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<p>The significance of interactive pedagogy in English education cannot be overstated, as it fosters student engagement, collaboration, and active learning, thereby enhancing both academic performance and comprehensive capabilities. This article presents a structured three-step strategy designed to integrate curriculum thinking into the teaching of English at higher vocational levels through a blended online and offline approach. Central to this methodology is the development of a robust “online + offline” teaching quality evaluation index system, innovatively constructed using a combination of rough set theory and a backpropagation (BP) neural network algorithm. Furthermore, the effectiveness of this pedagogical approach is quantitatively analyzed using a Markov chain model, which evaluates the progression of students’ English proficiency. The analysis reveals that sustained application of the proposed teaching methodology is likely to elevate students’ English performance to an estimated score of 84.273, marking a substantial improvement of 5.443 points over traditional methods. Empirical validation of the model’s effectiveness was achieved through student evaluations across three critical areas: Civic Integration Effectiveness, Pre-Class Preview, and Follow-Up Testing. The results of the post-test assessments yielded mean scores of 3.565, 3.564, and 3.695, respectively, indicating a significant enhancement in learning outcomes, as evidenced by p-values of less than 0.05. This statistical analysis confirms the significant impact of the innovative pedagogical strategy on student learning outcomes.</p>
</abstract>

The significance of interactive pedagogy in English education cannot be overstated, as it fosters student engagement, collaboration, and active learning, thereby enhancing both academic performance and comprehensive capabilities. This article presents a structured three-step strategy designed to integrate curriculum thinking into the teaching of English at higher vocational levels through a blended online and offline approach. Central to this methodology is the development of a robust “online + offline” teaching quality evaluation index system, innovatively constructed using a combination of rough set theory and a backpropagation (BP) neural network algorithm. Furthermore, the effectiveness of this pedagogical approach is quantitatively analyzed using a Markov chain model, which evaluates the progression of students’ English proficiency. The analysis reveals that sustained application of the proposed teaching methodology is likely to elevate students’ English performance to an estimated score of 84.273, marking a substantial improvement of 5.443 points over traditional methods. Empirical validation of the model’s effectiveness was achieved through student evaluations across three critical areas: Civic Integration Effectiveness, Pre-Class Preview, and Follow-Up Testing. The results of the post-test assessments yielded mean scores of 3.565, 3.564, and 3.695, respectively, indicating a significant enhancement in learning outcomes, as evidenced by p-values of less than 0.05. This statistical analysis confirms the significant impact of the innovative pedagogical strategy on student learning outcomes.

Focusing on “Online + Offline” Interaction, Exploring the Civic and Political Construction of Public English Courses in Higher Vocational Colleges and Universities

Applied Mathematics and Nonlinear Sciences

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

The significance of interactive pedagogy in English education cannot be overstated, as it fosters student engagement, collaboration, and active learning,...

Focusing on “Online + Offline” Interaction, Exploring the Civic and Political Construction of Public English Courses in Higher Vocational Colleges and Universities

Publié en ligne: 05 août 2024

Pages: -

Reçu: 14 avr. 2024

Accepté: 05 juil. 2024

DOI: https://doi.org/10.2478/amns-2024-1990

Mots clés
Rough set, BP neural network, Markov chain, Teaching quality evaluation

© 2024 Tingting He et al., published by Sciendo

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

Focusing on “Online + Offline” Interaction, Exploring the Civic and Political Construction of Public English Courses in Higher Vocational Colleges and Universities

Publié en ligne: 05 août 2024

Pages: -

Reçu: 14 avr. 2024

Accepté: 05 juil. 2024

DOI: https://doi.org/10.2478/amns-2024-1990

Mots clésRough set, BP neural network, Markov chain, Teaching quality evaluation

© 2024 Tingting He et al., published by Sciendo

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

Mots clés
Rough set, BP neural network, Markov chain, Teaching quality evaluation