Students’ Perceived Teacher Readiness and Student Satisfaction as Predictors of AI Integration in Indonesian Vocational High Schools

Abstract

Meaningful artificial intelligence (AI) integration in vocational education involves not only technical infrastructure but also students’ perceptions of teacher readiness and their learning experiences. However, evidence explaining how these factors are associated with AI integration in Indonesian vocational high schools remains limited. This study aimed to examine the direct and mediated relationships among students’ perceived teacher readiness, student satisfaction, and AI integration. A cross-sectional explanatory survey was conducted with students from five public and private vocational high schools in Yogyakarta. Of 105 questionnaires distributed, 99 complete responses were analysed. Participants were recruited through teacher-facilitated sampling. Quantitative data were analysed using partial least squares structural equation modelling, while open-ended responses were analysed through descriptive thematic coding to contextualise the findings. Students’ perceived teacher readiness was positively associated with AI integration and student satisfaction, while student satisfaction was positively associated with AI integration. Student satisfaction partially mediated the relationship between perceived teacher readiness and AI integration. The model explained 32.4% of the variance in student satisfaction and 68.1% in AI integration. Open-ended responses highlighted pedagogical judgement, practical professional development, ethical validation, equitable access, rapid feedback, and practice-oriented simulation. The conclusions are limited to student perceptions and the participating schools in this context.