Toward Piano Teaching Evaluation Based on Neural Network

With the rise of piano teaching in recent years, many people participated in the team of learning steel playing. However, expensive piano teaching fees and its unique one-to-one teaching model have caused piano education resources to be very short, so learning piano performance has become a very extravagant event. The factors affecting music performance are varying, and there are many types of their evaluation such as rhythm, expressiveness, music, and style grasp. The computer is used to simulate this evaluation process to essentially identify the mathematical relationship between factors affecting music performance and evaluation indicators. The use of computer multimedia software for piano teaching has become a feasible way to alleviate the contradiction. This paper discusses the implementation method of piano teaching software, the issues of computer piano teaching, the computer teaching as one-way knowledge, and the lack of interaction. The neural network (NN) model is used to evaluate the piano performance and simulate teachers to guide students through their exercise. The performance of the proposed system is tested for the piano music of “Ode to Joy,” which is different from the collection of NN training samples, and is delivered ten times by another piano teacher, student A (piano level 6), and student B (piano level 5).

An Examination of Conservatory Students’ Piano Lesson Self-Efficiency and Computer Literacy: The Case of Trabzon University State Conservatory

In this study, the self-efficacy of conservatory students was determined in piano lessons. The piano lesson self-efficacy scale developed by Kurtuldu (2017) was used. The scale was applied to 55 students studying at the Musicology and Music Theory departments at Trabzon University State Conservatory in the academic year of 2020-2021. The result of this research revealed that significant differences were found only at the grade level between the piano lesson self-efficacy of the conservatory students. There was no significant difference in variables such as gender, the program attended at the conservatory, the type of high school graduated, the status of receiving piano education before undergraduate education, and the presence of a piano at the students’ houses. As a result, several suggestions were put forward by evaluating the emerging differences in the context of computer literacy and distance education.

SOME PROBLEMS OF CHINESE PROFESSIONAL PIANO EDUCATION ON THE EXAMPLE OF ALL 3 CATEGORIES OF CHINESE UNIVERSITIES

В статье с целью выявления комплекса проблем, ограничивающих дальнейшее развитие китайского пианизма, предложен анализ китайских музыкальных вузов, готовящих профессиональных пианистов. Делается вывод о наличии общих для всех 3-х категорий вузов проблем, не смотря на различие целей и средств обучения будущих специалистов. In order to find a set of problems limiting the further development of Chinese pianism, the article offers an analysis of Chinese music universities that train professional pianists. It is concluded that there are problems common to all 3 categories of universities, despite the difference in goals and means of training future specialists.

Pedagogical Analysis of the Baroque Period Piano Repertoire: Example of Italy

The aim of this study is to access editions of Italian Baroque works in place; to examine the availability of these works in terms of gaining techniques for playing in piano education, to gain new works aimed at different pedagogical stages in the field and to acquire new but unknown works in piano education repertoire. This research was carried out with the literature review model. During the first three months of the research, 158 baroque period composers were found among 2173 Italian composers. 50 composers composing on keyboard instruments were reached among 158 baroque composers. For this research study, the library of Dipartimento delle Arti dell’Universita di Bologna the Sala Borsa library, the Giovanni Martini Conservatory library and international museum and library of music in Bologna were visited and the works of composers made on the keyboard instruments were found. The number of works performed by composer on keyboard instruments is quite high. However, according to the objective of the project, it is aimed to perform pedagogical analysis by selecting one work from each composer. For analysis, created to the work evaluation forms prepared by the researcher. 50 works analyzed according to this form. While 48 Italian works can be used in piano education, 6 Italian works are not suitable for piano education. However, in order to use these works in piano education, these must be arranged from organ to pianoforte. An example of this is presented in this study.

Piano Education of Children Using Musical Instrument Recognition and Deep Learning Technologies Under the Educational Psychology

The objective of the study was to enhance quality education in the traditional pre-school piano education. Deep Learning (DL) technology is applied to piano education of children to improve their interest in learning music. Firstly, the problems of the traditional piano education of children were analyzed with the teaching patterns discussed under educational psychology, and a targeted music education plan was established. Secondly, musical instrument recognition technology was introduced, and the musical instrument recognition model was implemented based on DL. Thirdly, the proposed model was applied to the piano education of children to guide the music learning of students and improve their interest in piano learning. The feature recognition and acquisition of the proposed model were improved. Finally, the different teaching patterns were comparatively analyzed through the Questionnaire Survey (QS). The experimental results showed that the instrument recognition accuracy of Hybrid Neural Network (HNN) is 97.2%, and with the increase of iterations, the recognition error rate of the model decreases and stabilizes. Therefore, the proposed HNN based on DL for musical instrument recognition can accurately identify musical features. The QS results showed that the introduction of musical instrument recognition technology in the piano education of children can improve their interest in piano learning. Therefore, the establishment of the piano education patterns based on the piano education model can improve the effectiveness of teaching piano to students. This research provides a reference for the intelligentization of children's piano education.