Artificial Intelligence in Teaching Music Skills and Teachers' Attitudes Towards It in the Sultanate of Oman
Authors: Mohamed Asmaa Abdel Sabour , Mahmoud Sherif Mohamed , Khalladi Yassine Mohammed 
Published: February 2025

Objective: The study aimed to identify the attitudes of music skills teachers in Oman towards the use of artificial intelligence (AI) in teaching and to understand the challenges they face in integrating AI into their teaching methods.
 
Theoretical Framework: The proliferation of modern learning resources and technological advancements, especially the emergence of artificial intelligence, have significantly impacted educational institutions. Oman is striving to align its education system with the digital transformation outlined in Oman Vision 2040, which emphasizes high-quality education, the integration of technology, innovation, entrepreneurship, and skill-building.
 
Method: This study adopted a descriptive analytical method, analyzing a questionnaire completed by music skills teachers in Oman regarding their opinions on AI in teaching. The survey focused on three main axes: knowledge of AI, its use in teaching music skills, and the challenges faced by teachers in integrating AI into their practice.
 
Results and Discussion: The results indicated that music skills teachers in Oman have a positive attitude towards the use of artificial intelligence in teaching. Regarding knowledge of AI, the statement "I strive to develop my knowledge about artificial intelligence and its applications in various fields" received the highest mean score of 4.14 with a standard deviation of 0.808, showing a strong commitment to learning about AI. In terms of using AI in teaching music skills, the statement "I intend to use artificial intelligence technologies in the future" ranked highest with a mean score of 4.24 and a standard deviation of 0.761, reflecting a positive intention to integrate AI into their future teaching practices. However, when it came to challenges, the statement "Lack of specialized training in artificial intelligence for music skills teachers" emerged as the most significant barrier, with the highest mean of 4.26 and a standard deviation of 0.782, pointing to the lack of adequate training as the primary obstacle in AI adoption for teaching music skills.
 
Conclusion: The study concludes that music skills teachers in Oman generally have positive attitudes toward the use of AI in teaching. However, the main challenge identified was the lack of specialized training for teachers, which hinders the effective implementation of AI in music education.
 
Research Implications: This research highlights the need for better training and resources for teachers to effectively incorporate AI in their teaching practices. It also emphasizes the importance of curriculum updates to align with AI advancements.
 
Originality/Value: This study provides valuable insights into the perspectives of music skills teachers in Oman on the integration of AI in teaching, contributing to the growing body of research on AI in education in the Middle East.
Contributions: The study contributes to the understanding of the role of AI in music education, specifically in Oman, and identifies key barriers that must be addressed for effective integration.