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Application of Network Technology in English Interpretation Classes: Pathways and Effectiveness Research

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DOI: 10.23977/trance.2024.060505 | Downloads: 22 | Views: 932

Author(s)

Zhang Qian 1

Affiliation(s)

1 English Department, Xi'an Fanyi University, Xi'an City, Shaanxi Province, China

Corresponding Author

Zhang Qian

ABSTRACT

In recent years, the integration of network technology into English interpretation classes has significantly transformed traditional pedagogical methods. This paper delves into the pathways and effectiveness of incorporating network technology to enhance the learning outcomes of English interpretation in universities. It provides a comprehensive overview of how various technologies, such as AI-aided translation tools, online collaboration platforms, and real-time feedback systems, are reshaping students' learning habits and the modern educational environment. The study concludes with practical recommendations for educators on effectively integrating these technologies into their curriculum to optimize student engagement and learning outcomes. By adopting these practices, educators can enhance student engagement, facilitate a more interactive learning experience, and ultimately improve learning outcomes in English interpretation classes.

KEYWORDS

Network Technology, Interpretation Classes, Learning Outcomes

CITE THIS PAPER

Zhang Qian, Application of Network Technology in English Interpretation Classes: Pathways and Effectiveness Research. Transactions on Comparative Education (2024) Vol. 6: 26-31. DOI: http://dx.doi.org/10.23977/trance.2024.060505.

REFERENCES

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[3] Han Daeun. "An analysis of Korean EFL learners' experience on English classes using AI chatbot." Robotics & AI Ethics 6.3 (2021): 1-9.
[4] Biernacka, Agnieszka. "Virtual classes as an innovative tool for conference interpreter training." e-mentor 77.5 (2018): 30-35.
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[6] Al-Jarf, Reima. "Text-to-Speech Software as a Resource for Independent Interpreting Practice by Undergraduate Interpreting Students." Online Submission 2.2 (2022): 32-39.

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