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<p>Blended teaching combines the advantages of online teaching and offline teaching, which breaks the limitation of time and space to a certain extent and is of great significance to helping learners improve their learning efficiency and teachers’ teaching level and quality. This paper firstly designs a blended teaching model for the background of Internet+ education and improves the functional design of each part of the model. Secondly, the extreme gradient prediction model of students’ academic level is proposed for the blended model, and a strong learner is formed by integrating multiple weak learners to correct the misclassification. Finally, the blended model of instruction is evaluated and analyzed. The model achieves an accurate prediction accuracy of 65% for MEDIUM students and 75% for PERFECT students, with an average prediction accuracy of 58.4%, which is more than 50%, and can predict students’ academic level situations more accurately. The functional indicators all scored 74.4, the efficiency indicators all scored 71.35, and the usability of the platform exceeded 70. The Internet+education platform’s professional-type English, the online and offline hybrid teaching model, can effectively improve learners’ learning efficiency, as well as improve teachers’ teaching standards and quality.</p>
</abstract>

Blended teaching combines the advantages of online teaching and offline teaching, which breaks the limitation of time and space to a certain extent and is of great significance to helping learners improve their learning efficiency and teachers’ teaching level and quality. This paper firstly designs a blended teaching model for the background of Internet+ education and improves the functional design of each part of the model. Secondly, the extreme gradient prediction model of students’ academic level is proposed for the blended model, and a strong learner is formed by integrating multiple weak learners to correct the misclassification. Finally, the blended model of instruction is evaluated and analyzed. The model achieves an accurate prediction accuracy of 65% for MEDIUM students and 75% for PERFECT students, with an average prediction accuracy of 58.4%, which is more than 50%, and can predict students’ academic level situations more accurately. The functional indicators all scored 74.4, the efficiency indicators all scored 71.35, and the usability of the platform exceeded 70. The Internet+education platform’s professional-type English, the online and offline hybrid teaching model, can effectively improve learners’ learning efficiency, as well as improve teachers’ teaching standards and quality.

A hybrid online and offline teaching model of professional English for Internet+ education platform

Applied Mathematics and Nonlinear Sciences

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

Blended teaching combines the advantages of online teaching and offline teaching, which breaks the limitation of time and space to a certain extent and is of...

A hybrid online and offline teaching model of professional English for Internet+ education platform

Published Online: Oct 04, 2023

Page range: -

Received: Dec 14, 2022

Accepted: Apr 14, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00473

Keywords
Learning efficiency indicator, Internet+education, Limit gradient enhancement model, Prediction accuracy, Functional indicator

© 2023 Lin Li, published by Sciendo

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

A hybrid online and offline teaching model of professional English for Internet+ education platform

Published Online: Oct 04, 2023

Page range: -

Received: Dec 14, 2022

Accepted: Apr 14, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00473

KeywordsLearning efficiency indicator, Internet+education, Limit gradient enhancement model, Prediction accuracy, Functional indicator

© 2023 Lin Li, published by Sciendo

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

Keywords
Learning efficiency indicator, Internet+education, Limit gradient enhancement model, Prediction accuracy, Functional indicator