AI literacy and vocational students’ complex problem-solving skills: a moderated mediation model of systematic thinking, cognitive load, and perceived school ICT support

As technological advancements such as Artificial Intelligence (AI) reshape the landscape of work, career development in vocational education is increasingly oriented toward dynamic, long-term personal growth. In this context, Complex Problem-Solving Skills (CPS) have become a critical competence, reflecting students’ capacity to address ill-structured tasks and adapt to rapidly changing environments. Grounded in Social Cognitive Theory, this study examines the relationship between AI Literacy and students’ self-reported Complex Problem-Solving Skills (CPS) in higher vocational colleges and the cognitive pathways that may help explain this relationship. This study posits that AI Literacy, as a personal agentic factor, is positively associated with self-reported CPS both directly and indirectly through Systematic Thinking Skills and cognitive load, and that perceived school information and communication technology (ICT) support may condition the strength of these associations. To provide temporal separation among the focal measures, a multi-wave survey was administered to 784 students from six higher vocational institutions at three time points. Data were analyzed using SPSS and Mplus. Results indicated that AI Literacy was significantly associated with self-reported CPS, with significant indirect effects estimated through Systematic Thinking Skills and the six-item cognitive-load composite. Notably, the associations between AI Literacy and these cognitive factors were stronger at higher levels of perceived school ICT support. These findings highlight the relevance of AI Literacy and students’ perceptions of ICT support to self-reported CPS and their preparation for AI-integrated workplaces.