This presentation introduces an innovative approach to early childhood music education through Sound Art, highlighting its potential to foster musical creativity in young children. It will explore Murray Schafer’s concept of the soundscape, inviting educators to understand the acoustic environment as a pedagogical resource that nurtures active listening, imagination, and sonic experimentation. The session will also examine the use of non-conventional graphic representations—including lines, symbols, and sound maps—as tools that allow children to express musical ideas beyond traditional notation, expanding their creative possibilities. Furthermore, the talk will outline the unique benefits of Sound Art compared to other musical practices in supporting creativity, such as its accessibility, its emphasis on sensory exploration, and the freedom it offers for manipulating diverse sound materials without technical constraints.

In this lecture, we will take a closer look at performance anxiety. What causes it? Are there people who are more prone to performance anxiety? And is having performance anxiety and being a professional musician mutually exclusive? We will try to find answers to all of these questions and more based on studies in music psychology, and discover different treatment methods recommended by researchers.

This presentation examines the transformative potential of Music Education 4.0 within a post-digital, anthropocentric framework. Instead of perceiving technology as the primary catalyst of change, the framework regards emerging and immersive tools as resources that enhance human agency, musical meaning-making, and culturally and socially grounded learning. From this perspective, Music Education 4.0 revisits traditional pedagogical approaches through immersive, interactive, and reflective learning experiences, aligned with STREAM strategies that promote cross-disciplinary thinking and the development of communication, creativity, and critical judgment. Music Education 4.0 establishes a foundational framework for an extended, adaptable learning ecology in which learners engage with music through embodied participation and iterative experimentation. Students investigate digital music production to compose, remix, and refine musical ideas, while maker-oriented practices encourage hands-on building, prototyping, and redesign of instruments and sound artifacts, thereby enhancing creativity and problem-solving skills. Programming and immersive environments, such as virtual reality (VR) and augmented reality (AR), can further enhance spatial, musical, and conceptual comprehension through situated exploration and interactive scenarios. Concurrently, AI-enabled tools—ranging from generative music systems to personalized assistants—provide timely and responsive feedback and scaffolding, supporting differentiated learning pathways while emphasizing questions of authorship, accountability, and ethical use that are integral to post-digital educational contexts. Participants will explore current developments in the fields of Music, Technology, and Education through the analysis of real-world and authentic case studies and recent research findings. This consideration includes how post-digital conditions influence both opportunities and challenges in music teacher training. The session further highlights how STREAM strategies can effectively integrate arts and sciences, allowing educators to create comprehensive, context-aware learning experiences that are explicitly centered on human values, critically informed, and adaptable to the swiftly changing musical and technological environments.

How do we make sense of music, and how can this process be described, analysed, or modelled computationally? This talk presents a conceptual trajectory from traditional music-theoretical approaches to contemporary computational and cognitive perspectives on music. Beginning with core analytical notions such as structure, repetition, pattern, expectation, and musical meaning, it examines how these concepts can be reformulated as formal representations, algorithms, and data-driven models. The talk addresses key questions at the intersection of music theory, musicology, artificial intelligence, and cognitive science: what constitutes a musical pattern, how listeners segment and organise musical streams, and what is gained or lost when musical understanding is translated into computational terms. Through selected examples from symbolic music analysis, it illustrates how computational models can formalise theoretical concepts and critically inform established analytical practices, highlighting computation as a complementary framework that promotes explicitness, enables large-scale analysis, and supports new perspectives on musical knowledge.