Embedding far transfer in higher education: A fractal systems model for adaptive expertise and equity in STEM learning

STEM-focused higher education systems worldwide face increasing pressure to prepare learners for complex, ill-structured challenges, from climate resilience to AI ethics, that demand adaptive expertise and integrative thinking. Yet most higher education environments remain oriented toward near transfer, emphasizing the application of knowledge within familiar boundaries more consistently than flexible reasoning across diverse contexts. This essay advances the Fractal Systems Model (FSM), an equity-centered conceptual framework that integrates cognitive, sociocultural, and systems-theoretical perspectives to examine how higher education systems might be designed to support adaptive expertise. FSM reconceptualizes far transfer as a potentially designable system property shaped by recursively aligned learning processes across educational scales. Drawing on research in cognitive science, situated learning, equity studies, and Discipline-Based Education Research, the model specifies how opportunities for abstraction, integration, and recontextualization can recur across the micro, meso, and macro levels of higher education. FSM further proposes that alignment across these levels may strengthen opportunities for far transfer and adaptive expertise while reducing reliance on isolated courses or selective enrichment experiences. The model offers researchers, practitioners, and policymakers an empirically testable systems framework for examining how equitable learning ecosystems can be designed to support adaptive expertise for the complex challenges of the twenty-first century.