Reframing human–AI collaboration in higher education: behavioral pathways from generative AI to critical thinking and ethical creativity

Generative AI is increasingly positioned not only as a tool for accelerating production but also as a collaborator that reshapes how individuals regulate cognition, enact innovation, and negotiate creative integrity. This study developed a dual-mediation framework to explain how AI-assisted tool use, hereafter referred to as AI engagement, is associated with higher-order competencies. Drawing on Social Cognitive Theory, we conceptualized self-regulated learning (SRL) and innovative behavior (IB) as behavioral pathways linking AI-assisted tool use to critical thinking (CT) and creative integrity (CI). Survey data from undergraduate students in design-related higher education were analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that AI-assisted tool use was positively associated with SRL and IB, which were in turn associated with CT and CI. Significant indirect effects further indicated that reflective regulation and purposeful innovation served as important mechanisms through which AI-assisted engagement was linked to higher-order growth. A complementary qualitative phase illustrated how learners framed AI as a “cognitive partner” for idea clarification, iteratively repurposed AI-generated outputs for innovation, and grappled with questions of authorship and attribution. By integrating quantitative modeling with qualitative insights, the study reframes AI not merely as a productivity booster but as a catalyst for reflective, innovative, and ethically attuned practices in AI-mediated design contexts. These findings provide context-specific evidence for understanding human–AI collaboration and offer practical directions for embedding responsibility and criticality in AI-mediated learning environments, while advancing a process-oriented account of how learners translate AI-assisted engagement into cognitive and ethical development.