In a rapidly changing educational and workforce landscape, new frameworks are needed to gauge the health of e-learning ecosystems. This paper introduces the MOSAIC model (Modular, Outcome-based, Stackable, Adaptive, Integrated Curriculum), offering a structured approach to designing and evaluating e-learning programs. We identify several “ecosystem health” indicators—such as pedagogical metabolism (the speed and efficiency of feedback loops)—to illustrate how online curricula can adapt to emerging challenges and learner needs. Drawing on AI-driven adaptive technologies and relevant literature, we show how MOSAIC fosters both resilience and scalability, ensuring responsiveness from individual courses to global networks. Ultimately, this framework aligns with calls for lifelong learning and workplace readiness, underscoring its relevance to “The Future of Learning and Work.”

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From Micro to Global: Gauging the Health of E-learning Ecosystems with MOSAIC

  • J. Cory Pettijohn

摘要

In a rapidly changing educational and workforce landscape, new frameworks are needed to gauge the health of e-learning ecosystems. This paper introduces the MOSAIC model (Modular, Outcome-based, Stackable, Adaptive, Integrated Curriculum), offering a structured approach to designing and evaluating e-learning programs. We identify several “ecosystem health” indicators—such as pedagogical metabolism (the speed and efficiency of feedback loops)—to illustrate how online curricula can adapt to emerging challenges and learner needs. Drawing on AI-driven adaptive technologies and relevant literature, we show how MOSAIC fosters both resilience and scalability, ensuring responsiveness from individual courses to global networks. Ultimately, this framework aligns with calls for lifelong learning and workplace readiness, underscoring its relevance to “The Future of Learning and Work.”