Personalized translator training in the era of digital intelligence: Opportunities, challenges, and prospects

This study investigates the transformative effects of digital intelligence on translator education through a theoretical and exploratory approach, employing both bibliometric and content analysis to derive its findings. It systematically examines the evolution of translator training methodologies through the integration of AI, ChatGPT, large language models (LLMs), and 5G, providing a comprehensive framework for understanding these changes. Key findings reveal that personalized learning, supported by digital tools, significantly enhances student engagement and skill acquisition. However, challenges such as ensuring data quality, mitigating excessive dependence on technology, and maintaining ethical standards persist. The study underscores the critical necessity of developing advanced training platforms and strategies that foster effective teacher-student interactions and uphold academic integrity. Furthermore, it emphasizes the importance of continuous innovation in educational practices to equip future translators for the demands of a digital and highly connected world. These insights offer valuable guidance for educators and policymakers in crafting curricula that are both forward-thinking and resilient.

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Publication Details

Journal
Heliyon
Published
2024-10-01
DOI
https://doi.org/10.1016/j.heliyon.2024.e39354
Citations
11
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
3.82
Controls
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article

Personalized translator training in the era of digital intelligence: Opportunities, challenges, and prospects

Xujun Tian
11 citations
Heliyon
Natural Language Processing Techniques
3.82
article

Personalized translator training in the era of digital intelligence: Opportunities, challenges, and prospects

Xujun Tian
article en
11 citations

Abstract

This study investigates the transformative effects of digital intelligence on translator education through a theoretical and exploratory approach, employing both bibliometric and content analysis to derive its findings. It systematically examines the evolution of translator training methodologies through the integration of AI, ChatGPT, large language models (LLMs), and 5G, providing a comprehensive framework for understanding these changes. Key findings reveal that personalized learning, supported by digital tools, significantly enhances student engagement and skill acquisition. However, challenges such as ensuring data quality, mitigating excessive dependence on technology, and maintaining ethical standards persist. The study underscores the critical necessity of developing advanced training platforms and strategies that foster effective teacher-student interactions and uphold academic integrity. Furthermore, it emphasizes the importance of continuous innovation in educational practices to equip future translators for the demands of a digital and highly connected world. These insights offer valuable guidance for educators and policymakers in crafting curricula that are both forward-thinking and resilient.

HeliyonVol. 10(20)
Shanghai Lixin University of Accounting and Finance (CN)
Openalex Percentile: Top 6%
Natural Language Processing Techniques
3.82
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Personalized translator training in the era of digital intelligence: Opportunities, challenges, and prospects — Xujun Tian · Heliyon (2024) | TGRS Research Map | TGRS