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<p>The assessment of intercultural communicative competence (ICC) is increasingly recognized as a critical component of students’ professional competency development in higher education settings. This paper explores the objectives of cultivating ICC and proposes an assessment scheme aligned with the principles of competency cultivation and the ICC acquisition model. To elucidate the linkage between teaching activities and ICC development, the Apriori algorithm is employed to analyze their relationships and to construct a weight matrix for these activities. Further, the Sim Rank algorithm is applied to determine similarities among students, while the K-means algorithm is used to cluster students into distinct groups. The assessment system’s feasibility is validated by analyzing the variations in assessment outcomes. This study also conducts a detailed graphical analysis of students’ attitudes towards ICC and examines the influence of five dimensions of English language proficiency—listening, speaking, reading, writing, and translating—on ICC. The results reveal a strong correlation between the three ICC dimensions—attitude, knowledge, and skill—with the overall ICC level. These dimensions are ranked in terms of correlation strength as follows: knowledge (0.963), skill (0.881), and attitude (0.758). Additionally, a positive correlation exists between the five facets of English language proficiency and cross-cultural variables, suggesting that learning English and cultivating ICC are mutually reinforcing. This underscores the need to enhance English language instruction to effectively support the development of ICC.</p>
</abstract>

The assessment of intercultural communicative competence (ICC) is increasingly recognized as a critical component of students’ professional competency development in higher education settings. This paper explores the objectives of cultivating ICC and proposes an assessment scheme aligned with the principles of competency cultivation and the ICC acquisition model. To elucidate the linkage between teaching activities and ICC development, the Apriori algorithm is employed to analyze their relationships and to construct a weight matrix for these activities. Further, the Sim Rank algorithm is applied to determine similarities among students, while the K-means algorithm is used to cluster students into distinct groups. The assessment system’s feasibility is validated by analyzing the variations in assessment outcomes. This study also conducts a detailed graphical analysis of students’ attitudes towards ICC and examines the influence of five dimensions of English language proficiency—listening, speaking, reading, writing, and translating—on ICC. The results reveal a strong correlation between the three ICC dimensions—attitude, knowledge, and skill—with the overall ICC level. These dimensions are ranked in terms of correlation strength as follows: knowledge (0.963), skill (0.881), and attitude (0.758). Additionally, a positive correlation exists between the five facets of English language proficiency and cross-cultural variables, suggesting that learning English and cultivating ICC are mutually reinforcing. This underscores the need to enhance English language instruction to effectively support the development of ICC.

Cultivation of Intercultural Communication Competence of English Teacher Training Students in Colleges and Universities in Ethnic Areas under the Background of Deep Learning

Applied Mathematics and Nonlinear Sciences

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

The assessment of intercultural communicative competence (ICC) is increasingly recognized as a critical component of students’ professional competency...

Cultivation of Intercultural Communication Competence of English Teacher Training Students in Colleges and Universities in Ethnic Areas under the Background of Deep Learning

Publié en ligne: 05 août 2024

Pages: -

Reçu: 03 avr. 2024

Accepté: 27 juin 2024

DOI: https://doi.org/10.2478/amns-2024-1980

Mots clés
Sim Rank algorithm, Weight matrix, Cluster analysis, Correlation analysis, Intercultural communication competence

© 2024 Doumei Zhong, published by Sciendo

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

Cultivation of Intercultural Communication Competence of English Teacher Training Students in Colleges and Universities in Ethnic Areas under the Background of Deep Learning

Publié en ligne: 05 août 2024

Pages: -

Reçu: 03 avr. 2024

Accepté: 27 juin 2024

DOI: https://doi.org/10.2478/amns-2024-1980

Mots clésSim Rank algorithm, Weight matrix, Cluster analysis, Correlation analysis, Intercultural communication competence

© 2024 Doumei Zhong, published by Sciendo

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

Mots clés
Sim Rank algorithm, Weight matrix, Cluster analysis, Correlation analysis, Intercultural communication competence