ÇEVRİMİÇİ MÜZİK EĞİTİMİ ALANINDAKİ ARAŞTIRMA DURUMU, AĞIRLIK NOKTALARI VE EVRİM: BİBLİYOMETRİK BİR İNCELEME

Öz

ÖZ Günümüzün hızlı bilgi gelişimi çağında, dijital teknolojinin hızlı ilerlemesi özellikle önemli hale gelmiş ve birçok alanı derinden yeniden şekillendirmiştir. Küresel olarak, kişiselleştirilmiş öğrenme talebi, yükselen bir eğitim modeli olarak, gün geçtikçe artarken, birleşik eğitim standartlarının tartışılması ve aranması da kademeli olarak güçlenmektedir. Bu eğitim çeşitliliği ile standardizasyonun paralel takibi, toplumun kaliteli eğitime olan beklentilerini ve taleplerini yansıtmaktadır. Bu bağlamda, eğitim modellerinin dönüşümüne tanık olduk, özellikle işbirlikçi öğrenmenin ve eğitim kaynaklarının paylaşımının geniş çapta kabul görmesi ve değer kazanması dikkat çekicidir. Bu eğilim sadece geleneksel eğitim uygulamalarında değil, aynı zamanda çevrimiçi eğitim alanında da önemli ölçüde kendini göstermiş ve gelişmiştir. Bu eğitim değişimi dalgasında, çevrimiçi müzik eğitimi sektörü, kendine özgü çekiciliği ve potansiyeliyle geniş çapta ilgi çekmiştir. Yaratıcılık ve duygusal ifade açısından zengin bir sanatsal form olan müzik eğitimi, çevrimiçi trendiyle öğrenenlere yeni öğrenme deneyimleri ve imkanlar sunmuştur. Bununla birlikte, çevrimiçi müzik eğitiminin hızlı gelişimine rağmen, mevcut araştırmalar geri kalmaktadır; özellikle etkili yazarlar, popüler konular ve evrimsel eğilimler gibi bibliyometrik göstergelerin nicel ve ampirik analizi açısından eksiklikler bulunmaktadır. Bu boşluğu doldurmak amacıyla, araştırmamız küresel otoriteye sahip Web of Science (WOS) veri tabanından elde edilen zengin verileri kullanmaktadır. Sistematik literatür incelemesi ve analizi yoluyla, çevrimiçi müzik eğitimi alanının temel içeriklerini ve özelliklerini ortaya çıkarmayı amaçlıyoruz. Bu süreçte, güçlü bir analiz aracı olan VOSviewer'ı kullanarak, bu alanın yazar dağılımı, coğrafi katkılar, anahtar dergiler, birlikte meydana gelen anahtar kelimeler ve birlikte atıf yapılan referanslar gibi çok boyutlu yönlerini derinlemesine anlamamıza yardımcı oluyoruz. Bu kapsamlı analiz serisi sayesinde, çevrimiçi müzik eğitimi alanının mevcut durumunu net bir şekilde tasvir etmekle kalmıyor, aynı zamanda bu alanın öncü sıcak noktalarını ve gelecekteki evrimsel eğilimlerini de ortaya koyuyoruz. Bu çalışmadan elde edilen bulgular, bu alandaki akademisyenlere ve eğitimcilere kapsamlı ve çok boyutlu bir bakış açısı sunmayı hedeflemekte olup, gelecekteki araştırmaları ve çalışmaları için güçlü bir referans ve rehberlik sağlamayı amaçlamaktadır.

Anahtar Kelimeler

• çevrimiçi müzik eğitimi
• e-öğrenme
• VOSviewer
• bibliyometrik
• görsel analiz

RESEARCH STATUS, HOTSPOTS AND EVOLUTION IN THE FIELD OF ONLINE MUSIC EDUCATION: A BIBLIOMETRIC REVIEW

Abstract

ABSTRACT In the contemporary era of swift informational advancement, the rapid progression of digital technology has become especially significant, profoundly reshaping numerous fields. Globally, the demand for personalized learning, an emerging educational model, is increasing day by day, while the discussion and pursuit of unified educational standards are also gradually strengthening. This parallel pursuit of educational diversity and standardization reflects society's expectations and demands for high-quality education. Against this backdrop, we have witnessed the transformation of educational models, particularly the widely recognized and valued importance of collaborative learning and the sharing of educational resources. This trend is not only evident in traditional educational practices but also significantly manifested and developed in the field of online education. In this wave of educational change, the online music education sector has attracted widespread attention with its unique charm and potential. Music education, as an artistic form rich in creativity and emotional expression, has provided learners with brand-new learning experiences and possibilities through its online trend. However, despite the rapid development of online music education, existing research lags, particularly in the quantitative and empirical analysis of bibliometric indicators such as influential authors, popular topics, and evolutionary trends. To fill this gap, our research utilizes abundant data from the globally authoritative Web of Science (WOS) database. Through systematic literature review and analysis, we aim to reveal the core content and characteristics of the online music education field. In this process, we employ VOSviewer, a powerful analytical tool, which helps us gain a deep understanding of multiple dimensions within this field, including the distribution of authors, geographical contributions, key journals, co-occurring keywords, and co-cited references. Through this series of in-depth analyses, we not only clearly depict the current status of the online music education field but also reveal its frontier hotspots and future evolution trends. The insights from this study aim to provide scholars and educators in this field with a comprehensive and multidimensional perspective, serving as a strong reference and guidance for their future research and work.

Keywords

• online music education
• e-learning
• VOSviewer
• bibliometrics
• visual analysis

Kaynakça

1. Abramo, G., D'Angelo, C. A., and Viel, F. (2011). The field-standardized average impact of national research systems compared to world average: The case of Italy. Scientometrics, 88(2), 599–615.
2. Bai, J. (2022). Design of the Artificial Intelligence Vocal System for Music Education by Using Speech Recognition Simulation. Computational intelligence and neuroscience,2022.
3. Bernard, C., Weiss, L., and Abeles, H. (2018). Space to Share: Interactions Among Music Teachers in an Online Community of Practice. Bulletin of the council for research in music education, 215, 75–94.
4. Biasutti, M. (2011). The student experience of a collaborative e-learning university module. Computers and education, 57(3), 1865–1875.
5. Biasutti, M. (2018). Strategies adopted during collaborative online music composition. International journal of music education, 36(3), 473–490.
6. Brookes, B. C. (1985). Sources of information on specific subjects by S.C. Bradford. Journal of information science, 10(4), 173–175.
7. Camlin, D. A., and Lisboa, T. (2021). The digital 'turn' in music education (editorial). Music education research, 23(2), 129–138.
8. Crawford, R. (2017). Rethinking teaching and learning pedagogy for education in the twenty-first century: Blended learning in music education. Music education research, 19(2), 195–213.

9. Dai, D. (2021). Artificial Intelligence Technology Assisted Music Teaching Design. Scientific programming, 2021,1-10.
10. Dammers, R. J. (2009). Utilizing Internet-Based Videoconferencing for Instrumental Music Lessons. Applications of research in music education, 28(1), 17–24.
11. de Bruin, L. (2021). Instrumental Music Educators in a COVID Landscape: A Reassertion of Relationality and Connection in Teaching Practice. Frontiers in rsychology. 11: 624717.
12. Dehghanzadeh, H., Farrokhnia, M., Dehghanzadeh, H., Taghipour, K., and Noroozi, O. (2023). Using gamification to support learning in K-12 education: A systematic literature review. British journal of educational technology, 2023.
13. Diem, A., and Wolter, S. C. (2013). The Use of Bibliometrics to Measure Research Performance in Education Sciences. Research in higher education, 54(1), 86–114.
14. Ding, X., and Yang, Z. (2022). Knowledge mapping of platform research: A visual analysis using VOSviewer and CiteSpace. Electronic commerce research, 22(3), 787–809.
15. Dorfman, J., Matthews, W., Resta, C., and Venesile, C. (2021). Looking Into the Virtual Space: Teacher Perceptions of Online Graduate Music Education. Bulletin of the council for research in music education, 229, 71–90. DOI:10.5406/bulcouresmusedu.229.0071
16. Dreamson, N., and Park, G. (2023). Metaverse-Based Learning Through Children's School Space Design. International journal of art and design education, 42(1), 125–138.
17. Gelineau-Morel, R., and Dilts, J. (2021). Virtual Education During COVID-19 and Beyond. Pediatric neurology, 119, 1–2.
18. Goncharova, M. S., and Gorbunova, I. B. (2020). Mobile Technologies in the Process of Teaching Music Theory. Propósitos y representaciones,8(SPE3), e705.
19. González-González, C. S., Infante-Moro, A., and Infante-Moro, J. C. (2020). Implementation of E-Proctoring in Online Teaching: A Study about Motivational Factors. Sustainability, 12(8), 3488.
20. Gudoniene, D., and Rutkauskiene, D. (2019). Virtual and Augmented Reality in Education. Baltic journal of modern computing, 7(2),293-300. DOI:10.22364/bjmc.2019.7.2.07
21. Habe, K., Biasutti, M., and Kajtna, T. (2021). Wellbeing and flow in sports and music students during the COVID-19 pandemic. Thinking skills and creativity, 2021, 39: 100798.
22. Hicks, D., Tomizawa, H., Saitoh, Y., and Kobayashi, S. (2004). Bibliometric techniques in the evaluation of federally funded research in the United States. Research evaluation, 13(2), 76–86.
23. Hwang, G.-J., and Tu, Y.-F. (2021). Roles and Research Trends of Artificial Intelligence in Mathematics Education: A Bibliometric Mapping Analysis and Systematic Review. Mathematics, 9(6), 584.
24. Ignacio Pozo, J., Perez Echeverria, M.-P., Casas-Mas, A., Lopez-Iniguez, G., Cabellos, B., Mendez, E., Antonio Torrado, J., and Bano, L. (2022). Teaching and learning musical instruments through ICT: the impact of the COVID-19 pandemic lockdown. Heliyon, 8(1), e08761.
25. Ismail, M. J., Anuar, A. F., and Loo, F. C. (2022). From Physical to Virtual: A New Learning Norm in Music Education for Gifted Students. International review of research in open and distributed learning, 23(2), 44–62.
26. Jia, K., Wang, P., Li, Y., Chen, Z., Jiang, X., Lin, C.-L., and Chin, T. (2022). Research Landscape of Artificial Intelligence and E-Learning: A Bibliometric Research. Frontiers in rsychology, 13:795039.
27. Johnson, C. (2017). Teaching music online: Changing pedagogical approach when moving to the online environment. London review of education, 15, 439–456.
28. Johnson, C. and Hawley, S. (2017). Online music learning: Informal, formal and STEAM contexts. International journal on innovations in online education,1(2),2377-9527.
29. Kang, M., Kim, S., Park, G., Lee, G., and Kil, M. (2006). Design of DRM-LMS model in M-learning environment. Knowledge-based intelligent information and engineering systems, 2006,1075-1082.
30. Kara, M. (2020). Distance education: A systems view of online learning: by Michael G. Moore and Greg Kearsley, Belmont, CA, Wadsworth Cengage Learning, 2012, 361.ISBN:978-1-111-52099-1. Educational review, 72(6), 800–800.
31. Katz, Y. J. (2000). The Comparative Suitability Of Three ICT Distance Learning Methodologies For College Level Instruction. Educational media international, 37(1), 25–30.
32. Katz, Y. J. (2002). Attitudes affecting college students' preferences for distance learning: College students' preferences for distance learning. Journal of computer assisted learning, 18(1), 2–9.
33. Koutsoupidou, T. (2016). Online Distance Learning and Music Training: Benefits, drawbacks and challenges. Open Learning: The Journal of Open, Distance and e-Learning, 29(3), 243-255.
34. Luo, W., and Hong, H. (2022). Approaches and Methods of Music Education Innovation Based on Digital Image Technology. Mobile information systems, 2022.
35. Marín Suelves, D., Gabarda Méndez, V., and Vidal Esteve, M. I. (2021). E-learning and development of key competencies: A bibliometric study. EDMETIC, 10(2), 106–138.
36. Martins, L. L., and Kellermanns, F. W. (2004). A Model of Business School Students' Acceptance of a Web-Based Course Management System. Academy of management learning and education, 3(1), 7–26.
37. Oliveira, W., Hamari, J., Shi, L., Toda, A. M., Rodrigues, L., Palomino, P. T., and Isotani, S. (2023). Tailored gamification in education: A literature review and future agenda. Education and information technologies, 28(1), 373–406.
38. Partti, H., and Karlsen, S. (2010). Reconceptualising musical learning: New media, identity and community in music education. Music education research, 12(4), 369–382.
39. Paule-Ruiz, M., Alvarez-Garcia, V., Perez-Perez, J., Alvarez-Sierra, M., and Trespalacios-Menendez, F. (2017). Music learning in preschool with mobile devices. Behaviour and information technology, 36(1), 95–111.
40. Pesek, M., Suhadolnik, L., Savli, P., and Marolt, M. (2020). Motivating Students for Ear-Training with a Rhythmic Dictation Application. Applied sciences-basel, 10(19),6781.
41. Pesek, M., Vucko, Z., Savli, P., Kavcic, A., and Marolt, M. (2020). Troubadour: A Gamified e-Learning Platform for Ear Training. IEEE, 8, 97090–97102.
42. Piccoli, G., Ahmad, R., and Ives, B. (2001). Web-Based Virtual Learning Environments: A Research Framework and a Preliminary Assessment of Effectiveness in Basic IT Skills Training. MIS Quarterly 25(4), 401-426.
43. Pike, P. (2017). Improving music teaching and learning through online service: A case study of a synchronous online teaching internship. International journal of music education, 35(1), 107–117.
44. Rucsanda, M., Belibou, A., and Cazan, A. (2021). Students' Attitudes Toward Online Music Education During the COVID 19 Lockdown. Frontiers in rsychology, 12,753785.
45. Sala, N. (2021). Virtual Reality, Augmented Reality, and Mixed Reality in Education: A Brief Overview. Current and prospective applications of virtual reality in higher education, 48–73.
46. Song, Y., Wei, K., Yang, S., Shu, F., and Qiu, J. (2020). Analysis on the research progress of library and information science since the new century. Library hi tech, 41(4), 1145-1157.
47. Tambouratzis, G., Bakamidis, S., Dologlou, I., Carayannis, G., and Dendrinos, M. (2002). The IMUTUS interactive music tuition system. The journal of the acoustical society of america, 111(5_Supplement), 2348-2348.
48. Tambouratzis, G., Perifanos, K., Voulgari, I., Askenfelt, A., Granqvist, S., Hansen, K. F., Orlarey, Y., Fober, D., and Letz, S. (2008). VEMUS: An Integrated Platform to Support Music Tuition Tasks.IEEE, 972–976.
49. Teo, T. (2016). Modelling Facebook usage among university students in Thailand: The role of emotional attachment in an extended technology acceptance model. Interactive learning environments, 24(4), 745–757.
50. Trentin, G. (1997). Telematics and on‐line teacher training: The Polaris Project. Journal of computer assisted learning, 13(4), 261–270.
51. Van Eck, N. J., and Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.
52. Wang, X., Wang, Q., and Chen, Y. (2020). Analysis of Music Online Teaching Curriculum Arrangement Based on BP Neural Network Model. Journal of physics: conference series, 1648(3), 032101.
53. Xu, N., and Zhao, Y. (2021). Online Education and Wireless Network Coordination of Electronic Music Creation and Performance under Artificial Intelligence.Wireless communications and mobile computiong,2021,1-9.
54. Xu, Y. (2022). The New Media Environment Presents Challenges and Opportunities for Music Education in Higher Education. journal of environmental and public health,2022,1-11.
55. Yang, C. (2022). Monitoring and Sharing of Music Teaching Environment Resources Using Big Data Technology. journal of environmental and public health,2022,1-10.
56. Zhang, X., Chen, Y., Hu, L., and Wang, Y. (2022). The metaverse in education: Definition, framework, features, potential applications, challenges, and future research topics. Frontiers in rsychology, 13:1016300.
57. Zhang, Y., Zhao, Y., Luo, Y., Yang, X., and Tan, D. (2022). The relation between autonomy support and music enjoyment in online learning for music undergraduates in the post-COVID-19 era. Frontiers in rsychology, 13:1062546.
58. Zheng, H., and Dai, D. (2022). Construction and Optimization of Artificial Intelligence-Assisted Interactive College Music Performance Teaching System. Scientific programming, 2022, 1–9.
59. Zhou, T. (2023). Bibliometric analysis and visualization of online education in sports. Cogent social sciences, 9(1), 2167625.