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Titlebook: Learning and Teaching in the Music Studio; A Student-Centred Ap Juan Ignacio Pozo,María Puy Pérez Echeverría,José Book 2022 The Editor(s)

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書(shū)目名稱(chēng)Learning and Teaching in the Music Studio
副標(biāo)題A Student-Centred Ap
編輯Juan Ignacio Pozo,María Puy Pérez Echeverría,José
視頻videohttp://file.papertrans.cn/583/582916/582916.mp4
概述This book advocates for a radical change in music teaching and learning methods.Argues for the need for pedagogical change in music instruction settings.Illustrates concepts through theoretical approa
叢書(shū)名稱(chēng)Landscapes: the Arts, Aesthetics, and Education
圖書(shū)封面Titlebook: Learning and Teaching in the Music Studio; A Student-Centred Ap Juan Ignacio Pozo,María Puy Pérez Echeverría,José  Book 2022 The Editor(s)
描述This book advocates for a radical change in music teaching and learning methods, allowing for a break from the traditional conservatory model still in use in many classrooms. The product of twenty years of interdisciplinary work by musicians, music teachers, and psychologists, the book proposes to place the focus of music education on the students themselves and on their mental and physical activity, with the aim of helping them to manage their own goals and emotions. This alternative is based on a new theoretical framework, as well as numerous real, concrete examples of how to put it into practice with students of different ages and in different environments. This book focuses primarily on teaching instrumental music, but its content will be useful for any teacher, student, musician, or researcher interested in improving music education in any environment, whether formal or informal, in which it takes place.Chapters 3, 4, 6 and 18 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..
出版日期Book 2022
關(guān)鍵詞student-centred learning; instrumental pedagogy; educational psychology of music; constructivism and co
版次1
doihttps://doi.org/10.1007/978-981-19-0634-3
isbn_softcover978-981-19-0636-7
isbn_ebook978-981-19-0634-3Series ISSN 1573-4528 Series E-ISSN 2214-0069
issn_series 1573-4528
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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1573-4528 education in any environment, whether formal or informal, in which it takes place.Chapters 3, 4, 6 and 18 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..978-981-19-0636-7978-981-19-0634-3Series ISSN 1573-4528 Series E-ISSN 2214-0069
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José Antonio Torrado,María Puy Pérez Echeverría,Juan Ignacio Pozo
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MSE, RMSE and MAE. Our work shows that the model generated by XGBRegressor is the most efficient in our case while Random Forest is the least efficient. As future work, we aim to apply the proposed process to test the performance of other regression algorithms and to test the impact of using deep l
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