CSME 2023 Abstracts


Area 1 - Computer Supported Music Education

Full Papers
Paper Nr: 6
Title:

A Music Programming Course for Undergraduate Music Conservatory Students: Evaluation and Lessons Learnt

Authors:

Marcella Mandanici and Simone Spagnol

Abstract: This paper introduces the content and organisation of a music programming course offered to undergraduate Conservatory students in the spring of 2022. A number of evaluation procedures, including pre- and post-course questionnaires and exercises, and a final assignment have been administered by the teacher. Results indicate an increased confidence in the use of computers and programming, although some aspects of creativity and computational thinking need further revision. The authors examine the course content in light of the results obtained, discuss the followed approach, and make assumptions for the improvement of both course content and assessment methods.
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Paper Nr: 8
Title:

A Mobile Serious Game to Foster Music Sight Reading with Different Clefs

Authors:

Adriano Baratè, Andrea Brugaletta and Luca A. Ludovico

Abstract: This work introduces a mobile app that aims to promote the sight-reading of music with different positions of the clef on the stave. Relying on the principles of game-based learning, the app offers applications primarily in the didactic field: by facilitating and encouraging the learning of this challenging aspect of music, the app on one side contributes to the preservation of intangible musical heritage and, on the other, serves practical educational purposes such as the preparation for Conservatory exams. The results of early experimentation show a general appreciation by test users as it concerns engagement, but also highlight a number of interaction aspects to be improved.
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Short Papers
Paper Nr: 7
Title:

Interactive Generation of Musical Corpora for Piano Education: Opportunities and Open Challenges

Authors:

Filippo Carnovalini, Antonio Rodà and Geraint A. Wiggins

Abstract: Learning to play a musical instrument such as a piano requires many hours of exercises, generally taken from a “method” book. These books are collections of progressive exercises intended to teach specific techniques and address the commonest mistakes and difficulties that players face while learning. One downside of these books is that the exercises are not personalized to the students and thus cannot address specific difficulties and characteristics of each learner. Given the many recent advances in the field of music generation, we propose that it should be possible to generate exercises automatically to form a personalized method for each student. The teacher would describe the characteristics of the student and their strengths and weaknesses to a software system, as well as the teaching goals that should be covered in the generated exercises, and the system would create exercises that are specific to the needs of the student and the concerns of the teacher, allowing for a more effective and engaging learning experience. In this paper, we describe a project trying to design such a system, stating research questions, describing the tentative methodology, and outlining its potential impact for both research in music generation and in computer-supported education.
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