<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In advancing quality education, there is a pressing necessity to equip students in higher education with global perspectives and skills in intercultural communication. This study leverages the TSPCK knowledge transformation model to deliver an extensive exploration and application in the realms of goal orientation, content structuring, foundational learning, strategy deployment, and the execution of assessments within the framework of multicultural music education. The adaptive learning system’s learner model is meticulously crafted by assessing learners’ preliminary knowledge, evaluating their challenges with music knowledge, and estimating their overall knowledge proficiency, with validation conducted across six distinct datasets. Multicultural elements in college music education are strategically utilized to investigate their influence on students’ aesthetic interests and musical literacy. Empirical results indicate a residual mean score of 2.0501 for music aesthetic literacy within a multicultural context, suggesting that exposure to multicultural music education broadens students’ perspectives significantly. Furthermore, this educational approach encourages students to cultivate a deeper appreciation and respect for the nuances and commonalities across various cultures. Enhancing the quality of music education in tertiary institutions and promoting a profound understanding and proficiency in diverse music cultures are identified as pivotal elements in achieving these educational outcomes.</p>
</abstract>

In advancing quality education, there is a pressing necessity to equip students in higher education with global perspectives and skills in intercultural communication. This study leverages the TSPCK knowledge transformation model to deliver an extensive exploration and application in the realms of goal orientation, content structuring, foundational learning, strategy deployment, and the execution of assessments within the framework of multicultural music education. The adaptive learning system’s learner model is meticulously crafted by assessing learners’ preliminary knowledge, evaluating their challenges with music knowledge, and estimating their overall knowledge proficiency, with validation conducted across six distinct datasets. Multicultural elements in college music education are strategically utilized to investigate their influence on students’ aesthetic interests and musical literacy. Empirical results indicate a residual mean score of 2.0501 for music aesthetic literacy within a multicultural context, suggesting that exposure to multicultural music education broadens students’ perspectives significantly. Furthermore, this educational approach encourages students to cultivate a deeper appreciation and respect for the nuances and commonalities across various cultures. Enhancing the quality of music education in tertiary institutions and promoting a profound understanding and proficiency in diverse music cultures are identified as pivotal elements in achieving these educational outcomes.

The Application of Multiple Music Cultures in College Music Teaching in the Background of Internet

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In advancing quality education, there is a pressing necessity to equip students in higher education with global perspectives and skills in intercultural...

The Application of Multiple Music Cultures in College Music Teaching in the Background of Internet

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 14 abr 2024

Aceptado: 08 jul 2024

DOI: https://doi.org/10.2478/amns-2024-2000

Palabras clave
Knowledge transformation, Knowledge level estimation, Adaptive learning, Learner modeling, Multi-cultural music

© 2024 Hongsheng Ren et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Application of Multiple Music Cultures in College Music Teaching in the Background of Internet

Publicado en línea: 05 ago 2024

Páginas: -

Recibido: 14 abr 2024

Aceptado: 08 jul 2024

DOI: https://doi.org/10.2478/amns-2024-2000

Palabras claveKnowledge transformation, Knowledge level estimation, Adaptive learning, Learner modeling, Multi-cultural music

© 2024 Hongsheng Ren et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
Knowledge transformation, Knowledge level estimation, Adaptive learning, Learner modeling, Multi-cultural music