Music software with a Machine Learning-based feedback system as an alternative for initial piano study in children

Abstract

As evidenced in the literature, music has accompanied the human being for millennia, in different situations, emotions, and activities. In addition, not only does it allow expressions of internal personal states and feelings, but it can also produce many positive effects on those who practice it. Various authors have explored these benefits that musical activity brings, mainly in children. They highlight positive aspects of learning music in different areas of knowledge, in school performance and even improvements in the IQ of infants. However, despite the large number of studies regarding the benefits of music in children and the different nascent teaching alternatives, in Colombia the situation continues to be dramatic in terms of the incorporation of musical activity in the school curriculum. The foregoing added to political factors, teaching spaces and teacher training. In this way, the present work offers a new musical learning alternative, aimed at children from 7 to 11 years old, through musical software focused on the initial teaching of the instrumental keyboard. It is important to mention that the software has a feedback system based on decision trees, which allows reinforcing the topics covered in the application. Finally, a comparative analysis is presented between teaching using the software and traditional teaching with the book, through an Investigation-Action carried out over six days with two students from a public school in the city of Bogotá, Colombia. This investigation action allowed us to observe positive results based on the comments and performance of the participants, which opens a great possibility for the subsequent scaling of this application.