“Filter” or “Accelerator”? A Mixed-Methods Study of the Driving Mechanisms of Innovative Work Behaviour among Higher Vocational Education Teachers Under AI Ethics Constraints

Artificial intelligence (AI) empowerment and “human–machine collaboration” have triggered a wave of transformation and innovation in vocational education, while simultaneously raising concerns about the ethical challenges posed by the “black box” nature of AI. Drawing on the Attribution Theory and Self-Determination Theory, this study develops a moderated mediation model and employs multiple regression together with Johnson-Neyman method and fuzzy-set qualitative comparative analysis to analyse 413 survey responses. The findings indicate that basic psychological needs constitute the core driving force behind higher vocational education teachers’ AI involvement and innovative work behaviour, whereas institutional learning support exerts its effect only when effectively combined with other factors. AI ethics negatively moderates the effect of AI involvement on innovative work behaviour, thereby uncovering the “filter” role in shaping teachers’ pedagogical innovation. Furthermore, the fsQCA identifies three equivalent configurations leading to high levels of innovative work behaviour and reveals the underlying complex causal relationships. This confirms the dual role of AI ethics as both a “filter” and a “steering wheel” in higher vocational education teachers’ innovation. Based on these insights, the study proposes concrete policy recommendations aimed at helping higher vocational education teachers to better balance innovation and responsibility when applying AI.