ABSTRACT As artificial intelligence (AI) and digital technologies continue to advance, their integration into higher music education reshapes traditional pedagogical approaches, particularly in sight‐singing and aural training, core components of musicianship. This systematic review examines empirical studies that explore the application, effectiveness and pedagogical integration of AI and digital tools to enhance these skills in higher education contexts. Following PRISMA guidelines, the review synthesises findings from diverse methodological approaches, ranging from quasi‐experimental designs to case studies. It highlights both AI‐powered platforms, such as intelligent tutoring systems and adaptive learning environments, and non‐AI digital tools, such as EarMaster and MIDI‐based systems. Results indicate that interactive and adaptive technologies significantly enhance pitch perception, rhythmic accuracy and melodic dictation when integrated within constructivist and blended learning models. However, critical limitations persist, including accessibility disparities, insufficient teacher training and the limited transparency of AI algorithms. The review identifies key gaps in longitudinal research, expressive skill development and cross‐cultural applicability. Findings aim to inform future curriculum design, policy development and innovation in AI‐assisted music pedagogy, supporting more inclusive, adaptive and pedagogically grounded approaches to aural and sight‐singing instruction.
Chen et al. (2026) studied this question.