| Since the beginning of the 21st century,countries around the world have been working on transformative solutions to achieve deep learning and exploring what kind of talents to cultivate for the new century.On this basis,China has put forward the core literacy for student development in China as well as the core literacy for each subject,and has started to develop deep learning teaching improvement projects.Deep learning is an important vehicle for promoting student learning and developing core literacies,advocating unit learning and teaching units to help students achieve meaningful development.In this regard,based on the existing literature and focusing on the subject of music,the author uses questionnaires,interviews and case studies to carry out research,proposes a deep learning-based high school music unit teaching design and explores the process of applying deep learning concepts to high school music unit teaching.Firstly,through literature reading,the current situation and trends of research on deep learning and unit teaching at home and abroad are sorted out,research insights are gained,and the necessity of this study is argued.At the same time,focusing on the subject of music,the connotation,characteristics and significance of deep learning in music are clarified.Secondly,questionnaires and interviews were used to understand the current status of in-depth learning and teaching of music in senior secondary schools.The survey found that students’ intrinsic motivation and interest in music learning were predominant,but the level of engagement in learning needed to be improved;their performance in applying and evaluating music knowledge was fair,but not optimistic overall;their ability to integrate music performance and information needed to be strengthened;and the overall effect of music learning was more desirable and positive.Teachers are generally unfamiliar with deep learning and familiar with unit teaching but need to go deeper;they agree with and support the use of unit teaching to promote deep learning in music;there are individual differences in how deep teaching is done in actual classrooms.The above situation illustrates the necessity and applicability of this study and provides a realistic basis for the subsequent research.Finally,based on theoretical analysis and investigation of the current situation,the author combines the ADDIE model and the Deep Learning Teaching Improvement Practice Model 2.0,and constructs a model of teaching design for a high school music unit in the context of deep learning,with the five key steps of "determining the unit learning theme,determining the unit learning objectives,determining the unit learning activities,selecting teaching strategies and designing evaluation schemes " The five key steps are: identifying the learning topic of the unit,determining the learning objectives of the unit,defining the learning activities of the unit,selecting teaching strategies and designing assessment schemes.At the same time,this study uses the Han folk songs unit in the senior secondary music appreciation module as a model and designs a unit teaching case of "Han folk songs-genre and colour zone".Through practice,it was found that this model could facilitate students’ in-depth learning of music to a certain extent.Based on this,the author proposes five suggestions for implementing this model: "pay attention to the integrated design of the unit and the integration of subjects;pay attention to the aesthetic practice of music and the setting of key questions;pay attention to the selection of music works and materials and the accumulation of a library of songs;encourage and guide students to participate in musical expression;pay attention to students’ feedback in class and reflect diligently on continuous improvement".The aim is to provide more references for the use of this model.This study is expected to provide reference for frontline music teachers in both theory and practice,but the research is still in its infancy,and the model and practice of high school music unit teaching design in the deep learning perspective needs further research and improvement. |