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Does AI ‐assisted creation of polyphonic music increase academic motivation? The DeepBach graphical model and its use in music education
11 references·0 citing·44 second hop
Does AI ‐assisted creation of polyphonic music increase academic motivation? The DeepBach graphical model and its use in music education (2024)Does AI ‐assisted creation of polyphonic …THE EFFECT OF TEACHER COMMUNICATION ABILITY AND LEARNING MOTIVATION ON STUDENT LEARNING OUTCOMES IN ECONOMIC LESSONS FOR CLASS XI IPS SMA EKASAKTI IN PADANG ACADEMIC YEAR 2015/2016 (2022)THE EFFECT OF TEACHER COMMUNI…Communication and Learning Revisited (2021)Communication and Learning Re…Music Learning Today (2020)Music Learning TodayEmotion-based AI Music Generation System with CVAE-GAN (2020)Emotion-based AI Music Genera…Challenges and Future Directions of Big Data and Artificial Intelligence in Education (2020)Challenges and Future Directi…Artificial intelligence methods for music generation: a review and future perspectives (2020)Artificial intelligence metho…Technology Use and Attitudes in Music Learning (2019)Technology Use and Attitudes …On the Crossroad of Artificial Intelligence: A Revisit to Alan Turing and Norbert Wiener (2018)On the Crossroad of Artificia…A Postdigital Future for Music Education: Definitions, Implications, and Questions (2018)A Postdigital Future for Musi…Self-determination theory applied to flow in conservatoire music practice: The roles of perceived autonomy and competence, and autonomous and controlled motivation (2017)Self-determination theory app…Psychological needs satisfaction and value in students’ intentions to study music in high school (2017)Psychological needs satisfact…Flow: The Psychology of Optimal Experience (1991)Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions (2000)The "What" and "Why" of Goal Pursuits: Human Needs and the Self-Determination of Behavior (2000)Psychological Needs and Motivational Outcomes in a High School Orchestra Program (2018)Motivation to pursue a career in music: The role of social constraints in university music programs (2019)Using Self-Determination Theory to Examine Musical Participation and Well-Being (2019)Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. 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(1980)THE DICTIONARY OF AFFECT IN LANGUAGE (1989)EmoMusicTV: Emotion-Conditioned Symbolic Music Generation With Hierarchical Transformer VAE (2023)Prosedur Penelitian Suatu Pendekatan Praktik (2006)Metode Penelitian Pendidikan (2008)Belajar dan Faktor faktor yang Mempengaruhinya (2015)Children's Talk and the Development of Reasoning in the Classroom (1999)Explaining the dialogic processes of teaching and learning: The value and potential of sociocultural theory (2012)Exploring Engagement in Tasks in the Language Classroom (2016)Music education and distance learning during COVID-19: a survey (2021)The Well-being and Instructional Experiences of K-12 Music Educators: Starting a New School Year During a Pandemic (2021)A Music Teacher’s Blended Teaching and Learning Experience during COVID-19: Autoethnography of Resilience (2022)
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References

  • 2020Challenges and Future Directions of Big Data and Artificial Intelligence in Education764 cited
  • 2019Technology Use and Attitudes in Music Learning112 cited
  • 2017Self-determination theory applied to flow in conservatoire music practice: The roles of perceived autonomy and competence, and autonomous and controlled motivation94 cited
  • 2021Communication and Learning Revisited81 cited
  • 2017Psychological needs satisfaction and value in students’ intentions to study music in high school65 cited
  • 2020Music Learning Today59 cited
  • 2022THE EFFECT OF TEACHER COMMUNICATION ABILITY AND LEARNING MOTIVATION ON STUDENT LEARNING OUTCOMES IN ECONOMIC LESSONS FOR CLASS XI IPS SMA EKASAKTI IN PADANG ACADEMIC YEAR 2015/201645 cited
  • 2020Artificial intelligence methods for music generation: a review and future perspectives39 cited
  • 2020Emotion-based AI Music Generation System with CVAE-GAN37 cited
  • 2018On the Crossroad of Artificial Intelligence: A Revisit to Alan Turing and Norbert Wiener36 cited
  • 2018A Postdigital Future for Music Education: Definitions, Implications, and Questions34 cited

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