National Ballad Creation Education Under Artificial Intelligence and Big Data

Area of Science:

• Music Education
• Artificial Intelligence
• Computational Musicology

Background:

• Traditional ballad creation education faces challenges in efficiency and requires improvement.
• Enhancing students' creative abilities is crucial for preserving and developing China's unique ballad culture.

Purpose of the Study:

• To investigate methods for upgrading student creative levels in ballad composition.
• To explore the integration of music theory, big data analytics, and AI in music education.

Main Methods:

• Developed an optical music recognition (OMR) method using artificial intelligence (AI) and style imitation learning.
• Applied the AI-based system to a school curriculum for ballad creation education.
• Conducted comparative experiments to evaluate the novelty of AI-generated ballads and student outcomes.

Main Results:

• AI-generated ballads demonstrated slightly superior novelty compared to imitation templates.
• Students using the AI system showed significantly improved learning interest.
• Comparative experiments revealed enhanced creative performance in oral language among students.

Conclusions:

• The proposed AI system is suitable for ballad creation courses, offering a novel approach to music education.
• This research provides a foundation for AI-driven music creation and its application in educational settings.