The functional approach to the teaching of translation: a case study on Beiying and its English translations

With the development of social economy, English is still the main language of global communication, and China’s demand for English translators is also higher and higher. In college education, English translation is a very popular and important subject. Although the teaching mode is constantly changing, it still lags behind the speed of social and economic development. Traditional English translation teaching has many disadvantages in teaching theory and methods. This paper discusses the problems existing in translation teaching for English majors and then puts forward a new teaching mode of educational multiattitude resources, to really improve the quality of translation teaching for English majors. The resource pool of cloud computing is composed of a large number of resource nodes with different performances, but as the number of users gradually grows, the demand also increases. How to efficiently allocate large-scale cloud tasks to limited resource nodes and to achieve load balancing is an important issue that needs to be studied in cloud computing. This paper first uses the literature method, in-depth study of the theoretical development, and application bottleneck of education multiposture teaching mode at the same time to understand the problems existing in the current English translation teaching and design a new teaching mode for experimental application research and finally analyzes the comparison of the English translation ability of the control group and the experimental group without teaching method. After a period of experiment, the average score of the control group is 70.53, and the average score of the experimental group is 75.89. It can be seen that the average score of the experimental group is about 5 points higher than that of the control group; this shows that the intelligent optimization algorithm of cloud computing is combined with translation teaching that can improve the students’ overall English translation level to a certain extent and is more conducive to the students’ comprehensive mastery of knowledge.

Essay grading is an important and difficult task in natural language processing. Most of the existing works focus on grading non-native English essays, such as essays in TOEFL. However, these works are not applicable for Chinese essays due to word segmentation and different syntax features. Considering lexical features are important for essay grading, in this paper, we study the expert evaluation standard and propose an interpretable lexical grading method for essays. We first study different levels of vocabulary provided by experts and introduce a quantitative evaluation framework on lexical features. Based on these standards, we quantify the Chinese essay dataset of 12 education grades in primary and middle schools and propose a set of interpretable features. Then a Bi-LSTM network model is proposed for semantically grading essay, which accepts a sequence of word vectors as input and integrates attention mechanism in terms of lexical richness. We evaluate our method on real datasets and the experimental results show that it outperforms other methods on the task of lexically Chinese essay grading. Besides, our method gives interpretable results, which are helpful for practical applications.

Hailed as the gem of Eastern and Western culture, essay is one of the four major literary genres. With the further development of the May 4th Movement, a large amount of excellent essays have seen the light of day, among which have been translated into foreign languages. Essays cover a wide range of themes with diversified styles and flexible ways of writing, which are closer to our spoken language and easy to express one’s sentiment and feelings. However, these intrinsic characteristics cause the difficulty of essay translation. As a result, the cause of Chinese essay translation lagged behind other literary genres. Owing to his life experience and special liking for essay translation, Mr. Zhang Peiji is very proficient in translating such a peculiar genre. His master pieces of translation, Selected Modern Chinese Essays have precisely bridged the gap of essay translation in China. This article focuses on the aesthetic representation of Zhang Peiji’s Selected Modern Chinese Essays 1 from the perspective of Xu Yuanchong’s “Three-beauty Principle”, namely the beauty of sound, form and sense to explore better strategies in aesthetics representation. Beauty in sound can be demonstrated with onomatopoeia, reduplicated word, alliteration and rhyme. Beauty in form can be conveyed through four-character phrase, parallelism and rhetorical question. The beauty of sense remains top priority among the “Three-beauty Principle”, which needs translators to make appropriate wording and context reconstruction as well as properly tackle with fuzzy language by bring into full play their subjectivity. More importantly, the author hope to appeal to more translators and readers to realize the importance of essays and its translation and put into practice. It is our duty bound to introduce Chinese culture to the rest of the world and contribute our own endeavor to the cause of Chinese essay translation.

Writing is an important part of language learning and is considered the best approach to demonstrate the comprehensive language skills of students. Manually grading student essays is a time-consuming task; however, it is necessary. An automated essay scoring system can not only greatly improve the efficiency of essay scoring, but also provide more objective score. Therefore, many researchers have been exploring automated essay scoring techniques and tools. However, the technique of scoring Chinese essays is still limited, and its accuracy needs to be enhanced further. To improve the accuracy of the scoring model for a Chinese essay, we propose an automated scoring approach based on a deep learning model and validate its effect by conducting two comparison experiments. The experimental results indicate that the accuracy of the proposed model is significantly higher than that of multiple linear regression (MLR), which was commonly used in the past. The three accuracy rates of the proposed model are comparable to those of the novice teacher. The root mean square error (RMSE) of the proposed model is slightly lower than that of the novice teacher, and the correlation coefficient of the proposed model is also significantly higher than that of the novice teacher. Besides, when the predicted scores are not very low or very high, the two predicted models are as good as a novice teacher. However, when the predicted score is very high or very low, the results should be treated with caution.

English learning occupies a very important position in college students' learning, and English translating is a skill that must be mastered to learn English, and translating can be used to measure the comprehensive level of college students' English learning. However, surveys show that English translation is still a difficult part of the English learning process for college students. Traditional translation teaching only focuses on the result and ignores the process; the classroom atmosphere is dull; students are not highly motivated to write; and students' knowledge of translating and its skills are lacking. Therefore, translating teaching should combine results and process and explore teaching methods that can improve students' interest and translating ability. In this paper, scaffolded teaching is the main teaching method, and multimodal teaching is used to support scaffolded teaching in college English translating teaching. This study provides experimental support for the interactive group teaching method. It also provides a feasible teaching method option for college English teachers to implement student-centered teaching practices and helps college English teachers transition from the traditional teacher-oriented indoctrination classroom teaching method to a student-centered teaching method that combines English skill development and skill application. In addition, students in the experimental group were equipped with the ability to self-correct and spontaneously improve on problems that occurred in their language. This study finds that in the group interactive cooperative teaching method, the teacher's heuristic teaching with questions to promote answers can effectively improve college students' intrinsic motivation to learn English; students' cooperative exploration of the questions raised by the teacher in the group is conducive to cultivating students' autonomy in English learning; in the teaching activities, the use of teaching materials to train students' skills instead of sentence-by-sentence translation and grammatical analysis of sentence structures can help students master At the same time, the interactive and cooperative group teaching method, which involves students in learning through group activities, can effectively improve students' English performance.

As a universal language, English makes a better communication between China and the developed countries, English language teaching has become increasingly important in more and more Chinese Schools. At the beginning, when Chinese students start to learn a second language, they need to translate the second language such as English into Chinese in the first hand, and this procedure will help them to understand and learn English better. For English language translation teachers, they need to research and create the suitable、effective method of learning English translation for most students constantly in order to improve the English translation learning efficiency of the Chinese students. The local culture of China is quite different from the culture of other English speaking countries. When our Chinese students study English language translation, at the same time, they need to learn the different culture in different countries and learn how to accept and face up the cultural background difference between our country and the other English speaking countries. In the meantime, during the time of teaching English translation, the English translation subject teachers need to guide the students to learn and understand the difference in practice, and help them to establish a comprehensive and correct idea of learning English translation (through teaching right and different translation skills.

In the era of big data, with the rise of online media and the wide application of mobile terminals in education and teaching, more and more students rely too much on convenient mobile devices such as tablets and mobile phones to search for videos, audio and text that match their preferences. The network English translation learning resources, over time, lead to resistance to the traditional translation course teaching methods. Especially when teachers use traditional methods to present teaching resources that are duplicated with online resources in the classroom, students will be more resistant to traditional English translation teaching. In this era, the English professional translation course will usher in a new round of teaching reform, and then the author will carry out detailed analysis.

With the continuous development of society and the changes of the times, English has gradually become one of a fundamental requirement for talents. As the cradle of cultivating talents, colleges and universities play a pivotal role in educational reform. In the new era, the development of modern information technology demands English teaching to maintain innovation and keep pace with the times. The task-based language teaching approach is used in the translation teaching for English majors in colleges and universities to explore a new mode of English teaching. In teaching, by allowing students to complete the corresponding target tasks, develop students' ability to comprehensively use information, and promote the effective cultivation of students' English translation ability, thereby improving students' English cross-cultural level and translation ability. College English teaching should prioritize the cultivation of students' practical translation ability. Therefore, based on the characteristics of task-based language teaching, artificial intelligence technology is introduced into English translation teaching for English majors to assist in completing tasks using intelligent translation, so as to realizing a new model of student-centered English teaching. Taking English translation teaching as an example, this paper discusses how to reform the translation teaching for English majors in colleges and universities under the new situation of artificial intelligence application in the field of translation.

At present, most vocational colleges have set up English majors accordingly, and translation is a compulsory course for English majors. Although some concrete measures have been taken to implement the teaching mode and method of translation teaching, there are still some problems in the practice of translation teaching. Higher vocational students have some misunderstandings in English translation, which requires teachers to improve teaching methods and promote students’ initiative to participate in teaching. How to change the position of translation teaching in higher vocational English teaching and improve the level of English translation teaching is a hot issue for all English teachers. Based on an in-depth analysis of the characteristics of English translation teaching in higher vocational colleges, this paper expounds in detail the strategies for improving the effectiveness of English translation teaching in higher vocational colleges based on data mining.

This paper explores the diversified strategies of English translation teaching and the objectives of English translation teaching from various aspects and constructs a diversified teaching model of English translation. Then, it applies the structural equation modeling analysis method to deeply investigate the influence mechanism of diversified teaching of English translation on students’ English thinking, constructs a path model of the influence of diversified teaching of English translation on students’ overall and sub-competence of English thinking, and analyzes its influence effect. Finally, the moderating effect of diversified teaching of English translation on the English proficiency of students at different levels was investigated using the method of multi-cluster structural analysis. It is found that the total effect value of diversified teaching on critical thinking in English translation and problem-solving ability in English translation is 0.726 and 0.716, respectively, of which the indirect effect value accounts for 40.59% and 52.36% of the total effect value, respectively. This study verifies the feasibility, superiority, and universality of the teaching model proposed in this paper from several aspects.

Study on the Application of Presentation Approach to C-E Translation Teaching--A Case Study of Vocational English Students

English translation is an important means to help students improve their oral English ability, which is the basic method to cultivate students’ good English literacy. With the continuous popularization of network technology, English translation teaching has also ushered in another climax. In teaching practice, we should actively use translation as an English teaching strategy, which will give full play to the advantages of English translation. On the one hand, under the positive transfer of mother tongue, English translation can improve the comprehensive language ability. On the other hand, English translation can improve the efficiency of English teaching. This paper first analyses the importance of translation teaching in English teaching. Then, this paper puts forward some problems in English translation teaching. Finally, some suggestions are put forward.

Translation competence is crucial for both academic and professional success. After exploring the deficiencies in current college English translation teaching, this paper proposes to strengthen translation teaching for non-English majors in college English teaching in the e-learning era, which is also in line with the requirements of Guidelines on College English Teaching. A translation teaching experiment was conducted based on the PACTE translation competence model. The results of the data analysis showed that translation teaching based on this model really made a difference in non-English majors’ translation competence.

English translation is a powerful tool for international communication and learning a powerful tool in the world civilization and scientific and technological knowledge. In order to ensure the quality of teaching, develop students' information literacy, cultivate students' innovative spirit and practical ability of translation, further deepen the English education reform and comprehensively promote quality education, under the current background of actively promoting the modernization and information of education, according to the current existing problems of translation teaching for English major, we mainly analyzed the status of translation teaching, discussed the feasibility of translation teaching for English major based multimedia network environment, and studied the construction of translation teaching aiming at improving the translation teaching effectiveness and students' English language proficiency. KEYWORD: Translation teaching; English major; Multimedia; Network

Translation teaching is changed as artificial intelligence and deep learning constructs a wonderland. The traditional forms of teaching translation are devoid of personalized feedback, adaptive methods of learning, and dynamic error correction-all components that do not allow the student to attain high translation accuracy and fluency proficiency. This study investigates the application of a Transformer-based deep learning model and reinforcement learning algorithms in English translation education for the secondary school level. The study creates a system of AI-aided translation teaching which includes elements such as in-time feedback, adjusted translation exercises, and automated error diagnosis. The transformer models are for contextually accurate translations while reinforcement learning would ensure flexibility in difficult levels dependent on student performance. Effectiveness was evaluated through a study of 342 high school students concerning measures like translation accuracy and fluency, cultural adaptation, and error reduction. The findings showed apparent progress in translation performances, where BLEU scores rose from 45.3 to 62.7 and perplexity values declined from 21.4 to 14.8, reflecting greater translation precision and coherence. In addition, grammar errors decreased by 10.9%-12.6%, spelling errors by 11.4%-12.6% and contextual logic errors by 14.7%-19.5%, thus confirming the working of a reinforcement learning-based feedback mechanism. It concludes that AI-powered teaching of translations is an approach of learning that is scalable, efficient, and above all, student-centered in imparting translation precision, fluency, and cultural bearing. The combination of Transformer models and reinforcement learning is a promising perspective for the intelligent translation teaching of the future as it would enable real-time personalized feedback and optimization of learning throughout life.