CCA-AI model: enhanced cognitive cooperation with artificial intelligence

Abstract

The ubiquity of Generative Artificial Intelligence (GAI) has substantially reconfigured academic production and knowledge management. However, recent empirical research shows that seamless, utilitarian collaboration with these tools fosters functional dependence that reduces cognitive persistence and compromises students' independent performance. This paper addresses this epistemological tension by proposing the Augmented Cognitive Cooperation Model with AI (CCA-IA Model). Moving away from technocentric approaches, the model introduces the principle of productive misalignment, positing that deep learning emerges from didactically designed friction and cognitive tension between the machine and the subject. The conceptual architecture is structured into three interdependent layers: Operational Cognition (hybrid execution base), Metacognitive Regulation (exclusively human axis of strategic monitoring), and Epistemic Validation (critical-social vertex of human control). Additionally, the model outlines four practical modes of cooperation (Exploratory, Dialogic, Instrumental, and Critical-Reflective) and formulates five theoretical propositions for future empirical testing. The paper concludes that the era of AI demands an ontological shift in assessment models, replacing the grading of the final product with a rigorous mapping of the human validation process. The framework provides a strategic contribution to the resilience and sustainability of intellectual capital within the Lusophone economic space.