EFFECTS OF AN AI-ENHANCED LEARNING ENVIRONMENT ON VOCATIONAL SKILLS AND LEARNING MOTIVATION: EVIDENCE FROM LOGISTICS EDUCATION IN CHINA

The rapid integration of artificial intelligence (AI) into the logistics industry has intensified the demand for vocational graduates with strong vocational skills and sustained learning motivation. However, empirical evidence on how AI-enhanced learning environments influence vocational learning outcomes remains limited, particularly in logistics education. Grounded in Self-Determination Theory (SDT) and Constructivist Learning Theory (CLT), this study examined the effects of an AI-enhanced learning environment on logistics students’ vocational skills and learning motivation in a Chinese vocational college using a convergent parallel mixed-methods design. Quantitative data from 120 second-year logistics students (experimental vs. control groups) and qualitative data from 20 semi-structured interviews were collected. Results showed that the AI-enhanced learning environment significantly improved students’ vocational skills and learning motivation (autonomy, competence, relatedness) compared to traditional instruction. This study validates the applicability of SDT and CLT in logistics vocational education and provides empirical support for AI-enabled vocational education practice.