers predominantly examine how music educators adapted online teaching practices during the COVID-19 lockdown, highlighting the use of ICT-based strategies to address lesson planning, assessment, and work-life balance (Biasutti, et al., 2023). In Australia, studies emphasize transitioning older adults’ face-to-face instrument lessons to online formats, illustrating the need for robust technical support and creative digital pedagogy (MacRitchie et al. 2023), as well as exploring gender-related media multitasking behaviors and virtual improvisation communities that foster social connectedness (Cotten, et al., 2014; MacDonald et al. 2021). Meanwhile, scholars in Russia investigate early childhood music education by examining parent-teacher collaboration and the mixed acceptance of digital tools (Ivanova et al. 2020), propose e-learning frameworks to enhance music teacher training (Karkina et al. 2023), and analyze how machine learning may shape human creativity in musical production (Farina et al. 2024). Collectively, these international studies underscore shared concerns about technology’s capabilities, limitations, and implications for sustaining and innovating music education.Fig. 6Annual volume of publications in countries.Full size imageResearch hot topicsKeywords condense the core content of papers, and their co-occurrence analysis can reveal key themes in a research field. In this study, VOSviewer was used to cluster keywords from the documents and generate a knowledge map for keywords that appeared at least ten times (Fig. 7).Fig. 7Knowledge map of keyword clustering co-occurrence in sample literature.Full size imageThe results show that research on the application of technology in music education focuses on four areas: Technological Integration and Interaction, Adaptive Learning and Creative Pedagogies, Educational Frameworks and Performance, and Diverse Inclusion of Children and Adolescents. We analyzed high-frequency keywords and their corresponding connection strengths and categorized the main content under each theme into four hot topics (Table 5): Technological Integration and Interaction, Adaptive Learning and Creative Pedagogies, Educational Frameworks and Performance, and Diverse Inclusion of Children and Adolescents.Table 5 High-frequency keywords on technology hot topics supporting music education research.Full size tableResearch theme 1: technological integration and interactionThe first cluster focuses on the integration of technology and interaction between educational stakeholders, exploring technology acceptance, innovative teaching tools, and digital communication methods to enhance educational motivation and transmission. This cluster comprises three categories:
Technology adoption and effects
The impact of technology on acceptance, motivation, and learning outcomes in music education. When technology facilitates and enhances the music learning experience, educators and students are more likely to adopt it. The integration of digital technology can significantly boost student motivation and learning outcomes, indicating a positive correlation between technology acceptance and educational transmission (Waddell and Williamon, 2019). Studies by Dorfman (2016) further emphasize the crucial impact of technology on music education.
Educational technology methods
Enhancing music education through AI, AR, and other means. These tools promote effective communication in education, providing immersive educational experiences that engage students in deep learning. Research by Dai (2021) and Turchet et al. (2018) integrates these technologies into music education, enhancing interactive educational experiences. ICT also plays a key role in improving music education learning experiences. Digital audio technology is pivotal in music classrooms (Kladder, 2021), while Zhang and Sui (2017) explore the specific applications of digital music technology, combining it with traditional teaching methods to enhance middle school music classroom effectiveness. The importance of ICT and digital tools in enhancing music education aligns with findings by Brown (1999), who underscores the role of digital representation in music education.
Different educational backgrounds and practices
The application of technology in music education encompasses various educational stages, especially secondary and higher education. Studies by Busen-Smith (1999) and Walls (2000) point out that technology integration meets diverse educational activities, supplying the educational needs of different stages, enhancing teaching effectiveness and student engagement. The application of technology adapts to evolving comprehensive teaching methods.
Research theme 2: adaptive learning and creative pedagogiesThe second cluster focuses on the adaptive teaching strategies adopted by educators during the COVID-19 pandemic, transforming music education into online platforms with creativity and popularity, comprising two categories.
Online learning and participation
During the COVID-19 pandemic, online and remote learning platforms (e.g., YouTube) supported educational engagement. These platforms allowed teachers to continue teaching outside the traditional classroom environment but required overcoming barriers to remote education, ensuring high teaching engagement through creative teaching methods and digital tools (Biasutti et al., 2021).
Innovation and cognitive development
Conversely, teachers’ transition to online platforms also promoted innovation and cognition. Educators explored creative pedagogies for online education, such as placing instrument lessons in virtual environments to ensure student engagement. Vaizman (2022) aligns with findings on creative pedagogical adaptations, such as using virtual environments for instrumental lessons to maintain student involvement.
Research theme 3: educational frameworks and performanceThe third cluster reflects the use of digital technology in classrooms and higher education, enhancing teaching practices and performance evaluation.
Teaching methods impact on performance
Teaching methods affect students’ performance in music education. Asare et al. (2023) explore the integration of ICT in music education, showcasing its potential to increase student engagement and personalize learning experiences, emphasizing that technology-driven education offers new possibilities that traditional methods may lack.
Research theme 4: diverse inclusion of children and adolescentsThe fourth cluster highlights the development of skills to ensure educational inclusivity, addressing the diverse cultural and gender-specific needs in the learning environment. The diverse inclusion of children and adolescents is crucial for the application of technology in music classrooms. Armstrong (2011) points out that technology in music education may inadvertently perpetuate gender stereotypes. Welch et al. (2008) emphasize the impact of gender and music genres on higher education learning outcomes, necessitating inclusive teaching methods that cater to these differences.Analysis of research theme evolutionCitespace visualizations provide an analysis of the evolution of themes in technology-enabled music education. By analyzing the time distribution and density of keywords, the changes and emerging trends in research can be tracked (Fig. 8). The following analysis is conducted according to the time dimension.Fig. 8Temporal track of high-frequency keywords.Full size imageFirst phase: foundation of educational technology (1991–2000)This phase primarily focuses on the foundational research on technology in music education. Keywords such as “information technology,” “secondary education,” “curriculum development,” and “higher education” appear. The studies mainly explore the benefits of information technology in educational environments, but the integration of technology and music education is not yet deep. Digital technology in music education is recognized for its three functions: tool, instrument, and thinking medium, emphasizing the multifaceted impact of digital audio on music creation and presentation (Brown, 1995). Other studies examine the overall impact of technology on education, such as redesigning electroacoustic music courses and teaching methods in higher education in the UK to meet growing educational demands (Smith and Clarke, 1993). Early technology faced limitations such as insufficient equipment and lack of training.Second phase: technological advancement and focus (2006–2021)This phase shows the gradual and specific integration of technology into music education. Keywords like “digital technology,” “performance,” “design,” and “emerging literacies” appear. Music technology is gradually incorporated into educational curricula, especially in secondary and higher education. Studies find that music learners have a positive attitude toward technology, enhancing learning outcomes (Kardos, 2012). High schools in New Jersey introduce technology-supported music courses, though not systematically taught, mostly as independent courses. Music technology courses become more systematic and diverse. For instance, North Greenville University’s music technology courses train students to use various software tools such as Finale and Notation, helping teachers instruct students in software skills (Griffin and Holland, 2008). Sastre et al. (2013), in collaboration with Carnegie Mellon University, developed new software for various educational scenarios, showcasing the significant potential of technology in promoting student creativity and music education. Additionally, the application of new music information retrieval (MIR) technologies, such as accompaniment separation, real-time practice, and guitar transcription, provides more creative tools and practical opportunities for students.Third phase: comprehensive integration of emerging technologies (2022 and beyond)This phase demonstrates the comprehensive integration and application of emerging technologies (AR, AI) in music education. Keywords such as “artificial intelligence,” “virtual reality,” “metaverse,” and “digital tools” appear. AI is used in music education to personalize learning based on student interests (Yu et al., 2023). Virtual reality creates immersive music education environments, allowing students to compose and interact with music in virtual spaces. Digital tools play a significant role in remote music education, especially during the COVID-19 pandemic, helping students continue music learning and maintain social connections (Begic and Begic, 2023). These tools not only improve learning speed and effectiveness but also promote more sustainable learning.The three phases show that the development of music education technology has evolved from “enhancing teaching performance” to “transforming teaching models,” and finally to “enhancing learning experiences.” Early-stage research primarily uses technology to improve the efficiency and effectiveness of music education (Brown, 1995), with technology applied as an auxiliary tool in specific teaching segments. Mid-stage research begins to focus on the transformative impact of technology on teaching models, promoting self-directed and collaborative learning. The latest phase shifts the focus to enhancing learners’ experiences through technology, providing personalized and immersive learning environments, and fully integrating technology into the educational system.The development of music education technology has undergone a transition from an “external driving force” to an “internal traction force,” and finally to “three-dimensional innovation force.” This development is driven by multiple factors, such as social changes, technological advancements, and evolving educational needs. Early technology primarily served the needs of basic education. With the widespread adoption of digital technology and the internet, educational technology deeply integrates and transforms traditional teaching models. The latest phase’s focus on AI and VR meets the need for personalized and immersive learning, becoming a crucial driver of educational transformation and teaching effectiveness enhancement (Yu et al., 2023; Waddell and Williamon, 2019).Future research directionsThis article uses Citespace to reveal future research directions in the field of technology-enabled music education. According to Table 6, the burst keywords ending in the last 5 years include model, higher education, online learning, distance education, and music teaching. These keywords are categorized into two frontier themes: Remote and Online Education, and Higher Education and Model Innovation.Table 6 Top 15 keywords with the strongest citation bursts.Full size tableRemote and online education
Online learning
Online learning is a vital component of remote and online education, utilizing the internet and digital technology to deliver instruction without the constraints of traditional classroom settings. Online learning provides a convenient mode of learning for students, promoting self-directed and personalized teaching (Kardos, 2012; Waddell and Williamon, 2019; Kladder, 2021; Yu et al., 2023; Begic and Begic, 2023; Hosken, 2019). The main research themes include the development and application of online learning platforms and tools, the teaching effectiveness of online learning, and the online learning experiences of students.
Distance education
Distance education refers to the use of the internet for instructional activities, especially during the COVID-19 pandemic, which saw a surge in demand for distance education, resulting in numerous studies examining its application effects (Karkina et al., 2021; Koutsoupidou, 2014; Strenacikova, 2023; Shaw and Mayo, 2021; Walls, 2008; Ozer and Üstün, 2020; Vyshynskyi and Yahodzynska, 2017; Wang et al., 2023). These studies share similarities with online learning research, focusing on themes such as the development and application of tools, the impact of distance education on music education outcomes, the role of teachers in distance education, and students’ learning experiences in distance education.
Higher education and model innovation
Higher education
Higher music education based on innovative educational models not only enhances students’ musical skills but also cultivates their social responsibility and artistic literacy (Buryakova and Buryakov, 2020; Gaunt et al., 2021; Li et al., 2021; Zhou, 2018). These studies focus on the academic development of higher music education, such as traditional conservatories transitioning into research institutions through advanced performance training and artistic research to improve educational quality. They also explore the diverse application of music education models in vocational education, emphasizing the importance of music education in cultivating students’ comprehensive qualities (Zhou, 2018). Additionally, the internationalization and diversification of higher music education are significant, such as the innovative music education model at India’s KM Music Conservatory, combining local and international factors to create a multicultural educational environment.
Model and music teaching
Educational models refer to the innovation and optimization of teaching methods and strategies to enhance learning experiences and teaching outcomes. Innovative educational models in higher music education improve students’ musical skills while cultivating their comprehensive qualities and social responsibility (Buryakova and Buryakov, 2020; Conway, 2020; Zhou, 2018; Gaunt et al., 2021; Pervushina and Kryuchkova, 2018). These studies focus on the diverse development and application of educational models, such as the multi-level educational model in the French higher music education system, emphasizing curriculum complementarity and consistency in competitive exams (Buryakova and Buryakov, 2020). Scholars also explore the role of music education in vocational education in enhancing students’ comprehensive qualities (Zhou, 2018). Additionally, innovative approaches to music creation, analyzing different teaching methods and students’ learning experiences, propose process- and art-based creative learning models that transform students’ learning activities into professional activities, enhancing educational effectiveness (Pervushina and Kryuchkova, 2018).
Conclusion and implicationsThis study uses bibliometric analysis to track the dynamics of research on technology-enabled music education over the past 30 years based on the WoS core database. The findings reveal that:Research on technology-enabled music education peaked in 2022, forming a core group of authoritative journals, including the International Journal of Music Education, Music Education Research, and British Journal of Music Education, with key authors such as Irina B. Gorbunova, Michele Biasutti, and Diego Calderon-Garrido, and major research forces from countries like China, the USA, and Spain, with notable collaboration intensity between China and the USA.The current research focuses on four hot topics: technological integration and interaction, adaptive learning and creative pedagogies, educational frameworks and performance, and the diverse inclusion of children and adolescents. Among these, technological integration and interaction highlight the application of digital technology to enhance motivation and learning outcomes in music education, represented by emerging technologies such as AI and AR. Adaptive learning and creative pedagogies emphasize online learning platforms promoting innovation and cognitive development during the COVID-19 pandemic, maintaining high teaching engagement despite remote education barriers. Educational frameworks and performance research focus on the use of technology in classrooms and higher education to enhance teaching practices and performance evaluation. The diverse inclusion of children and adolescents addresses the diverse cultural and gender-specific needs in the learning environment.We identify two future research directions for technology-enabled music education: Remote and Online Education and Higher Education and Model Innovation. Under the Remote and Online Education theme, research continues to explore online learning and distance education, focusing on the design and application of digital tools, instructional strategies for virtual classrooms, and the experiences of students and teachers. These studies emphasize how emerging platforms can improve access, interactivity, and personalized learning. Meanwhile, Higher Education and Model Innovation addresses the transformation of higher music education and model-based teaching approaches. Scholars investigate how innovative educational frameworks, including multi-level or process-based models, can advance both technical proficiency and broader competencies such as social responsibility, cultural sensitivity, and artistic creativity. Rethinking curriculum structure, integrating research-driven performance training, and fostering multicultural exchange.The significance of this study lies in its comprehensive and systematic examination of the evolution of technology-supported music education over the past three decades. Theoretically, it provides a detailed analysis of hot topics and frontier evolution in this field, gaining insights into the current status and trends in this field. Through visual research maps, it enriches the theoretical framework in this field, offering new perspectives. contributing to the overall healthy development of this field. Practically, this study highlights key publications and contributions from research institutions, helping scholars identify researchers and trends in this field. This is crucial for integrating technological innovations into music education curriculum design, ensuring its functionality and relevance within the educational environment.In conclusion, technology has profoundly reshaped music education, broadening access, diversifying instructional strategies, and fueling creative exploration. With digital tools such as VR, AI-driven applications, and interactive platforms, educators can bridge geographical gaps, engage learners with personalized content, and foster deeper collaboration. These innovations also promote inclusivity by accommodating diverse learning preferences, supporting students with special needs, and exposing learners to global musical cultures. In classrooms, real-time feedback and adaptive systems enhance skill development, while online repositories offer vast educational resources that enrich traditional curricula. Furthermore, technology empowers teachers to refine assessment methods, encouraging performance-based tasks that capture nuanced progress. As the digital transformation continues, stakeholders in education—ranging from policymakers to teachers—must integrate technological advancements thoughtfully and ethically, ensuring that pedagogy evolves in parallel.Research limitationsThis study mainly selects core literature from the WoS database, which may lead to the omission of relevant literature from other databases, potentially affecting the research conclusions to some extent. Although this study used professional software for bibliometric analysis and obtained relatively objective quantitative data, the interpretation of research hotspots (topic clusters) and the analysis and interpretation of research topic evolution will inevitably be subjective, and the influence of subjectivity on data analysis cannot be completely avoided. Therefore, the next study will conduct an in-depth study of the Hot Topics algorithm in the software and the principles behind it to ensure the objectivity and accuracy of the results from a technical dimension. In addition, the scope of the literature will be accurately screened, and higher-quality articles and journals will be selected to minimize the adverse effects of personal subjectivity on research analysis.
Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
ReferencesAria M, Cuccurullo C (2017) Bibliometrix: an R-tool for comprehensive science mapping analysis. J Informetr 11(4):959–975. https://doi.org/10.1177/2059204318811786Article
MATH
Google Scholar
Armstrong V (2011) Technology and the gendering of music education. Routledge, London. https://doi.org/10.4324/9781315612003Asare S, Twum EO, Amoah J (2023) Teaching for the digital stage: preparing future music educators for the ICT-driven classroom at colleges of education. Int J Multidiscip Res 15(2):89–102
Google Scholar
Atabek O, Burak S (2020) Pre-school and primary school pre-service teachers’ attitudes towards using technology in music education. Eurasian J Educ Res 20(87):47–68. https://doi.org/10.14689/ejer.2020.87.3Article
MATH
Google Scholar
Begic A, Begic JS (2023) Application of digital technology in music teaching. Školski vjesnik 72(1):45–56. https://doi.org/10.38003/sv.72.2.4Article
Google Scholar
Biasutti M, Frate S, Concina E (2019) Music teachers’ professional development: assessing a three-year collaborative online course. Music Educ Res 21(1):116–133. https://doi.org/10.1080/14613808.2018.1534818Article
MATH
Google Scholar
Biasutti M, Antonini Philippe R, Schiavio A (2021) Assessing teachers’ perspectives on giving music lessons remotely during the COVID-19 lockdown period. Musicae Sci 26(4):585–603. https://doi.org/10.1177/1029864921996033Article
Google Scholar
Biasutti M, Philippe RA, Schiavio A (2023) E-learning during the COVID-19 lockdown: an interview study with primary school music teachers in Italy. Int J Music Educ 41(2):256–270. https://doi.org/10.1177/02557614221107190Article
PubMed
Google Scholar
Bradford SC (1934) Sources of information on specific subjects. Engineering 137(3550):85–86MATH
Google Scholar
Brown AR (1995) Digital technology and the study of music. Int J Music Educ 25(1):14–19. https://doi.org/10.1177/025576149502500102Article
MATH
Google Scholar
Brown AR (1999) Music, media and making: humanising digital media in music education. Int J Music Educ 33(1):10–17. https://doi.org/10.1177/025576149903300103Article
MATH
Google Scholar
Buryakova LA, Buryakov AG (2020) French higher music education system. Problems Contemporary Science Practice 7(4):112–119
Google Scholar
Busen-Smith M (1999) Developing strategies for delivering music technology in secondary PGCE courses. Br J Music Educ 16:197–213Article
MATH
Google Scholar
Calderon-Garrido D, Gustems-Carnicer J (2021) Adaptations of music education in primary and secondary school due to COVID-19: the experience in Spain. Music Educ Res 23(2):139–150. https://doi.org/10.1080/14613808.2021.1902488Article
Google Scholar
Chen X, Hu Z, Wang C (2024) Empowering education development through AIGC: a systematic literature review. Educ Inf Technol 29(13):17485–17537. https://doi.org/10.1007/s10639-024-12549-7Article
Google Scholar
Chen J, Wang C, Tang Y (2022) Knowledge mapping of volunteer motivation: a bibliometric analysis and cross-cultural comparative study. Front Psychol. https://doi.org/10.3389/fpsyg.2022.883150Consejo Europeo (2018) Recomendación del Consejo de 22 de mayo de 2018 relativa a las competencias clave para el aprendizaje permanente. Diario Oficial de la Unión Europea de 4 de junio de 2018, C189:1–13Conway CM (2020) Teaching music in higher education. Oxford University Press, Oxford. https://doi.org/10.1093/oso/9780190945305.001.0001Cotten SR, Shank DB, Anderson WA (2014) Gender, technology use and ownership, and media-based multitasking among middle school students. Comput Human Behav 35:99–106. https://doi.org/10.1016/j.chb.2014.02.041Article
MATH
Google Scholar
Crawford R (2013) Evolving technologies require educational policy change: music education for the 21st century. Australas J Educ Technol. https://doi.org/10.14742/ajet.268Dai D (2021) Artificial intelligence technology assisted music teaching design. Sci Program 2021:9141339. https://doi.org/10.1155/2021/9141339. 1-9141339: 10Article
Google Scholar
de Solla Price DJ (1963) Little science, big science. Columbia University Press, New York. https://doi.org/10.7312/pric91844-005Devaney K (2023) Investigating how composing teaching and assessment in English secondary school classrooms reinforce myths about composers and their creative practices. Br J Music Educ 40(1):3–19. https://doi.org/10.1017/S0265051722000134Article
Google Scholar
Domínguez-Lloria S, Pino-Juste M (2020) Análisis comparativo de la formación inicial del profesorado de música de primaria y secundaria en Europa. Revista Electrónica de LEEME, December, 224–239. https://doi.org/10.7203/LEEME.46.18033Donthu N, Kumar S, Mukherjee D, Pandey N, Lim WM (2021) How to conduct a bibliometric analysis: an overview and guidelines. J Bus Res 133:285–296. https://doi.org/10.1016/j.jbusres.2021.04.070Article
Google Scholar
Dorfman J (2016) Teachers’ experiences in one-to-one computing environments. J Res Music Educ 64(2):159–178. https://doi.org/10.1177/0022429416649947Article
MATH
Google Scholar
Farina M, Lavazza A, Sartori G et al. (2024) Machine learning in human creativity: status and perspectives. AI Soc 39(6):3017–3029. https://doi.org/10.1007/s00146-023-01836-5Article
MATH
Google Scholar
Gaunt H, Duffy C, Coric A, González Delgado IR, Messas L, Pryimenko O, Sveidahl H (2021) Musicians as “makers in society”: a conceptual foundation for contemporary professional higher music education. Front Psychol 12:660089. https://doi.org/10.3389/fpsyg.2021.713648Article
Google Scholar
Giráldez A (2013) Enseñar artes en un mundo digital: Diez propuestas para la formación del profesorado. PÓS 38(5):85–104. https://periodicos.ufmg.br/index.php/revistapos/article/view/15466
Google Scholar
Gorbunova IB, Zalivadny MS (2020) The complex model of the semantic space of music: structure and features. Problemy Muzykalnoi Nauki-Music Scholarship 4:20–32. https://doi.org/10.33779/2587-6341.2020.4.020-032Article
MATH
Google Scholar
Griffin J, Holland M (2008) Musicians on the cutting edge of technology. Delta Kappa Gamma Bull 75(1):29–35MATH
Google Scholar
Guo S, Zhang Y, Sun Z (2024) Digital Empowerment of Excellent Traditional Chinese Music Culture Education. In: Streitz NA, Konomi, S (eds) Distributed, ambient and pervasive interactions Springer Nature, Switzerland, pp 231–241. https://doi.org/10.1007/978-3-031-60012-8_14Gustems J, Calderón D (2014) Estudio bibliométrico de los artículos de educación musical incluidos en DIALNET 2003-2013. Rev Electrónica de LEEME 33:27–39
Google Scholar
Hash PM (2021) Remote learning in school bands during the COVID-19 shutdown. J Res Music Educ 68(4):381–397. https://doi.org/10.1177/0022429420967008Article
PubMed
MATH
Google Scholar
Hosken D (2019) An introduction to music technology. Routledge, London. https://doi.org/10.4324/9780203539149Humberstone JHB, Zhao C, Liu D et al. (2024) Stimulating music educator worldview change through a pedagogy of provocation, critical thinking and peer-review. Int J Music Educ 42(1):47–67. https://doi.org/10.1177/02557614221149223Article
MATH
Google Scholar
Ivanova R, Berechikidze I, Gazizova F et al. (2020) Parent–teacher interaction and its role in preschool children’s development in Russia. Education 48:3–13. https://doi.org/10.1080/03004279.2019.1646296Article
Google Scholar
Jin F, Sun L, Pan Y, Lin CH (2025) High heels, compass, spider-man, or drug? Metaphor analysis of generative artificial intelligence in academic writing. Comput Educ 228:105248. https://doi.org/10.1016/j.compedu.2025.105248Article
MATH
Google Scholar
Jing Y, Wang C, Chen Y, Wang H et al. (2024a) Bibliometric mapping techniques in educational technology research: A systematic literature review. Educ Inf Technol 29(8):9283–9311. https://doi.org/10.1007/s10639-023-12178-6Article
MATH
Google Scholar
Jing Y, Wang C, Chen Z, Shen S et al. (2024b) A bibliometric analysis of studies on technology-supported learning environments: hot topics and frontier evolution. J Comput Assist Learn 40(3):1185–1200. https://doi.org/10.1111/jcal.12934Article
MATH
Google Scholar
Jorgensen ER (2008) Questions for music education research. Music Educ Res 10(3):331–346. https://doi.org/10.1080/14613800802280050Article
MATH
Google Scholar
Jorquera MC (2017) Las buenas prácticas como reflejo del estado de la educación musical: una revision bibliográfica. Rev Int Educ Musical 5:71–83. https://doi.org/10.12967/RIEM-2017-5-p071-083Article
Google Scholar
Kardos L (2012) How music technology can make sound and music worlds accessible to student composers in further education colleges. Br J Music Educ 29(2):143–151. https://doi.org/10.1017/S0265051712000186Article
MATH
Google Scholar
Karkina S, Valeeva R, Starčič AI (2021) Improving professional skills of music teachers through the use of distance learning. J Inf Technol Res 14:187–199. https://doi.org/10.4018/JITR.2021040110Article
MATH
Google Scholar
Karkina S, Mena J, Valeeva R et al. (2023) Fostering future music teachers’ professional skills: developing a signature pedagogy using e-learning. Front Educ. https://doi.org/10.3389/feduc.2023.1162748Kladder J (2021) Digital audio technology in music teaching and learning: a preliminary investigation. J Music Technol Educ 14(3):245–258. https://doi.org/10.1386/jmte_00040_1Article
Google Scholar
Koutsoupidou T (2014) Online distance learning and music training: Benefits, drawbacks and challenges. Open Learn 29(3):243–255. https://doi.org/10.1080/02680513.2015.1011112Article
Google Scholar
Lee M, Nguyen T (2021) Virtual reality and artificial intelligence in music classrooms. J Educ Technol 42(1):88–102. https://doi.org/10.1177/0047239521998752Article
MATH
Google Scholar
Li K, Weng L, Wang X (2021) The state of music therapy studies in the past 20 years: a bibliometric analysis. Front Psychol 12:697726. https://doi.org/10.3389/fpsyg.2021.697726Article
PubMed
PubMed Central
MATH
Google Scholar
Lin Y, Yu Z (2023) Extending technology acceptance model to higher-education students’ use of digital academic reading tools on computers. Int J Educ Technol Higher Educ 20(1):34. https://doi.org/10.1186/s41239-023-00403-8Article
MATH
Google Scholar
Lin Y, Yu Z (2024) An integrated bibliometric analysis and systematic review modelling students’ technostress in higher education. Behav Inform Technol. https://doi.org/10.1080/0144929X.2024.2332458Lotka AJ (1926) The frequency distribution of scientific productivity. J Wash Acad Sci 16(12):317–323MATH
Google Scholar
Ma Y (2024) Bibliometric study of 40 years of research in Chinese music archaeology. Sage Open. https://doi.org/10.1177/21582440241308339MacDonald R, Burke R, De Nora T et al. (2021) Our virtual tribe: sustaining and enhancing community via online music improvisation. Front Psychol. https://doi.org/10.3389/fpsyg.2020.623640MacRitchie J, Chmiel A, Radnan M et al. (2023) Going online: successes and challenges in delivering group music instrument and aural learning for older adult novices during the COVID-19 pandemic. Music Sci 27(3):596–615. https://doi.org/10.1177/10298649221097953Article
Google Scholar
Marín-Suelves D, Méndez VG, Monzonís NC (2022) Music education and technology: trends in research. Rev Electron Complut Invest Educ Musical 19:275–286. https://doi.org/10.5209/reciem.74693Article
Google Scholar
Mercado EM, Draut DM (2024) Eighth- and ninth-grade students’ perceptions of a curriculum designed to support adolescent female vocal development: an action research study. Res Stud Music Educ 46(1):98–113. https://doi.org/10.1177/1321103X221149661Article
Google Scholar
Merrick B, Joseph D (2023) ICT and music technology during COVID-19: Australian music educator perspectives. Res Stud Music Educ 45(1):189–210. https://doi.org/10.1177/1321103X221092927Article
PubMed
MATH
Google Scholar
Merrick B (2024) Informed teaching and practice in music education: exploring music technologies, curriculum design and learning environments in an everchanging world. In: Johnson C, King A (eds) Music, technology, innovation. RoutledgeMielke S, Andrews BW (2023) Composing for students: composers’ reflections on the process of creating educational music. Res Stud Music Educ 45(2):379–396. https://doi.org/10.1177/1321103X221114613Article
MATH
Google Scholar
Ortiz Molina MA, Sadio-Ramos FJ, Bernabé Villodre M del M (2021) Desenvolvimento de competências por meio das TIC e formação de professores de Música: uma experiência biográfica. Developing creativity through ICT and music teachers’ training: a biographical experience. https://doi.org/10.35699/1983-3652.2021.25419Ozer B, Üstün E (2020) Evaluation of students’ views on the Covid-19 distance education process in music departments of fine arts faculties. J Educ Train Stud 8(3):121–131MATH
Google Scholar
Pervushina O, Kryuchkova NV (2018) The contextual approach in the system of musical education in institutions of higher education. Music Scholarship 4(2):178–192MATH
Google Scholar
Romera MJ (1992) Potencialidad de la bibliometría para el estudio de la ciencia. Aplicación a la Educación Especial. Rev Educ 297:459–478
Google Scholar
Sánchez-Marroquí J, Vicente-Nicolás G (2024) Bibliometric study of scientific production in music education from 2000 to 2022. Int J Music Educ. https://doi.org/10.1177/02557614231220654Sastre J, Cerdà J, García W, Hernandez CA, Lloret N, Murillo A, Dannenberg R (2013) New technologies for music education. In: Proceedings of the second international conference on E-learning and E-technologies in education (ICEEE). 149–154. https://doi.org/10.1109/ICeLeTE.2013.6644364Savage J (2007) Reconstructing music education through ICT. Res Educ 78(1):65–77. https://doi.org/10.7227/RIE.78.6Article
Google Scholar
Schiavio A, Biasutti M, Philippe RA (2021) Creative pedagogies in the time of pandemic: a case study with conservatory students. Music Educ Res 23(2):167–178. https://doi.org/10.1080/14613808.2021.1881054Article
Google Scholar
Seddon F, Biasutti M (2008) Non-music specialist trainee primary school teachers’ confidence in teaching music in the classroom. Music Educ Res 10(3):403–421. https://doi.org/10.1080/14613800802280159Article
MATH
Google Scholar
Serrano R (2017) Tecnología y educación musical obligatoria en España: referentes para la implementación de buenas prácticas. Rev Electron Complut Invest Educ Musical 14:153–169Article
Google Scholar
Shang X, Liu Z, Gong C et al. (2024) Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023. Humanit Soc Sci Commun 11(1):1–21. https://doi.org/10.1057/s41599-024-03658-2Article
MATH
Google Scholar
Shaw RD, Mayo W (2021) Music education and distance learning during COVID-19: A survey. Arts Educ Policy Rev 123(2):143–152. https://doi.org/10.1080/10632913.2021.1931597Article
MATH
Google Scholar
Smith G, Clarke M (1993) Electro-acoustic music in higher education. Br J Music Educ 10(1):85–90. https://doi.org/10.1017/S0265051700001546Article
MATH
Google Scholar
Strenacikova M (2023) Musical art distance education after pandemic. Acta Educ Gen 13:79–97. https://doi.org/10.2478/atd-2023-0023Article
Google Scholar
Turchet L, Fischione C, Essl G, Keller D, Barthet M (2018) Internet of musical things: vision and challenges. IEEE Access 6:61994–62017. https://doi.org/10.1109/ACCESS.2018.2872625Article
Google Scholar
Uludag AK, Satir UK (2023) Seeking alternatives in music education: the effects of mobile technologies on students’ achievement in basic music theory. Int J Music Educ. https://doi.org/10.1177/02557614231196972Vaizman T (2022) Teaching musical instruments during COVID-19: teachers assess struggles relations with students and leveraging. Music Educ Res 24(2):152–165. https://doi.org/10.1080/14613808.2022.2053512Article
Google Scholar
Väkevä L (2017) Defining and acknowledging music education technology in music teacher training. In: Ruthmann SA, Roger Mantie R (eds) The Oxford handbook of technology and music education. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199372133.013.56VanEck NJ, Waltman L (2010) Software survey: VOSviewer a computer program for bibliometric mapping. Scientometrics 84(2):523–538. https://doi.org/10.1007/s11192-009-0146-3Article
MATH
Google Scholar
Vyshynskyi V, Yahodzynska I (2017) Distance learning for music disciplines in higher education: challenges and prospects. Proc Soc Inf Technol Teacher Educ Int Conf 3:585–598. https://doi.org/10.17770/sie2017vol3.2382Article
Google Scholar
Waddell G, Williamon A (2019) Technology use and attitudes in music learning. Front ICT 6:1–15. https://doi.org/10.3389/fict.2019.00011Article
MATH
Google Scholar
Walls K (2000) Technology for future music educators. J Music Teach Educ 9(2):14–21. https://doi.org/10.1177/105708370000900204Article
MATH
Google Scholar
Walls K (2008) Distance learning in graduate music teacher education. J Music Teach Educ 18(1):55–66. https://doi.org/10.1177/1057083708323140Article
MATH
Google Scholar
Wang C, Chen X, Yu T et al. (2024a) Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11(1):1–17. https://doi.org/10.1057/s41599-024-02717-yArticle
MATH
Google Scholar
Wang CL, Dai J, Zhu KK, Yu T, Gu XQ (2023) Understanding the continuance intention of college students toward new E-learning spaces based on an integrated model of the TAM and TTF. Int J Hum-Comput Int 40(24):8419–8432. https://doi.org/10.1080/10447318.2023.2291609Article
MATH
Google Scholar
Wang C, Wang H, Li Y et al. (2024b) Factors influencing university students’ behavioral intention to use generative artificial intelligence: integrating the theory of planned behavior and AI literacy. Int J Hum Comput Int. https://doi.org/10.1080/10447318.2024.2383033Wang CL, Chen XJ, Hu ZB, Jin S, Gu XQ (2025) Deconstructing university learners’ adoption intention towards AIGC technology: a mixed-methods study using ChatGPT as an example. J Comp Assist Learn. https://doi.org/10.1111/jcal.13117Welch G, Papageorgi I, Haddon L, Creech A, Morton F, Bézenac C, Duffy C, Potter J, Whyton T, Himonides E (2008) Musical genre and gender as factors in higher education learning in music. Res Pap Educ 23(2):203–217. https://doi.org/10.1080/02671520802048752Article
Google Scholar
Yang C, Liu T (2022) Social media data in urban design and landscape research: a comprehensive literature review. Land 11(10):1796. https://doi.org/10.3390/land11101796Article
MATH
Google Scholar
Yu X, Ma N, Zheng L, Wang L, Wang K (2023) Developments and applications of artificial intelligence in music education. Technologies 11(1):7. https://doi.org/10.3390/technologies11020042Article
CAS
MATH
Google Scholar
Zhang P, Sui X (2017) Application of digital music technology in music pedagogy. Int J Emerg Technol Learn 12(12):4–12. https://doi.org/10.3991/ijet.v12i12.7966Article
MATH
Google Scholar
Zhou N (2018) Reflections on using music education to improve the comprehensive quality of higher vocational students. Soc Sci Humanit 26(2):115–128. https://doi.org/10.25236/ssah.2018.203Article
MathSciNet
MATH
Google Scholar
Download referencesAuthor informationAuthors and AffiliationsSchool of Literature, Zhengzhou University, Zhengzhou, ChinaYidi MaDepartment of Education Information Technology, Faculty of Education, East China Normal University, Shanghai, ChinaChengliang WangAuthorsYidi MaView author publicationsYou can also search for this author in
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