Speaking Up with AI: Empowering Vocational Students’ English Fluency and Motivation through ELSA
Keywords:
AI-assisted learning, ELSA, Speaking fluency, Motivation, Vocational educationAbstract
Grounded in Communicative Language Teaching, Sociocultural Theory, and Self-Determination Theory, this study investigates the role of AI-mediated dialogue in enhancing vocational students’ speaking proficiency and motivation. Oral English competence is a critical employability skill in the era of globalization and Industry 4.0, yet Indonesian vocational learners often struggle with fluency, pronunciation, and speaking confidence. To address this issue, this study integrated ELSA, a mobile-based AI speaking application, into vocational English instruction. The research aimed to examine the effectiveness of ELSA in improving speaking performance, explore changes in student motivation, and identify pedagogical and infrastructural challenges. A mixed-methods design was employed involving 30 eleventh-grade vocational students in Garut district. Quantitative data were collected through Likert-scale questionnaires, while qualitative data were obtained from classroom observations and semi-structured interviews. The findings revealed significant improvements in fluency, pronunciation accuracy, and speaking confidence. Students demonstrated heightened motivation, increased self-regulated practice, and reduced speaking anxiety, attributed to ELSA’s real-time feedback and gamified features. However, challenges related to internet connectivity, limited device access, and restrictions of the free application version were identified, necessitating teacher mediation and institutional support. This study highlights the pedagogical potential of AI-powered speaking tools to bridge classroom instruction and workplace communication demands and emphasizes the need for blended pedagogical strategies and adequate infrastructure to ensure equitable and sustainable AI integration in vocational education.
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