Over the past decade, higher education has evolved through three distinct paradigms: the emergence of Massive Open Online Courses (MOOCs), the integration of Smart Teaching technologies into classrooms, and the rise of AI-enhanced learning. Each paradigm is intended to address specific challenges in traditional education: MOOCs enable ubiquitous access to learning resources; Smart Teaching supports real-time interaction with data-driven insights; and generative AI offers personalized feedback and on-demand content generation. However, these paradigms are often implemented in isolation due to their disparate technological origins and policy-driven adoption. This paper examines the origins, strengths, and limitations of each paradigm, and advocates a unified pedagogical perspective that synthesizes their complementary affordances. We propose a three-layer instructional framework that combines the scalability of MOOCs, the responsiveness of Smart Teaching, and the adaptivity of AI. To demonstrate its feasibility, we present a curriculum design for a project-based course. The findings highlight the framework's potential to enhance learner engagement, support instructors, and enable personalized yet scalable learning.

翻译：过去十年间，高等教育经历了三个显著范式的演进：大规模开放在线课程（MOOCs）的兴起、智慧教学技术与课堂的融合，以及人工智能增强学习的崛起。每个范式都旨在应对传统教育中的特定挑战：MOOCs实现了学习资源的泛在获取；智慧教学通过数据驱动的洞察支持实时互动；而生成式人工智能则提供个性化反馈与按需内容生成。然而，由于技术起源的差异和政策驱动的实施方式，这些范式往往被孤立应用。本文审视了各范式的起源、优势与局限，并倡导一种整合其互补功能的统一教学视角。我们提出了一个三层教学框架，该框架融合了MOOCs的可扩展性、智慧教学的响应能力以及人工智能的自适应性。为论证其可行性，我们展示了一个项目式课程的课程设计方案。研究结果凸显了该框架在提升学习者参与度、支持教师教学以及实现个性化且可扩展学习方面的潜力。