Integrating generative artificial intelligence into blended music theory education: Student motivation, attitudes and experiences
Journal of Music, Technology and Education, cilt.17, sa.3, ss.195-218, 2024 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 17 Sayı: 3
- Basım Tarihi: 2024
- Doi Numarası: 10.1386/jmte_00082_1
- Dergi Adı: Journal of Music, Technology and Education
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
- Sayfa Sayıları: ss.195-218
- Anahtar Kelimeler: blended learning, educational technology, generative artificial intelligence, music education, student motivation, web-based learning tools
- Atatürk Üniversitesi Adresli: Evet
Özet
Rapid developments in educational technologies have transformed teaching and learning practices, particularly through the integration of web-based tools and generative artificial intelligence (GenAI). In music education, these technologies offer new opportunities for personalized, interactive and student-centred learning experiences. This study investigates the effects of GenAI-supported blended music theory education on students’ motivation, attitudes and learning experiences. A case study design was employed with fifteen high school students studying music at a fine arts high school in Türkiye. Over a six-week period, music theory instruction was delivered through a blended learning approach supported by a GenAI-based web platform focusing on ear-training exercises. Data were collected through motivation and attitude scales, teacher diaries and semi-structured student interviews. Qualitative data were analysed using content analysis, while quantitative findings were examined descriptively. The results suggest that students perceived GenAI-supported blended music theory education as fostering their motivation to learn and active engagement. Students reported positive attitudes towards the use of GenAI in music education, although concerns related to ethical issues were also expressed. The findings highlight the pedagogical potential of GenAI in music education and underscore the importance of examining its integration from multiple educational perspectives.