Teaching digital methods in higher education poses a particular challenge, as the exponential increase in available digital resources require the search for innovative practices to accelerate the learning of new skills (Al-Zahrani & Alasmari, 2024). The growing need for computational skills makes it necessary to redesign the traditional teaching model in which a central role is attributed to a personalized approach to teaching.

In relation to previous technological innovations in education that required long periods of adaptation, artificial intelligence was incorporated almost instantaneously into students' learning practices, creating an urgent need for educators to redefine their teaching approaches (Bowen & Watson, 2024). This integration does not mean sidelining the educator, but upgrades their role by transforming them into a designer of learning experiences who utilizes technology to achieve pedagogical goals (Leaton Gray & Cukurova, 2024). On the other hand, concerns arise regarding ethical issues such as personal data protection, transparency, reliability, and the implications of content generated by artificial intelligence (Al-Zahrani, 2024).

The purpose of the research is to evaluate the effectiveness of a hybrid teaching model that incorporates artificial intelligence as a teaching assistant for learning digital methods and programming for musicology students. The model was applied to students of the Department of Music Studies at the National and Kapodistrian University of Athens who attended the course "Digital methods in historical musicology" and subsequently participated in a research to evaluate the model.

The research methodology combined quantitative techniques through structured questionnaires with parallel qualitative investigation through targeted interviews. Comparative analysis of student performance revealed remarkable improvement in both efficiency and speed of solving exercises. The findings demonstrate significant enhancement of students' abilities in solving technical problems and a noticeable reduction in the time required to acquire basic programming skills. On the other hand, there is a clear distinction in the effectiveness of the educational tool on the time axis, with higher success rates in immediate problem solving and lower in long-term skills development.

The conclusions of the research concern the digital humanities in general, proposing a balanced pedagogical approach that utilizes artificial intelligence as a complementary learning tool while ensuring the development of autonomous skills by students. The proposed approach offers an innovative hybrid teaching model, providing a framework for the effective integration of artificial intelligence in education.

• Digital environment and music Education
• Curricula and critical approaches

Tassos Kolydas is a member of the Laboratory-Teaching Staff of the Department of Music Studies of the National and Kapodistrian University of Athens. He has studied musicology (PhD), computer science (MSc), and guitar. He has published musicological and computer science papers in both Greek and international journals. His research interests revolve around Greek art music, digital cultural heritage management and information and communication technologies in education. He has taught courses in historical musicology and digital musicology at the University of Athens and the University of Ioannina. He has developed web applications as part of research projects for the University of Athens, the Greek National Opera, the Institute for Research in Music Acoustics, the University of Ioannina, etc. He is a member of the Hellenic Musicological Society, the Greek Branch of IAML, the Hellenic Orff - Schulwerk Association and the Greek Society for Music Education . More information: https://www.kolydart.gr/