This article presents the SYNAPSE model, a four-phase framework designed to guide the pedagogical integration of artificial intelligence (AI) in learning environments. Grounded in cognitive science, motivation theory, and self-regulated learning research, the model conceptualizes learning as a dynamic process of activation, adaptation, participation, and consolidation. Each phase corresponds to specific cognitive functions and motivational drivers, offering educators and developers a structured approach to foster learner engagement and autonomy. Three qualitative studies conducted in upper-secondary classrooms explored how students interacted with AI-enhanced educational tools such as multimodal prompts, adaptive feedback systems, and learning dashboards. The findings reveal substantial variation in learner profiles and emphasize the crucial role of teacher mediation in shaping the pedagogical effectiveness of these tools. While AI can enhance strategic thinking and self-regulation, it cannot replace the pedagogical and ethical scaffolding necessary for deep learning. The SYNAPSE model contributes to the responsible use of AI in education by aligning design principles with cognitive development and motivational integrity. It provides an operational framework for teacher training, tool design, and educational policy that centers human learning within technological innovation.
Sarah Chardonnens (Tue,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: