Generative AI in Vocational High School Design Cluster Practice Courses: Influences on Motivation and Effectiveness

In recent years, artificial intelligence (AI) technologies have rapidly advanced and found extensive applications in image design, text generation, and interactive media, increasingly being integrated into educational contexts.Among these technologies, generative AI characterized by real-time interactivity, multimodal content generation, and text-to-image conversion capabilities has demonstrated significant potential as an instructional tool in vocational high school design courses.However, empirical research on the integration of generative AI in vocational design education remains limited, and the effects on students' learning motivation and academic performance have yet to be thoroughly examined.This study investigates the impact of integrating generative AI on students' learning motivation and effectiveness in a computer graphics course at a vocational high school in Taiwan.An experimental design was employed, utilizing a cyclical learning model consisting of four stages: observation, summarization, questioning, and application.The course was conducted over two weeks, with three 50-minute sessions each week.Following the intervention, students completed an assessment of learning effectiveness and a questionnaire on learning motivation.Analysis using paired-sample t-tests, one-way ANOVA, and Pearson correlation revealed that the integration of generative AI significantly enhanced students' learning effectiveness.Although the gains in learning motivation were modest, the intervention resulted in tangible improvements in student learning effectiveness.