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

<p>The traditional teaching mode can no longer meet the diversified needs of current students, so exploring effective teaching methods has become an important issue in education. Language education, particularly Japanese language teaching, is facing unprecedented challenges and opportunities due to globalization. The technique of multi-group structural modeling is used to explore the diversified and innovative practices of Japanese language teaching in this paper. The study analyzes the perceived differences between different groups of students in learning Japanese, and discusses the key factors that affect the effectiveness of learning Japanese. The study utilizes accurate survey data and incorporates teacher-student support, teaching conditions, teacher quality, and language atmosphere. These factors greatly influenced Japanese language learning outcomes, with teacher and student support being the most prominent factor, which explained 22% of the variance in learning outcomes. Structural equation modeling analysis further verified the positive influence of teaching conditions and teacher literacy on teaching satisfaction. The study verified the validity of multicluster structural modeling in the practice of Japanese language teaching innovation through the comparative experiments between the experimental class and the control class, in which the experimental class’s performance in Japanese intensive reading was higher than that of the control class after adopting the innovative teaching path. So, the diversified and creative practice of teaching Japanese based on the multicluster structural model improves students’ learning effectiveness and teaching satisfaction.</p>
</abstract>

The traditional teaching mode can no longer meet the diversified needs of current students, so exploring effective teaching methods has become an important issue in education. Language education, particularly Japanese language teaching, is facing unprecedented challenges and opportunities due to globalization. The technique of multi-group structural modeling is used to explore the diversified and innovative practices of Japanese language teaching in this paper. The study analyzes the perceived differences between different groups of students in learning Japanese, and discusses the key factors that affect the effectiveness of learning Japanese. The study utilizes accurate survey data and incorporates teacher-student support, teaching conditions, teacher quality, and language atmosphere. These factors greatly influenced Japanese language learning outcomes, with teacher and student support being the most prominent factor, which explained 22% of the variance in learning outcomes. Structural equation modeling analysis further verified the positive influence of teaching conditions and teacher literacy on teaching satisfaction. The study verified the validity of multicluster structural modeling in the practice of Japanese language teaching innovation through the comparative experiments between the experimental class and the control class, in which the experimental class’s performance in Japanese intensive reading was higher than that of the control class after adopting the innovative teaching path. So, the diversified and creative practice of teaching Japanese based on the multicluster structural model improves students’ learning effectiveness and teaching satisfaction.

Diversified and Innovative Practices of Japanese Language Teaching Based on Multi-Cohort Structural Modeling

Applied Mathematics and Nonlinear Sciences

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

The traditional teaching mode can no longer meet the diversified needs of current students, so exploring effective teaching methods has become an important...

Diversified and Innovative Practices of Japanese Language Teaching Based on Multi-Cohort Structural Modeling

Publié en ligne: 01 avr. 2024

Pages: -

Reçu: 02 févr. 2024

Accepté: 09 févr. 2024

DOI: https://doi.org/10.2478/amns-2024-0793

Mots clés
Multicluster structural modeling, Japanese language teaching, Diversified innovation, Learning outcomes

© 2024 Huiqin Tang, published by Sciendo

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

Diversified and Innovative Practices of Japanese Language Teaching Based on Multi-Cohort Structural Modeling

Publié en ligne: 01 avr. 2024

Pages: -

Reçu: 02 févr. 2024

Accepté: 09 févr. 2024

DOI: https://doi.org/10.2478/amns-2024-0793

Mots clésMulticluster structural modeling, Japanese language teaching, Diversified innovation, Learning outcomes

© 2024 Huiqin Tang, published by Sciendo

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

Mots clés
Multicluster structural modeling, Japanese language teaching, Diversified innovation, Learning outcomes