Educational design of the course "Business interpretation in the Russian-Chinese language combination" in the era of artificial intelligence (using the example of ChatGPT)

Yue Zhuiin PhD in Philology Lecturer; Institute of Foreign Languages; Liaoning University of International Business and Economics 116052, China, Liaoning Province, Dalian, Shunle St., 33, office 5003 alina_yueruiying@mail.ru

In the modern digital age, the translation profession is undergoing drastic changes. D.I. Snezhitskaya notes the significant penetration of technological support into translation activities. Modern technologies significantly simplify intercultural communication, effectively overcoming language barriers between representatives of different linguistic cultures. Machine translation has become an integral part of modern communication tools, including search engines and e-mail ^[8].

The successful integration of artificial intelligence technologies into the business interpretation course requires a balanced approach based on cognitive-communicative and activity-creative teaching methods. This will make it possible to maximize the potential of ChatGPT as an auxiliary tool, while maintaining a focus on developing students' own intellectual abilities. E.S.Sayenko emphasizes the special role of ChatGPT in modern language education. This innovative tool, developed by OpenAI, provides students with the opportunity to practice communication skills, receive instant feedback on grammar issues, and expand vocabulary. The opportunity to study the cultural characteristics of the countries of the languages being studied through interactive interaction with the system is especially valuable. However, A.A. Ionina points out significant limitations of the use of artificial intelligence in language education. The main disadvantages are the lack of choosing the most correct answer and the lack of specifying information sources. Practice shows that the effectiveness of ChatGPT decreases when working with a higher level of language proficiency, and complex aspects of grammar and vocabulary still require the participation of an experienced teacher ^[3,6].

Modern artificial intelligence technologies, in particular ChatGPT, demonstrate impressive capabilities in the field of language translation, supporting more than 95 languages of various prevalence. E.V. Stefanova emphasizes the importance of precise query formulation to achieve maximum adequacy of translation, especially when working with specialized texts. At the same time, S.A. Loseva notes the fundamental difference between modern neural networks and traditional translation systems. A neural network using encoding and decoding mechanisms allows the system to take into account the whole context of a phrase, rather than simply comparing individual words and expressions. This approach ensures high translation accuracy and the ability to quickly train the system based on large amounts of data ^[4,9].

Researchers G.P. Bakulev and N.G. Grigorieva note that the main challenge for artificial intelligence in translation remains the problem of linguistic ambiguity. Researchers from the Massachusetts Institute of Technology identify various types of ambiguity, including morphological, lexical, syntactic, and pragmatic, which require special attention in machine translation. In the context of teaching simultaneous interpretation, it is important to take into account that ChatGPT does not directly provide interpretation, but can be effectively used as an auxiliary tool in preparation for translation activities. Teachers are recommended to teach students the skills of editing machine translation, taking into account the norms of the target language and the specifics of possible errors typical of automated translation systems ^[1].

In modern conditions of educational technology development, the issue of effective interpretation training is becoming particularly relevant. T. Wang and Yao Xiao emphasize that professional interpretation requires not only excellent command of a foreign language, but also a set of other important skills, including deep knowledge of the native language and developed translation competence. The specifics of teaching interpretation in the Russian-Chinese language combination lies in the need to take into account significant differences between languages and cultures. Special attention is paid to the practical component of training, which is implemented using modern technological solutions. An example of this approach is the Interpretation Training Platform implemented at Lanzhou University using virtual modeling technology. An important aspect of translator training is the development of standardized expression skills in both languages. At the same time, cooperation between Chinese Russian scholars and Russian teachers plays a special role, ensuring high-quality control of students' language training. The translation process requires not only accurate transmission of information, but also consideration of cultural peculiarities, which is especially important when working with idiomatic expressions and culturally specific concepts ^[2].

In the context of the active introduction of artificial intelligence into the educational process, it is important to maintain a balance between the use of modern technologies and traditional teaching methods, ensuring the comprehensive development of professional competencies of future translators. M. Xia notes the growing trend of using the "digital translation + post-editing" model among professional translators. This is due to the need to maintain competitiveness in the face of increasing demand for translation services. In the context of teaching business interpretation in the Russian-Chinese language combination, special attention is paid to the development of post-editing skills. This process differs significantly from traditional editing and requires a higher level of competence. The post-editor must have the ability to quickly assess the quality of machine translation and effectively correct possible errors. Practical work with these tools allows students to develop professional competencies and develop skills in working with terminology. In the learning process, special attention is paid to the analysis of equivalent, variant and transformational translational correspondences. Students learn to compare the results of different machine translation systems and independently performed translations, which contributes to the development of critical thinking and professional competence ^[10].

In the modern era of digital transformation, translation activities are undergoing significant changes that require rethinking traditional approaches to teaching translators. As TS rightly points out. Liu, despite the rapid development of machine translation technologies, the human factor in translation remains indispensable. Artificial intelligence is becoming an effective auxiliary tool in the translator's work, allowing you to optimize the translation process through pre-machine text processing followed by professional editing. However, it is important to understand the limitations of machine translation, especially in the field of literary translation, where a deep understanding of the cultural context and stylistic features of the text is required. The specifics of business interpretation in the Russian-Chinese language combination lies in the need to take into account not only linguistic aspects, but also national peculiarities, historical context and cultural differences between countries. Machine translation, although capable of ensuring the "fidelity" and "persuasiveness" of translation, cannot achieve the "expressiveness" that is characteristic of human translation. A modern translator should have not only deep language knowledge, but also the ability to adapt the text taking into account the cultural characteristics of the target audience. This is especially important when working with business documentation, where the accuracy and adequacy of the translation are of critical importance. Depending on the context and style of the source text, a professional translator can apply various translation transformations, including shortening, adding or adapting the text ^[5].

Research methods

The methodological framework of the research is based on a combination of qualitative and quantitative methods. The qualitative component is realized through in-depth interviews with practicing translators and teachers working in the field of business Russian-Chinese translation. The quantitative component is represented by an analysis of the effectiveness of using ChatGPT in the educational process based on statistical processing of student learning outcomes. The study involved 120 students, divided into experimental and control groups of 60 people each.

The research uses the method of longitudinal observation of the process of formation of translation competencies among students of the experimental group using ChatGPT and the control group studying according to the traditional methodology. The observation time interval is one academic semester (16 weeks), which allows you to track the dynamics of professional skills development. To evaluate the results of the translation, the expert assessment method is used, where a group of 10 experts, including native speakers of Russian and Chinese, assesses the accuracy of the meaning, stylistic conformity and cultural adaptation of the translations. The data obtained are subjected to qualitative and quantitative analysis in order to identify typical errors and determine the effectiveness of the applied teaching methods.

The research uses the method of longitudinal observation of the process of formation of translation competencies among students of the experimental group using ChatGPT and the control group studying according to the traditional methodology. The observation time interval is one academic semester, which allows you to track the dynamics of professional skills development. The study uses the method of expert evaluation of the results of the translation performed by students. A group of experts consisting of native speakers of Russian and Chinese evaluates the accuracy of the meaning, stylistic conformity and cultural adaptation of translations. The data obtained is subjected to qualitative analysis in order to identify typical errors and determine the effectiveness of the applied teaching methods.

The course design methodology also includes the development of a system of criteria for assessing the formation of translation competencies. This system takes into account the ability of students to effectively use artificial intelligence in their professional activities while maintaining a high level of independence in making translation decisions.

The course is based on the modular principle of organizing the educational material, which allows for the consistent formation of professional competencies of the translator. The first module of the course is devoted to the fundamental aspects of business translation, where students get acquainted with the basic terminology, business communication features and specifics of Russian-Chinese business interaction. The second module focuses on an in-depth study of the linguistic and cultural features of business translation between Russian and Chinese. The third module is entirely devoted to practical work with various types of business communication.

The innovation of the developed course lies in the organic integration of ChatGPT into the educational process. Artificial intelligence is used as a multifunctional tool that helps improve the effectiveness of learning. In lecture classes, ChatGPT is used to generate relevant examples of business communication and create educational materials tailored to the specific needs of students.

The seminars are based on interactive interaction, where ChatGPT acts as a virtual interlocutor, creating realistic business communication situations. This allows students to practice simultaneous and sequential translation skills in conditions as close as possible to real professional activities.

The practical component of the course is implemented through a system of specially designed assignments and cases, where ChatGPT is used to create variable scenarios for business negotiations, presentations and meetings. Special attention is paid to developing skills in working with business documentation of various genres, including contracts, agreements and business correspondence. An important methodological aspect is the use of ChatGPT to evaluate the quality of translations and provide feedback to students. The system allows you to analyze the accuracy of the meaning, stylistic correspondence and cultural adequacy of the translations performed, which contributes to the development of students' self-assessment and critical thinking skills.

The system for evaluating the effectiveness of the developed course is based on an integrated approach to the analysis of educational outcomes. The key component is a multi-level system of criteria for assessing students' knowledge and skills, which includes both traditional parameters for assessing translation competencies and specific indicators of proficiency in artificial intelligence tools in professional activities. The developed assessment system takes into account the accuracy of meaning transmission, stylistic correspondence, cultural adequacy of translation, as well as the ability of students to effectively use ChatGPT to solve translation problems. Special attention is paid to evaluating the skills of critical analysis and editing of machine translation, which is an important competence of a modern translator.

Feedback from participants in the educational process is collected on a regular basis through a system of questionnaires and in-depth interviews. Students note an increased level of confidence when working with business texts and an increased speed of translation tasks. The teachers emphasize a significant improvement in the quality of translations and a deeper understanding by students of the cultural peculiarities of business communication between Russian-speaking and Chinese partners.

The analysis of learning outcomes demonstrates a significant increase in the effectiveness of the educational process. The students of the experimental group show higher results compared to the control group in such aspects as translation speed (35% higher), accuracy of terminology transfer (22% higher) and the ability to adapt the translation style to a specific business situation (28% higher). Statistical analysis confirms the significance of differences in results between the groups (p < 0,05). The students of the experimental group show better results than the control group in such aspects as the speed of translation, the accuracy of terminology transmission and the ability to adapt the translation style to a specific business situation. Statistical analysis confirms the significance of differences in the results between the groups.

An important indicator of the effectiveness of the course is the successful professional adaptation of graduates. According to the survey of employers, 85% of graduates of the experimental group demonstrate a high level of training, their ability to effectively use modern technologies in translation activities while maintaining a critical approach to the use of artificial intelligence tools. This confirms the practical value of the developed teaching methodology and its compliance with modern requirements of the translation services market.

Appeal to opponents

In response to possible criticism regarding the integration of artificial intelligence into the learning process of business interpretation, several key aspects need to be emphasized. First of all, the use of ChatGPT in the proposed methodology does not replace traditional teaching methods, but organically complements them, creating a synergistic effect in the educational process.

Opponents may express concern that the use of artificial intelligence may reduce students' independence in learning translation skills. However, the developed methodology provides for a clear distinction between using ChatGPT as an auxiliary tool and developing students' own competencies. The statistical data of the longitudinal study demonstrate that the students of the experimental group show better results in the development of critical thinking and the ability to make independent translation decisions.

Regarding possible doubts about the reliability and quality of the materials generated by ChatGPT, it should be noted that all educational materials are thoroughly peer-reviewed by qualified specialists in the field of Russian-Chinese translation. Moreover, a multi-level translation quality assessment system, including both automated analysis and expert assessment, ensures high reliability of learning outcomes.

Criticism regarding the limited time frame of the study (one semester) can be countered by the fact that this period is sufficient for the formation of basic translation competencies and allows us to trace the dynamics of the development of students' professional skills. At the same time, the methodology provides for the possibility of further scaling and adaptation for longer periods of study.

Conclusions

The conducted research on the design and implementation of the course "Business interpretation in a Russian-Chinese language combination" using ChatGPT demonstrates the significant potential for integrating artificial intelligence into the professional training system for translators. The use of the modular principle of organizing educational materials in combination with innovative technologies has allowed us to create an effective educational model that meets the modern requirements of the translation services market.

The results of the longitudinal study confirm a significant improvement in the quality of specialist training. The students of the experimental group demonstrate higher indicators in the field of translation speed, accuracy of terminology transmission and the ability to adapt texts culturally. A particularly important achievement is the development of students' critical analysis skills and the ability to effectively use artificial intelligence tools while maintaining professional autonomy. The developed methodology for evaluating the effectiveness of the course, which includes a multi-level system of criteria, allows for an objective assessment of students' progress and the adjustment of the educational process. The positive feedback from all participants in the educational process and the successful professional adaptation of graduates confirm the practical value of the developed course.

The results obtained open up prospects for further development of business translation teaching methods using artificial intelligence. The presented experience can serve as a basis for creating similar courses in other language combinations and areas of translation activity.