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<p>With the rapid development of artificial intelligence technology, its application in education has become increasingly widespread, especially in English teaching in colleges and universities. Using artificial intelligence technology to build an intelligent teaching mode can effectively improve the quality of teaching and students’ learning efficiency. The study adopts Bayesian algorithm and Bayesian-based learning tracking model (BKT and BF-BKT) as the main methods to optimize the teaching mode by analyzing learners’ mastery of knowledge points and behavioral performance. The results show that the maximum response time of the model is only 1038.59 milliseconds when the number of users is 120, proving the model’s efficiency in handling large-scale data. In addition, the intelligent teaching model positively impacted both teacher-student interaction and student learning ability. The teacher speech ratio decreased from 80.26% to 62.53%, and the students’ autonomy and participation increased significantly; the mean value of students’ learning ability in independent learning and critical thinking exceeded 4.00. The application of AI technology in teaching English in colleges and universities can significantly improve the quality of teaching and students’ learning effect.</p>
</abstract>

With the rapid development of artificial intelligence technology, its application in education has become increasingly widespread, especially in English teaching in colleges and universities. Using artificial intelligence technology to build an intelligent teaching mode can effectively improve the quality of teaching and students’ learning efficiency. The study adopts Bayesian algorithm and Bayesian-based learning tracking model (BKT and BF-BKT) as the main methods to optimize the teaching mode by analyzing learners’ mastery of knowledge points and behavioral performance. The results show that the maximum response time of the model is only 1038.59 milliseconds when the number of users is 120, proving the model’s efficiency in handling large-scale data. In addition, the intelligent teaching model positively impacted both teacher-student interaction and student learning ability. The teacher speech ratio decreased from 80.26% to 62.53%, and the students’ autonomy and participation increased significantly; the mean value of students’ learning ability in independent learning and critical thinking exceeded 4.00. The application of AI technology in teaching English in colleges and universities can significantly improve the quality of teaching and students’ learning effect.

Research on the Construction of English Intelligent Teaching Mode in Colleges and Universities Facilitated by Artificial Intelligence Technology

Applied Mathematics and Nonlinear Sciences

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

With the rapid development of artificial intelligence technology, its application in education has become increasingly widespread, especially in English...

Research on the Construction of English Intelligent Teaching Mode in Colleges and Universities Facilitated by Artificial Intelligence Technology

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 17. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0657

Schlüsselwörter
Artificial intelligence technology, College English teaching, Intelligent teaching mode, Bayesian algorithm

© 2024 Xiaoyan Huang, published by Sciendo

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

Research on the Construction of English Intelligent Teaching Mode in Colleges and Universities Facilitated by Artificial Intelligence Technology

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 17. Jan. 2024

Akzeptiert: 22. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0657

SchlüsselwörterArtificial intelligence technology, College English teaching, Intelligent teaching mode, Bayesian algorithm

© 2024 Xiaoyan Huang, published by Sciendo

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

Schlüsselwörter
Artificial intelligence technology, College English teaching, Intelligent teaching mode, Bayesian algorithm