Artificial intelligence-enabled pedagogy in management education: An empirical investigation of student engagement, learning outcomes, and graduate employability
TL;DR
An integrated model linking AI tool use, perceived learning, engagement, critical thinking, self-efficacy, learning outcomes, and employability, with digital literacy as antecedent and faculty support as moderator is tested, confirming that pedagogical scaffolding is essential to converting AI exposure into educational value.
Abstract
Generative artificial intelligence (AI) has rapidly transformed management education, yet empirical evidence on how it shapes student engagement, learning, and employability remains fragmented. This study tests an integrated model linking AI tool use, perceived learning, engagement, critical thinking, self-efficacy, learning outcomes, and employability, with digital literacy as antecedent and faculty support as moderator. Cross-sectional survey data from 612 management students across five world regions were analysed using covariance-based structural equation modelling, bootstrapped mediation, and multi-group moderation. The structural model exhibited excellent fit (χ 2 /df = 1.97; SRMR = 0.038; RMSEA = 0.047; CFI = 0.966), and all 12 hypothesised paths were supported. AI tool use exerted both direct and indirect effects on employability via engagement, critical thinking, self-efficacy, and learning outcomes. Faculty support significantly amplified the AI–engagement and AI–learning relationships, confirming that pedagogical scaffolding is essential to converting AI exposure into educational value. The findings extend the technology-enabled learning literature and offer evidence-based policy implications for accreditation bodies, business schools, and curriculum designers.