Author
Abstract
The integration of science, technology, engineering, and mathematics and education has accelerated due to the rapid growth of national information technology. Thanks to advancements in the internet of things technology, students can learn in a new way using mobile devices and online education platforms. Despite the fact that the internet of things is a science and technology, it can be used in education and teaching. This is especially true in English classes, where the internet of things can help pupils break free from the restrictions of traditional teaching. When teachers and students can instantly access information using internet of things technology, the English teaching process becomes more efficient. Learners can use mobile terminals for online learning and self-control learning steps, arrange learning time, and strengthen learning content based on their own shortcomings. The main contents of this work are as follows: (1) This study designs an internet of things-oriented online education platform for English language teaching, in order to provide a good learning environment and improve their comprehensive English strength. (2) This study offers a new BP network to assess the impact of an IoT-oriented online education platform on English language instruction. In order to improve the ability to search for the optimal solution, the grey wolf optimization (GWO) algorithm was first modified; then, the reverse learning (RL) mechanism was added to the grey wolf algorithm to develop the RLGWO algorithm. Using RLGWO to optimize BP and construct RLGWO-BP, the model is used to evaluate the improvement effect of the internet of things-oriented online education platform on English language teaching. The systematic experiment verifies the validity and reliability of this work.
Suggested Citation
Deyong Chen & Naeem Jan, 2022.
"Application of IoT-Oriented Online Education Platform in English Teaching,"
Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-9, June.
Handle:
RePEc:hin:jnlmpe:9606706
DOI: 10.1155/2022/9606706
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