Research on AI-Enabled Language Services for the International Communication of Vocational Education
DOI:
https://doi.org/10.70088/p9ta9z59Keywords:
AI translation, vocational education, international communicationAbstract
This study investigates the design, implementation, and empirical performance of AI-enabled language services tailored to enhance the international communication of vocational education. Drawing on a multi-phase mixed-methods approach, we developed and deployed a modular translation and localization pipeline integrating neural machine translation, domain-specific terminology alignment, and pedagogical register adaptation. The system was evaluated across three vocational domains—automotive technician training, nursing certification, and industrial robotics instruction—using authentic curricular materials from 12 national vocational education providers. Quantitative metrics included translation accuracy (measured via BLEU-4, TER, and domain-expert adjudicated fidelity scores), cross-lingual instructional coherence (assessed through task-based comprehension testing with 327 bilingual trainees), and real-time usability (via session analytics and instructor feedback logs). Results demonstrate statistically significant improvements in terminological consistency (+41.3% over generic MT baselines), pedagogical appropriateness (+36.7% expert-rated alignment), and learner task success rate (+28.9%) when domain-adapted AI services are applied. Crucially, the system reduced average localization turnaround time from 17.2 days to 2.4 hours per module without compromising instructional integrity. Findings affirm that purpose-built AI language infrastructure—not merely off-the-shelf translation tools—is essential for preserving technical precision, procedural clarity, and cultural relevance in global vocational education dissemination. The research establishes a replicable framework for embedding linguistic intelligence into vocational curriculum interoperability, with direct implications for policy harmonization, transnational qualification recognition, and equitable access to high-skill training pathways.References
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