Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence
This paper examines the application of artificial intelligence technology in business English teaching and artificial intelligence in natural language processing and recognition to receive good results. These two technologies are suitable for business English teaching innovation. At this time, the i...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns.2023.2.01628 |
| _version_ | 1797340484535844864 |
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| author | Liu Shengming |
| author_facet | Liu Shengming |
| author_sort | Liu Shengming |
| collection | DOAJ |
| description | This paper examines the application of artificial intelligence technology in business English teaching and artificial intelligence in natural language processing and recognition to receive good results. These two technologies are suitable for business English teaching innovation. At this time, the introduction of the concept of ADDIE is the process of integrating artificial intelligence technology into the business English teaching innovation model. The business English teaching model is designed to utilize the conditional random field expansion model to address the label bias limitations of the entropy model. Add the LSTM model to this basis to handle speech recognition and translation tasks to complete the construction of a business English teaching model based on LSTM-CRF. After speech recognition, detect the existence of grammatical errors in the sentence through the multi-task model, deform the LSTM model, and use the deformed Bi-LSTM to construct the multi-task learning model framework. The objective of controlled experiments and empirical analyses is to investigate the students’ willingness to learn AI Business English and their learning effects. The experiment shows that among the seven items of students’ willingness survey, only the mean value of the hedonic motivation variable is 3.93, and the mean value of the remaining six items is above 4. Students’ willingness to learn AI is high. In the comprehensive learning engagement degree, the mean value of the engagement is 1.457, and the highest value reaches 1.83278, and the students have a high degree of engagement in AI English learning. |
| first_indexed | 2024-03-08T10:04:14Z |
| format | Article |
| id | doaj.art-6b209aeac20242f38b7a3423f72b2b04 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:04:14Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-6b209aeac20242f38b7a3423f72b2b042024-01-29T08:52:45ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01628Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial IntelligenceLiu Shengming01Panzhihua University, Panzhihua, Sichuan, 617000, China.This paper examines the application of artificial intelligence technology in business English teaching and artificial intelligence in natural language processing and recognition to receive good results. These two technologies are suitable for business English teaching innovation. At this time, the introduction of the concept of ADDIE is the process of integrating artificial intelligence technology into the business English teaching innovation model. The business English teaching model is designed to utilize the conditional random field expansion model to address the label bias limitations of the entropy model. Add the LSTM model to this basis to handle speech recognition and translation tasks to complete the construction of a business English teaching model based on LSTM-CRF. After speech recognition, detect the existence of grammatical errors in the sentence through the multi-task model, deform the LSTM model, and use the deformed Bi-LSTM to construct the multi-task learning model framework. The objective of controlled experiments and empirical analyses is to investigate the students’ willingness to learn AI Business English and their learning effects. The experiment shows that among the seven items of students’ willingness survey, only the mean value of the hedonic motivation variable is 3.93, and the mean value of the remaining six items is above 4. Students’ willingness to learn AI is high. In the comprehensive learning engagement degree, the mean value of the engagement is 1.457, and the highest value reaches 1.83278, and the students have a high degree of engagement in AI English learning.https://doi.org/10.2478/amns.2023.2.01628addie modelconditional random fieldlstm-crf modelbi-lstmbusiness english teaching68t01 |
| spellingShingle | Liu Shengming Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence Applied Mathematics and Nonlinear Sciences addie model conditional random field lstm-crf model bi-lstm business english teaching 68t01 |
| title | Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence |
| title_full | Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence |
| title_fullStr | Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence |
| title_full_unstemmed | Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence |
| title_short | Research on the Innovation of Business English Teaching Mode in Colleges and Universities under the Background of Artificial Intelligence |
| title_sort | research on the innovation of business english teaching mode in colleges and universities under the background of artificial intelligence |
| topic | addie model conditional random field lstm-crf model bi-lstm business english teaching 68t01 |
| url | https://doi.org/10.2478/amns.2023.2.01628 |
| work_keys_str_mv | AT liushengming researchontheinnovationofbusinessenglishteachingmodeincollegesanduniversitiesunderthebackgroundofartificialintelligence |