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Innovative Exploration of Vocational English Writing Instruction Based on Machine Translation Technology

Author(s)

Wu Juan

Affiliation(s)

Suzhou Vocational Institute of Industrial Technology, Suzhou, Jiangsu, China

Abstract

This study aims to explore innovative application pathways of machine translation technology in vocational English writing instruction, addressing current issues such as inefficiency and insufficient personalized guidance in this field, thereby enhancing teaching quality and student writing skills. The research employs literature review, action research, questionnaire surveys, and experimental comparison methods. Initially, a theoretical framework integrating machine translation technology with vocational English writing instruction is constructed through a review of relevant domestic and international literature. Subsequently, the current status of vocational English writing instruction and the application bottlenecks of machine translation technology are analyzed. Based on this analysis, an innovative instructional model incorporating machine translation technology is designed, including restructuring teaching processes and optimizing evaluation systems. A teaching experiment lasting one semester is conducted with students from two vocational colleges, comparing the writing achievements, learning motivation scale data, and teacher interview results between the experimental and control groups to validate the effectiveness of the innovative model. The findings reveal that the judicious application of machine translation technology significantly enhances vocational students’ English writing efficiency and text quality, boosts their autonomous learning abilities, and alleviates teachers’ grading burdens, thus optimizing resource allocation in teaching. However, it is crucial to guide students in the appropriate use of technology to prevent over-reliance.

Keywords

Machine Translation Technology; Vocational English; Writing Instruction; Teaching Innovation; Instructional Model

References

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