Yapay zekâ, yapay zekâ söyle bana: Keman eğitiminde yapay zekâ destekli geri bildirimin entonasyona etkisine yönelik bir model çalışması

Öz

Grimm Kardeşler’in ünlü masalında sihirli ayna, “Ayna, ayna söyle bana…” sorusuna gerçeği yanıtlayarak kraliçeye karşı dürüst davranır. Benzer biçimde, bu araştırmada üretken yapay zekâ, keman öğrencilerinin entonasyon performanslarına ilişkin anlık ve nesnel geri bildirimler sunan bir “dijital ayna” işlevi görmüştür. Karma yöntem araştırma deseninin kullanıldığı bu çalışmanın amacı, üretken yapay zekâ destekli geri bildirimin keman eğitiminde entonasyon becerisini geliştirmedeki etkisini, süreçte sunulan içeriklerin kapsamını ve öğrencilerin uygulamaya ilişkin deneyimlerini bütüncül olarak incelemektir. Çalışma grubu, 2024-2025 akademik yılında Türkiye’deki bir devlet üniversitesinin müzik eğitimi bölümüne kayıtlı 12 keman öğrencisinden oluşmuştur. Dört haftalık deneysel süreçte, öğrencilerin performansları Cubase yazılımında kaydedilmiş, frekans analizi yapılarak cent cinsinden entonasyon verileri elde edilmiştir. Bu veriler, öğretmen müdahalesi olmaksızın ChatGPT ve DeepSeek yapay zekâ sistemleri tarafından analiz edilerek değerlendirilmiş ve öğrencilere teknik ile müzikal boyutta öneriler sunulmuştur. Nicel veriler, Bağımlı Örnekler t-testi ile öntest–sontest puanları karşılaştırılarak analiz edilmiş; sonuçlar, sontest lehine istatistiksel olarak anlamlı bir fark ortaya koymuştur. Nitel veriler ise betimsel analiz yöntemiyle incelenmiş; öğrenciler, yapay zekânın sağladığı detaylı analizlerden, kişiselleştirilmiş çok boyutlu önerilerden ve motivasyon artırıcı yönlendirmelerden memnuniyet duyduklarını ifade etmiştir. Çalışma, müzik eğitimi bağlamında ve özellikle keman eğitiminde üretken yapay zekâ destekli geri bildirimin entonasyon becerisi üzerindeki etkisine yönelik sınırlı sayıdaki araştırmalara deneysel ve nitel bulgular sunarak literatüre katkı sağlamaktadır. Gelecek çalışmalarda, görsel ve işitsel geri bildirim unsurlarını entegre eden ve öğrencinin çalışma planını otomatik olarak uyarlayabilen sistemlerin geliştirilmesi önerilmektedir.

Anahtar Kelimeler

• müzik eğitimi
• keman eğitimi
• entonasyon
• bilgisayar destekli öğrenme
• yapay zekâ
• geri bildirim

AI AI tell me: A model study on the effect of artificial intelligence-assisted feedback on intonation in violin education

Öz

In the famous fairy tale by the Brothers Grimm, the magic mirror responds truthfully to the question, “Mirror, mirror, tell me…,” thus acting with honesty toward the queen. Similarly, in this study, generative artificial intelligence functioned as a “digital mirror” by providing instant and objective feedback on violin students’ intonation performance. The aim of this study, which employed a mixed-methods research design, was to comprehensively examine the effect of generative AI-assisted feedback on the development of intonation skills in violin education, the scope of the content delivered during the process, and students’ experiences with the application. The study group consisted of 12 violin students enrolled in the Department of Music Education at a state university in Türkiye during the 2024–2025 academic year. Over a four-week experimental process, students’ performances were recorded using Cubase software, and intonation data in cents were obtained through frequency analysis. These data were analyzed and evaluated by the ChatGPT and DeepSeek AI systems (without teacher intervention), which then provided students with both technical and musical recommendations. Quantitative data were analyzed by comparing pre-test and post-test scores using the paired-samples t-test. The results revealed a statistically significant difference in favor of the post-test. Qualitative data were examined through descriptive analysis, and students reported satisfaction with the detailed analyses, personalized multi-dimensional recommendations, and motivational guidance provided by the AI. This study contributes to the limited body of research on the effect of generative AI-assisted feedback on intonation skills in the context of music education, particularly violin instruction, by presenting both experimental and qualitative findings. Future studies are recommended to develop systems that integrate visual and auditory feedback elements and can automatically adapt students’ practice plans.

Anahtar Kelimeler

• music education
• violin education
• intonation
• computer-based learning
• artificial intelligence
• feedback

Kaynakça

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