Differential Impacts of Pair and Self-Dynamics on Written Languaging Attributes and Translation Task Performance in EFL Context

Keshanchi, Elnaz; Pourdana, Natasha; Khalili, Gholamhassan Famil

doi:10.1007/s42321-022-00113-w

Cited by 4 publications

(1 citation statement)

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“…Finally, students can use multimedia equipment for independent learning [11]. There are very rich teaching resources on the multimedia platform, which provides very good conditions for students to learn Japanese translation independently anytime and anywhere [12]. In addition to completing homework after class, students can also learn what they are interested in independently [13].…”

Section: Introductionmentioning

confidence: 99%

The Development Strategy of the Multimedia Fusion Mode of Big Data Technology in Japanese Translation Teaching

Qian

2022

Advances in Multimedia

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With the in-depth development of economic globalization, the connection and communication between China and other countries in the world are increasingly deepened, so the task of cultivating translation talents in various languages is particularly important. In the teaching process, teachers mainly focus on explaining theoretical knowledge and lack of classroom interaction, resulting in a boring and dull classroom atmosphere. At the same time, it does not pay attention to the practice of translation after class and often pays attention to interpretation and neglects written translation, which leads many students to think that Japanese translation is difficult and boring, which greatly reduces students’ enthusiasm for learning. In view of this situation, the application of multimedia technology in Japanese translation teaching proposes that the application of multimedia technology in Japanese teaching can improve the interest of students in Japanese learning and improve the teaching effect of Japanese teaching. Firstly, this paper constructs a logistic semantic ontology model based on automatic calibration of Japanese translation, extracts Japanese semantic features through this model, and performs relational mapping on the extracted Japanese semantic features. Starting from each aspect, optimize the automatic calibration algorithm of Japanese translation, find the best semantic relevance feature in each sentence, and realize automatic optimization, thereby improving the automatic calibration of Japanese translation machines and the registration of subject words.

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Section: Introductionmentioning

confidence: 99%