Over the past decade, higher education has undergone successive shifts driven by three major developments: Massive Open Online Courses (MOOCs), Smart Teaching technologies, and AI-enhanced learning. Each paradigm emerged to address specific limitations of traditional education: MOOCs enable ubiquitous access to learning resources; Smart Teaching supports real-time interaction with data-driven insights; and generative AI offers scalable personalization and on-demand content generation. However, these paradigms are often adopted in isolation, limiting their systemic pedagogical potential. This paper proposes a unified instructional framework that integrates these approaches under a coherent teaching-driven logic. The framework distinguishes three complementary dimensions of instructional design: structured exposure (MOOCs), adaptive allocation (Smart Teaching), and efficiency amplification (AI). To operationalize this integration, we formalize the framework as a layered knowledge transformation model and illustrate its behavior through a step-by-step learning example. The results demonstrate how each layer contributes to measurable and functionally distinct gains in knowledge mastery.

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