Research on the Impact of Generative Artificial Intelligence Usage Behavior on the Learning Outcomes of Higher Vocational Students

作者：Yanbo Song, Kangjian Zhao, Li Li, Wei Dong · 发表于：Behavioral Sciences · 年份：2026 · DOI：10.3390/bs16071166 · 研究领域：Artificial Intelligence in Healthcare and Education、Online Learning and Analytics、AI in Service Interactions

Generative Artificial Intelligence (GenAI) has been increasingly integrated into vocational education teaching and students’ learning. Thus, instructing higher vocational students to use GenAI effectively and improving their self-reported perceptions of learning outcomes are critical. Based on the talent development requirements of vocational education, this study developed and validated the GenAI Usage Behavior Scale and the Higher Vocational Students’ Perceived Learning Outcomes Scale. Subsequently, an empirical analysis was conducted using data from 1110 valid questionnaires collected from Chinese higher vocational students. According to the descriptive statistical analysis, the overall usage behavior of higher vocational students was generally at a medium–high level. They performed relatively well in terms of usage habits, moderately in usage contexts, and showed a relatively low frequency of use. The overall evaluation for higher vocational students’ perceived learning outcomes was rated as above average with competency development ranking highest, followed by skill application and knowledge mastery. As for group differences, the results of the independent samples t-test and one-way analysis of variance (ANOVA) revealed no overall significant differences in perceived learning outcomes across genders. Significant differences were only observed in the skill application dimension across grades, while all dimensions of perceived learning outcomes showed statistically signifi...