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Does AI‐assisted creation of polyphonic music increase academic motivation? The DeepBach graphical model and its use in music education.

Background: In the modern music industry, AI music generators have gained particular importance. The use of AI greatly simplifies the creation of polyphony. In addition, it can increase student motivation and interest. Aims: This study focuses on the AI‐assisted creation of polyphonic music. The pur...

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Publicado en:Journal of Computer Assisted Learning Vol. 40; no. 4; pp. 1365 - 1373
Autor principal: Yuan, Na
Formato: research tables/charts Journal Article
Publicado: Wiley-Blackwell Aug2024
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Aug2024
      vid: 40
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1111/jcal.12957
        178531891
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        atl: Does AI‐assisted creation of polyphonic music increase academic motivation? The DeepBach graphical model and its use in music education.
      aug:
        au: Yuan, Na
        affil: School of Music and Dance, Harbin University, Harbin, China
      sug:
        subj:
          Artificial Intelligence
          Music Education
          Motivation
          Digital Technology
          Graphics
          Students, College
          Human
          Male
          Female
          Control Group
          Learning Methods
          Outcomes of Education
          Independent Variable
          Multivariate Statistics
          T-Tests
          Data Analysis Software
          Descriptive Statistics
          Male
          Female
      ab: Background: In the modern music industry, AI music generators have gained particular importance. The use of AI greatly simplifies the creation of polyphony. In addition, it can increase student motivation and interest. Aims: This study focuses on the AI‐assisted creation of polyphonic music. The purpose of this study is to determine how creating polyphony through the Deep Bach model impacts the academic motivation of music university students. Materials & Methods: Achieving this goal is possible by conducting an experimental training program based on the use of the above‐mentioned model. Results: The results show that students in the experimental group have higher motivation than the control group participants. Therefore, AI‐based music creation has the potential to become a new trend in music education. Implications: The findings of this study can be useful for music education experts, providing empirical data on the effectiveness of AI in music education. The use of the data can ultimately improve the learning process. Future research can focus on developing alternative AI models as well as investigating their effectiveness in music education.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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