Construction of “Interactive” English Translation Teaching Model Based on Data-Driven Learning

Abstract

With the growth of international trade, there is a greater demand for people with a diverse professional background and a high level of foreign language translation skills. This thesis covers the fundamental concepts and evolution of data-driven learning, well-known data-driven learning systems, common statistical parameters and analytical statistical methods of data-driven learning, and commonly used data-driven learning indexing software and its basic functions. A basic knowledge outline and data-driven learning thinking method are provided. Although English translation is widely used, there are still many flaws in professional training. In response to the current situation in which college English translation teaching is difficult to adapt to new requirements of college English teaching and talent training, it is proposed to combine multimedia technology and corpus, as well as support constructivist learning theory, data-driven learning theory, and autonomous learning theory, to create a “data-driven Learning (DLL) college English translation teaching model,” beginning with the teaching materials, teaching objectives, and a “data-driven Learning (DLL) college English translation teaching model,” starting from the teaching materials, teaching the impact of the model on college students’ translation learning. The results of the experiments show that this mode is associated with a significant improvement in students’ translation learning abilities. This model is shown to be effective when used in college English translation classes.

Artificial Intelligence Technologies in College English Translation Teaching

“…The main attention in teaching English translation should be given to the development of the thinking abilities of students, the improvement of their theoretical knowledge and skills, as well as their reasonable application in practice. The ability of students to innovate and solve practical problems is important for translation work, therefore, the methodology of teaching translation should be aimed not only at improving the professional skills and knowledge of students in the field of translation, but also at developing the ability to solve problems in the context of a rapid innovative digital transformation of socio-economic life society (Huang, 2022 ). Multimodality is a typical feature of modern education and an inevitable requirement to improve the efficiency of translation skills and models.…”

Interactive Music Learning Model Based on RBF Algorithm

“…erefore, teachers need to actively guide students through classroom instruction, use motivating and effective assessments (individual classroom extra credit, group assessment, and music grade percentages), and provide opportunities for students to demonstrate their musical skills in order to create a strong desire to learn creative writing. By constructing an "interactive" learning model, it is clear that students' thinking skills are enhanced and their individual musical perception, participation, confidence, and expression are strengthened [27][28][29][30][31][32][33][34][35]. In terms of knowledge, experience, personality, spirit, culture, etc., the vision is enhanced, life is empathized and experienced, life is enlightened, and spirituality is enriched, and the direction of development of teachers and students tends to the realm of truth and beauty.…”

The Effect of Critical Thinking on Translation Technology Competence Among College Students: The Chain Mediating Role of Academic Self-Efficacy and Cultural Intelligence

“…100 Through the "data-driven learning college English translation teaching model", students were open to discussing their answers and looking for justifications for their choices, which greatly enhanced their translation capabilities. 101 As a sub-competence of translation competences, translation technology competence is also impacted by critical thinking skills. When given the responsibility of reviewing machine translation work, students are expected to acquire critical thinking ability 102 because the performance of machine translation post-editing was affected by translator's critical thinking through self-regulation.…”