A Comparative Study of Generative AI Use Among Secondary and University Students in Macao: A Technology Acceptance Model Perspective

Abstract

Generative AI (GenAI) is rapidly altering learning environments, yet comparative research spanning secondary and higher education remains scarce. Grounded in the Technology Acceptance Model (TAM), this cross-sectional study surveyed Macao secondary (n = 487) and university (n = 401) students in 2026 using convenience sampling; only respondents who had previously used GenAI were retained for analysis, and cross-group adoption mechanisms were evaluated with multi-group structural equation modeling. Results indicate high structural consistency across cohorts: the chain from perceived ease of use through perceived usefulness to behavioral intention holds robustly, with perceived usefulness acting as the primary mediator, and perceived popularity positively predicting behavioral intention in both groups. After correcting for multiple comparisons, the only robust cross-group difference among the 10 structural paths is the direct effect of perceived ease of use on behavioral intention, which is present among secondary students (partial mediation) but absent among university students (full mediation, primarily via perceived usefulness). Measurement-invariance testing further indicated that some perceived-ease-of-use and perceived-popularity items were not fully equivalent across learning stages; accordingly, and given the observational design, the estimated paths are interpreted as associations rather than confirmed causal effects. These findings clarify stage-specific GenAI adoption and yield actionable implications for differentiated educational guidance and digital literacy cultivation.