Data-Driven Teaching Model Design of College English Translation Using Intelligent Processing Technology

Zhang, Jie

doi:10.1155/2022/6559772

Cited by 8 publications

(6 citation statements)

References 4 publications

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“…Generally speaking, a corpus [19][20][21] is a huge number of papers that people have gathered and organized for use in a certain field. For the study of word similarity calculation utilizing large-scale corpora, many researchers have used traditional mutual information approaches, which are based on the principle of mutual information.…”

Section: Related Workmentioning

confidence: 99%

An English Writing Grammar Error Correction Technology Based on Similarity Algorithm

Li¹

2022

Security and Communication Networks

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Students are the focus of English writing instruction, which emphasizes their initiative and creativity in the classroom, fosters the development of their self-directed learning and comprehensive language skills, raises their overall English level and mastery ability, and cultivates well-rounded English learners. It is to get yourself out of the dilemma of Chinese English. This study proposes an automatic error correction method for English writing grammar based on a similarity algorithm, which is applied to students during the English writing process. To address the issue of grammatical errors, this study proposes an ontology and grammar rules based on the English writing corpus. Our experimental results demonstrate that our highlighting algorithm can effectively correct grammatical errors in written English, demonstrating the algorithm’s efficacy.

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Section: Related Workmentioning

confidence: 99%

An English Writing Grammar Error Correction Technology Based on Similarity Algorithm

Li¹

2022

Security and Communication Networks

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“…Such DDL activities increase attention and grammar awareness, which can help language learning in the long run. Translation teaching based on data-driven learning [1,2] can help learners develop their ability to learn independently and improve their cognitive and metacognitive skills.…”

Section: Introductionmentioning

confidence: 99%

“…(1) This paper combines data-driven learning with college English translation teaching and introduces the theory and learning methods of deep learning in detail. (2) In the face of two translation teaching methods, use traditional teaching and DDL teaching to design experiments, respectively. This paper compares the performance of the two methods by evaluating the experimental results and draws the conclusion that DDL is superior to traditional teaching.…”

Section: Introductionmentioning

confidence: 99%

English Translation Teaching Algorithm in Colleges and Universities Using Data-Driven Deep Learning

Wang

2022

Mobile Information Systems

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The data-driven learning model is a newer learning method. It not only provides learners with rich, diverse, and real-language big data, but it also creates an ideal learning environment for them because of its corpus-based teaching and learning characteristics. This paper will look at how to analyze and research data-driven learning in college English translation classes, as well as describe the data-driven approach. This paper presents the problem of data-driven translation teaching design, then expands on the concepts and learning methods of deep learning, and conducts case design and analysis of college English translation teaching. The results of the experiments show that there are numerous issues in traditional translation instruction, some of which are caused by students and others by teachers. The overall situation of the experimental group is better than that of the control group after the application of the college English translation teaching design, indicating that the DDL method is better than the traditional method ( Mean = 5.02 > 0 ), and the overall effect of DDL is better than that of the traditional method.

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“…e semantic problem in the arti cial intelligence perspective is one of the most central problems among the many di culties faced by arti cial intelligence. e philosophical debate and questioning of the semantic problem have posed an inevitable and serious challenge to the advancement of AI [3]. It has been sixty-ve years since the concept of arti cial intelligence (AI) was introduced at the Dartmouth Conference in 1956.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Big Data Technology on Phrase and Syntactic Coherence in English Translation

2022

Mathematical Problems in Engineering

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In the era of big data, data are ubiquitous. The proliferation of data leads to a surge in the demand for communication, which in turn promotes a surge in the demand for language services. Big data technology is a comprehensive technology, and its important feature is a more active technological factor, where technological development and technological innovation dominate, which will have an incalculable impact on the development of the translation industry. In the language service industry, much information that used to be difficult to quantify will be transformed into data for storage and processing, and a large number of complex items to be translated will gradually surface. Therefore, it is the general trend of the translation industry to stimulate and utilize the unexplored values hidden inside the data and develop the blue ocean of the language service industry. Traditional translation researchers are confined to the study of language and text and are not fully aware of it. The huge role played by translation technology in today’s business environment, and the traditional translation theory can hardly describe and explain the new modern translation technology phenomenon and translation technology activities. Whether we are ready for it or not, the rapid development of translation technology in the era of big data will lead to significant changes in translation inquiry and translation teaching on a global scale. The integration and development of translation with cloud computing, big data, the Internet, and artificial intelligence are driving a series of innovations in the traditional translation model. The development of translation technologies and tools is breaking new ground, rapidly expanding into all aspects of the translation industry and triggering disruptive changes in the language service industry.

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Data-Driven Teaching Model Design of College English Translation Using Intelligent Processing Technology

Cited by 8 publications

References 4 publications

An English Writing Grammar Error Correction Technology Based on Similarity Algorithm

An English Writing Grammar Error Correction Technology Based on Similarity Algorithm

English Translation Teaching Algorithm in Colleges and Universities Using Data-Driven Deep Learning

The Impact of Big Data Technology on Phrase and Syntactic Coherence in English Translation

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