The associations of AI-integrated entrepreneurship education versus traditional entrepreneurship education on undergraduates’ entrepreneurial intention and its antecedents

This study investigates the differential associations between AI-integrated entrepreneurship education (AIEE), traditional entrepreneurship education (TEE), and college students’ entrepreneurial intention (EI) using survey data collected from a university in Suzhou, China. Adopting a quasi-experimental design with two intact classes, the present research cannot disentangle the standalone effect of AI tools from the full instructional package. Grounded in the Theory of Planned Behavior (TPB) and the Entrepreneurial Potential Model (EPM), this research compares path strength differences and group-specific indirect effects across AIEE and TEE groups, focusing on entrepreneurial attitudes (ATE), subjective norms (SN), perceived behavioral control (PBC), perceived desirability (PD), and perceived feasibility (PF). Multi-group partial least squares structural equation modeling (PLS-SEM) results based on 133 valid participants (AIEE: n = 68; TEE: n = 65) reveal that paths from ATE and PBC to EI, alongside the group-specific indirect effects via PD and PF, are significantly stronger in the AIEE group. This work provides small-scale quasi-experimental evidence for contextual entrepreneurship education research. Due to non-random class assignment, single-site sampling, cross-sectional data, unmeasured confounders, and the inability to isolate pure AI effects, all findings are interpreted as correlational rather than causal, offering actionable implications for the iterative optimization of entrepreneurship curricula.