Empowering Higher-Order Thinking through Generative AI: The Mediating Roles of Teachers’ Digital Literacy and Pedagogical Innovation in Vocational Education

Abstract

As Generative AI (GenAI) becomes integral to vocational education, this study investigates how teachers’ GenAI proficiency fosters student higher-order thinking (HOT), and the mediating roles of digital literacy and innovative AI-supported pedagogy. Using a correlational design with 200 teacher–800 student dyads in Guangxi’s vocational tourism programs, teachers completed the GenAI Application Ability Scale (α = .88), Digital Literacy Inventory (α = .85), and Innovative Teaching Strategies Questionnaire (α = .82), while students responded to a 14-item HOT Skills Scale (α = .90). Confirmatory factor analysis confirmed construct validity; structural equation modeling with bias-corrected bootstrapping assessed direct and indirect effects. Results show a strong direct path from GenAI ability to HOT (β = .45, p < .001; 95% CI [.35, .55]). Mediation analyses reveal significant indirect effects via digital literacy (β = .32, p < .001; 95% CI [.24, .40]) and teaching strategies (β = .28, p < .001; 95% CI [.18, .38]), yielding a total indirect effect of .60 (p < .001; 95% CI [.50, .70]). The model accounted for 50% of HOT variance. This work underscores the need for training that fuses AI fluency with pedagogical innovation to prepare teachers for AI-enhanced classrooms.