نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Language skill gaps among tourist guides, particularly in high-traffic urban destinations, pose a structural barrier to service quality and local sustainable development. This study aims to design an intelligent foreign language education framework for tourist guides in Tehran Province, adopting a geo-educational perspective. Employing an exploratory mixed-methods design, data were collected from 84 active guides via a researcher-made questionnaire (validated with CVR/CVI and Cronbach’s alpha > 0.80) and an open-ended question. Quantitative data were analyzed using descriptive statistics, ANOVA, and regression, while qualitative data underwent reflexive thematic analysis via MAXQDA. Findings revealed a significant spatial disparity in language needs (p=0.018), with peripheral counties reporting the highest demand (M=4.42). A notable gap exists between using AI for translation (90.4%) versus active learning (44.1%), with structural barriers (unstable internet, 69%) outweighing individual ones. Qualitative analysis identified "location-based intelligence" and "localized content" as dominant themes. The joint display demonstrated strong methodological convergence, confirming that guides seek context-aware, non-robotic tools that preserve local narratives. The study concludes that AI integration fosters local sustainability only when content is spatially personalized and access is equitably distributed, offering a preliminary four-layer framework for regional policy-making.
کلیدواژهها English
