A Study of the Mechanisms of Generative AI Mobile Learning App's Impact on Vocational Students' Self-Directed Oral Technical Communication Skills

Jie Liang, Marlissa Omar, Intan Farahana Kamsin

The rapid development of artificial intelligence (AI) has broken the time and space limitations of traditional classroom learning and provides vocational school students with a convenient and new forms of mobile learning supported by generative AI applications. In order to explore the impact of mobile learning app tools on students' oral technical communication skills, this study adopts a qualitative investigation and research design to analyze the current status of vocational school students' self-directed oral technical communication skills with a questionnaire, builds a controlled experimental process of generative AI mobile learning app-assisted intervention teaching, and synthesizes the survey results, quiz data, and interview transcripts to discuss the students' oral technical communication skills' changes. Considering the mechanism of further quantifying the improvement of the competence, research variables were set up, and logistic regression model was selected as the test tool to test and examine the specific connection between the two. The results indicate that both the experimental and control groups showed imporovements after the intervention; however, the gains in the control group were almost negligible. The independent samples t-test results also revealed that the post-test scores of the experimental group were significantly higher than those of the group (p<0.01). Logistic regression analysis further demonstrated that AI simulation realism, AI feedback adaptivity, app course fit, and ease of use of the app had significant positive effects on the learning outcomes. These findings confirm the positive role of generative AI mobile earning in promoting the development of vocational students' oral technical communication skills.