Developing Deep Learning-Based Esp Materials For Hospitality Students In Vocational High School
DOI:
https://doi.org/10.56667/de_journal.v6i2.1999Keywords:
English for Specific Purposes, Hospitality, Needs Analysis, Deep Learning, Materials DevelopmentAbstract
This study aims to develop relevant and adaptive English for Specific Purposes (ESP) materials for students in the Hospitality Department at vocational high schools. The research employed the Research and Development (R&D) 4D model (Define, Design, Develop, Disseminate). Data were collected through questionnaires, interviews, expert validation sheets, tests, and documentation. The needs analysis based on the Need, Lack, and Want framework revealed that students require English proficiency for front office operations, guest relations, and handling complaints, while existing materials are still too general and not sufficiently aligned with industry demands. Students also expressed a strong preference for role play activities and the integration of digital technologies, such as AI-powered chatbots, to support authentic learning. Expert validation confirmed content feasibility with a Content Validity Index (CVI) of 0.92, while design and interactivity aspects received an average score of 88%. A limited product trial showed a significant improvement in students’ average scores from 62.3 to 78.5 after using the developed materials. These findings highlight that deep learning-based ESP materials can enhance relevance, effectiveness, and employability readiness of vocational hospitality students.
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