RETRACTED: The method of emotional education in music teaching

Hong, Ha; Luo, Weisheng

doi:10.1177/0020720920983559

Cited by 16 publications

(16 citation statements)

References 5 publications

(4 reference statements)

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“…e internal composition of knowledge is composed of three inseparable parts: symbolic representation, logical form, and meaning system. e understanding of knowledge should go beyond a single symbolic representation to the understanding of the subject thought and the meaning carried by symbolic knowledge [13][14][15]. Shallow learning only stays at the simple surface of the symbolic learning of knowledge, which is difficult to stimulate students' learning initiative, affect students' in-depth understanding of discipline ideas and methods, and the significance and value of discipline knowledge, and is not conducive to the development of students' high-order thinking ability [16,17].…”

Section: R E T R a C T E D R E T R A C T E D R E T R A C T E Dmentioning

confidence: 99%

Application of the Iot Network and the Deep Learning Concept in Music Teaching

Shuangling

Ya-fen

2022

Security and Communication Networks

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In order to realize students’ in-depth understanding of music teaching content, it is necessary to reasonably allocate teaching materials according to the teaching content. Therefore, this paper puts forward the application of the concept of the Iot network and deep learning in music teaching. After the teaching resources are vectorized, the distinguishing local registration method of the DLA model is used to extract their features. Based on the dimension of the teaching content, the features of the teaching content are output in the DLA model, the music teaching resources are allocated according to the minimum matching error criterion, the hyperbolic tangent function is taken as the activation function, and the feature error is filtered by maximum aggregation. The experimental results show that the design method can, according to the music teaching content, have more than 80% accuracy in the shallow distribution and deep distribution of teaching materials, and play a positive role in promoting students’ in-depth learning.

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Section: R E T R a C T E D R E T R A C T E D R E T R A C T E Dmentioning

confidence: 99%

Application of the Iot Network and the Deep Learning Concept in Music Teaching

Shuangling

Ya-fen

2022

Security and Communication Networks

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“…To achieve the unity of music features and advertising features, reference [ 2 ] investigates the relationship between the emotional characteristics of music and advertising effects; reference [ 3 ] suggests a method of music therapy for the emotional needs of the elderly. Reference [ 4 ] investigated how to convey individualised emotional traits through music instruction; Chowdhury et al [ 5 ] employed machine learning algorithms to foretell the emotional elements of musical compositions; and Hong and Luo [ 6 ] studied the ways that musical emotional characteristics are taught and talked about some typical ways that these musical characteristics are taught.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Analysis of Music Retrieval Based on Emotional Tags Environment

Bao

2022

Journal of Environmental and Public Health

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In general, tags are used to interpret the content of music, while the music itself expresses emotion. The emotional information conveyed by the same music is described by a large number of emotion tags in various ways. This paper proposes and establishes an algorithm for music retrieval based on emotional tags. By modelling user emotional tags and music, a bipartite graph with emotional tags and music as nodes is first created. The tags and semantic similarity between the music are then calculated using the T_SimRank algorithm, and the popularity of the music is calculated using the T_PageRank algorithm. Finally, the two methods are combined using the concept of ranking learning to produce the final ranking of the music. Experiments demonstrate that the method suggested in this paper can better satisfy user retrieval needs than conventional cosine similarity and tag co-occurrence-based similarity methods and that the fusion of multiple methods is preferable to a single method.

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“…Literature [17] suggests that there are music teachers who were asked to reflect on their teaching practices and compare their experiences in individual and collective teaching environments, noting that college music teachers are less present in collective settings. Literature [18] states that music teachers should be adept at utilizing appropriate teaching methods and approaches in the process of music teaching.…”

Section: Introductionmentioning

confidence: 99%

Vocal music curriculum design and teaching quality evaluation in colleges and universities based on interactive structure model

2024

Applied Mathematics and Nonlinear Sciences

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Aiming at the current phenomenon of low teacher-student interaction in vocal music teaching, this paper combines the interaction structure model for the innovation and practice of college vocal music courses. Then, this paper uses Euclidean distance to improve the binary tree SVM multi-class classification algorithm, calculates the distance between the teaching samples of each vocal music course, classifies the samples for processing, and obtains the DBT-SVM multi-class classification algorithm. Finally, the DBT-SVM algorithm was used to establish an evaluation model for vocal course teaching quality in colleges and universities to assess the quality of vocal course teaching models. Each three-level index of teaching motivationality has an evaluation score above 80, which is a good level. The evaluation score for the pedagogical index is 89.44, which is almost excellent. The average score of the second-level index of interpersonal interaction is 74.52, which needs to be further improved. The teaching model of the college vocal music course proposed in this paper lays the foundation for the interactive transformation of vocal music teaching and provides a reference model for the improvement of the learning effect of college students’ vocal music courses.

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RETRACTED: The method of emotional education in music teaching

Cited by 16 publications

References 5 publications

Application of the Iot Network and the Deep Learning Concept in Music Teaching

Application of the Iot Network and the Deep Learning Concept in Music Teaching

[Retracted] Analysis of Music Retrieval Based on Emotional Tags Environment

Vocal music curriculum design and teaching quality evaluation in colleges and universities based on interactive structure model

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