AI-Driven Web Translation Technologies as Tools to Boost Article Writing Skills: Comparative Insights on ChatGPT, Google Translate, QuillBot, and DeepL Translate

Abstract

This study investigates the effectiveness of AI-driven web translation technologies as tools for enhancing article writing skills, focusing on ChatGPT, Google Translate, QuillBot, and DeepL Translate. The research addresses the growing need for understanding how these AI tools can be optimally utilized in academic writing contexts. Through a mixed-methods approach, the study employed a survey of 20 ESL participants across various academic institutions and conducted comparative analyses of 25 academic sentences translated by each tool. The methodology combined quantitative analysis of user satisfaction metrics and qualitative assessment of translation quality across multiple dimensions. Results indicate that ChatGPT emerged as the preferred tool (45% preference rate, 4.4/5 satisfaction), followed by DeepL (25%, 4.2/5), with high-reliability scores (Cronbach's Alpha >0.7) across all measured dimensions. Translation analysis revealed distinct strengths among tools, with ChatGPT excelling in maintaining academic tone and context, while DeepL showed superior precision in vocabulary selection. The findings suggest that a hybrid approach, primarily utilizing ChatGPT supplemented by DeepL for specific translation needs, optimizes writing enhancement outcomes. This study contributes to the understanding of AI tool integration in academic writing workflows and suggests future research should explore the long-term impact of AI-assisted writing on academic language development and writing proficiency.

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