Music Technology for STEAM Education

Abstract:

The educational movement of STEAM is about bringing Arts at the heart of the academic curriculum in order to cultivate creative skills of young people, alongside with the knowledge and skills they acquire in STEM fields (i.e. Science, Technology, Engineering and Mathematics). As a STEAM-oriented solution, the iMuSciCA project (Interactive Music Science Collaborative Activities) presents an interdisciplinary pedagogy framework that connects different disciplines with each other on an inquiry and collaborative manner. It directly addresses the current requirements in education and learning for new pedagogical methodologies and innovative educational technology tools by supporting active, discovery-based, personalized and more engaging learning, while providing students and teachers with opportunities for collaboration, co-creation and collective knowledge building. iMuSciCA offers a suite of software tools and services mostly related to music which are built on top of new enabling technologies, and are integrated on a web-based platform that delivers interactive music activities to secondary school students with the aim to support mastery of core academic content on STEM subjects (Physics, Geometry, Mathematics, and Technology). Enabling technologies, including interactive pen on touchpad, 3D object design and printing, as well as new multimodal interfaces that combine advanced music generation and processing, are deployed in order to implement a web-based workbench aiming at STEAM learning. The contribution of the Institute for Language and Speech Processing in the iMuSciCA project involves the development of methods for interacting with virtual music instruments using camera sensors, the development of advanced real-time visualization tools for music analysis, the deployment of algorithmic composition methods for enhancing music creativity as well as applying conventional Music Information Retrieval techniques in the context of a STEAM education platform.

Biographies:

Dr. Aggelos Gkiokas is a Postdoctoral Research Associate at the Institute for Language and Speech Processing of Athena Research and Innovation Center (ILSP/ATHENA RIC). He holds a PhD Degree in Music Information Retrieval and his main research interests are automatic music rhythm analysis, music similarity, audio visualization. 

Kosmas Kritsis is a Research Associate at the Institute for Language and Speech Processing of Athena Research and Innovation Center (ILSP/ATHENA RIC). He is a PhD Candidate at the department of Informatics of the University of Piraeus (UniPi) and holds a MSc in Sound & Music Computing from Pompeu Fabra University of Barcelona (UPF). His academic experience and research interest includes scientific areas, such as Human-Computer Interaction, Audio Signal Processing, Computer Vision and Machine Learning.