Generative AI and Higher-Order Thinking in Vocational Education: A Study of Human-Machine Collaboration

Abstract

This study dives into how Generative Artificial Intelligence (GenAI) can boost higher-order thinking skills among vocational college students in Guangxi, China. The researchers used a quasi-experimental mixed-methods approach, involving 70 students from information technology and engineering programs. They split the students into two groups: one that experienced GenAI-enhanced interactive teaching and another that followed traditional instruction. The experimental group utilized GenAI in specific roles like “virtual debater” and “decision consultant,” which helped them engage more actively in debates, case analyses, and reflective decision-making. The quantitative results from pre- and post-tests showed a notable improvement in critical thinking, logical reasoning, and reflective skills for the students in the experimental group. Meanwhile, qualitative data gathered from observations, student journals, and interviews highlighted an increase in metacognitive awareness, deeper engagement with problem-solving tasks, and a positive view of AI as a helpful partner in learning. However, there were also concerns about students becoming too reliant on AI tools and the necessity for guided facilitation. The findings indicate that when implemented thoughtfully, GenAI tools can significantly enhance higher-order thinking in vocational education, especially when paired with teaching strategies that promote active learning and reflection. This study underscores the importance of integrating AI ethically and calls for customized instructional designs to ensure fair access and ongoing cognitive growth. These insights add to the ongoing conversation about human-machine collaboration in education and provide valuable guidance for future curriculum innovations in tech-driven learning environments.